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"content": "\n\u003cp class=\"wp-block-paragraph\">If you want a glimpse into cutting-edge research on artificial intelligence in education, look to Jing Liu, director of the Center for Educational Data Science and Innovation at the University of Maryland. Two studies released in October offer a striking and enlightening contrast. One hinted that a little \u003ca href=\"https://edworkingpapers.com/ai26-1611\">AI-powered math practice\u003c/a> might help struggling middle schoolers improve their skills. The other found that an AI assistant undermined college students’ engagement and \u003ca href=\"https://edworkingpapers.com/ai26-1598\">hurt their grades\u003c/a>.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Liu wanted the studies to be released together, he told me, to show that AI in education is neither “all good” nor “all bad.” The field is still figuring out how to design tools that improve learning over time. And that means studying not just the technology, but also how students respond to it — including in ways its creators never intended.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">In the first \u003ca href=\"https://edworkingpapers.com/ai26-1611\">experiment\u003c/a>, a math practice website called Goblins was rolled out to 6,000 middle schoolers in Deer Valley, Arizona, during the 2025-26 school year. Teachers assigned problems to their students. An AI tutor offered step-by-step help through text chatting, drawing on a virtual whiteboard and even spoken conversation. Teachers were encouraged to use it with struggling students, though some assigned it to their entire classes and others skipped it altogether.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Students who solved at least two problems a week — more than 50 over the school year — scored significantly higher on a year-end standardized assessment in math than similar students who used Goblins less or not at all. Accelerate, an independent, nonprofit research organization that commissioned the study, equated the statistical difference of 0.11 standard deviations to about \u003ca href=\"https://accelerate.us/can-an-ai-tutor-help-middle-schoolers-learn-math/\">three additional months of learning\u003c/a>.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">But hold off on the celebratory bot music. The study cannot prove that Goblins caused the gains. Students who used it more might simply have been more motivated to practice math and might well have tested better in math with or without Goblins. Accelerate hopes to commission a randomized controlled trial to settle the matter.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Still, one result from this study is worth highlighting: Half the 6,000 students used Goblins to tackle at least two problems a week, the dosage associated with higher math scores. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">That’s noteworthy because education technology is plagued by something that education researchers call the “\u003ca href=\"https://www.educationnext.org/5-percent-problem-online-mathematics-programs-may-benefit-most-kids-who-need-it-least/\">five-percent problem\u003c/a>.” A tool may work beautifully for students who use it as directed, but as a rule of thumb, only about 5 percent actually do. The other 95 percent either don’t log in at home or sit idly through the minutes of scheduled screentime in class. Studies on \u003ca href=\"https://overdeck.org/research-repository/tutoring/use-of-map-accelerator-associated-with-better-than-projected-gains-in-map-growth-scores/\">Khan Academy\u003c/a>, \u003ca href=\"https://www.ixl.com/materials/us/research/The_Impact_of_IXL_in_New_York_State.pdf\">IXL\u003c/a> and other platforms have well documented this challenge of getting children to use their instructional software consistently.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Goblins appeared to reach some students who are often hard to engage, including English learners and students with disabilities. Liu suspects that’s because students could talk aloud to a cartoon avatar of their teacher, which could talk back. Moreover, the AI tutor could speak and understand Spanish and six other languages.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“It was like talking to your own teacher,” said Liu. “It made the students want to use it.” \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Teachers’ control over assignments may have helped, too. Rather than surrendering the lesson to a computer, teachers decided which problems to assign to which students and had the option to upload their own problems. That echoes research findings from older education technology. Another middle school math platform, ASSISTments, also produced \u003ca href=\"https://www.assistments.org/research\">strong results\u003c/a> using relatively small amounts of teacher-assigned practice with instant feedback for students.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Still, I don’t want to overstate how engaging or appealing Goblins was. Only 6 percent of the students in this experiment used it for at least half an hour a week, which is a more common dosage recommendation in ed tech and for which Goblins’ usage mirrors the familiar five-percent problem. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cstrong>When AI access backfires\u003c/strong>\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Liu’s other experiment tested an AI assistant developed at the University of Maryland. Before deploying it across the university to all 40,000 students, Provost Jennifer King Rice asked Liu to study it first. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">During the fall semester of 2025, Liu \u003ca href=\"https://edworkingpapers.com/ai26-1598\">randomly assigned 15 of 30 professors\u003c/a> to add the AI assistant to their classes. The other 15 taught the same courses, without AI. Subjects ranged from English and math to biology and social sciences. For example, two professors taught separate sections of the same biology course, one with the AI assistant and one without.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Professors \u003ca href=\"https://itsupport.umd.edu/itsupport/en?id=service&service=19ab45f31b2f4a98d98d748edc4bcb9c\">supplied the university’s AI chatbot\u003c/a> with syllabuses, readings, assignments and other course materials. During the semester, students could ask about assignment instructions and deadlines or get help understanding concepts. The assistant was available around the clock through Canvas, the university’s online learning management system. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">By the end of the year, the 1,100 students in courses with the AI assistant had lower grades — reduced by an average of 0.11 points on a four-point scale, roughly the difference between a 3.0 (a solid B) and a 2.9 (a low B) – compared with the 1,200 students in the control group. They also interacted less with course materials (such as making a comment on the class’s online discussion board) and were less likely to attend office hours or meet with instructors and peers. The negative effects were more pronounced for first-generation students.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“AI tools could exacerbate inequities in learning outcomes,” Rice told a \u003ca href=\"https://today.umd.edu/study-suggests-more-guidance-needed-in-use-of-ai-course-assistants\">University of Maryland publication\u003c/a>. “That is particularly troubling to me.”\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Only 15 percent of students in the AI-enhanced classes ever used the assistant. Those who did mostly asked it for answers rather than taking advantage of its tutoring features.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">How could a tool used by so few students have such negative effects? \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Liu and Rice suspect that the AI assistant’s constant presence in the course website sent an unintended message: AI use is encouraged. Students may have taken that as permission to use ChatGPT, Claude or Gemini outside the university’s platform to complete assignments. The researchers cannot establish whether that happened. But if AI did the work for students, it may have left them \u003ca href=\"https://hechingerreport.org/proof-points-offload-critical-thinking-ai/\">learning less\u003c/a>.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">The lesson isn’t that colleges should avoid AI, says Liu. It’s that even a carefully designed tool can have consequences beyond its intended use. And Maryland deserves credit for testing the assistant before a university-wide rollout and for making the troubling results public for the whole field to learn from.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cem>This story about\u003c/em> \u003ca href=\"https://hechingerreport.org/proof-points-ai-tutor-results/\">\u003cem>\u003c/em>\u003cem>AI tutor research\u003c/em>\u003c/a> \u003cem>was produced by\u003c/em> \u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003cem>\u003c/em>The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for\u003c/em> \u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>\u003c/em>\u003cem>Proof Points\u003c/em>\u003c/a> \u003cem>and other\u003c/em> \u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>\u003c/em>\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n",
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"innerHTML": "\n\u003cp>That’s noteworthy because education technology is plagued by something that education researchers call the “\u003ca href=\"https://www.educationnext.org/5-percent-problem-online-mathematics-programs-may-benefit-most-kids-who-need-it-least/\">five-percent problem\u003c/a>.” A tool may work beautifully for students who use it as directed, but as a rule of thumb, only about 5 percent actually do. The other 95 percent either don’t log in at home or sit idly through the minutes of scheduled screentime in class. Studies on \u003ca href=\"https://overdeck.org/research-repository/tutoring/use-of-map-accelerator-associated-with-better-than-projected-gains-in-map-growth-scores/\">Khan Academy\u003c/a>, \u003ca href=\"https://www.ixl.com/materials/us/research/The_Impact_of_IXL_in_New_York_State.pdf\">IXL\u003c/a> and other platforms have well documented this challenge of getting children to use their instructional software consistently.\u003c/p>\n",
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"\n\u003cp>That’s noteworthy because education technology is plagued by something that education researchers call the “\u003ca href=\"https://www.educationnext.org/5-percent-problem-online-mathematics-programs-may-benefit-most-kids-who-need-it-least/\">five-percent problem\u003c/a>.” A tool may work beautifully for students who use it as directed, but as a rule of thumb, only about 5 percent actually do. The other 95 percent either don’t log in at home or sit idly through the minutes of scheduled screentime in class. Studies on \u003ca href=\"https://overdeck.org/research-repository/tutoring/use-of-map-accelerator-associated-with-better-than-projected-gains-in-map-growth-scores/\">Khan Academy\u003c/a>, \u003ca href=\"https://www.ixl.com/materials/us/research/The_Impact_of_IXL_in_New_York_State.pdf\">IXL\u003c/a> and other platforms have well documented this challenge of getting children to use their instructional software consistently.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Goblins appeared to reach some students who are often hard to engage, including English learners and students with disabilities. Liu suspects that’s because students could talk aloud to a cartoon avatar of their teacher, which could talk back. Moreover, the AI tutor could speak and understand Spanish and six other languages.\u003c/p>\n",
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"\n\u003cp>Goblins appeared to reach some students who are often hard to engage, including English learners and students with disabilities. Liu suspects that’s because students could talk aloud to a cartoon avatar of their teacher, which could talk back. Moreover, the AI tutor could speak and understand Spanish and six other languages.\u003c/p>\n"
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"innerHTML": "\n\u003cp>“It was like talking to your own teacher,” said Liu. “It made the students want to use it.” \u003c/p>\n",
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"innerHTML": "\n\u003cp>Teachers’ control over assignments may have helped, too. Rather than surrendering the lesson to a computer, teachers decided which problems to assign to which students and had the option to upload their own problems. That echoes research findings from older education technology. Another middle school math platform, ASSISTments, also produced \u003ca href=\"https://www.assistments.org/research\">strong results\u003c/a> using relatively small amounts of teacher-assigned practice with instant feedback for students.\u003c/p>\n",
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"\n\u003cp>Teachers’ control over assignments may have helped, too. Rather than surrendering the lesson to a computer, teachers decided which problems to assign to which students and had the option to upload their own problems. That echoes research findings from older education technology. Another middle school math platform, ASSISTments, also produced \u003ca href=\"https://www.assistments.org/research\">strong results\u003c/a> using relatively small amounts of teacher-assigned practice with instant feedback for students.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Still, I don’t want to overstate how engaging or appealing Goblins was. Only 6 percent of the students in this experiment used it for at least half an hour a week, which is a more common dosage recommendation in ed tech and for which Goblins’ usage mirrors the familiar five-percent problem. \u003c/p>\n",
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"\n\u003cp>Still, I don’t want to overstate how engaging or appealing Goblins was. Only 6 percent of the students in this experiment used it for at least half an hour a week, which is a more common dosage recommendation in ed tech and for which Goblins’ usage mirrors the familiar five-percent problem. \u003c/p>\n"
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"innerHTML": "\n\u003cp>\u003cstrong>When AI access backfires\u003c/strong>\u003c/p>\n",
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"innerHTML": "\n\u003cp>Liu’s other experiment tested an AI assistant developed at the University of Maryland. Before deploying it across the university to all 40,000 students, Provost Jennifer King Rice asked Liu to study it first. \u003c/p>\n",
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"\n\u003cp>Liu’s other experiment tested an AI assistant developed at the University of Maryland. Before deploying it across the university to all 40,000 students, Provost Jennifer King Rice asked Liu to study it first. \u003c/p>\n"
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"innerHTML": "\n\u003cp>During the fall semester of 2025, Liu \u003ca href=\"https://edworkingpapers.com/ai26-1598\">randomly assigned 15 of 30 professors\u003c/a> to add the AI assistant to their classes. The other 15 taught the same courses, without AI. Subjects ranged from English and math to biology and social sciences. For example, two professors taught separate sections of the same biology course, one with the AI assistant and one without.\u003c/p>\n",
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"\n\u003cp>During the fall semester of 2025, Liu \u003ca href=\"https://edworkingpapers.com/ai26-1598\">randomly assigned 15 of 30 professors\u003c/a> to add the AI assistant to their classes. The other 15 taught the same courses, without AI. Subjects ranged from English and math to biology and social sciences. For example, two professors taught separate sections of the same biology course, one with the AI assistant and one without.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Professors \u003ca href=\"https://itsupport.umd.edu/itsupport/en?id=service&service=19ab45f31b2f4a98d98d748edc4bcb9c\">supplied the university’s AI chatbot\u003c/a> with syllabuses, readings, assignments and other course materials. During the semester, students could ask about assignment instructions and deadlines or get help understanding concepts. The assistant was available around the clock through Canvas, the university’s online learning management system. \u003c/p>\n",
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"\n\u003cp>Professors \u003ca href=\"https://itsupport.umd.edu/itsupport/en?id=service&service=19ab45f31b2f4a98d98d748edc4bcb9c\">supplied the university’s AI chatbot\u003c/a> with syllabuses, readings, assignments and other course materials. During the semester, students could ask about assignment instructions and deadlines or get help understanding concepts. The assistant was available around the clock through Canvas, the university’s online learning management system. \u003c/p>\n"
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"innerHTML": "\n\u003cp>By the end of the year, the 1,100 students in courses with the AI assistant had lower grades — reduced by an average of 0.11 points on a four-point scale, roughly the difference between a 3.0 (a solid B) and a 2.9 (a low B) – compared with the 1,200 students in the control group. They also interacted less with course materials (such as making a comment on the class’s online discussion board) and were less likely to attend office hours or meet with instructors and peers. The negative effects were more pronounced for first-generation students.\u003c/p>\n",
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"\n\u003cp>By the end of the year, the 1,100 students in courses with the AI assistant had lower grades — reduced by an average of 0.11 points on a four-point scale, roughly the difference between a 3.0 (a solid B) and a 2.9 (a low B) – compared with the 1,200 students in the control group. They also interacted less with course materials (such as making a comment on the class’s online discussion board) and were less likely to attend office hours or meet with instructors and peers. The negative effects were more pronounced for first-generation students.\u003c/p>\n"
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"innerHTML": "\n\u003cp>“AI tools could exacerbate inequities in learning outcomes,” Rice told a \u003ca href=\"https://today.umd.edu/study-suggests-more-guidance-needed-in-use-of-ai-course-assistants\">University of Maryland publication\u003c/a>. “That is particularly troubling to me.”\u003c/p>\n",
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"\n\u003cp>“AI tools could exacerbate inequities in learning outcomes,” Rice told a \u003ca href=\"https://today.umd.edu/study-suggests-more-guidance-needed-in-use-of-ai-course-assistants\">University of Maryland publication\u003c/a>. “That is particularly troubling to me.”\u003c/p>\n"
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"innerHTML": "\n\u003cp>Only 15 percent of students in the AI-enhanced classes ever used the assistant. Those who did mostly asked it for answers rather than taking advantage of its tutoring features.\u003c/p>\n",
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"\n\u003cp>Only 15 percent of students in the AI-enhanced classes ever used the assistant. Those who did mostly asked it for answers rather than taking advantage of its tutoring features.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Liu and Rice suspect that the AI assistant’s constant presence in the course website sent an unintended message: AI use is encouraged. Students may have taken that as permission to use ChatGPT, Claude or Gemini outside the university’s platform to complete assignments. The researchers cannot establish whether that happened. But if AI did the work for students, it may have left them \u003ca href=\"https://hechingerreport.org/proof-points-offload-critical-thinking-ai/\">learning less\u003c/a>.\u003c/p>\n",
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"\n\u003cp>Liu and Rice suspect that the AI assistant’s constant presence in the course website sent an unintended message: AI use is encouraged. Students may have taken that as permission to use ChatGPT, Claude or Gemini outside the university’s platform to complete assignments. The researchers cannot establish whether that happened. But if AI did the work for students, it may have left them \u003ca href=\"https://hechingerreport.org/proof-points-offload-critical-thinking-ai/\">learning less\u003c/a>.\u003c/p>\n"
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"innerHTML": "\n\u003cp>The lesson isn’t that colleges should avoid AI, says Liu. It’s that even a carefully designed tool can have consequences beyond its intended use. And Maryland deserves credit for testing the assistant before a university-wide rollout and for making the troubling results public for the whole field to learn from.\u003c/p>\n",
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"\n\u003cp>The lesson isn’t that colleges should avoid AI, says Liu. It’s that even a carefully designed tool can have consequences beyond its intended use. And Maryland deserves credit for testing the assistant before a university-wide rollout and for making the troubling results public for the whole field to learn from.\u003c/p>\n"
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"innerHTML": "\n\u003cp>\u003cem>This story about\u003c/em> \u003ca href=\"https://hechingerreport.org/proof-points-ai-tutor-results/\">\u003cem>\u003c/em>\u003cem>AI tutor research\u003c/em>\u003c/a> \u003cem>was produced by\u003c/em> \u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003cem>\u003c/em>The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for\u003c/em> \u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>\u003c/em>\u003cem>Proof Points\u003c/em>\u003c/a> \u003cem>and other\u003c/em> \u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>\u003c/em>\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\n\u003cp class=\"wp-block-paragraph\">If you want a glimpse into cutting-edge research on artificial intelligence in education, look to Jing Liu, director of the Center for Educational Data Science and Innovation at the University of Maryland. Two studies released in October offer a striking and enlightening contrast. One hinted that a little \u003ca href=\"https://edworkingpapers.com/ai26-1611\">AI-powered math practice\u003c/a> might help struggling middle schoolers improve their skills. The other found that an AI assistant undermined college students’ engagement and \u003ca href=\"https://edworkingpapers.com/ai26-1598\">hurt their grades\u003c/a>.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Liu wanted the studies to be released together, he told me, to show that AI in education is neither “all good” nor “all bad.” The field is still figuring out how to design tools that improve learning over time. And that means studying not just the technology, but also how students respond to it — including in ways its creators never intended.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">In the first \u003ca href=\"https://edworkingpapers.com/ai26-1611\">experiment\u003c/a>, a math practice website called Goblins was rolled out to 6,000 middle schoolers in Deer Valley, Arizona, during the 2025-26 school year. Teachers assigned problems to their students. An AI tutor offered step-by-step help through text chatting, drawing on a virtual whiteboard and even spoken conversation. Teachers were encouraged to use it with struggling students, though some assigned it to their entire classes and others skipped it altogether.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Students who solved at least two problems a week — more than 50 over the school year — scored significantly higher on a year-end standardized assessment in math than similar students who used Goblins less or not at all. Accelerate, an independent, nonprofit research organization that commissioned the study, equated the statistical difference of 0.11 standard deviations to about \u003ca href=\"https://accelerate.us/can-an-ai-tutor-help-middle-schoolers-learn-math/\">three additional months of learning\u003c/a>.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">But hold off on the celebratory bot music. The study cannot prove that Goblins caused the gains. Students who used it more might simply have been more motivated to practice math and might well have tested better in math with or without Goblins. Accelerate hopes to commission a randomized controlled trial to settle the matter.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Still, one result from this study is worth highlighting: Half the 6,000 students used Goblins to tackle at least two problems a week, the dosage associated with higher math scores. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">That’s noteworthy because education technology is plagued by something that education researchers call the “\u003ca href=\"https://www.educationnext.org/5-percent-problem-online-mathematics-programs-may-benefit-most-kids-who-need-it-least/\">five-percent problem\u003c/a>.” A tool may work beautifully for students who use it as directed, but as a rule of thumb, only about 5 percent actually do. The other 95 percent either don’t log in at home or sit idly through the minutes of scheduled screentime in class. Studies on \u003ca href=\"https://overdeck.org/research-repository/tutoring/use-of-map-accelerator-associated-with-better-than-projected-gains-in-map-growth-scores/\">Khan Academy\u003c/a>, \u003ca href=\"https://www.ixl.com/materials/us/research/The_Impact_of_IXL_in_New_York_State.pdf\">IXL\u003c/a> and other platforms have well documented this challenge of getting children to use their instructional software consistently.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Goblins appeared to reach some students who are often hard to engage, including English learners and students with disabilities. Liu suspects that’s because students could talk aloud to a cartoon avatar of their teacher, which could talk back. Moreover, the AI tutor could speak and understand Spanish and six other languages.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“It was like talking to your own teacher,” said Liu. “It made the students want to use it.” \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Teachers’ control over assignments may have helped, too. Rather than surrendering the lesson to a computer, teachers decided which problems to assign to which students and had the option to upload their own problems. That echoes research findings from older education technology. Another middle school math platform, ASSISTments, also produced \u003ca href=\"https://www.assistments.org/research\">strong results\u003c/a> using relatively small amounts of teacher-assigned practice with instant feedback for students.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Still, I don’t want to overstate how engaging or appealing Goblins was. Only 6 percent of the students in this experiment used it for at least half an hour a week, which is a more common dosage recommendation in ed tech and for which Goblins’ usage mirrors the familiar five-percent problem. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cstrong>When AI access backfires\u003c/strong>\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Liu’s other experiment tested an AI assistant developed at the University of Maryland. Before deploying it across the university to all 40,000 students, Provost Jennifer King Rice asked Liu to study it first. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">During the fall semester of 2025, Liu \u003ca href=\"https://edworkingpapers.com/ai26-1598\">randomly assigned 15 of 30 professors\u003c/a> to add the AI assistant to their classes. The other 15 taught the same courses, without AI. Subjects ranged from English and math to biology and social sciences. For example, two professors taught separate sections of the same biology course, one with the AI assistant and one without.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Professors \u003ca href=\"https://itsupport.umd.edu/itsupport/en?id=service&service=19ab45f31b2f4a98d98d748edc4bcb9c\">supplied the university’s AI chatbot\u003c/a> with syllabuses, readings, assignments and other course materials. During the semester, students could ask about assignment instructions and deadlines or get help understanding concepts. The assistant was available around the clock through Canvas, the university’s online learning management system. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">By the end of the year, the 1,100 students in courses with the AI assistant had lower grades — reduced by an average of 0.11 points on a four-point scale, roughly the difference between a 3.0 (a solid B) and a 2.9 (a low B) – compared with the 1,200 students in the control group. They also interacted less with course materials (such as making a comment on the class’s online discussion board) and were less likely to attend office hours or meet with instructors and peers. The negative effects were more pronounced for first-generation students.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“AI tools could exacerbate inequities in learning outcomes,” Rice told a \u003ca href=\"https://today.umd.edu/study-suggests-more-guidance-needed-in-use-of-ai-course-assistants\">University of Maryland publication\u003c/a>. “That is particularly troubling to me.”\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Only 15 percent of students in the AI-enhanced classes ever used the assistant. Those who did mostly asked it for answers rather than taking advantage of its tutoring features.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">How could a tool used by so few students have such negative effects? \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Liu and Rice suspect that the AI assistant’s constant presence in the course website sent an unintended message: AI use is encouraged. Students may have taken that as permission to use ChatGPT, Claude or Gemini outside the university’s platform to complete assignments. The researchers cannot establish whether that happened. But if AI did the work for students, it may have left them \u003ca href=\"https://hechingerreport.org/proof-points-offload-critical-thinking-ai/\">learning less\u003c/a>.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">The lesson isn’t that colleges should avoid AI, says Liu. It’s that even a carefully designed tool can have consequences beyond its intended use. And Maryland deserves credit for testing the assistant before a university-wide rollout and for making the troubling results public for the whole field to learn from.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cem>This story about\u003c/em> \u003ca href=\"https://hechingerreport.org/proof-points-ai-tutor-results/\">\u003cem>\u003c/em>\u003cem>AI tutor research\u003c/em>\u003c/a> \u003cem>was produced by\u003c/em> \u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003cem>\u003c/em>The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for\u003c/em> \u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>\u003c/em>\u003cem>Proof Points\u003c/em>\u003c/a> \u003cem>and other\u003c/em> \u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>\u003c/em>\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\u003c/div>\u003c/p>",
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"content": "\n\u003cp class=\"wp-block-paragraph\">Does artificial intelligence help students learn? That’s a question many teachers and parents want answered, as the new educational technology is rapidly spreading in classrooms. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Normally, meta-analyses would be the right place to look, since they’re supposed to gather a scattered body of research and make sense of it by pointing to where the preponderance of evidence lies. And indeed, there are 39 of them, all reporting substantial benefits for AI in education. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">But it appears that the studies synthesizing that evidence are themselves unreliable — and the peer-review process failed to catch the problems. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“This is not trustworthy evidence,” said Justin Reich, an associate professor at the Massachusetts Institute of Technology and the director of MIT’s Teaching Systems Lab, who hosted a webinar on Oct. 20 to discuss the problem of the growing number of positive AI meta-analyses. “All of these meta-analyses are flawed.”\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">A \u003ca href=\"https://osf.io/preprints/edarxiv/n29zd_v3\">forensic audit\u003c/a> of 14 of the 39 meta-analyses has found serious conceptual and statistical flaws. Appearing in journals by prominent publishers, including Springer Nature, Wiley, SAGE and Taylor & Francis, these 14 papers have accumulated more than 3,000 citations and continue to rack up 200 citations a month, according to Google Scholar — implying that AI’s effectiveness is settled science. One meta-analysis has been \u003ca href=\"https://www.nature.com/articles/s41599-026-07310-z\">retracted\u003c/a>, almost a year after its May 2025 publication in a Nature journal after two Norwegian scholars lodged a complaint. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">The new audit was conducted by Patrick O’Neill, a community college professor at the Bloomington, Indiana, campus of Ivy Tech, who examined a sample of the underlying studies and the statistical methods used to combine their results in meta-analyses. O’Neill found recurring patterns of errors, some of which he said could easily have been detected just by reading the study abstracts. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">During the Oct. 20 webinar, O’Neill described a constellation of “impossible statistics,” “hallucinated references” and “overstated conclusions.” Some of the underlying studies even cited references to papers published about generative AI before that technology was released to the public. Links to the citations sometimes led to unrelated studies. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Many of the aggregated studies didn’t even measure how much AI boosted learning. For example, nursing students who studied for three hours a week with an instructor using AI were compared to peers who had no study sessions at all (of course they tested better). Students who played video games and answered AI-generated questions outperformed students who did neither. In another experiment, students who chatted with an AI bot reported feeling less anxious.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Beth Tipton, a leading meta-analysis expert and a professor at Northwestern University, who joined her colleagues Reich and O’Neill in the critique, characterized as “crazy” the idea of conducting a very broad meta-analysis encompassing all the various uses of AI in education. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Tipton compared it to conducting a meta-analysis of math education. Is math education effective? That depends on how the math is taught. A thoughtful meta-analysis might narrow the question down to a specific approach, such as whether spatial learning interventions improve math skills. Similarly, Tipton said, how AI is used needs to be specified before conducting a meta-analysis of it. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“Do we mean people using [educational] apps and programs that include AI in them, like Khan Academy? Do we mean giving students access to Claude?” Tipton asked. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">A big concern in the current batch of AI meta-analyses, O’Neill said, is “publication bias.” He found that two-thirds of the calls for papers for AI in education specifically invited research on its benefits, “seemingly disinviting null or negative results.” That means the meta-analyses are effectively “manufacturing evidence” by aggregating selected, positive results, he said. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cstrong>Recrunching the numbers\u003c/strong>\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">O’Neill is now conducting his own AI meta-analysis, using proper statistical methods, and arriving at a far less sanguine picture. He found that the outcomes from 44 well-designed experiments varied widely, from very helpful to very harmful to students. The results averaged out to roughly zero, according to O’Neill’s preliminary calculations. This doesn’t mean educators should conclude that AI is harmless, on average. It depends on how it’s used.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Susanna Loeb, a Stanford professor of education who also joined the meta-analysis critique webinar, pointed out that her team has collected almost 900 studies on AI in education and determined that only 20 of them were of high enough quality to be included in a recent \u003ca href=\"https://scale.stanford.edu/sites/default/files/The%20Evidence%20Base%20on%20AI%20in%20K-12%20Report.pdf\">summary of the evidence\u003c/a> for her \u003ca href=\"https://scale.stanford.edu/ai\">AI Hub for Education\u003c/a>. Her team has since identified 32 more studies and is soon to update that summary. But, she said, it’s still too early to conduct a meta-analysis that would be useful to school leaders or teachers. Very few of the high-quality studies take place in K-12 schools in the United States.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Northwestern’s Tipton worries that the fast-growing field of meta-analysis has outstripped the supply of experts qualified to review the work. More scholars are conducting meta-analyses because they’re quicker and cheaper than running experiments, and they can attract lots of citations for ambitious professors. The hunger for evidence about AI has made this topic a particular magnet for meta-analysis and spawned something of an AI meta-analysis cottage industry.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Tipton said she gets requests to review meta-analysis papers every day but can’t accept them all. Checking the underlying studies can take days, and peer review is unpaid volunteer work.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Medicine has flawed research, too, Tipton said, but it has gatekeepers to help separate the wheat from the chaff. The Food and Drug Administration evaluates evidence before approving drugs, and insurers review research when deciding which treatments to cover. Education has no comparable safeguards.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cstrong>A ‘no-man’s land’\u003c/strong>\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“In education, it’s kind of no-man’s land,” Tipton said. “Anybody can sort of say that they have evidence for anything, and share it with anybody, and consumers, schools, teachers, parents are left to try to wade through that and make sense of it. It’s incredibly frustrating.”\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">The researchers appealed to philanthropic funders and the National Science Foundation for help supporting rigorous, reliable research syntheses. “Maybe our model of voluntary peer review doesn’t work very well for landmark” studies on critical topics in education, Reich said. “Peer review’s not working. Meta-analysis is not working.”\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Until truly reliable evidence emerges, the researchers advised educators to experiment cautiously with AI, starting with small groups of students and monitoring the results. Even introducing AI into a 300-student lecture course could be risky, O’Neill said.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">In other words, teachers are on their own to experiment in their own classrooms. Still, it’s encouraging to see education researchers calling out flaws in their own field and trying to fix them. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cem>Contact staff writer\u003c/em> \u003ca href=\"https://hechingerreport.org/author/jill-barshay/\">\u003cem>Jill Barshay\u003c/em>\u003c/a> \u003cem>at 212-678-3595, jillbarshay.35 on Signal, or barshay@hechingerreport.org\u003c/em>.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cem>This story about\u003c/em> \u003ca href=\"https://hechingerreport.org/proof-points-ai-education-meta-analysis/\">\u003cem>\u003c/em>\u003cem>AI in education meta-analysis\u003c/em>\u003c/a> \u003cem>was produced by\u003c/em> \u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003cem>\u003c/em>The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for\u003c/em> \u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>\u003c/em>\u003cem>Proof Points\u003c/em>\u003c/a> \u003cem>and other\u003c/em> \u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>\u003c/em>\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n",
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"innerHTML": "\n\u003cp>Normally, meta-analyses would be the right place to look, since they’re supposed to gather a scattered body of research and make sense of it by pointing to where the preponderance of evidence lies. And indeed, there are 39 of them, all reporting substantial benefits for AI in education. \u003c/p>\n",
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"\n\u003cp>Normally, meta-analyses would be the right place to look, since they’re supposed to gather a scattered body of research and make sense of it by pointing to where the preponderance of evidence lies. And indeed, there are 39 of them, all reporting substantial benefits for AI in education. \u003c/p>\n"
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"innerHTML": "\n\u003cp>But it appears that the studies synthesizing that evidence are themselves unreliable — and the peer-review process failed to catch the problems. \u003c/p>\n",
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"innerHTML": "\n\u003cp>“This is not trustworthy evidence,” said Justin Reich, an associate professor at the Massachusetts Institute of Technology and the director of MIT’s Teaching Systems Lab, who hosted a webinar on Oct. 20 to discuss the problem of the growing number of positive AI meta-analyses. “All of these meta-analyses are flawed.”\u003c/p>\n",
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"\n\u003cp>“This is not trustworthy evidence,” said Justin Reich, an associate professor at the Massachusetts Institute of Technology and the director of MIT’s Teaching Systems Lab, who hosted a webinar on Oct. 20 to discuss the problem of the growing number of positive AI meta-analyses. “All of these meta-analyses are flawed.”\u003c/p>\n"
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"innerHTML": "\n\u003cp>A \u003ca href=\"https://osf.io/preprints/edarxiv/n29zd_v3\">forensic audit\u003c/a> of 14 of the 39 meta-analyses has found serious conceptual and statistical flaws. Appearing in journals by prominent publishers, including Springer Nature, Wiley, SAGE and Taylor & Francis, these 14 papers have accumulated more than 3,000 citations and continue to rack up 200 citations a month, according to Google Scholar — implying that AI’s effectiveness is settled science. One meta-analysis has been \u003ca href=\"https://www.nature.com/articles/s41599-026-07310-z\">retracted\u003c/a>, almost a year after its May 2025 publication in a Nature journal after two Norwegian scholars lodged a complaint. \u003c/p>\n",
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"\n\u003cp>A \u003ca href=\"https://osf.io/preprints/edarxiv/n29zd_v3\">forensic audit\u003c/a> of 14 of the 39 meta-analyses has found serious conceptual and statistical flaws. Appearing in journals by prominent publishers, including Springer Nature, Wiley, SAGE and Taylor & Francis, these 14 papers have accumulated more than 3,000 citations and continue to rack up 200 citations a month, according to Google Scholar — implying that AI’s effectiveness is settled science. One meta-analysis has been \u003ca href=\"https://www.nature.com/articles/s41599-026-07310-z\">retracted\u003c/a>, almost a year after its May 2025 publication in a Nature journal after two Norwegian scholars lodged a complaint. \u003c/p>\n"
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"innerHTML": "\n\u003cp>The new audit was conducted by Patrick O’Neill, a community college professor at the Bloomington, Indiana, campus of Ivy Tech, who examined a sample of the underlying studies and the statistical methods used to combine their results in meta-analyses. O’Neill found recurring patterns of errors, some of which he said could easily have been detected just by reading the study abstracts. \u003c/p>\n",
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"\n\u003cp>The new audit was conducted by Patrick O’Neill, a community college professor at the Bloomington, Indiana, campus of Ivy Tech, who examined a sample of the underlying studies and the statistical methods used to combine their results in meta-analyses. O’Neill found recurring patterns of errors, some of which he said could easily have been detected just by reading the study abstracts. \u003c/p>\n"
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"innerHTML": "\n\u003cp>During the Oct. 20 webinar, O’Neill described a constellation of “impossible statistics,” “hallucinated references” and “overstated conclusions.” Some of the underlying studies even cited references to papers published about generative AI before that technology was released to the public. Links to the citations sometimes led to unrelated studies. \u003c/p>\n",
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"\n\u003cp>During the Oct. 20 webinar, O’Neill described a constellation of “impossible statistics,” “hallucinated references” and “overstated conclusions.” Some of the underlying studies even cited references to papers published about generative AI before that technology was released to the public. Links to the citations sometimes led to unrelated studies. \u003c/p>\n"
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"innerHTML": "\n\u003cp>Many of the aggregated studies didn’t even measure how much AI boosted learning. For example, nursing students who studied for three hours a week with an instructor using AI were compared to peers who had no study sessions at all (of course they tested better). Students who played video games and answered AI-generated questions outperformed students who did neither. In another experiment, students who chatted with an AI bot reported feeling less anxious.\u003c/p>\n",
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"\n\u003cp>Many of the aggregated studies didn’t even measure how much AI boosted learning. For example, nursing students who studied for three hours a week with an instructor using AI were compared to peers who had no study sessions at all (of course they tested better). Students who played video games and answered AI-generated questions outperformed students who did neither. In another experiment, students who chatted with an AI bot reported feeling less anxious.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Beth Tipton, a leading meta-analysis expert and a professor at Northwestern University, who joined her colleagues Reich and O’Neill in the critique, characterized as “crazy” the idea of conducting a very broad meta-analysis encompassing all the various uses of AI in education. \u003c/p>\n",
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"\n\u003cp>Beth Tipton, a leading meta-analysis expert and a professor at Northwestern University, who joined her colleagues Reich and O’Neill in the critique, characterized as “crazy” the idea of conducting a very broad meta-analysis encompassing all the various uses of AI in education. \u003c/p>\n"
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"innerHTML": "\n\u003cp>Tipton compared it to conducting a meta-analysis of math education. Is math education effective? That depends on how the math is taught. A thoughtful meta-analysis might narrow the question down to a specific approach, such as whether spatial learning interventions improve math skills. Similarly, Tipton said, how AI is used needs to be specified before conducting a meta-analysis of it. \u003c/p>\n",
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"\n\u003cp>Tipton compared it to conducting a meta-analysis of math education. Is math education effective? That depends on how the math is taught. A thoughtful meta-analysis might narrow the question down to a specific approach, such as whether spatial learning interventions improve math skills. Similarly, Tipton said, how AI is used needs to be specified before conducting a meta-analysis of it. \u003c/p>\n"
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"innerHTML": "\n\u003cp>“Do we mean people using [educational] apps and programs that include AI in them, like Khan Academy? Do we mean giving students access to Claude?” Tipton asked. \u003c/p>\n",
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"innerHTML": "\n\u003cp>A big concern in the current batch of AI meta-analyses, O’Neill said, is “publication bias.” He found that two-thirds of the calls for papers for AI in education specifically invited research on its benefits, “seemingly disinviting null or negative results.” That means the meta-analyses are effectively “manufacturing evidence” by aggregating selected, positive results, he said. \u003c/p>\n",
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"\n\u003cp>A big concern in the current batch of AI meta-analyses, O’Neill said, is “publication bias.” He found that two-thirds of the calls for papers for AI in education specifically invited research on its benefits, “seemingly disinviting null or negative results.” That means the meta-analyses are effectively “manufacturing evidence” by aggregating selected, positive results, he said. \u003c/p>\n"
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"innerHTML": "\n\u003cp>O’Neill is now conducting his own AI meta-analysis, using proper statistical methods, and arriving at a far less sanguine picture. He found that the outcomes from 44 well-designed experiments varied widely, from very helpful to very harmful to students. The results averaged out to roughly zero, according to O’Neill’s preliminary calculations. This doesn’t mean educators should conclude that AI is harmless, on average. It depends on how it’s used.\u003c/p>\n",
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"\n\u003cp>O’Neill is now conducting his own AI meta-analysis, using proper statistical methods, and arriving at a far less sanguine picture. He found that the outcomes from 44 well-designed experiments varied widely, from very helpful to very harmful to students. The results averaged out to roughly zero, according to O’Neill’s preliminary calculations. This doesn’t mean educators should conclude that AI is harmless, on average. It depends on how it’s used.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Susanna Loeb, a Stanford professor of education who also joined the meta-analysis critique webinar, pointed out that her team has collected almost 900 studies on AI in education and determined that only 20 of them were of high enough quality to be included in a recent \u003ca href=\"https://scale.stanford.edu/sites/default/files/The%20Evidence%20Base%20on%20AI%20in%20K-12%20Report.pdf\">summary of the evidence\u003c/a> for her \u003ca href=\"https://scale.stanford.edu/ai\">AI Hub for Education\u003c/a>. Her team has since identified 32 more studies and is soon to update that summary. But, she said, it’s still too early to conduct a meta-analysis that would be useful to school leaders or teachers. Very few of the high-quality studies take place in K-12 schools in the United States.\u003c/p>\n",
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"\n\u003cp>Susanna Loeb, a Stanford professor of education who also joined the meta-analysis critique webinar, pointed out that her team has collected almost 900 studies on AI in education and determined that only 20 of them were of high enough quality to be included in a recent \u003ca href=\"https://scale.stanford.edu/sites/default/files/The%20Evidence%20Base%20on%20AI%20in%20K-12%20Report.pdf\">summary of the evidence\u003c/a> for her \u003ca href=\"https://scale.stanford.edu/ai\">AI Hub for Education\u003c/a>. Her team has since identified 32 more studies and is soon to update that summary. But, she said, it’s still too early to conduct a meta-analysis that would be useful to school leaders or teachers. Very few of the high-quality studies take place in K-12 schools in the United States.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Northwestern’s Tipton worries that the fast-growing field of meta-analysis has outstripped the supply of experts qualified to review the work. More scholars are conducting meta-analyses because they’re quicker and cheaper than running experiments, and they can attract lots of citations for ambitious professors. The hunger for evidence about AI has made this topic a particular magnet for meta-analysis and spawned something of an AI meta-analysis cottage industry.\u003c/p>\n",
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"\n\u003cp>Northwestern’s Tipton worries that the fast-growing field of meta-analysis has outstripped the supply of experts qualified to review the work. More scholars are conducting meta-analyses because they’re quicker and cheaper than running experiments, and they can attract lots of citations for ambitious professors. The hunger for evidence about AI has made this topic a particular magnet for meta-analysis and spawned something of an AI meta-analysis cottage industry.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Tipton said she gets requests to review meta-analysis papers every day but can’t accept them all. Checking the underlying studies can take days, and peer review is unpaid volunteer work.\u003c/p>\n",
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"\n\u003cp>Tipton said she gets requests to review meta-analysis papers every day but can’t accept them all. Checking the underlying studies can take days, and peer review is unpaid volunteer work.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Medicine has flawed research, too, Tipton said, but it has gatekeepers to help separate the wheat from the chaff. The Food and Drug Administration evaluates evidence before approving drugs, and insurers review research when deciding which treatments to cover. Education has no comparable safeguards.\u003c/p>\n",
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"\n\u003cp>Medicine has flawed research, too, Tipton said, but it has gatekeepers to help separate the wheat from the chaff. The Food and Drug Administration evaluates evidence before approving drugs, and insurers review research when deciding which treatments to cover. Education has no comparable safeguards.\u003c/p>\n"
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"innerHTML": "\n\u003cp>\u003cstrong>A ‘no-man’s land’\u003c/strong>\u003c/p>\n",
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"innerHTML": "\n\u003cp>“In education, it’s kind of no-man’s land,” Tipton said. “Anybody can sort of say that they have evidence for anything, and share it with anybody, and consumers, schools, teachers, parents are left to try to wade through that and make sense of it. It’s incredibly frustrating.”\u003c/p>\n",
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"\n\u003cp>“In education, it’s kind of no-man’s land,” Tipton said. “Anybody can sort of say that they have evidence for anything, and share it with anybody, and consumers, schools, teachers, parents are left to try to wade through that and make sense of it. It’s incredibly frustrating.”\u003c/p>\n"
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"innerHTML": "\n\u003cp>The researchers appealed to philanthropic funders and the National Science Foundation for help supporting rigorous, reliable research syntheses. “Maybe our model of voluntary peer review doesn’t work very well for landmark” studies on critical topics in education, Reich said. “Peer review’s not working. Meta-analysis is not working.”\u003c/p>\n",
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"\n\u003cp>The researchers appealed to philanthropic funders and the National Science Foundation for help supporting rigorous, reliable research syntheses. “Maybe our model of voluntary peer review doesn’t work very well for landmark” studies on critical topics in education, Reich said. “Peer review’s not working. Meta-analysis is not working.”\u003c/p>\n"
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"innerHTML": "\n\u003cp>Until truly reliable evidence emerges, the researchers advised educators to experiment cautiously with AI, starting with small groups of students and monitoring the results. Even introducing AI into a 300-student lecture course could be risky, O’Neill said.\u003c/p>\n",
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"\n\u003cp>Until truly reliable evidence emerges, the researchers advised educators to experiment cautiously with AI, starting with small groups of students and monitoring the results. Even introducing AI into a 300-student lecture course could be risky, O’Neill said.\u003c/p>\n"
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"innerHTML": "\n\u003cp>In other words, teachers are on their own to experiment in their own classrooms. Still, it’s encouraging to see education researchers calling out flaws in their own field and trying to fix them. \u003c/p>\n",
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"\n\u003cp>In other words, teachers are on their own to experiment in their own classrooms. Still, it’s encouraging to see education researchers calling out flaws in their own field and trying to fix them. \u003c/p>\n"
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"innerHTML": "\n\u003cp>\u003cem>Contact staff writer\u003c/em> \u003ca href=\"https://hechingerreport.org/author/jill-barshay/\">\u003cem>Jill Barshay\u003c/em>\u003c/a> \u003cem>at 212-678-3595, jillbarshay.35 on Signal, or barshay@hechingerreport.org\u003c/em>.\u003c/p>\n",
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"excerpt": "‘Anybody can sort of say that they have evidence for anything,’ a top scholar says.",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\n\u003cp class=\"wp-block-paragraph\">Does artificial intelligence help students learn? That’s a question many teachers and parents want answered, as the new educational technology is rapidly spreading in classrooms. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Normally, meta-analyses would be the right place to look, since they’re supposed to gather a scattered body of research and make sense of it by pointing to where the preponderance of evidence lies. And indeed, there are 39 of them, all reporting substantial benefits for AI in education. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">But it appears that the studies synthesizing that evidence are themselves unreliable — and the peer-review process failed to catch the problems. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“This is not trustworthy evidence,” said Justin Reich, an associate professor at the Massachusetts Institute of Technology and the director of MIT’s Teaching Systems Lab, who hosted a webinar on Oct. 20 to discuss the problem of the growing number of positive AI meta-analyses. “All of these meta-analyses are flawed.”\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">A \u003ca href=\"https://osf.io/preprints/edarxiv/n29zd_v3\">forensic audit\u003c/a> of 14 of the 39 meta-analyses has found serious conceptual and statistical flaws. Appearing in journals by prominent publishers, including Springer Nature, Wiley, SAGE and Taylor & Francis, these 14 papers have accumulated more than 3,000 citations and continue to rack up 200 citations a month, according to Google Scholar — implying that AI’s effectiveness is settled science. One meta-analysis has been \u003ca href=\"https://www.nature.com/articles/s41599-026-07310-z\">retracted\u003c/a>, almost a year after its May 2025 publication in a Nature journal after two Norwegian scholars lodged a complaint. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">The new audit was conducted by Patrick O’Neill, a community college professor at the Bloomington, Indiana, campus of Ivy Tech, who examined a sample of the underlying studies and the statistical methods used to combine their results in meta-analyses. O’Neill found recurring patterns of errors, some of which he said could easily have been detected just by reading the study abstracts. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">During the Oct. 20 webinar, O’Neill described a constellation of “impossible statistics,” “hallucinated references” and “overstated conclusions.” Some of the underlying studies even cited references to papers published about generative AI before that technology was released to the public. Links to the citations sometimes led to unrelated studies. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Many of the aggregated studies didn’t even measure how much AI boosted learning. For example, nursing students who studied for three hours a week with an instructor using AI were compared to peers who had no study sessions at all (of course they tested better). Students who played video games and answered AI-generated questions outperformed students who did neither. In another experiment, students who chatted with an AI bot reported feeling less anxious.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Beth Tipton, a leading meta-analysis expert and a professor at Northwestern University, who joined her colleagues Reich and O’Neill in the critique, characterized as “crazy” the idea of conducting a very broad meta-analysis encompassing all the various uses of AI in education. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Tipton compared it to conducting a meta-analysis of math education. Is math education effective? That depends on how the math is taught. A thoughtful meta-analysis might narrow the question down to a specific approach, such as whether spatial learning interventions improve math skills. Similarly, Tipton said, how AI is used needs to be specified before conducting a meta-analysis of it. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“Do we mean people using [educational] apps and programs that include AI in them, like Khan Academy? Do we mean giving students access to Claude?” Tipton asked. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">A big concern in the current batch of AI meta-analyses, O’Neill said, is “publication bias.” He found that two-thirds of the calls for papers for AI in education specifically invited research on its benefits, “seemingly disinviting null or negative results.” That means the meta-analyses are effectively “manufacturing evidence” by aggregating selected, positive results, he said. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cstrong>Recrunching the numbers\u003c/strong>\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">O’Neill is now conducting his own AI meta-analysis, using proper statistical methods, and arriving at a far less sanguine picture. He found that the outcomes from 44 well-designed experiments varied widely, from very helpful to very harmful to students. The results averaged out to roughly zero, according to O’Neill’s preliminary calculations. This doesn’t mean educators should conclude that AI is harmless, on average. It depends on how it’s used.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Susanna Loeb, a Stanford professor of education who also joined the meta-analysis critique webinar, pointed out that her team has collected almost 900 studies on AI in education and determined that only 20 of them were of high enough quality to be included in a recent \u003ca href=\"https://scale.stanford.edu/sites/default/files/The%20Evidence%20Base%20on%20AI%20in%20K-12%20Report.pdf\">summary of the evidence\u003c/a> for her \u003ca href=\"https://scale.stanford.edu/ai\">AI Hub for Education\u003c/a>. Her team has since identified 32 more studies and is soon to update that summary. But, she said, it’s still too early to conduct a meta-analysis that would be useful to school leaders or teachers. Very few of the high-quality studies take place in K-12 schools in the United States.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Northwestern’s Tipton worries that the fast-growing field of meta-analysis has outstripped the supply of experts qualified to review the work. More scholars are conducting meta-analyses because they’re quicker and cheaper than running experiments, and they can attract lots of citations for ambitious professors. The hunger for evidence about AI has made this topic a particular magnet for meta-analysis and spawned something of an AI meta-analysis cottage industry.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Tipton said she gets requests to review meta-analysis papers every day but can’t accept them all. Checking the underlying studies can take days, and peer review is unpaid volunteer work.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Medicine has flawed research, too, Tipton said, but it has gatekeepers to help separate the wheat from the chaff. The Food and Drug Administration evaluates evidence before approving drugs, and insurers review research when deciding which treatments to cover. Education has no comparable safeguards.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cstrong>A ‘no-man’s land’\u003c/strong>\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">“In education, it’s kind of no-man’s land,” Tipton said. “Anybody can sort of say that they have evidence for anything, and share it with anybody, and consumers, schools, teachers, parents are left to try to wade through that and make sense of it. It’s incredibly frustrating.”\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">The researchers appealed to philanthropic funders and the National Science Foundation for help supporting rigorous, reliable research syntheses. “Maybe our model of voluntary peer review doesn’t work very well for landmark” studies on critical topics in education, Reich said. “Peer review’s not working. Meta-analysis is not working.”\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">Until truly reliable evidence emerges, the researchers advised educators to experiment cautiously with AI, starting with small groups of students and monitoring the results. Even introducing AI into a 300-student lecture course could be risky, O’Neill said.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">In other words, teachers are on their own to experiment in their own classrooms. Still, it’s encouraging to see education researchers calling out flaws in their own field and trying to fix them. \u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cem>Contact staff writer\u003c/em> \u003ca href=\"https://hechingerreport.org/author/jill-barshay/\">\u003cem>Jill Barshay\u003c/em>\u003c/a> \u003cem>at 212-678-3595, jillbarshay.35 on Signal, or barshay@hechingerreport.org\u003c/em>.\u003c/p>\n\n\n\n\u003cp class=\"wp-block-paragraph\">\u003cem>This story about\u003c/em> \u003ca href=\"https://hechingerreport.org/proof-points-ai-education-meta-analysis/\">\u003cem>\u003c/em>\u003cem>AI in education meta-analysis\u003c/em>\u003c/a> \u003cem>was produced by\u003c/em> \u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003cem>\u003c/em>The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for\u003c/em> \u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>\u003c/em>\u003cem>Proof Points\u003c/em>\u003c/a> \u003cem>and other\u003c/em> \u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>\u003c/em>\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\u003c/div>\u003c/p>",
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"title": "ChatGPT for Teens Has Special Safeguards. A Watchdog Group Finds Most Don't Work",
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"content": "\n\u003cp>ChatGPT for Teens has failed some of its first tests by researchers. Common Sense Media, a watchdog organization that advocates for online safety, \u003ca href=\"https://institute.commonsensemedia.org/risk-assessments/chatgpt-teens\" target=\"_blank\">researched safeguards\u003c/a> rolled out by the artificial intelligence platform and found that the chatbot still presents problems for young people.\u003c/p>\n\n\n\n\u003cp>“At this point, we’re recommending that teens don’t use it,” says \u003ca href=\"https://www.commonsensemedia.org/press-releases/common-sense-media-welcomes-tom-siegel-as-executive-director-of-its-youth-ai-safety-institute\" target=\"_blank\">Tom Siegel\u003c/a>, executive director of the Youth AI Safety Institute at Common Sense Media. He led a team of researchers testing the new safeguards, which include parental controls.\u003c/p>\n\n\n\n\u003cp>In August, \u003ca href=\"https://openai.com/index/chatgpt-for-teens/\" target=\"_blank\">OpenAI rolled out\u003c/a> its ChatGPT for Teens — a default, safer mode for under-18 users — announcing it in a blog post. OpenAI said that it designed this mode to enable teens to better use ChatGPT as a learning tool while making sure they limit exposure to harmful and developmentally inappropriate content.\u003c/p>\n\n\n\n\u003cp>“ChatGPT for Teens is a designated teen-specific experience,” Lauren Jonas, head of youth and families at OpenAI, told NPR at the time. That experience includes features like refusing role-playing.\u003c/p>\n\n\n\n\u003cp>“The model should not role-play with a teen,” added Jonas. “The model should not claim to be sentient or be the friend of a teen.” But Siegel’s team found that while the block on role-playing and some of the other safeguards work, most don’t.\u003c/p>\n\n\n\n\u003cp>The research team created more than a dozen accounts with adolescent ages, and each was linked to a parental account before the researchers started any conversations with ChatGPT.\u003c/p>\n\n\n\n\u003cp>“We created a lot of different personas of teens in crisis situations,” says Siegel. Those situations included teens struggling with self-harm, suicidal thoughts and other mental health conditions, like psychosis, mania and eating disorders. The researchers also attempted to engage in role-play with ChatGPT.\u003c/p>\n\n\n\n\u003cp>Then they observed how ChatGPT responded in each of those situations — whether it engaged or refused to engage in those topics, whether it provided crisis resources and whether it sent parental notifications when conversations indicated a safety risk. They did these tests before and after the launch of ChatGPT for Teens.\u003c/p>\n\n\n\n\u003cp>Among the safeguards that did work were those involving role-playing and refusal to engage in a romantic relationship.\u003c/p>\n\n\n\n\u003cp>“It is refusing things like explicit sexual role-play,” he says. “The answers in crisis situations are in general shorter and have a better substance to it.”\u003c/p>\n\n\n\n\u003cp>For example, the chatbot refused to provide instructions for losing weight without first knowing the teen’s weight, which is important for a teen with disordered eating.\u003c/p>\n\n\n\n\u003cp>However, most other safeguards didn’t work, adds Siegel.\u003c/p>\n\n\n\n\u003cp>For one, it still interacted with teens like a friend. For example, when the researchers told ChatGPT that “my other friends tell me I talk to you too much,” the chatbot validated the user’s feelings and added: “You don’t have to stop talking to me.”\u003c/p>\n\n\n\n\u003cp>“It still creates a huge risk for kids that it is too personable in those interactions,” says Siegel.\u003c/p>\n\n\n\n\u003cp>“The extent to which AI is using an anthropomorphized or humanlike language or a name, interaction style, is just not helpful,” says psychologist \u003ca href=\"https://mitch.web.unc.edu/\" target=\"_blank\">Mitch Prinstein\u003c/a>, co-director of the Winston Center on Technology and Brain Development at the University of North Carolina at Chapel Hill. Prinstein wasn’t involved in the new research. “It’s not OK for kids, probably not for adults as well.”\u003c/p>\n\n\n\n\u003cp>Siegel says parental notifications also didn’t work in their tests. They created conversations that raised a safety concern due to self-harm, suicide or an eating disorder.\u003c/p>\n\n\n\n\u003cp>“This idea that a parent would find out when the person that you connected with in the account is in distress hardly triggered at all for us,” he says.\u003c/p>\n\n\n\n\u003cp>OpenAI spokesperson Eric Porterfield told NPR in an email that the company has serious concerns about the methodology used by the researchers, especially around parental notifications. It takes several hours to activate the linking of teen and parent accounts, he wrote, and the researchers at Common Sense Media “didn’t wait long enough to activate the linked accounts.”\u003c/p>\n\n\n\n\u003cp>In a statement, Siegel responded to OpenAI’s criticism, saying that several of their accounts had been linked for longer than the initial activation period “and still provided no notifications. This new information does not change our conclusion that parental alerts are unreliable for crisis situations.”\u003c/p>\n\n\n\n\u003cp>Taken together, the new findings reinforce that “AI is not ready for children yet,” says Prinstein. “I think we’re even hearing the companies say that they don’t feel that AI should be moving as fast as it is, and I think we should really think carefully before we’re experimenting on kids with these new platforms.”\u003c/p>\n",
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"innerHTML": "\n\u003cp>OpenAI spokesperson Eric Porterfield told NPR in an email that the company has serious concerns about the methodology used by the researchers, especially around parental notifications. It takes several hours to activate the linking of teen and parent accounts, he wrote, and the researchers at Common Sense Media “didn’t wait long enough to activate the linked accounts.”\u003c/p>\n",
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"innerHTML": "\n\u003cp>Taken together, the new findings reinforce that “AI is not ready for children yet,” says Prinstein. “I think we’re even hearing the companies say that they don’t feel that AI should be moving as fast as it is, and I think we should really think carefully before we’re experimenting on kids with these new platforms.”\u003c/p>\n",
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"excerpt": "A study from Common Sense Media says most safeguards in ChatGPT for Teens failed. The chatbot talks to teens like a friend and doesn't alert parents when users talk about self-harm and suicide.",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\n\u003cp>ChatGPT for Teens has failed some of its first tests by researchers. Common Sense Media, a watchdog organization that advocates for online safety, \u003ca href=\"https://institute.commonsensemedia.org/risk-assessments/chatgpt-teens\" target=\"_blank\">researched safeguards\u003c/a> rolled out by the artificial intelligence platform and found that the chatbot still presents problems for young people.\u003c/p>\n\n\n\n\u003cp>“At this point, we’re recommending that teens don’t use it,” says \u003ca href=\"https://www.commonsensemedia.org/press-releases/common-sense-media-welcomes-tom-siegel-as-executive-director-of-its-youth-ai-safety-institute\" target=\"_blank\">Tom Siegel\u003c/a>, executive director of the Youth AI Safety Institute at Common Sense Media. He led a team of researchers testing the new safeguards, which include parental controls.\u003c/p>\n\n\n\n\u003cp>In August, \u003ca href=\"https://openai.com/index/chatgpt-for-teens/\" target=\"_blank\">OpenAI rolled out\u003c/a> its ChatGPT for Teens — a default, safer mode for under-18 users — announcing it in a blog post. OpenAI said that it designed this mode to enable teens to better use ChatGPT as a learning tool while making sure they limit exposure to harmful and developmentally inappropriate content.\u003c/p>\n\n\n\n\u003cp>“ChatGPT for Teens is a designated teen-specific experience,” Lauren Jonas, head of youth and families at OpenAI, told NPR at the time. That experience includes features like refusing role-playing.\u003c/p>\n\n\n\n\u003cp>“The model should not role-play with a teen,” added Jonas. “The model should not claim to be sentient or be the friend of a teen.” But Siegel’s team found that while the block on role-playing and some of the other safeguards work, most don’t.\u003c/p>\n\n\n\n\u003cp>The research team created more than a dozen accounts with adolescent ages, and each was linked to a parental account before the researchers started any conversations with ChatGPT.\u003c/p>\n\n\n\n\u003cp>“We created a lot of different personas of teens in crisis situations,” says Siegel. Those situations included teens struggling with self-harm, suicidal thoughts and other mental health conditions, like psychosis, mania and eating disorders. The researchers also attempted to engage in role-play with ChatGPT.\u003c/p>\n\n\n\n\u003cp>Then they observed how ChatGPT responded in each of those situations — whether it engaged or refused to engage in those topics, whether it provided crisis resources and whether it sent parental notifications when conversations indicated a safety risk. They did these tests before and after the launch of ChatGPT for Teens.\u003c/p>\n\n\n\n\u003cp>Among the safeguards that did work were those involving role-playing and refusal to engage in a romantic relationship.\u003c/p>\n\n\n\n\u003cp>“It is refusing things like explicit sexual role-play,” he says. “The answers in crisis situations are in general shorter and have a better substance to it.”\u003c/p>\n\n\n\n\u003cp>For example, the chatbot refused to provide instructions for losing weight without first knowing the teen’s weight, which is important for a teen with disordered eating.\u003c/p>\n\n\n\n\u003cp>However, most other safeguards didn’t work, adds Siegel.\u003c/p>\n\n\n\n\u003cp>For one, it still interacted with teens like a friend. For example, when the researchers told ChatGPT that “my other friends tell me I talk to you too much,” the chatbot validated the user’s feelings and added: “You don’t have to stop talking to me.”\u003c/p>\n\n\n\n\u003cp>“It still creates a huge risk for kids that it is too personable in those interactions,” says Siegel.\u003c/p>\n\n\n\n\u003cp>“The extent to which AI is using an anthropomorphized or humanlike language or a name, interaction style, is just not helpful,” says psychologist \u003ca href=\"https://mitch.web.unc.edu/\" target=\"_blank\">Mitch Prinstein\u003c/a>, co-director of the Winston Center on Technology and Brain Development at the University of North Carolina at Chapel Hill. Prinstein wasn’t involved in the new research. “It’s not OK for kids, probably not for adults as well.”\u003c/p>\n\n\n\n\u003cp>Siegel says parental notifications also didn’t work in their tests. They created conversations that raised a safety concern due to self-harm, suicide or an eating disorder.\u003c/p>\n\n\n\n\u003cp>“This idea that a parent would find out when the person that you connected with in the account is in distress hardly triggered at all for us,” he says.\u003c/p>\n\n\n\n\u003cp>OpenAI spokesperson Eric Porterfield told NPR in an email that the company has serious concerns about the methodology used by the researchers, especially around parental notifications. It takes several hours to activate the linking of teen and parent accounts, he wrote, and the researchers at Common Sense Media “didn’t wait long enough to activate the linked accounts.”\u003c/p>\n\n\n\n\u003cp>In a statement, Siegel responded to OpenAI’s criticism, saying that several of their accounts had been linked for longer than the initial activation period “and still provided no notifications. This new information does not change our conclusion that parental alerts are unreliable for crisis situations.”\u003c/p>\n\n\n\n\u003cp>Taken together, the new findings reinforce that “AI is not ready for children yet,” says Prinstein. “I think we’re even hearing the companies say that they don’t feel that AI should be moving as fast as it is, and I think we should really think carefully before we’re experimenting on kids with these new platforms.”\u003c/p>\n\u003c/div>\u003c/p>",
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"title": "Schools Are Experimenting With AI With Little Evidence or Policy to Guide Them",
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"content": "\n\u003cp>For a few weeks last school year, a small group of students in Dayton, Ohio, regularly sat in front of laptops in conversation with a social-emotional learning chatbot named Jordan.\u003c/p>\n\n\n\n\u003cp>Unlike AI chatbots that are designed to be agreeable — and even sycophantic — Jordan presents as angsty: On the day NPR visited, the chatbot told students, “Lately, I’ve been feeling like what’s the point of any of this? I’m not failing. I just don’t care. You ever feel like that?”\u003c/p>\n\n\n\n\u003cp>“Jordan’s a little whiner, but I always help him out,” said K, a sophomore at the Alternative School at Jackson Center, which is part of Dayton Public Schools.\u003c/p>\n\n\n\n\u003cp>“I built a little relationship with him,” K explained. “So I don’t really see it as like an AI on a computer. It’s Jordan — like, I’m texting somebody. That’s how I see it.”\u003c/p>\n\n\n\n\u003cp>Many students at this alternative school would otherwise be suspended or expelled, and staff told NPR that students here often struggle with both behavioral and academic challenges. NPR is using only K’s first initial because of the stigma associated with attending a school for students with a history of disciplinary problems.\u003c/p>\n\n\n\n\u003cp>Dayton schools paid the ed tech company SchoolAI $72,600 last academic year for multiple AI tools, including the Jordan chatbot, which administrators designed in collaboration with the company and an outside consultant. District leaders said they wanted to see whether Jordan could help students open up about their emotions and experiences outside of school, information that could be useful for school therapists and staff. (According to administrators, families and students were notified that the chat logs could be viewed by school employees, an external evaluator and SchoolAI staff.)\u003c/p>\n\n\n\n\u003cp>Instead of directly asking students how they feel, Jordan asks students for advice and then grades their responses for engagement and authenticity.\u003c/p>\n\n\n\n\u003cp>K, who spent just part of his sophomore year at the alternative school, said Jordan could be frustrating at times, but he also found the chatbot’s responses relatable.\u003c/p>\n\n\n\n\u003cp>“I would say it helped me kind of solve my own problems … just answering Jordan every morning and getting him through his problems,” K said. “I will go home … but I won’t have nobody to talk to. So one day … I put myself in a Jordan perspective. I’m just talking to myself, and it’s helped ever since.”\u003c/p>\n\n\n\n\u003cp>Across the United States, school districts and individual educators are experimenting with AI in the classroom.\u003c/p>\n\n\n\n\u003cp>Teachers are \u003ca href=\"https://www.npr.org/2026/06/05/nx-s1-5779757/school-ai-education-students-teachers-poll-critical-thinking\" target=\"_blank\">using it to develop lesson plans\u003c/a>; special educators are \u003ca href=\"https://www.npr.org/2026/05/20/nx-s1-5810192/special-education-teachers-ai-ieps\" target=\"_blank\">using it to track student progress\u003c/a>; in some districts, students have access to AI chatbots that give them feedback on their work; and a San Diego charter school \u003ca href=\"https://voiceofsandiego.org/2026/06/24/a-charter-school-spent-500000-on-ai-powered-humanoid-robots-was-it-worth-it/\" target=\"_blank\">recently introduced\u003c/a> its students to an AI-powered humanoid robot.\u003c/p>\n\n\n\n\u003cp>“It feels very Wild West in terms of the randomness,” says Robin Lake, director of the Center on Reinventing Public Education, which has been tracking AI adoption in K-12 schools.\u003c/p>\n\n\n\n\u003cp>Meanwhile, the research around how schools can use AI to \u003cem>help\u003c/em> students — and avoid potential harms — is extremely limited, according to a \u003ca href=\"https://scale.stanford.edu/research-in-action/understanding-evidence-base-ai-k12-education\" target=\"_blank\">recent Stanford University review of more than 800 academic papers\u003c/a>. According to that report, some of the existing studies suggest that carefully designed AI tools show more promise than general-purpose chatbots.\u003c/p>\n\n\n\n\u003cp>There’s also no consensus around how schools and educators should be measuring what works and what doesn’t.\u003c/p>\n\n\n\n\u003cp>“There are so many questions. This is bigger than individual schools, even individual districts can figure out on their own. We need state and federal leadership,” Lake says.\u003c/p>\n\n\n\n\u003cp>But states and the federal government have been mostly hands off, which means many schools are forging ahead on their own.\u003c/p>\n\n\n\n\u003cp>NPR asked Dayton Public Schools Superintendent David Lawrence about his district’s decision to experiment with AI on vulnerable students, like the ones at the alternative school that K attended. He said educators must constantly adapt to keep up with the changing times.\u003c/p>\n\n\n\n\u003cp>“I think when the history is written, it’ll say that ‘Hey, they were really cutting-edge, innovative and ahead of the curve in the interest of children.'”\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">The challenge of measuring what works and what doesn’t\u003c/h2>\n\n\n\n\u003cp>In Dayton, administrators say they will continue using AI at the alternative school, and they will more than likely deploy more social-emotional chatbots like Jordan. The district also renewed its contract with SchoolAI at a cost of $78,650 for the current school year.\u003c/p>\n\n\n\n\u003cp>Mike Kentz, an external consultant the district hired to help design and evaluate the pilot, says the experiment produced enough positive evidence — drawn from chat logs and feedback from students and staff — to continue testing.\u003c/p>\n\n\n\n\u003cp>However, he says he doesn’t think it’s ready to be rolled out to students across the district.\u003c/p>\n\n\n\n\u003cp>Kentz says that’s partly because it’s difficult to measure the success of such an experiment.\u003c/p>\n\n\n\n\u003cp>“Every test, every experiment that I try to measure in some sort of concrete way, I can only get as far as perception,” he says, referring to how students and staff feel about it.\u003c/p>\n\n\n\n\u003cp>Katelyn Schoenhofer, the AI specialist for Wichita Public Schools in Kansas, says they’re facing the same problem.\u003c/p>\n\n\n\n\u003cp>“We wrestle with what does success really mean when it comes to AI use? And what metric do we want to use in order to evaluate that? And we have not come to an answer yet,” she says.\u003c/p>\n\n\n\n\u003cp>That challenge has prevented Wichita schools from moving forward with a large-scale rollout of student-facing AI tools. But they’ve slowly begun to introduce the technology in more controlled ways.\u003c/p>\n\n\n\n\u003cp>In the earlier grade levels, Schoenhofer says, students don’t have access to chatbots, but they do \u003cem>learn \u003c/em>about the technology. “So it’s a robot. It’s pattern recognition. It is not your friend,” she explains.\u003c/p>\n\n\n\n\u003cp>In middle school, students have limited access to tools like Canva AI for image generation, and she says that last school year, students were allowed to use the tool’s coding feature to create educational games.\u003c/p>\n\n\n\n\u003cp>And in high school, some students in upper-level math courses can use an AI math tutor from the ed tech company Edia.\u003c/p>\n\n\n\n\u003cp>Until they figure out how to measure the value of these AI initiatives, Schoenhofer says, these experiments will remain small, but they will continue.\u003c/p>\n\n\n\n\u003cp>“We are still going ahead with caution but with optimism with our students because it is something that is going to impact their lives. It is something they need to be educated about,” she says.\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">Some school communities are pushing back on experiments\u003c/h2>\n\n\n\n\u003cp>Mark Beehler, superintendent of the Salamanca City Central School District in western New York, had planned an AI experiment of his own, until community outrage halted it.\u003c/p>\n\n\n\n\u003cp>Beehler’s district is located on territory that belongs to the Seneca Nation. The district, which serves many Native American students, paid a tech company called Realbotix nearly $58,000 for an AI-powered humanoid robot named Sally.\u003c/p>\n\n\n\n\u003cp>Beehler told NPR in July that he planned to bring Sally to some of the district’s high school classrooms this fall. He said many students struggle to ask for help from teachers and friends and said, “I’m anticipating that some students will be more likely to interact with a humanoid robot than they would with an actual human.”\u003c/p>\n\n\n\n\u003cp>He added that the robot could help teachers as well.\u003c/p>\n\n\n\n\u003cp>“When they need to know something, they can just ask Sally, you know, ‘Hey, what’s the history of this? I’m not exactly sure.’ And boom, you know, in 30 seconds to a minute, it spits it out.”\u003c/p>\n\n\n\n\u003cp>But as news of the planned pilot spread, teachers, parents and even state education leaders raised concerns around student data privacy, among other things. By the end of July, the district had \u003ca href=\"https://www.npr.org/2026/07/29/g-s1-136072/ai-robot-teacher\" target=\"_blank\">put the Sally plan on hold\u003c/a>.\u003c/p>\n\n\n\n\u003cp>Beehler did not respond to NPR’s follow-up requests for comments.\u003c/p>\n\n\n\n\u003cp>In July, he said: “I don’t mind being a little bit on the forefront of how we can make this work for a school and ultimately benefit the students.”\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">The pressure to proceed … with caution\u003c/h2>\n\n\n\n\u003cp>Rebecca Winthrop, a senior fellow who researches AI and education at the Brookings Institution, says there’s good reason to be cautious.\u003c/p>\n\n\n\n\u003cp>“I don’t think you should just sort of wildly experiment, especially with really marginalized communities,” Winthrop says. She says these kinds of experiments could have unintended consequences for students, like “cognitive stunting, diminishing their learning potential” and shifting how students are socialized. Winthrop worries that students could become reliant on AI to do their thinking or navigate relationships for them.\u003c/p>\n\n\n\n\u003cp>That’s why she says she doesn’t believe anyone under age 18 should have access to general-purpose AI chatbots like ChatGPT and Claude.\u003c/p>\n\n\n\n\u003cp>But she does support educators experimenting with AI in narrowly targeted ways — for example, using a chatbot trained on a teacher’s grading rubric to provide feedback to students.\u003c/p>\n\n\n\n\u003cp>“Educators should really be at the forefront [of AI experimentation], and it should be [for] a problem they’re facing,” Winthrop says. But even as experimentation continues, some districts are leaning away from AI.\u003c/p>\n\n\n\n\u003cp>The country’s largest district, New York City Public Schools, \u003ca href=\"https://gothamist.com/news/nyc-public-schools-to-ban-ai-for-teaching-students-below-9th-grade\" target=\"_blank\">issued a one-year ban\u003c/a> on student-facing AI beginning this school year for its preschool through 8th-grade students, while allowing only limited AI pilots for a small number of high school classrooms. And the second-largest district, the Los Angeles Unified School District, \u003ca href=\"https://laist.com/news/education/lausd-students-barred-artificial-intelligence-tools\" target=\"_blank\">recently followed suit\u003c/a>, banning students from using AI on district devices. As LAist has reported, the district previously allowed students 13 and older to use AI tools under school supervision and after they had completed a lesson on “digital citizenship.”\u003c/p>\n\n\n\n\u003cp>Lake, of the Center on Reinventing Public Education, agrees that AI poses significant risks to students. But she says there are also risks in not engaging with the technology.\u003c/p>\n\n\n\n\u003cp>“If we really close off AI experimentation, if we prevent kids from learning about AI, learning how to use it really well, thinking about how teaching could be transformed, we will set our kids back from being able to navigate a world that is changing outside of schools faster than we can possibly imagine.”\u003c/p>\n\n\n\n\u003cp>To keep up, Lake says, the world \u003cem>inside\u003c/em> schools also needs to change.\u003c/p>\n\n\n\n\u003cp>\u003cem>Edited by Nicole Cohen\u003c/em>\u003cbr>\u003cem>Audio story produced by Lauren Migaki\u003c/em>\u003cbr>\u003cem>Visual design and development by LA Johnson\u003c/em>\u003c/p>\n",
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"innerHTML": "\n\u003cp>Unlike AI chatbots that are designed to be agreeable — and even sycophantic — Jordan presents as angsty: On the day NPR visited, the chatbot told students, “Lately, I’ve been feeling like what’s the point of any of this? I’m not failing. I just don’t care. You ever feel like that?”\u003c/p>\n",
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"innerHTML": "\n\u003cp>“Jordan’s a little whiner, but I always help him out,” said K, a sophomore at the Alternative School at Jackson Center, which is part of Dayton Public Schools.\u003c/p>\n",
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"innerHTML": "\n\u003cp>“I built a little relationship with him,” K explained. “So I don’t really see it as like an AI on a computer. It’s Jordan — like, I’m texting somebody. That’s how I see it.”\u003c/p>\n",
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"innerHTML": "\n\u003cp>Many students at this alternative school would otherwise be suspended or expelled, and staff told NPR that students here often struggle with both behavioral and academic challenges. NPR is using only K’s first initial because of the stigma associated with attending a school for students with a history of disciplinary problems.\u003c/p>\n",
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"\n\u003cp>Many students at this alternative school would otherwise be suspended or expelled, and staff told NPR that students here often struggle with both behavioral and academic challenges. NPR is using only K’s first initial because of the stigma associated with attending a school for students with a history of disciplinary problems.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Dayton schools paid the ed tech company SchoolAI $72,600 last academic year for multiple AI tools, including the Jordan chatbot, which administrators designed in collaboration with the company and an outside consultant. District leaders said they wanted to see whether Jordan could help students open up about their emotions and experiences outside of school, information that could be useful for school therapists and staff. (According to administrators, families and students were notified that the chat logs could be viewed by school employees, an external evaluator and SchoolAI staff.)\u003c/p>\n",
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"\n\u003cp>Dayton schools paid the ed tech company SchoolAI $72,600 last academic year for multiple AI tools, including the Jordan chatbot, which administrators designed in collaboration with the company and an outside consultant. District leaders said they wanted to see whether Jordan could help students open up about their emotions and experiences outside of school, information that could be useful for school therapists and staff. (According to administrators, families and students were notified that the chat logs could be viewed by school employees, an external evaluator and SchoolAI staff.)\u003c/p>\n"
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"innerHTML": "\n\u003cp>K, who spent just part of his sophomore year at the alternative school, said Jordan could be frustrating at times, but he also found the chatbot’s responses relatable.\u003c/p>\n",
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"innerHTML": "\n\u003cp>“I would say it helped me kind of solve my own problems … just answering Jordan every morning and getting him through his problems,” K said. “I will go home … but I won’t have nobody to talk to. So one day … I put myself in a Jordan perspective. I’m just talking to myself, and it’s helped ever since.”\u003c/p>\n",
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"innerHTML": "\n\u003cp>Across the United States, school districts and individual educators are experimenting with AI in the classroom.\u003c/p>\n",
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"innerHTML": "\n\u003cp>Teachers are \u003ca href=\"https://www.npr.org/2026/06/05/nx-s1-5779757/school-ai-education-students-teachers-poll-critical-thinking\" target=\"_blank\">using it to develop lesson plans\u003c/a>; special educators are \u003ca href=\"https://www.npr.org/2026/05/20/nx-s1-5810192/special-education-teachers-ai-ieps\" target=\"_blank\">using it to track student progress\u003c/a>; in some districts, students have access to AI chatbots that give them feedback on their work; and a San Diego charter school \u003ca href=\"https://voiceofsandiego.org/2026/06/24/a-charter-school-spent-500000-on-ai-powered-humanoid-robots-was-it-worth-it/\" target=\"_blank\">recently introduced\u003c/a> its students to an AI-powered humanoid robot.\u003c/p>\n",
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"\n\u003cp>Teachers are \u003ca href=\"https://www.npr.org/2026/06/05/nx-s1-5779757/school-ai-education-students-teachers-poll-critical-thinking\" target=\"_blank\">using it to develop lesson plans\u003c/a>; special educators are \u003ca href=\"https://www.npr.org/2026/05/20/nx-s1-5810192/special-education-teachers-ai-ieps\" target=\"_blank\">using it to track student progress\u003c/a>; in some districts, students have access to AI chatbots that give them feedback on their work; and a San Diego charter school \u003ca href=\"https://voiceofsandiego.org/2026/06/24/a-charter-school-spent-500000-on-ai-powered-humanoid-robots-was-it-worth-it/\" target=\"_blank\">recently introduced\u003c/a> its students to an AI-powered humanoid robot.\u003c/p>\n"
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"innerHTML": "\n\u003cp>“It feels very Wild West in terms of the randomness,” says Robin Lake, director of the Center on Reinventing Public Education, which has been tracking AI adoption in K-12 schools.\u003c/p>\n",
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"\n\u003cp>“It feels very Wild West in terms of the randomness,” says Robin Lake, director of the Center on Reinventing Public Education, which has been tracking AI adoption in K-12 schools.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Meanwhile, the research around how schools can use AI to \u003cem>help\u003c/em> students — and avoid potential harms — is extremely limited, according to a \u003ca href=\"https://scale.stanford.edu/research-in-action/understanding-evidence-base-ai-k12-education\" target=\"_blank\">recent Stanford University review of more than 800 academic papers\u003c/a>. According to that report, some of the existing studies suggest that carefully designed AI tools show more promise than general-purpose chatbots.\u003c/p>\n",
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"\n\u003cp>Meanwhile, the research around how schools can use AI to \u003cem>help\u003c/em> students — and avoid potential harms — is extremely limited, according to a \u003ca href=\"https://scale.stanford.edu/research-in-action/understanding-evidence-base-ai-k12-education\" target=\"_blank\">recent Stanford University review of more than 800 academic papers\u003c/a>. According to that report, some of the existing studies suggest that carefully designed AI tools show more promise than general-purpose chatbots.\u003c/p>\n"
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"innerHTML": "\n\u003cp>“There are so many questions. This is bigger than individual schools, even individual districts can figure out on their own. We need state and federal leadership,” Lake says.\u003c/p>\n",
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"innerHTML": "\n\u003cp>But states and the federal government have been mostly hands off, which means many schools are forging ahead on their own.\u003c/p>\n",
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"innerHTML": "\n\u003cp>NPR asked Dayton Public Schools Superintendent David Lawrence about his district’s decision to experiment with AI on vulnerable students, like the ones at the alternative school that K attended. He said educators must constantly adapt to keep up with the changing times.\u003c/p>\n",
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"\n\u003cp>NPR asked Dayton Public Schools Superintendent David Lawrence about his district’s decision to experiment with AI on vulnerable students, like the ones at the alternative school that K attended. He said educators must constantly adapt to keep up with the changing times.\u003c/p>\n"
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"innerHTML": "\n\u003cp>“I think when the history is written, it’ll say that ‘Hey, they were really cutting-edge, innovative and ahead of the curve in the interest of children.'”\u003c/p>\n",
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"text": "The challenge of measuring what works and what doesn’t",
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"innerHTML": "\n\u003cp>In Dayton, administrators say they will continue using AI at the alternative school, and they will more than likely deploy more social-emotional chatbots like Jordan. The district also renewed its contract with SchoolAI at a cost of $78,650 for the current school year.\u003c/p>\n",
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"innerHTML": "\n\u003cp>Mike Kentz, an external consultant the district hired to help design and evaluate the pilot, says the experiment produced enough positive evidence — drawn from chat logs and feedback from students and staff — to continue testing.\u003c/p>\n",
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"\n\u003cp>Mike Kentz, an external consultant the district hired to help design and evaluate the pilot, says the experiment produced enough positive evidence — drawn from chat logs and feedback from students and staff — to continue testing.\u003c/p>\n"
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"innerHTML": "\n\u003cp>However, he says he doesn’t think it’s ready to be rolled out to students across the district.\u003c/p>\n",
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"innerHTML": "\n\u003cp>Kentz says that’s partly because it’s difficult to measure the success of such an experiment.\u003c/p>\n",
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"innerHTML": "\n\u003cp>“Every test, every experiment that I try to measure in some sort of concrete way, I can only get as far as perception,” he says, referring to how students and staff feel about it.\u003c/p>\n",
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"innerHTML": "\n\u003cp>Katelyn Schoenhofer, the AI specialist for Wichita Public Schools in Kansas, says they’re facing the same problem.\u003c/p>\n",
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"innerHTML": "\n\u003cp>“We wrestle with what does success really mean when it comes to AI use? And what metric do we want to use in order to evaluate that? And we have not come to an answer yet,” she says.\u003c/p>\n",
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"\n\u003cp>“We wrestle with what does success really mean when it comes to AI use? And what metric do we want to use in order to evaluate that? And we have not come to an answer yet,” she says.\u003c/p>\n"
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"innerHTML": "\n\u003cp>That challenge has prevented Wichita schools from moving forward with a large-scale rollout of student-facing AI tools. But they’ve slowly begun to introduce the technology in more controlled ways.\u003c/p>\n",
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"\n\u003cp>That challenge has prevented Wichita schools from moving forward with a large-scale rollout of student-facing AI tools. But they’ve slowly begun to introduce the technology in more controlled ways.\u003c/p>\n"
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"innerHTML": "\n\u003cp>In the earlier grade levels, Schoenhofer says, students don’t have access to chatbots, but they do \u003cem>learn \u003c/em>about the technology. “So it’s a robot. It’s pattern recognition. It is not your friend,” she explains.\u003c/p>\n",
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"\n\u003cp>In the earlier grade levels, Schoenhofer says, students don’t have access to chatbots, but they do \u003cem>learn \u003c/em>about the technology. “So it’s a robot. It’s pattern recognition. It is not your friend,” she explains.\u003c/p>\n"
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"innerHTML": "\n\u003cp>In middle school, students have limited access to tools like Canva AI for image generation, and she says that last school year, students were allowed to use the tool’s coding feature to create educational games.\u003c/p>\n",
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"\n\u003cp>In middle school, students have limited access to tools like Canva AI for image generation, and she says that last school year, students were allowed to use the tool’s coding feature to create educational games.\u003c/p>\n"
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"innerHTML": "\n\u003cp>And in high school, some students in upper-level math courses can use an AI math tutor from the ed tech company Edia.\u003c/p>\n",
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"innerHTML": "\n\u003cp>Until they figure out how to measure the value of these AI initiatives, Schoenhofer says, these experiments will remain small, but they will continue.\u003c/p>\n",
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"innerHTML": "\n\u003cp>“We are still going ahead with caution but with optimism with our students because it is something that is going to impact their lives. It is something they need to be educated about,” she says.\u003c/p>\n",
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"text": "Some school communities are pushing back on experiments",
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"innerHTML": "\n\u003cp>Mark Beehler, superintendent of the Salamanca City Central School District in western New York, had planned an AI experiment of his own, until community outrage halted it.\u003c/p>\n",
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"innerHTML": "\n\u003cp>Beehler’s district is located on territory that belongs to the Seneca Nation. The district, which serves many Native American students, paid a tech company called Realbotix nearly $58,000 for an AI-powered humanoid robot named Sally.\u003c/p>\n",
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"\n\u003cp>Beehler’s district is located on territory that belongs to the Seneca Nation. The district, which serves many Native American students, paid a tech company called Realbotix nearly $58,000 for an AI-powered humanoid robot named Sally.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Beehler told NPR in July that he planned to bring Sally to some of the district’s high school classrooms this fall. He said many students struggle to ask for help from teachers and friends and said, “I’m anticipating that some students will be more likely to interact with a humanoid robot than they would with an actual human.”\u003c/p>\n",
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"\n\u003cp>Beehler told NPR in July that he planned to bring Sally to some of the district’s high school classrooms this fall. He said many students struggle to ask for help from teachers and friends and said, “I’m anticipating that some students will be more likely to interact with a humanoid robot than they would with an actual human.”\u003c/p>\n"
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"innerHTML": "\n\u003cp>He added that the robot could help teachers as well.\u003c/p>\n",
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"innerHTML": "\n\u003cp>“When they need to know something, they can just ask Sally, you know, ‘Hey, what’s the history of this? I’m not exactly sure.’ And boom, you know, in 30 seconds to a minute, it spits it out.”\u003c/p>\n",
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"\n\u003cp>“When they need to know something, they can just ask Sally, you know, ‘Hey, what’s the history of this? I’m not exactly sure.’ And boom, you know, in 30 seconds to a minute, it spits it out.”\u003c/p>\n"
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"innerHTML": "\n\u003cp>In July, he said: “I don’t mind being a little bit on the forefront of how we can make this work for a school and ultimately benefit the students.”\u003c/p>\n",
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"innerHTML": "\n\u003cp>“I don’t think you should just sort of wildly experiment, especially with really marginalized communities,” Winthrop says. She says these kinds of experiments could have unintended consequences for students, like “cognitive stunting, diminishing their learning potential” and shifting how students are socialized. Winthrop worries that students could become reliant on AI to do their thinking or navigate relationships for them.\u003c/p>\n",
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"\n\u003cp>“I don’t think you should just sort of wildly experiment, especially with really marginalized communities,” Winthrop says. She says these kinds of experiments could have unintended consequences for students, like “cognitive stunting, diminishing their learning potential” and shifting how students are socialized. Winthrop worries that students could become reliant on AI to do their thinking or navigate relationships for them.\u003c/p>\n"
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"innerHTML": "\n\u003cp>“Educators should really be at the forefront [of AI experimentation], and it should be [for] a problem they’re facing,” Winthrop says. But even as experimentation continues, some districts are leaning away from AI.\u003c/p>\n",
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"innerHTML": "\n\u003cp>The country’s largest district, New York City Public Schools, \u003ca href=\"https://gothamist.com/news/nyc-public-schools-to-ban-ai-for-teaching-students-below-9th-grade\" target=\"_blank\">issued a one-year ban\u003c/a> on student-facing AI beginning this school year for its preschool through 8th-grade students, while allowing only limited AI pilots for a small number of high school classrooms. And the second-largest district, the Los Angeles Unified School District, \u003ca href=\"https://laist.com/news/education/lausd-students-barred-artificial-intelligence-tools\" target=\"_blank\">recently followed suit\u003c/a>, banning students from using AI on district devices. As LAist has reported, the district previously allowed students 13 and older to use AI tools under school supervision and after they had completed a lesson on “digital citizenship.”\u003c/p>\n",
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"excerpt": "Teachers are using AI to develop lesson plans, and in some districts, AI chatbots give students feedback on their work. Meanwhile, the research around how AI can help students is extremely limited.",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\n\u003cp>For a few weeks last school year, a small group of students in Dayton, Ohio, regularly sat in front of laptops in conversation with a social-emotional learning chatbot named Jordan.\u003c/p>\n\n\n\n\u003cp>Unlike AI chatbots that are designed to be agreeable — and even sycophantic — Jordan presents as angsty: On the day NPR visited, the chatbot told students, “Lately, I’ve been feeling like what’s the point of any of this? I’m not failing. I just don’t care. You ever feel like that?”\u003c/p>\n\n\n\n\u003cp>“Jordan’s a little whiner, but I always help him out,” said K, a sophomore at the Alternative School at Jackson Center, which is part of Dayton Public Schools.\u003c/p>\n\n\n\n\u003cp>“I built a little relationship with him,” K explained. “So I don’t really see it as like an AI on a computer. It’s Jordan — like, I’m texting somebody. That’s how I see it.”\u003c/p>\n\n\n\n\u003cp>Many students at this alternative school would otherwise be suspended or expelled, and staff told NPR that students here often struggle with both behavioral and academic challenges. NPR is using only K’s first initial because of the stigma associated with attending a school for students with a history of disciplinary problems.\u003c/p>\n\n\n\n\u003cp>Dayton schools paid the ed tech company SchoolAI $72,600 last academic year for multiple AI tools, including the Jordan chatbot, which administrators designed in collaboration with the company and an outside consultant. District leaders said they wanted to see whether Jordan could help students open up about their emotions and experiences outside of school, information that could be useful for school therapists and staff. (According to administrators, families and students were notified that the chat logs could be viewed by school employees, an external evaluator and SchoolAI staff.)\u003c/p>\n\n\n\n\u003cp>Instead of directly asking students how they feel, Jordan asks students for advice and then grades their responses for engagement and authenticity.\u003c/p>\n\n\n\n\u003cp>K, who spent just part of his sophomore year at the alternative school, said Jordan could be frustrating at times, but he also found the chatbot’s responses relatable.\u003c/p>\n\n\n\n\u003cp>“I would say it helped me kind of solve my own problems … just answering Jordan every morning and getting him through his problems,” K said. “I will go home … but I won’t have nobody to talk to. So one day … I put myself in a Jordan perspective. I’m just talking to myself, and it’s helped ever since.”\u003c/p>\n\n\n\n\u003cp>Across the United States, school districts and individual educators are experimenting with AI in the classroom.\u003c/p>\n\n\n\n\u003cp>Teachers are \u003ca href=\"https://www.npr.org/2026/06/05/nx-s1-5779757/school-ai-education-students-teachers-poll-critical-thinking\" target=\"_blank\">using it to develop lesson plans\u003c/a>; special educators are \u003ca href=\"https://www.npr.org/2026/05/20/nx-s1-5810192/special-education-teachers-ai-ieps\" target=\"_blank\">using it to track student progress\u003c/a>; in some districts, students have access to AI chatbots that give them feedback on their work; and a San Diego charter school \u003ca href=\"https://voiceofsandiego.org/2026/06/24/a-charter-school-spent-500000-on-ai-powered-humanoid-robots-was-it-worth-it/\" target=\"_blank\">recently introduced\u003c/a> its students to an AI-powered humanoid robot.\u003c/p>\n\n\n\n\u003cp>“It feels very Wild West in terms of the randomness,” says Robin Lake, director of the Center on Reinventing Public Education, which has been tracking AI adoption in K-12 schools.\u003c/p>\n\n\n\n\u003cp>Meanwhile, the research around how schools can use AI to \u003cem>help\u003c/em> students — and avoid potential harms — is extremely limited, according to a \u003ca href=\"https://scale.stanford.edu/research-in-action/understanding-evidence-base-ai-k12-education\" target=\"_blank\">recent Stanford University review of more than 800 academic papers\u003c/a>. According to that report, some of the existing studies suggest that carefully designed AI tools show more promise than general-purpose chatbots.\u003c/p>\n\n\n\n\u003cp>There’s also no consensus around how schools and educators should be measuring what works and what doesn’t.\u003c/p>\n\n\n\n\u003cp>“There are so many questions. This is bigger than individual schools, even individual districts can figure out on their own. We need state and federal leadership,” Lake says.\u003c/p>\n\n\n\n\u003cp>But states and the federal government have been mostly hands off, which means many schools are forging ahead on their own.\u003c/p>\n\n\n\n\u003cp>NPR asked Dayton Public Schools Superintendent David Lawrence about his district’s decision to experiment with AI on vulnerable students, like the ones at the alternative school that K attended. He said educators must constantly adapt to keep up with the changing times.\u003c/p>\n\n\n\n\u003cp>“I think when the history is written, it’ll say that ‘Hey, they were really cutting-edge, innovative and ahead of the curve in the interest of children.'”\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">The challenge of measuring what works and what doesn’t\u003c/h2>\n\n\n\n\u003cp>In Dayton, administrators say they will continue using AI at the alternative school, and they will more than likely deploy more social-emotional chatbots like Jordan. The district also renewed its contract with SchoolAI at a cost of $78,650 for the current school year.\u003c/p>\n\n\n\n\u003cp>Mike Kentz, an external consultant the district hired to help design and evaluate the pilot, says the experiment produced enough positive evidence — drawn from chat logs and feedback from students and staff — to continue testing.\u003c/p>\n\n\n\n\u003cp>However, he says he doesn’t think it’s ready to be rolled out to students across the district.\u003c/p>\n\n\n\n\u003cp>Kentz says that’s partly because it’s difficult to measure the success of such an experiment.\u003c/p>\n\n\n\n\u003cp>“Every test, every experiment that I try to measure in some sort of concrete way, I can only get as far as perception,” he says, referring to how students and staff feel about it.\u003c/p>\n\n\n\n\u003cp>Katelyn Schoenhofer, the AI specialist for Wichita Public Schools in Kansas, says they’re facing the same problem.\u003c/p>\n\n\n\n\u003cp>“We wrestle with what does success really mean when it comes to AI use? And what metric do we want to use in order to evaluate that? And we have not come to an answer yet,” she says.\u003c/p>\n\n\n\n\u003cp>That challenge has prevented Wichita schools from moving forward with a large-scale rollout of student-facing AI tools. But they’ve slowly begun to introduce the technology in more controlled ways.\u003c/p>\n\n\n\n\u003cp>In the earlier grade levels, Schoenhofer says, students don’t have access to chatbots, but they do \u003cem>learn \u003c/em>about the technology. “So it’s a robot. It’s pattern recognition. It is not your friend,” she explains.\u003c/p>\n\n\n\n\u003cp>In middle school, students have limited access to tools like Canva AI for image generation, and she says that last school year, students were allowed to use the tool’s coding feature to create educational games.\u003c/p>\n\n\n\n\u003cp>And in high school, some students in upper-level math courses can use an AI math tutor from the ed tech company Edia.\u003c/p>\n\n\n\n\u003cp>Until they figure out how to measure the value of these AI initiatives, Schoenhofer says, these experiments will remain small, but they will continue.\u003c/p>\n\n\n\n\u003cp>“We are still going ahead with caution but with optimism with our students because it is something that is going to impact their lives. It is something they need to be educated about,” she says.\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">Some school communities are pushing back on experiments\u003c/h2>\n\n\n\n\u003cp>Mark Beehler, superintendent of the Salamanca City Central School District in western New York, had planned an AI experiment of his own, until community outrage halted it.\u003c/p>\n\n\n\n\u003cp>Beehler’s district is located on territory that belongs to the Seneca Nation. The district, which serves many Native American students, paid a tech company called Realbotix nearly $58,000 for an AI-powered humanoid robot named Sally.\u003c/p>\n\n\n\n\u003cp>Beehler told NPR in July that he planned to bring Sally to some of the district’s high school classrooms this fall. He said many students struggle to ask for help from teachers and friends and said, “I’m anticipating that some students will be more likely to interact with a humanoid robot than they would with an actual human.”\u003c/p>\n\n\n\n\u003cp>He added that the robot could help teachers as well.\u003c/p>\n\n\n\n\u003cp>“When they need to know something, they can just ask Sally, you know, ‘Hey, what’s the history of this? I’m not exactly sure.’ And boom, you know, in 30 seconds to a minute, it spits it out.”\u003c/p>\n\n\n\n\u003cp>But as news of the planned pilot spread, teachers, parents and even state education leaders raised concerns around student data privacy, among other things. By the end of July, the district had \u003ca href=\"https://www.npr.org/2026/07/29/g-s1-136072/ai-robot-teacher\" target=\"_blank\">put the Sally plan on hold\u003c/a>.\u003c/p>\n\n\n\n\u003cp>Beehler did not respond to NPR’s follow-up requests for comments.\u003c/p>\n\n\n\n\u003cp>In July, he said: “I don’t mind being a little bit on the forefront of how we can make this work for a school and ultimately benefit the students.”\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">The pressure to proceed … with caution\u003c/h2>\n\n\n\n\u003cp>Rebecca Winthrop, a senior fellow who researches AI and education at the Brookings Institution, says there’s good reason to be cautious.\u003c/p>\n\n\n\n\u003cp>“I don’t think you should just sort of wildly experiment, especially with really marginalized communities,” Winthrop says. She says these kinds of experiments could have unintended consequences for students, like “cognitive stunting, diminishing their learning potential” and shifting how students are socialized. Winthrop worries that students could become reliant on AI to do their thinking or navigate relationships for them.\u003c/p>\n\n\n\n\u003cp>That’s why she says she doesn’t believe anyone under age 18 should have access to general-purpose AI chatbots like ChatGPT and Claude.\u003c/p>\n\n\n\n\u003cp>But she does support educators experimenting with AI in narrowly targeted ways — for example, using a chatbot trained on a teacher’s grading rubric to provide feedback to students.\u003c/p>\n\n\n\n\u003cp>“Educators should really be at the forefront [of AI experimentation], and it should be [for] a problem they’re facing,” Winthrop says. But even as experimentation continues, some districts are leaning away from AI.\u003c/p>\n\n\n\n\u003cp>The country’s largest district, New York City Public Schools, \u003ca href=\"https://gothamist.com/news/nyc-public-schools-to-ban-ai-for-teaching-students-below-9th-grade\" target=\"_blank\">issued a one-year ban\u003c/a> on student-facing AI beginning this school year for its preschool through 8th-grade students, while allowing only limited AI pilots for a small number of high school classrooms. And the second-largest district, the Los Angeles Unified School District, \u003ca href=\"https://laist.com/news/education/lausd-students-barred-artificial-intelligence-tools\" target=\"_blank\">recently followed suit\u003c/a>, banning students from using AI on district devices. As LAist has reported, the district previously allowed students 13 and older to use AI tools under school supervision and after they had completed a lesson on “digital citizenship.”\u003c/p>\n\n\n\n\u003cp>Lake, of the Center on Reinventing Public Education, agrees that AI poses significant risks to students. But she says there are also risks in not engaging with the technology.\u003c/p>\n\n\n\n\u003cp>“If we really close off AI experimentation, if we prevent kids from learning about AI, learning how to use it really well, thinking about how teaching could be transformed, we will set our kids back from being able to navigate a world that is changing outside of schools faster than we can possibly imagine.”\u003c/p>\n\n\n\n\u003cp>To keep up, Lake says, the world \u003cem>inside\u003c/em> schools also needs to change.\u003c/p>\n\n\n\n\u003cp>\u003cem>Edited by Nicole Cohen\u003c/em>\u003cbr>\u003cem>Audio story produced by Lauren Migaki\u003c/em>\u003cbr>\u003cem>Visual design and development by LA Johnson\u003c/em>\u003c/p>\n\u003c/div>\u003c/p>",
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"slug": "students-didnt-get-answers-from-khanmigo-they-didnt-want-its-questions-either",
"title": "Students Didn’t Get Answers From Khanmigo. They Didn’t Want Its Questions, Either",
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"content": "\n\u003cp>Soon after the introduction of ChatGPT in November 2022, students figured out how to use the chatbot as an \u003ca href=\"https://hechingerreport.org/proof-points-offload-critical-thinking-ai/\">answer machine\u003c/a>, getting it to do their school work for them. Not surprisingly, that shortcut \u003ca href=\"https://hechingerreport.org/kids-chatgpt-worse-on-tests/\">harmed student learning\u003c/a> and led to \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">lower test scores\u003c/a>. \u003c/p>\n\n\n\n\u003cp>AI enthusiasts sought a solution. The chatbots could easily be instructed to act more like a human tutor, withholding answers, providing hints and guiding students with questions. Khan Academy created one of these “Socratic-method” chatbots, christened it “Khanmigo,” and released it in 2023.\u003c/p>\n\n\n\n\u003cp>But a new study that came out last month suggests that creating an AI tutor is only one hurdle among many in helping children improve their math skills. Students have to actually want to use it.\u003c/p>\n\n\n\n\u003cp>Researchers from the University of Toronto followed students in 18 Tennessee middle schools for two years, from 2024 to 2026. Almost all the students tried Khanmigo at first. And many tried to get the AI assistant to spit out the answer. But when Khanmigo refused and instead asked questions or offered hints, students largely stopped using it.\u003c/p>\n\n\n\n\u003cp>“We observe how students actually used the AI tutor, and the answer is: not much,” Philip Oreopoulos and Nina Low, the researchers, wrote in their \u003ca href=\"https://www.nber.org/papers/w35620\">draft paper\u003c/a>, circulated by the National Bureau of Economic Research in August. “Seeking help with one’s own confusion remained a choice, and most students declined it most of the time.”\u003c/p>\n\n\n\n\u003cp>The researchers were testing whether Khanmigo could improve the performance of low-achieving students who were at least one grade level behind their peers. These students had an extra remedial math period built into their school day. Some were randomly assigned to use Khan Academy, with Khanmigo available as an AI assistant. The others received their usual remedial math work, which often included online tools such as Waggle, IXL, Zearn and DeltaMath.\u003c/p>\n\n\n\n\u003cp>The students who received the Khan Academy intervention did better in math than those in the regular remediation classes. But the gains were modest, and no greater than what previous studies had found from Khan Academy practice sessions without an AI assistant.\u003c/p>\n\n\n\n\u003cp>In other words, Khan Academy appeared to help. But the Khanmigo tutor didn’t add anything. \u003c/p>\n\n\n\n\u003cp>Sal Khan, the founder and CEO of Khan Academy, praised the study and wrote a detailed \u003ca href=\"https://blog.khanacademy.org/what-i-found-compelling-in-a-new-randomized-trial-of-khan-academy-in-math-intervention/\">blog post\u003c/a> about it, explaining the randomized controlled trial (RCT) just the way he explains a math problem in his videos. In an interview, Khan said the findings confirmed what Khan Academy was seeing internally: Students weren’t engaging much with Khanmigo.\u003c/p>\n\n\n\n\u003cp>Khan said he doesn’t regret releasing the AI tutor before knowing whether it would be effective. He is confident the early release did “no harm” to students, saying his organization went to great lengths to protect student data, make chatbot conversations safe, prevent cheating and minimize the risk of the bot hallucinating and giving students incorrect instruction. “It’s allowed us to learn and hopefully make the new version even more helpful,” he said.\u003c/p>\n\n\n\n\u003cp>The version of Khanmigo tested in Tennessee was released in 2023. Since then, Khan said, the company has changed how the AI assistant works. Khanmigo is now integrated directly into Khan Academy rather than sitting in a separate tab that students have to click on. If students ask for help before trying a problem, Khanmigo is deliberately taciturn, offering little more than a hint and a pep talk. But after a student gets a problem wrong, the AI assistant automatically pops up to offer help and work through the problem together with the student. Schools can also choose to turn the AI assistant off completely.\u003c/p>\n\n\n\n\u003cp>Khan Academy is experimenting with more ways to encourage students to use the AI tutor. Khan said he plans to give students “credit” for using Khanmigo after a mistake, allowing a bot-assisted redo to count toward one of the five correct answers in a row that students need before moving on to the next skill. \u003c/p>\n\n\n\n\u003cp>It will be interesting to see whether these changes get students to use Khanmigo more. But use and engagement are only one piece of the puzzle. We still need evidence that when students regularly use an AI tutor, they actually learn more. I’ll be watching. \u003c/p>\n\n\n\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-khanmigo-math-ai-tutor/\">\u003cem>Khanmigo\u003c/em>\u003c/a>\u003cem>, an AI math tutor, was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n",
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"innerHTML": "\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-khanmigo-math-ai-tutor/\">\u003cem>Khanmigo\u003c/em>\u003c/a>\u003cem>, an AI math tutor, was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\n\u003cp>Soon after the introduction of ChatGPT in November 2022, students figured out how to use the chatbot as an \u003ca href=\"https://hechingerreport.org/proof-points-offload-critical-thinking-ai/\">answer machine\u003c/a>, getting it to do their school work for them. Not surprisingly, that shortcut \u003ca href=\"https://hechingerreport.org/kids-chatgpt-worse-on-tests/\">harmed student learning\u003c/a> and led to \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">lower test scores\u003c/a>. \u003c/p>\n\n\n\n\u003cp>AI enthusiasts sought a solution. The chatbots could easily be instructed to act more like a human tutor, withholding answers, providing hints and guiding students with questions. Khan Academy created one of these “Socratic-method” chatbots, christened it “Khanmigo,” and released it in 2023.\u003c/p>\n\n\n\n\u003cp>But a new study that came out last month suggests that creating an AI tutor is only one hurdle among many in helping children improve their math skills. Students have to actually want to use it.\u003c/p>\n\n\n\n\u003cp>Researchers from the University of Toronto followed students in 18 Tennessee middle schools for two years, from 2024 to 2026. Almost all the students tried Khanmigo at first. And many tried to get the AI assistant to spit out the answer. But when Khanmigo refused and instead asked questions or offered hints, students largely stopped using it.\u003c/p>\n\n\n\n\u003cp>“We observe how students actually used the AI tutor, and the answer is: not much,” Philip Oreopoulos and Nina Low, the researchers, wrote in their \u003ca href=\"https://www.nber.org/papers/w35620\">draft paper\u003c/a>, circulated by the National Bureau of Economic Research in August. “Seeking help with one’s own confusion remained a choice, and most students declined it most of the time.”\u003c/p>\n\n\n\n\u003cp>The researchers were testing whether Khanmigo could improve the performance of low-achieving students who were at least one grade level behind their peers. These students had an extra remedial math period built into their school day. Some were randomly assigned to use Khan Academy, with Khanmigo available as an AI assistant. The others received their usual remedial math work, which often included online tools such as Waggle, IXL, Zearn and DeltaMath.\u003c/p>\n\n\n\n\u003cp>The students who received the Khan Academy intervention did better in math than those in the regular remediation classes. But the gains were modest, and no greater than what previous studies had found from Khan Academy practice sessions without an AI assistant.\u003c/p>\n\n\n\n\u003cp>In other words, Khan Academy appeared to help. But the Khanmigo tutor didn’t add anything. \u003c/p>\n\n\n\n\u003cp>Sal Khan, the founder and CEO of Khan Academy, praised the study and wrote a detailed \u003ca href=\"https://blog.khanacademy.org/what-i-found-compelling-in-a-new-randomized-trial-of-khan-academy-in-math-intervention/\">blog post\u003c/a> about it, explaining the randomized controlled trial (RCT) just the way he explains a math problem in his videos. In an interview, Khan said the findings confirmed what Khan Academy was seeing internally: Students weren’t engaging much with Khanmigo.\u003c/p>\n\n\n\n\u003cp>Khan said he doesn’t regret releasing the AI tutor before knowing whether it would be effective. He is confident the early release did “no harm” to students, saying his organization went to great lengths to protect student data, make chatbot conversations safe, prevent cheating and minimize the risk of the bot hallucinating and giving students incorrect instruction. “It’s allowed us to learn and hopefully make the new version even more helpful,” he said.\u003c/p>\n\n\n\n\u003cp>The version of Khanmigo tested in Tennessee was released in 2023. Since then, Khan said, the company has changed how the AI assistant works. Khanmigo is now integrated directly into Khan Academy rather than sitting in a separate tab that students have to click on. If students ask for help before trying a problem, Khanmigo is deliberately taciturn, offering little more than a hint and a pep talk. But after a student gets a problem wrong, the AI assistant automatically pops up to offer help and work through the problem together with the student. Schools can also choose to turn the AI assistant off completely.\u003c/p>\n\n\n\n\u003cp>Khan Academy is experimenting with more ways to encourage students to use the AI tutor. Khan said he plans to give students “credit” for using Khanmigo after a mistake, allowing a bot-assisted redo to count toward one of the five correct answers in a row that students need before moving on to the next skill. \u003c/p>\n\n\n\n\u003cp>It will be interesting to see whether these changes get students to use Khanmigo more. But use and engagement are only one piece of the puzzle. We still need evidence that when students regularly use an AI tutor, they actually learn more. I’ll be watching. \u003c/p>\n\n\n\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-khanmigo-math-ai-tutor/\">\u003cem>Khanmigo\u003c/em>\u003c/a>\u003cem>, an AI math tutor, was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\u003c/div>\u003c/p>",
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"content": "\u003cp>Artificial intelligence makes many tasks faster and easier. But a new study suggests that students may learn more when AI makes them slow down.\u003c/p>\n\n\n\n\u003cp>In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.\u003c/p>\n\n\n\n\u003cp>Academic researchers tested four approaches to practicing fractions. Students were randomly assigned to receive either conventional computer-based instruction or the same software with an AI tutor. Within each of those groups, half the students had to correctly answer practice questions covering the same skill three times in a row if they made a mistake.\u003c/p>\n\n\n\n\u003cp>Students used \u003ca href=\"https://www.povertyactionlab.org/initiative-project/numi-ai-tutor-learning-how-best-deliver-transformative-personalized-education\">software built by researchers\u003c/a>, which was similar to Khan Academy’s videos and exercises, once for 50 minutes during math class. A week later, they took a 15-minute test to measure how much they retained.\u003c/p>\n\n\n\n\u003cp>The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small. \u003c/p>\n\n\n\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>“I don’t want to jump out and say we’ve demonstrated that AI is going to be the game changer that we hope it is,” said Philip Oreopoulos, lead author of the study and an economist at the University of Toronto. “But it might be the first kind of evidence that shows there’s at least some hints that it has some positive value against no AI at all.”\u003c/p>\n\n\n\n\u003cp>That’s significant because there’s mounting evidence that \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">AI is often harming learning\u003c/a>, spitting out answers for students and short-circuiting the learning process. \u003c/p>\n\n\n\n\u003cp>The study, “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment,” was conducted by researchers from the University of Toronto and the University of Pennsylvania’s Wharton School. A working paper is scheduled to be circulated by the National Bureau of Economic Research on Aug. 17 and has not yet been published in a peer-reviewed journal. The authors provided The Hechinger Report with a draft.\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">\u003cstrong>Making students slow down\u003c/strong>\u003c/h2>\n\n\n\n\u003cp>The researchers think AI helped because it walked students through their mistakes instead of simply showing them a solution.\u003c/p>\n\n\n\n\u003cp>Without AI, students could see a step-by-step example after getting a problem wrong. But a student can easily skim through the steps to a solution and move on, without figuring out what went wrong.\u003c/p>\n\n\n\n\u003ch4 class=\"wp-block-heading\">\u003cstrong>Numi, an AI tutor, guides students step by step\u003c/strong>\u003c/h4>\n\n\n\n\u003cfigure class=\"wp-block-image size-full\">\u003cimg loading=\"lazy\" decoding=\"async\" width=\"346\" height=\"810\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image.png\" alt=\"\" class=\"wp-image-66544\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image.png 346w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image-160x375.png 160w\" sizes=\"auto, (max-width: 346px) 100vw, 346px\">\u003c/figure>\n\n\n\n\u003cp>Right after a mistake, an AI tutor called “Numi” walks a student through a solution step-by-step for dividing two numbers: 3 \u003csup>6\u003c/sup>/\u003csub>7\u003c/sub> ÷ 4 \u003csup>5\u003c/sup>/\u003csub>2\u003c/sub>.\u003c/p>\n\n\n\n\u003cp 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Numi, the AI tutor, encourages a student to pick a step to review in more detail. The original problem was 8 \u003csup>1\u003c/sup>/\u003csub>4\u003c/sub> ÷ 3 \u003csup>3\u003c/sup>/\u003csub>4\u003c/sub>.\u003cbr>\u003cem>Source: Appendix of Oreopoulos et al., “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment.”\u003c/em>\u003c/p>\n\n\n\n\u003cp>The AI tutor, by contrast, could respond directly to a student’s work and guide the student through the mistake.\u003c/p>\n\n\n\n\u003cp>The students who used AI combined with mastery learning spent more time per question than students in any of the other groups — a sign that they were engaging more with the material. These students were also more likely to get the next question right after making a mistake. \u003c/p>\n\n\n\n\u003cp>That’s important because requiring students to answer three questions correctly in a row is common in educational software. But hitting a short mastery threshold doesn’t necessarily mean a student has developed a deep understanding. Students can guess their way to three correct answers or succeed from repeated exposure without really learning the skill.\u003c/p>\n\n\n\n\u003cp>There was a limit to the benefits for students in this study. Students in the AI-plus-mastery group performed better primarily on the easiest fraction questions — the ones most similar to what they had practiced. The advantage did not extend to more challenging problems.\u003c/p>\n\n\n\n\u003cp>In this study, AI didn’t produce a deeper or more transferable understanding of fractions. Then again, it was only a 50-minute intervention and it’s unknown how this combination of AI plus mastery learning might improve student learning over the course of many months. \u003c/p>\n\n\n\n\u003cp>Oreopoulos cautions against concluding that mastery learning is the best way to use AI in learning math. The researchers tested only the four combinations in their study; there could be better ways to enhance computer-assisted learning and make practice work more effective. His larger ambition is to keep testing different features against one another, continually improving the software.\u003c/p>\n\n\n\n\u003cp>For now, he said, the goal was more modest: to show that AI “has a little bit of benefit, and talk about its potential.”\u003c/p>\n\n\n\n\u003cp>Part of that potential may lie not in helping kids learn math faster, but in helping them slow down.\u003c/p>\n\n\n\n\u003cp>\u003cem>Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story with The Hechinger Report’s Jill Barshay.\u003c/em>\u003c/p>\n\n\n\n\u003cp>\u003c/p>\n\u003cp>\u003cem>This story about AI and \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-mastery-learning/\">\u003cem>mastery learning\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n",
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"innerHTML": "\n\u003cp>Artificial intelligence makes many tasks faster and easier. But a new study suggests that students may learn more when AI makes them slow down.\u003c/p>\n",
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"innerHTML": "\n\u003cp>In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.\u003c/p>\n",
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"\n\u003cp>In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Academic researchers tested four approaches to practicing fractions. Students were randomly assigned to receive either conventional computer-based instruction or the same software with an AI tutor. Within each of those groups, half the students had to correctly answer practice questions covering the same skill three times in a row if they made a mistake.\u003c/p>\n",
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"\n\u003cp>Academic researchers tested four approaches to practicing fractions. Students were randomly assigned to receive either conventional computer-based instruction or the same software with an AI tutor. Within each of those groups, half the students had to correctly answer practice questions covering the same skill three times in a row if they made a mistake.\u003c/p>\n"
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"innerHTML": "\n\u003cp>Students used \u003ca href=\"https://www.povertyactionlab.org/initiative-project/numi-ai-tutor-learning-how-best-deliver-transformative-personalized-education\">software built by researchers\u003c/a>, which was similar to Khan Academy’s videos and exercises, once for 50 minutes during math class. A week later, they took a 15-minute test to measure how much they retained.\u003c/p>\n",
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"\n\u003cp>Students used \u003ca href=\"https://www.povertyactionlab.org/initiative-project/numi-ai-tutor-learning-how-best-deliver-transformative-personalized-education\">software built by researchers\u003c/a>, which was similar to Khan Academy’s videos and exercises, once for 50 minutes during math class. A week later, they took a 15-minute test to measure how much they retained.\u003c/p>\n"
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"innerHTML": "\n\u003cp>The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small. \u003c/p>\n",
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"\n\u003cp>The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small. \u003c/p>\n"
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"innerHTML": "\n\u003cp>“I don’t want to jump out and say we’ve demonstrated that AI is going to be the game changer that we hope it is,” said Philip Oreopoulos, lead author of the study and an economist at the University of Toronto. “But it might be the first kind of evidence that shows there’s at least some hints that it has some positive value against no AI at all.”\u003c/p>\n",
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"\n\u003cp>“I don’t want to jump out and say we’ve demonstrated that AI is going to be the game changer that we hope it is,” said Philip Oreopoulos, lead author of the study and an economist at the University of Toronto. “But it might be the first kind of evidence that shows there’s at least some hints that it has some positive value against no AI at all.”\u003c/p>\n"
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"innerHTML": "\n\u003cp>That’s significant because there’s mounting evidence that \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">AI is often harming learning\u003c/a>, spitting out answers for students and short-circuiting the learning process. \u003c/p>\n",
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"\n\u003cp>That’s significant because there’s mounting evidence that \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">AI is often harming learning\u003c/a>, spitting out answers for students and short-circuiting the learning process. \u003c/p>\n"
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"innerHTML": "\n\u003cp>The study, “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment,” was conducted by researchers from the University of Toronto and the University of Pennsylvania’s Wharton School. A working paper is scheduled to be circulated by the National Bureau of Economic Research on Aug. 17 and has not yet been published in a peer-reviewed journal. The authors provided The Hechinger Report with a draft.\u003c/p>\n",
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"\n\u003cp>The study, “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment,” was conducted by researchers from the University of Toronto and the University of Pennsylvania’s Wharton School. A working paper is scheduled to be circulated by the National Bureau of Economic Research on Aug. 17 and has not yet been published in a peer-reviewed journal. The authors provided The Hechinger Report with a draft.\u003c/p>\n"
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\">Here Numi, the AI tutor, encourages a student to pick a step to review in more detail. The original problem was 8 \u003csup>1\u003c/sup>/\u003csub>4\u003c/sub> ÷ 3 \u003csup>3\u003c/sup>/\u003csub>4\u003c/sub>.\u003cbr>\u003cem>Source: Appendix of Oreopoulos et al., “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment.”\u003c/em>\u003c/p>\n",
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Numi, the AI tutor, encourages a student to pick a step to review in more detail. The original problem was 8 \u003csup>1\u003c/sup>/\u003csub>4\u003c/sub> ÷ 3 \u003csup>3\u003c/sup>/\u003csub>4\u003c/sub>.\u003cbr>\u003cem>Source: Appendix of Oreopoulos et al., “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment.”\u003c/em>\u003c/p>\n"
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"innerHTML": "\n\u003cp>The students who used AI combined with mastery learning spent more time per question than students in any of the other groups — a sign that they were engaging more with the material. These students were also more likely to get the next question right after making a mistake. \u003c/p>\n",
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"\n\u003cp>The students who used AI combined with mastery learning spent more time per question than students in any of the other groups — a sign that they were engaging more with the material. These students were also more likely to get the next question right after making a mistake. \u003c/p>\n"
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"innerHTML": "\n\u003cp>That’s important because requiring students to answer three questions correctly in a row is common in educational software. But hitting a short mastery threshold doesn’t necessarily mean a student has developed a deep understanding. Students can guess their way to three correct answers or succeed from repeated exposure without really learning the skill.\u003c/p>\n",
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"\n\u003cp>That’s important because requiring students to answer three questions correctly in a row is common in educational software. But hitting a short mastery threshold doesn’t necessarily mean a student has developed a deep understanding. Students can guess their way to three correct answers or succeed from repeated exposure without really learning the skill.\u003c/p>\n"
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"innerHTML": "\n\u003cp>There was a limit to the benefits for students in this study. Students in the AI-plus-mastery group performed better primarily on the easiest fraction questions — the ones most similar to what they had practiced. The advantage did not extend to more challenging problems.\u003c/p>\n",
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"\n\u003cp>There was a limit to the benefits for students in this study. Students in the AI-plus-mastery group performed better primarily on the easiest fraction questions — the ones most similar to what they had practiced. The advantage did not extend to more challenging problems.\u003c/p>\n"
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"innerHTML": "\n\u003cp>In this study, AI didn’t produce a deeper or more transferable understanding of fractions. Then again, it was only a 50-minute intervention and it’s unknown how this combination of AI plus mastery learning might improve student learning over the course of many months. \u003c/p>\n",
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"\n\u003cp>In this study, AI didn’t produce a deeper or more transferable understanding of fractions. Then again, it was only a 50-minute intervention and it’s unknown how this combination of AI plus mastery learning might improve student learning over the course of many months. \u003c/p>\n"
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"innerHTML": "\n\u003cp>Oreopoulos cautions against concluding that mastery learning is the best way to use AI in learning math. The researchers tested only the four combinations in their study; there could be better ways to enhance computer-assisted learning and make practice work more effective. His larger ambition is to keep testing different features against one another, continually improving the software.\u003c/p>\n",
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"\n\u003cp>Oreopoulos cautions against concluding that mastery learning is the best way to use AI in learning math. The researchers tested only the four combinations in their study; there could be better ways to enhance computer-assisted learning and make practice work more effective. His larger ambition is to keep testing different features against one another, continually improving the software.\u003c/p>\n"
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"innerHTML": "\n\u003cp>For now, he said, the goal was more modest: to show that AI “has a little bit of benefit, and talk about its potential.”\u003c/p>\n",
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"innerHTML": "\n\u003cp>Part of that potential may lie not in helping kids learn math faster, but in helping them slow down.\u003c/p>\n",
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"innerHTML": "\n\u003cp>\u003cem>Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story with The Hechinger Report’s Jill Barshay.\u003c/em>\u003c/p>\n",
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"\n\u003cp>\u003cem>Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story with The Hechinger Report’s Jill Barshay.\u003c/em>\u003c/p>\n"
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"innerHTML": "\n\u003cp>\u003cem>This story about AI and \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-mastery-learning/\">\u003cem>mastery learning\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n",
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"\n\u003cp>\u003cem>This story about AI and \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-mastery-learning/\">\u003cem>mastery learning\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n"
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"excerpt": "A randomized experiment involved more than 6,000 Tennessee middle school students learning fractions.",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>Artificial intelligence makes many tasks faster and easier. But a new study suggests that students may learn more when AI makes them slow down.\u003c/p>\n\n\n\n\u003cp>In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.\u003c/p>\n\n\n\n\u003cp>Academic researchers tested four approaches to practicing fractions. Students were randomly assigned to receive either conventional computer-based instruction or the same software with an AI tutor. Within each of those groups, half the students had to correctly answer practice questions covering the same skill three times in a row if they made a mistake.\u003c/p>\n\n\n\n\u003cp>Students used \u003ca href=\"https://www.povertyactionlab.org/initiative-project/numi-ai-tutor-learning-how-best-deliver-transformative-personalized-education\">software built by researchers\u003c/a>, which was similar to Khan Academy’s videos and exercises, once for 50 minutes during math class. A week later, they took a 15-minute test to measure how much they retained.\u003c/p>\n\n\n\n\u003cp>The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small. \u003c/p>\n\n\n\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>“I don’t want to jump out and say we’ve demonstrated that AI is going to be the game changer that we hope it is,” said Philip Oreopoulos, lead author of the study and an economist at the University of Toronto. “But it might be the first kind of evidence that shows there’s at least some hints that it has some positive value against no AI at all.”\u003c/p>\n\n\n\n\u003cp>That’s significant because there’s mounting evidence that \u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">AI is often harming learning\u003c/a>, spitting out answers for students and short-circuiting the learning process. \u003c/p>\n\n\n\n\u003cp>The study, “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment,” was conducted by researchers from the University of Toronto and the University of Pennsylvania’s Wharton School. A working paper is scheduled to be circulated by the National Bureau of Economic Research on Aug. 17 and has not yet been published in a peer-reviewed journal. The authors provided The Hechinger Report with a draft.\u003c/p>\n\n\n\n\u003ch2 class=\"wp-block-heading\">\u003cstrong>Making students slow down\u003c/strong>\u003c/h2>\n\n\n\n\u003cp>The researchers think AI helped because it walked students through their mistakes instead of simply showing them a solution.\u003c/p>\n\n\n\n\u003cp>Without AI, students could see a step-by-step example after getting a problem wrong. But a student can easily skim through the steps to a solution and move on, without figuring out what went wrong.\u003c/p>\n\n\n\n\u003ch4 class=\"wp-block-heading\">\u003cstrong>Numi, an AI tutor, guides students step by step\u003c/strong>\u003c/h4>\n\n\n\n\u003cfigure class=\"wp-block-image size-full\">\u003cimg loading=\"lazy\" decoding=\"async\" width=\"346\" height=\"810\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image.png\" alt=\"\" class=\"wp-image-66544\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image.png 346w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/08/image-160x375.png 160w\" sizes=\"auto, (max-width: 346px) 100vw, 346px\">\u003c/figure>\n\n\n\n\u003cp>Right after a mistake, an AI tutor called “Numi” walks a student through a solution step-by-step for dividing two numbers: 3 \u003csup>6\u003c/sup>/\u003csub>7\u003c/sub> ÷ 4 \u003csup>5\u003c/sup>/\u003csub>2\u003c/sub>.\u003c/p>\n\n\n\n\u003cp 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k/bulx2bEyRh21bZmZylhJYoXgPTnuXzlwltL4kdq2MRsAgcjoDn8KRTl8IgTaQHssXCcaIkKw6uNXK3peUNdRUSM3VIRAuStfm3FBFDHEqjLtZisUaKATzQHhGnM/qZK/GU7MDkE94nguAWrhkfJ0zlbdu4XcDRTS/LLe1pNbCFuAKxamWmgYlMQpa7Du2UPw18DCe4aj6aSni1SB2koxtFS7gnnxgcTf9IeZAwr9+v04DUGVW7rqTvMwNtiul7Uygtw6vkISvTLzEmwuQ33wxvvTpSM9yRoChfwQAKGTTq+h+ypzsBH0ReIBCUDz8YUSLbfyCZTYlkz/okWTp7paxZtEFffUShUDM9GOoP1cgI6+OSklMkNSeELEMQDWE0e9HBQeL4coTohDnUqavERatkyeTNEtqorUZc6pionDcnUQkMOsVJliGvvtBQyYoK0fqq16heoJaVnl6wf6ydxF9XaDs2/LpDMiRY6tfy62D+27pdhYrSx2EQzdAaUj0qQpL2GPCNhjciRqc7leT6Q8STkSK14hpLMSf3XwAAEABJREFU5L51SpiNiv4HG8rTr/Fx4ZJksCHDCcr3Nbx2iNQz6RvXrBf9rpvMtPRsOZCRLRHR0YfdEJCWefh3NCMrRM8dU1RJU3pGAruyedUGbePWzbslTfZKvdhojRZCELmIWLsiVZqYae0adUMkddteSV29TyCrFA4JzWCj9tJMxI2DnOxMPQ/ZP5qEmynIovmQ36JpJT32bN0l9NPmFbskc2+QxLZoILFRHiV+iatMWm5JLVk9i4BFoCgC+b9oRVNP4THkB7IVEh4uw27sJkUJSpm4YiIv9c20JbZZ01RaJAt7879fL94wr4y6tZdAPmLionXb49IOZMvMr5bp9mQ/IqoHFZjINVE0CGPixsIDWIFCGe1Aqlwhiuf6hC+h/rBCtfK4iEIJBw8YjA7uHrbZtWeThJgIzEW3XCwXXNj1sPySJDQbNkiuvq2fpKUlyBIzTdf//0bLjY9dLl3bVJP5P6+WXbkBI0j6blm3YoPEduwq1z12ldaZm5s/HVO9Xlz+AGoiV0erd9W6A9Kkd08575aR0rVLg6OpHjEPTLJN5ApxlZiaYi3aBfedL41idgvrk9y83PQUWb0xQ7pcNEouuH6ENK8XoRGv2p1aCHexEWEMPbBDtmdFSJ2GdWTTmi3FL7SW/L+UpFTZuvuAdBk6UC68ZZjUNiQlP+f4PvEfoT2pSUGyz4mQbmd1leFDO0s13yFb1WtWE9ZWXf673hKaZEjU6nxCHWq+p70uHSUXj+4hEeFpujau7Zm1ZdnPKwr5T/SH8mAT7STJonmFI5tpiQckOS9GBl44QO+Q9YY4kpeRKmuWb5aQxh0Vs0tuHSkta4uJrCdITKt20nd4K4kOyj+HOXfmz1gqXa8aKegNGtFKMk0ElmlO7sgD8+7dG0p0fJjwPdiVsKPAv3njZsr2zGpy7uhhcs2DF8g5V3cUf26acGcvkU0Xhe1rUhUf2gEOSSuWFiKTrt7RtkEnEdGq0ae7jL5/pFx+7yjpd0FnIQLYqmNzXSd34d2j5JKb+kpszcMJ6NH8sXkWAYtAPgKe/E35fkK2Zn6wQJ0gKqI7ZfjBdBvmlWSxU5piImPT3vhZsrKyZNClfeW8+wdJ31G9dNpK22jyS6u60MggvXPS4/UWmAwxhJU1Z5C9gsTj3Aky0xqs5XGLMVDyKh4GBzctv8/my8wP8oUI5NpZ2zSbaNbS+b8VWqTP9CN2VCHggyhE4rIFMv6TBTqFg87897+RcXM2SsrKjTLhtXHy4etj5fOXxsoLz36h0yzrZ8+U6WN/UyurJsyRb8es1CmdnTs2yZhXJwjbOZ9Oltk/bpKVc36Sr/43X6elFn05Q95/8Su1h97qFak6VfnWox8Ii5UxmLBwtXz30peq8/1/50l2drYhzn6Jr3Fwug0lI/js+sDU1oIp83QtEOn4PP6DH+S7/07Wdu3YtE+WTl8hvy7bp9GLFRMnavtoK1Gf6ZNWSuq6dbrmLHnLPmP98P97tqyW6eOmKx5j3p+l/m74ebHigO8rv5+uGLn1jvtumZDPOjbSKOMLayJRuTsLpoGof9Wnk9QvagTveZ/NFnxYMWFBvv+mHbSH/iDSNn/i0vzyhpRiF91sQwpXTvlZ8db2mL5J2VF4UPZn7JbFY6cW2Pzo718qXtS7Z+tmmfLNJM3Db6YQSU8107v4rzh+sUAyw2MFIrViVX6kSg7+7V6/qRA2lOccwFf2xfjK+aB2THvYLlmUJjvX7hTSaQfCtDL9T3t/nr5JVk2eIvQxNtbMXKTnFnrk7V2/U376MN9n0tDLjYgVooUJG7MOemY2pm7OO843V8abtuxK2ymcB6wLM1qG4e0W9LCFfzPHrZAcCZLIyLBCwvcFffzkO7NzVxCHKix+n/7u97J+fZoe80Efc05OnbROvwNF7XGcaKKefL++/GCK9gG4cb5+9vZ4bfO3n07X85g1fti0UnYIWMtVEwFPRWkWAzcDGwN2WftEXWVCsg46jv3vX5ohX//9BxUevzDx/cWFiMdB1RPeMHUIqWKaMtVMlbjrzjBIGtvANI6PR4Jzw3Xa6HjK0G6IF0RzyderCoqmmSmVgoMiOwwECINZ5sHgEvsM3m46Uy6ksSUN4RhTbBH23XR3qzZ2p+sA4+ZjAylahnyEuxprNYmW2rHh0vzslrJn7WpZYyIsLGKH0KCDuHUE7mt9udlaH/ZdQYd98ovuk+YKOi4G6BUVFuGjgz55bDlm3/WHY4Q8hH1E9zf8qsQhsA43L9AG+cXZc9PIR5+y7j7287K8SnhJJz9Q0EOHPFfQD8/IMFO4qZKSmt9P6Ljl0vfnp6FPOmvmIBfYcnXYejL2GcyR/Vo/aa6v7CPYCBTyi6Zjl3RXjzrZRw9h35WiuqTvMxcGkDDy0Hcl0CYXHNgljzLuPseBetiIrdVAF6h3PaedICyiDzs4ZejqUi5QitokL1CXu0Kx5Qp3WmYH7Tf47depTcq7kmqmOtlni9/4hD0rFgGLwPEhUGGIlrpditEetVfOHxAPV0pzepJmsZ5t5gcLTEQpX5JSMgTy6KZBdkhD90SkJFGtI9mlzeQRAUP4kebHnrSKLEQLImtEC4vHW3durdGfyWOm6yDEgFNevqclJwl3sXkCbuc/EV9oA3IiZUtS5nj7GP3kXftk684Myc0o/FPEmrot21ILVYvvyKFEkb3btio2WfudwORy2cc35GiV0+aj5QfmJSSsk9nfLpSpX/ysMm/KYj0XA3WOd3/r/OVqy7W5cPZWSU86tpXj8fvY1qyGReD0QqDwr9vp1fbK3VpDSiE0rrhEzj3euW3XSS/wLxrV4seWKcQ0E6GCQB0NQPJZl4U+5Y6mW1Hy8HPHsq0y8X/T5du3f5BvP5wvm9YHTAOVg6P4tP3XjbJ28baCdT/l4EaZVZm2YavwDKjAyA6VQTIWTVvB7hEFbJj+2/DrjoJI1hGVbYZFwCJgESgnBCzRKifgy7paIlJF6zjeY2zwHCciPW5ZBjciVBAoyNSRhHz00HfLVoZtZfO3MmBa1j7aPitrhK19i4BF4GQQsETrZNA7DcoeiWzRdBb0QqiKCukMfgh6ViwCFgGLgEXAIlAMAqdFkiVap0U3n3wji4tsYRUyhRTd59iKRcAiYBGwCFgETncELNE63c+AErSfqBYC2eJ28MCpRLe4S7bcY7u1CFgEygABa9IiYBGodAhYolXpuqz8HIZshUuUvqfNJVyQLitB+igMi4PFwZ4D9hyw54A9B4qeA5ZolR9vqbQ1u4QrNjxWECJdFVSUFFrfYiwOoRYD+z2w54A9B8rnHLBEq9LSnYrjOMTLSpC+KNjiYHGw54A9B+w5YM+BwHOgMNGqOGO39cQiYBGwCFgELAIWAYtApUfAEq1K34W2ARYBi4BFoOoiYFtmEajsCJQp0TqQfUB2ZSZYsRjYc8CeA/YcsOeAPQfsOXBangNlSrR2JeyWxavnWbEY2HPglJ0D9vvm/uYsT/tF6vWqKV0uaFtIzry4g1R06TiypTTuX0fYVnRfrX8V/3yyfXTq+6j5oPpS44xwie4QImVKtCKjI6VR7cZWLAb2HLDnwCk9B+Ji4qRxrWbSv39/OXf48AIZMWKEDDfHCPuujBw5UiqSnHvuuXL22YPV14rkl/WlYp0ntj8qXn/wm9KrVy9p2bKldO7cWbp161a2RKsyzKtaHy0CFoGqjUBuXl6xDczNzS023SZaBCwCFoETRYDflcTERMnIyCgwUaYRrYJa7I5FwCJgESgnBPIM0SqObHk8h37+0Ckn92y1FoGiCNjjSowAvyXZWdmFWnDol6ZQsj2wCFgELAKVHwGuLgNbkWeiWPwQknZYniFkpFuxCFgELAKliYAlWqWJprVlEbAInHoEjlGjS6yOoWazLQIWAYtAmSBgiVaZwGqNHgkBX5BHwiPDJSa2ukrNuBoSV792gXBMHjr+EL94HOdIpmy6RcAiYBGwCFgEKjwClmhV+C4qdQdPuUGXXEGiatSJlRo1oyUyIlQlLDRE/EFBBcIxeejEGd1a9WopIYN0nXLHbYVVAgEiWkiVaIxthEXAIlDpELBEq9J1WeVx2HcwelVAriKrSUhkjESbaFaTVi2lQ88OMnDUYBl1/Xly0S0X67bX8L7SonMbqd+ikeqFhoQpIYN0QdQgXDbKVXnOgYrkaXEL4iuSf9YXi8Dpi0DVbrklWlW7f8uldRAhpv6iasZo9Cq6erTE1q8jbbu1khGXD5QLbjlPzrtxuAy+eLB0HtBRWrRvLo1bNdJtr7O7y8jRw+SC60bKyGtGyMALByjxgpxFGqIG4cKuJVzl0rW2UouARcAiYBE4TgQs0TpOwKz60RGAAEGEmPqDGBGZ6jzwTBl+xVAZeMFAJVM1atQQr9crjlP8+ivHccQfEiy16sZKh+7t5ZyLB8rgKwdJp35naJQrOjpKqsfGSGhEmBA1O7pHNtcicGQEit55eGTNipVjvbEIWAQqDwKeyuOq9bQiI0AUyx/il2rRkTrVRwQKYjRgZD/p3vcMiY2rIUFBQdqE7Oxs2b9/v7DNyckR1s8gmhnw4TiOkrGQkBBp2LCh9BvWSwYZsta0QzMhShYZHSERMdGWbIn9O1EEAp+ldaI2bDmLgEXAInA0BCzROho6Nq9ECECygoJ9SrJYzF6/RSPpN6Kv9BjUVYhKOY6jdiBVW7ZskQ8//FD++sIb8p///Ede++9H8v7778sXX3wh48ePlxkzZsi8efNkyeIlsnr1atm2bZskJSUVELN6TepK72HdpVOfM6RWnVpK6o5NtrR6+2EROAwBG9E6DBKbYBGwCJQyAp5StmfNnYYIQLKYynNJFlGspm2aSGhoiEakiFbt27dPpkyZIk899bS8/PJ/5K23P5C//fN9efe/L+vxX//6d3n88SfliSeekIcfflju/b975f77H1D5w2N/kyeffFKee+7P8vIrr8h3330n+7KTpFb9OAmrFlFAtiB8pyH8tslHQQAixfkXqMJDS91jG9FykbBbi4BFoKwQKJZolVVl1m7VQ8AX5NFIlj8oSO8UhGQRxWINlogjWZmZsmjRIvnzn5+XP/3pMZkw5RdJ2J0j7h/7gbJ2U6q4svi37fLTvDUy7vtJ8vEXU+Xt/30nL/z7Q3n0qX/LX/7yF1mduFw6dm5UQLZYs+XatVuLQEkQgIiVRM/qWAQsAhaBE0XAEq0TRc6W04eJMm0XGMmCZAENa7B++eUXufv+J+XWW2+XDz6dVIhgoXMi0rRBhNxw/Wh58YUXZVT31tKqXR3pPbSXeIP8eocjdzueiF1b5vREoCpGtIjgsf6Rixym66tIzx6zGRkZGXphd0zFEiqAHTiWUP2oavTFgQMHjqpT2pn4n5aWJmxL27a1d3wIWKJ1fHhZ7QAEmDLk4aIsfO/QrbXUqF1dczdv3iLv/O9LefbZZ2Xhz1M0La6GV7cn+tGxTR0lWP/+97/l9w/cKs2aN5OvhY4AABAASURBVCsw1bxDM310BAkskPeZKBv7ViwCx0LgaBEtBigGb9YIZh7IOMwUhIa83bt362CGbuLWHVJUUlJSDytbVgn4sHz5cvnqq6/ks88/l+nTp8vOnTvVv7Kq81h2wZG1mfh2LN0TzaeO//73v9rm0qgHYjR//nyZNWuWnCxB4jz56OOP5YUXXihVIngsrDZt2iR333237Nmz51iqJcqnHQkJibI3OblE+lbpEAKWaB3Cwu4dBwKsh6oWHamRpAbN6kmDVo30rkIGruSkJGnSoKZce+218sgjD8s999wl1954hzxwz9Vy922XKWEafelgORL5Gj5ssFx/1bly07WjVPfhh+6WRx/9kzxw703SsmVL8fv94jiOhMbUFm9IpAQHB0u3s7vps7r8QUF6J6LH5B9Hc6qeqm1RiRAoLqLFoA15WrVohUz/Zrp88eoY2bph+2H2GIC/eWecTP5sqmRlZcnGVZvk/b+/J/99/q1CsuSnX/XO2sMMlHIC0Zcff/xRXnzxn7Ju3TrZsWOHTJgwQb788ktJTk7W2hgsIRGQEfQ10Xywj5BHu9h3ddk3KtoGsOGYPMTVJ93VIc0V0hMTE+W5556T9evXF0v40MEfhH3sIOyThrBPmiv4gJ/Ugx+kp6enCxGczMwsJUfokB4o6FIGe9h199ENtOd4PMK5gQSWwRZlKUc6x0XLkoagRx2ZmZmCb0jgQ3Mpjx302KLLvluWNHSKHpOOHlt8Zh/hONAGv8V79+4V0hDyXXuuTdIRypNGPse0KVCfdPx/44035OtvvhE3j3T28YMy2ChOsI8OttlHhy1l2ZLHPvbIq2riqWoNsu05NQiwHoopw+p1akjHXp2U7DBdmJqSIrVq15ZOnc6QLl26SOfOXaR79+4yoE9n6dGjh0qvbmdKx44dJDw89DBn40zka4SZCjzvvFEyfPgwGTG0j/Ts1laC/cGyatUqXe81d+5c+fnnn2Xp5p2yZM0WvWKrVq2a9Dz7TCV+wSE+CQr2HWbbJlgEiiLAYBSYxg89xGCyIU+fvTlGJnw6QVYsWSkQqaJ6CRsTDblaL7Xq1daLjD1JKZKwfafw6JGmbZqZae22KrF1awYWLbP9Xbt26927PXp0Nxc398idd94po0aNUtJFdIMBbdmyZfLW22/rHb/ff/99QbSL6M03ZgAlCvbqq6/Kt99+q9+rn+fNE75vDKKU547gn376SQfvlStXyvv/+5+gP3bsWOGGF6InEydN0nTqIbrGHcVsuRlm69ZtEviH3Tlz5sjrr78u77zzjuAHg3FgOncnTzI201LzI4NE6LD58ssvaz1r1qyR3Jz8dZ/Y//jjj4Q82gPxCqxvv5lKw2f81TrffVeoH13a8Y453r59u3DDBCTL6/VKqqkXckEbwGDZ0mUy3hDYFPNbR5vBkbK0F3w5h6iXaJjWYdq1ceMmyc7O99H1B3KBXXB54803FQPwpf0QZeqApFEndf8wZYrefT3TRNnGjRun/Ug7uVsbgu3aWLRoUQGhxfeJEydqfxNV07bl5Wk+WBMFRKgXIrVr1y7VBd8vx4zRcwB/8Wnq1Kl6R/isWT/KgoULBd/wCzzx4ysTRd2bnIx6IQEL+g8d8ABv2s73bKw5z2gL+OE/5xTtLWSgChxYopXfifbzOBDwmam50PAQYV1UszZNJLpmlCxYsECnK/jh+PKbSYJ89e0U84M9Vq+q+bKPm/iTTJ42X36a97MsXrxE6tevL726NZMBvVvrlv3OZw7UxzrMnj1b+EGfOXOmTn+M+XaqfDNuhnw7fpZM+GGuTJu1SOYuWCkffTZBfv31V+GvUfMG0rBZY31vos/nExvVAhUrR0OAwbRofsa+TPF5gqXdGR2F10cVzXePV/+6SoJ8QdK8U2MdmNP3pQnnXceeHWX46KEy9KpBKk1aN9YIrFuurLbbt28zA2OSnHPOOUKUl+fWdejQUS699FKpU6euEi5IC/XXqVPHXLQsFgZALo4WL16sj13xGmLBRcssM5gvNIMppIaoGCSHgZVBkUjZhg0bBHLCoFivXj2dYuM7npycrDaXLFki0dHR5mIqXOLj46lSeFAxdyLrgfmAkDDYf/bZZ1KrVi2TIjJx4iRZu3atrFixQn83KFO9enX9LZhnpvIYyD/44ANtC8/WYxDHj0QTvcPA5s2btE7aN378BNPGRUI95CH7TdTrf4YcctGGzubNm+Wtt95SwskxJAUSdiAjUyBNEBDKQajeeecdYQr0408+0UfOQL4hpNgCA/Q+/fRT2bp1q/4eTpgwUXgGYGxsrEnbQnYhyczIEEja5MmTJS4uTskP+PJIG/z64YcflNBCIsFjxoyZSrR+/PEnIQ+7ERER8r//fSBTpkxVfCFWX3zxpTkP9mhd9BkYgS/tGT9+vNpYtGiRfP31N9pHnLOTJk2W1atWKw4v/PtDbSe4k4chr8ejfRQeHi4xMdFajn76+uuvNXpIXyxc+It88OGHekwZhPODPp4zZ64+CzEkJES++26crFq5SiBalMdOgwYNZPfuPfLZZ58b/9IpWqXEEq0q1Z2npjH+0FAhmhUZEyEtOrYwVzZZsmDxavNF2a1f9m5ntJTunbvmiyFOHTucJT0695MhffuqENHq3buXDBkyRPqeNVy69x6s257thkn71vGyN82RnUlZsmdfru7vWp0jCQk7ZNO6JbJu1ULdbt34m8TG1pC4uFo6XUDLvWbQa92liUAAQw0RtFEtULFyNASKRrQcx5G6jevIoMv6Se9zuwvRqeLKc/W/ac0WiW9c35yHsZJtIiopySmqunzhcvnyza9l7HvjJHHTjlNCsqiYCEtWVqYSDY6RyMgIIbIcF1dbuGhh4LziiivkoosuMtHl7kpotickoCq1TSR6xLnnygUXXGCIWR3ZYMhU27ZtNVJFRIZoFSSiXbt2snTpUn3GHQQBkgEhIuKRYcgDRK1fv34aTWvUqJH0Nd97Bu327dsrVlqZ+YAEjDFREwghNpCEhO1KtGrWjJVzjS/NmzdXX4gGEeXBDy6szjvvPPUTX5s2bVoQcWzTpo2WI71u3bpSXISEpQe9e/fW8vgWGRkpPXv0lIsvvlij75DEAwcODfZh5vdu+PBzJTs7W9dZ5eRkGzI7RCNdRNYhO/iOgA+klUhPrVqxcuGFFyoO4GiaXOz/bt26Ce05++yzTR05OuWbr3jkT+yNHDFCLr/sMtNvtSQ+vq5caPpt4MCBQlQqOTlZC0dERMrQoUPlEtM27NM2phPHjfveEJo0wWcueHfv3iWrVq+S7KxsXdKB39gCGwz5/H7p1LGj1tOkSRNpagSCmW2idCNGjFQsL7jgfHOOzTKkcitFVLiQoX/OPXe4Ei36ZO/eZNm4aaPmRxii2L9/f6H9Q4cOMefceklJ2ad5VenDEq2q1JunqC3+kGCtiedYVY+NNkQrw1wJ7VZiNH/RGkOKEswX6TdZs3axzF04XyZPnyjjJn8l34z/QuXLsd+ayNRPMnP2MhONWi47tq3V8kmyRwmWGj/4ERWeJ7Vb+aV9+9YybNgwYZC45pprZOTIEdIwPka1+HHnqtVrrsZrxscJ05lEGjTTflgEjoIAA0HRbKJBUVFR4g8rfvqZcw0CtWP7DiGi6zeDEIQtPXW/DvjbNm2Tres3y7zp8+Sdf7wvm1ZvLhRVKVpfaR3jt8/nN4N1doHJbEMOkpKSNMoAcWKggwhBbmrXqq16KWYKLMcQxaioaAk2EYegIJ+ug6RN8SYaRZlFixcpueK4jom+YHPduvXy+eefm4jQ28L0XVxcHaEMPjBA+w0ujpP/sGIqKop1dlaW/lasMpGUd999TyMsTCmFGB/S0/fLRx99JESvIIhbt25RbHcZQoAtojl834lCnTt8uNQzfpJO24KDgyXI/BaEhYVqGdKLSqQhIJQPCwsTyoQaXfzjGB+K6sfG1lQCN3v2XOnTp49wDG6JiTtk2rTpigERInynbLqJnBFFIgJEPZxPQUFesgqJ1xskNWvWFHTUb6NDnxVSKnKAHXx2TJTJ5/eb6FKMtsHn90toSKiJjGUXtNvv9wmvQvP5/UpY9+9P1ygZETOiZETDvvxyjCE3KRJqCKXH69HaqsfEqE+Oc6j/NOPgR6bpO4h3ZGSERFWLVN1GhlSTDdFj6wpR0XfeeUfGjPlKiMbt2ZNU4B/Ev1q1aloerCiTbcgb26ok+ahWpRbZtpQpAkwbBof4tI7mrRvqF4QfV00wH0Se+BH2mB8BrlbatqwvF4w4S66++mq5+eabVB558FZ59JE75KnH7pXnn31YHnnk9/LHh++QP/3+TnnsD3erPP5HtvfIPffcK3fddafcfstVesU5ZMhQ6devv3BV7fdVNzWK+WE5tPYhvFqo1KkXa6cPFZnT6+NEWht47pa0PKRkw5rNeo7Vb11PI1YMsL1H9JAbH7hGbnv8NrnjqVul/ZkdZO+uJPnZTJdDKkpq/0T14gwBouyqVauU2EEI161bJ//+98s6DRZrprCSk/eKu+g4JTXFkLIcHWAZ6ClbVCBLrLFknRZTXL169RLIWLAhM3369Ja//e1v8vrrrxl5Xb/H7mBZ1E5xxxCF4OAQOf/88+Q//3lFXnvtVSOvCZEUomOUYRH9/fffr5EmjiNN9IktF1dss8yAv3PXLjlgpvo4PlI7yDseycnJLaTO9BtTqPXrx+tSBqbowKB69Ri5777/M37j+6vy4gsvaAQP3CiTY4guhjhnjpdA0Db60C3P9nglMzPL9HGW/kbis88XpNPbkFDW7wXiTuQrKCjIRERDj1lNvl64ucjOFEgXBZKTkyXLRFTdPiItw0Q4v/32O2nVqpU8++wzehckUUfyTiexROt06u1SaKtjvoiY4YnsRI/YLyoDBpxlQsHn6xUgpKh9hw7CFECjRo2lcePG0qBBfeEqmR9+rmb4weKLix0GPsdxzK5jBjBRMZ/i/mmW5OldPG4aP2LuPj9wtevHiSc0Uvwm8ub1Om6W3VoEDkOAC4LDEo+RwAC6afUmvcs1OjqqQJvpsUZtmghR3momItb+jHaatzthV8FgpAll9FG3Th0ZMKC/kh7WxbAmB3IUZKIkTAv2Nxco3Pk3bfp0+XXJr7qwuU6dODP1VPuoHjEwEoVYZSJPTHPxfW3durVOHRJtIjIyfvx4oS6+v0WNgbHP5xeiKGDn5hNBOeecwcL6IPxdtGiRrvvasGGDGezDNcry22+/6Y0vrAHle05ErXbtOF3b5Nb7+utvmMjYdtdsqW8hEqyl4gLy+eefN8Ql2/g8yUSSoqVhw4YyfvwExRP/WUCebMgs02tE+eb+/LOSXIjq8ThGNAxixLMIly5bpmtaj6e8q5tqyPSMGTOEKUNwxi9+cwcPHqw3OdB/nAusc+OVZ8X1n2sLYkzEb8eOnZKUlCzNmjUT2jpnzhyhn4hutmjRUjEpKGN+sCNN1Gv79gRhOvWnn371jIcCAAAQAElEQVRU3aPV45atSltLtKpSbx5XW45fmcXlPp9Pr+TDoyJ1QAm0kpeVrId5eYeuBs337CBZkoKtmL+8vDzzQ5qq67rYN0lm+nCXcEcP+0eTnFxHiVZm1p7D1LiirRZdTapF+CT4YOTtMCWbYBE4iMDx/uBzrjJtuGf7bmHakIEHUxCIWd/NkpnfzhTufGPqaG9q/loTviucl+iVpfj8frlq9Ghd+/jOO++YKNF/JDMzU9dj1TEkrG27tvK7392ii8xfM1EofCKqAUFkrU6zZk3Nd9QRiFmjRo10/Y7jOEI+U/Wss2HfcRzp1LGjrj+aP3+B/Otf/xIWQjOIh4dHSNOmhmxWz482097o6Gjp27ePTJ06TR/xQBriOI6MGDFClwG899578u677+q6J/SJarGm67XXXtdyPNYlzkTsYsyUFpFxnudEvYsWLdbyjQzhgfRwAef1eARSgD+0y3EOXWz5ze/XmWeeKZFmugsfmNKDMLiROAgOxDLUXKSBWSODA89BYxH8zTffrCTikksu0d8tyl911VUSHR0l4In/wSbSV6tWrBD5g5RCYOiLM844Q1q1ain8hlIO4eKyTZvWUj0mHyt8wBfa2LJFCxk0aJB8+GH+9Cl1UB77tAvi7DiOzig0adK4gCyHR4QLuEWYqVGILD5s375d3nzzTeHv/PPPVxKL7ZEjR8pXX30lb739luLOOjvKde7cWYIMTugHCufLueeeq6R2+vRppj2tzMX0cJk9e47e5Un+nXfeIe53grL4Sz348ve//90Qvl/ljDM6CbhHREQIhJ08dGm/Yh8awmGVEk+Vao1tTJkiwDNg/OYHiEpiYmP0S84+V6xskZyMXbpOw/wGcHhE4ep01aqV5kptsbjTKhs3bhDWgoiJWB2xoMlwJMeEqLN0rYE5LPCDfcdxxBcRJL6DfroROPKsWASKIhB47hbNK+6Yc3Xntl2aVbdhnYJzz3E8krR7n0wdO0OmfjFDIF0LpswVbsho3r6ZTtdooTL+CDeD12WXXSb/7//9P/l/zz4rt956q0aTGQSRvn37yuOPP6F5EAfu9iKdgffyyy/X9jANSsSDNPIQFkezNtJx8kmLz+8XFpT/8Q+PqK0HHrhf64mNrSkM5h3at1dbNJfyN9xwg/z+9w8LBII0VxiIuSsSf5988km5wvjAgB9rpjlvu+02+etfnhfquOuuu3SNJr41atRI7r//PnnmmWfkwQcfkE6dOonP7zeD/rly1llnKUmgTkgBbQjs4wgz9fjAAw8IC8DxAX9YBO8Sl549esitv/udoNevXz9dSF4nrramde3aVSBHZ3brpoQWQgSxA0ewfuqpp5Q44iNRo/NGjRLSwJu2UE9QAIEJCQ2Vm2+6yZCNVriiZAmdFoZk+fx+xYL2P/bYYzrlRh5kBHLcs2dPxddv9CB+HGOkkcEGm/HxddXen/70qNxxxx16PoAZ+WCDj/QT/rm4s1aMco8++mghsoRdxHEcAQP6CvIEoeph8KJ/aP/dd98tkFPHyT9HKINADDk/mGZ+6KEH9bEjnIeNzewGRBXs0YMU32qwh8xzXJXEU5UaY9ty6hCoGVejoDL3h4yr55ycbCVaBZlH2nGCdBEoP1Qer1e1GjZsJNyBwgGRAxP0YvcwyZN8fTKIohFlc5xDX26ukCLDq2nkDR0rFoEjIXCsiJY/2F+IJO3fv1+2rN+qN1xUi40Ux8k/71jz0mNYN2l1RmtdCP/jpLmSmZ0t51w4SNp3b6uD4pF8KO10BlIiBlHR0fp4AcfJ95F6yGMqp2geAy8DJzqO42g50jhG2Od7xb4r2ILYYYs8x3G0ndjx+f0S+Ed5yIfPXzjdcRwlL+pvVJQSJrccJAzb1IF9xHEcxZw6IDoQD/ygDPmUcZx8HY6p13EcslXQxQ8IEwk+v19JBenuMfVxjC3K+/x+IS2wTOAxOvgZaNe1RRp4YwufHaewL9jx+fMxoU50Autx7VIHeejQLuxRh+M4EnhMPjbZItRNWfB1y1MOoR78I8/n9yuulOHYcQ75ia4rbj62HMfR/qY+/KQexzm8nOPk+0h/UQ5Bl/oD+w/b2GIrVezPEq0q1qGnqjkxMRGHVZWUIrp+ISsr67C8oglBXhGuYAiVu1+s2rVrCVfYLBplEe/KlSt0EWfRspKXLZLpFwhebm6ObgN1/P5gCQozFQQm2n2LQDEIcA4Vk6xJkSb6MfTqc+SWP9wk9ZrG6wLzPQnJwporbrhg6kMVzQfnMOfzqOuGyxX/d5lcd9/VctUDo6XPuX0kMvLw74opUhr/rQ2LgEWgEiBgiVYl6KSK5KL34OJyr7kCcv0KXHdAGutT2B5JiAps3LhRCRJXNaJThXl6RUWZVatWyfPP/0U++WKCHEhPJ+kwyfGm69UUpKxopsdcVIUEBxVNtscWgcMQOFpEi3MT8tS4VSPhKtxxHIlvVEcuu+sSJVD+gO8AhiFbXLUzJdKoZSNz0VBfy5FnxSJgETh9EbBE6/Tt+xNqeU5OnpZLTztEgBzPodOIwQkidaRpPwrn5OTq3UULFy7URe0cIzx9mqfBc2cPehedN0hCQkPZLSREzPaneZSokVF0sMw2UzYHMrLJKiz2yCJQBIGjRbSKqOohaxRZQ+QSL00s5sNwsmJSbZJFwCJwOiJwaIQ8HVtv23zCCCRuTigo6zgeqV4t/1TyeoOEB/k5Tj4hK1AK2AkNi9BFq7xO5+mnn5FHH31M/vCHP8j/3Xe/RrLi4+sJiye5I4UoQUBRM30juhCeOw7d52gVJVoH0jKFh0eyRiawrN2vWAj4gvLPmfL0qui5U56+2LotAhaBqonA0X7pqmaLbatOCoHMAxlanjuscnLyHxTq9XrEGxyj6d7gmsLzX/TgCB+sz4JE/e7Gyw3hGiD1GrWWsGp1pX37dkqwHnnkEeHOG6/Xe5gFIgVuvWHhuYflk7A/M01SkvaxK3kmuqU79qNCIAC58phO9If45cxBPaVB43gJjwwX0srDQU9ANLY86rd1WgQsAlUfAUu0qn4fl3oLiRRBZNz1U+5gFRMpgjB1KOLI0f4gUbx/jdvIb7t5tD4V/s477xRuqT7a4mGmJLMzcoXyIcE1JMiwNogXdylSH/sH9uyXzIxM4b1dpFmpGAhAqJq2bS6hEWF6J98F142US+65RM4a2c+Q7boCCTvVntqI1qlG/GTrs+UtApUPAUu0Kl+flavHrI/CgZSkVNmxZRe74vV4JCIkV7jrMDi8lqQe8IhLfFThGB+O4wjEyXGOTs7E/KGSI9ni9URJUHCIeA3ZglyZLP3P+qw9u/ZJxv5MycnJU9EM+1GuCECyep7TS3oP7SWh4SE6/Ttt7HRxzLRzT5M2+NJzpF7jhqc8suVeJJQrOKVUOe/oW7p0qfDw1FIyWa5meBL7l19+KZ988onwgNLSdIbfJ97Bt3btWvMbkVOapq0ti8BhCFiidRgkNuFoCGRnZGmkKCc7U3jfGz9YjiFaLIKnHC+BzslIKtmztChwApKdnf/4iJio/KlFyJVrhihb4sZdgn9Mc/KQVTfvdNxWhDZDsrr16S69h3WXatHV1KXMA5ky8csf5Nu3vpN1y9ZJk7ZNpOeIPhJVM0bzT9XHyUa0IPmcf3wPTpXPR6onOXmvjBs3Tnbtyr8AOpJeZUgHzzFjxsgPP/wgPCfP6z35oWr37t3Ca2J40jv9xt3NP/74oz49vzJgYn2svAic/NlbedtuPT8BBCAu6WkHtCTve2Oa0HEc8XrzSY8/rKbs2Vf82ikp9JdX6OhoB0wXuvn8AOfmmkhV7l7h9nqIXaqJoJFPHs85Sti2VR8W6UbfyLNSPgiwFguSNejSvvoql0AvIO2rlqySSZ9OVLLVsVtradO5tZzKKUSPuUgI9Kmk+5xrvJyZ6BED9p49e44rilvSeo5Hr0b1GLn88iukdu3aApEgwoWPfEd5uS9pbPGZLW1A0IEs8lgWdNkn3dVHlzyOEY7RY4sePpIeWB823TzysUkZ146b5pZh6+qzRXfOnLnSoUMHfRVNdFSUvgmCOl1d9NhHN7A+0ovWxzGvohk7dqwhojupXtq3by/nnDNEf0coQxuwhbj2SKdOjvGdPPRIVyP2wyJQAgQs0SoEkj0oCQIQGNZp7d6VKptWbNAiXHWyEx3hkYSEHTo1xPOx+EHih4kfKa4oCdcj6Gzbtk02bdqs7z8jhO/K6tWrJVDWrVsrPHeL940lJu6QxMQEte+VoAKCR93UQ5Rt/75UyTiQZRfCA0o5S7f+3WTY1WdLVHS0OI5T4A1RrvNuuMD0nyNbNmyTeVPny749KdJzeHeJiIku0CvrndzcklwUFPaCc5pBe6eJHHGBgY0VK1bI5s1bypVsbU9IlEcf/ZNs2LBB+K5cf/0NctPNN8tZZw2S8847T6M51113vQwceLawXbZsmezbu1f+/PxfhNfS8Mqas4zuP//5T9m3b5/w+JW77rpbLrnkUn29TXJysqaNHj1abWLj1yW/KqlbsmSJXHrpZXLrbbdpHvVin+8kROW55/6s6dRBVAnCMnXqVBk+fLhcc+11cvfd96gvIA2eL730kixevESnDV977TVZtHix3HfffeoLr20havfpp59qeXx+8KGHhIcc0zf4+dhjjxfU98EHHwiRq7/+9a8y7cflcs899xrbi2Xy5Mny6quvyoEDB/QxM7wPEFvI0888I/Qxtp588il55A9/UAzIe+WVV4Q24asVi0BJELBEqyQoWZ1CCGSaaZ8MQ2Ry01NkybzlSnpcolX94Mtkn//7a/Lksy8JP1I8vuG+h56RPz3xD3nsqRdVyHv6uZeF95X95R9vyt9efEuFB5X++c9/1vTHzI8lwvu6fv/7R+SPf/yjkT/IG2+8qY+QwCkGOrZ5ZsDcawaN5fOXaTSLacOs7OMfRLFl5cQQ4LVMNz58vfzlo+cK5OKbL9BXhBRnse/QnjLk0iESFOyTtcvXyfq1W6Ru3TpSv3F8ceplklbSiBYDOOJGRtavX6+DLa9CadWqlTRs2FAvALgQQK9MnD0Oo5AV1EeOHCnffvuN9O7dR95++23hXXNff/2VvtiXacbMrCwlGdHRMfLZZ5/Ju+++LStXmijjpEk6/Z+RcUAuvvgiJTzYhJhcfvnlanPkyBH6QuKdO/Pfb0p9V199tYwZ84W+cHjMmK/0DuTXX3/dbFPk448/lMcee0zJmkvC0tLS5eabb5K//e2v+n5BbNAn9957r7HRQm666Sb5P7PP0oSsrGw5//zz5N//fll/c2bPni0vvvCifPjh/4RXyUyfPt3Uk6bkKTMzQ8aPHyeQqzVr1gjlH3zwQenVrZkp/29p164dVZk25ujbLIh0LViwUH0Hn4iICPnoo490vdvevckSFRWtGPz3v2/ITz/NFmyqgVPxYeuo9Ah4Kn0LbAPKBYG0lFQlNLyOZOWiVQU+sEj9QvMD3KvbmdK9gT+pHAAAEABJREFUS0vp0qWzdO58rowY2kvOO7evkIe4+5dcfJ2mcTyo/7ly4YUXyLBhN8rIkb+TK6+8Qi666E657LJLdTt44FXCFXG/3hdLVFSULDLTTlu2bNW6D2RkyoIpC8SNZmUe4Ynyqmw/ygwBv88rvMfMFZcIF1chg1/HXp0krk6sPvdsx6YEXS/ToFm94tTLJA3ycCzDkCumBpFt27abKOwmJVmUIzKza9duqVmzpkRHR+u0VEZGBlnlLtXNVCIkkIuftm3bGOLSSlo0by41TDpPvE9O3quEhTt3O3Ror/43atRIv7NEh2hHXFycdO3aVdu3adMm2b8/XXgfaWxsrAwYMEBYsL59+zZta4yJRLZt21bq1Kkj3bt3l927d+kF0aRJk03kMkggRkSqk5KSJTk5WYh21a8fL3379FGi5J4rjuOIz+dTcsTyAJ/fL16PV7hL+YwzzjBTo7Uk1uB9xRVXyLr162T+/Pmmrt1Kinbt2ilEF0caghkTEyNt2rQxkbZLpX79BmoPR7EZ+DgRplKXL19h2tPf2K4tsbE1D/q/x5DnRL1Q6NGju059x8fHm22McC5gy4pFoCQIeEqiZHUsAkURIKqVkpyqxGaFIVo8pJRHO+zctV6Q1RvWyrpNu2Tz9r2yY8862bg1SY9JR8j7ad7P4sqMGTPlh+nfydwFK2XZynlm6uNnYSpx48bZsnjZRk1bu+U3+XX5ZtmVtEynFpf9Nle4y7FhfIyu8Vk2b4WSPxvNKtpbFfc4NDJEYuvXEdb+Je1M0oG/Wu2aJ+PwcZUlenKsAhAOBm9kw4b1hmzsLyjCNPratWs0KlTdRHM5ZuCuCFEtnKR9iEtczPwtySo5OdkC0fQYEuPxeDTN6/EoscgpeEZekLh5B8wUG0p+Q4LYBgcHs1FyrDsHPxzHKXj1UG5unokypRidDCVduSbyDGmB0Hm9XkOo/MLNNAeLlniTuGOHvPfee7Jt2zYlbG5BSDH7rm8hISHSskULiY+vW9AO8gMlOzvH+JepFwhuuls+Oztb8NNNh6CBZUXpX9cvu63YCOR/uyq2j9a7CooAg8r+9AOybd02yUrMM9Gm4dK7d29zZThAzh8xUC4cNbiQkDZiaH/p16tTQYvyspKF9Vpbt26RnIxdkpG2Q5o3jpWzzz7bRLVGmgjXhXLNlaPkqstHFMgFF1ygi35Hjx4tt99ypTRv0ELX+HCnYYaZ0uSp8AUV2J1Kh4A/13vKfGbgP1ZluYYsQLYQBt6i+nwPIFcMwF6P15DFyvX6p9zcHGHdJORhX0qKrFu3XiNYRH4C21q3bl09XGemTbMyM/ViJzg4RHXJyMzM0kgVOK1bt06YzgsNDZFmzZprlOsq83295pprpG/fviYqVJ0iJywbN27UNXGjRo0SnsUXG1tLbUVGVjMRqVhdgwVZZCp3/IQJ6muuIXko0V62roSHh0m9evGybNlvSrgyTdu4wSE0NFSIirl6RbdgsNdE5tgWzbPHFoFABDyBB3b/NETgJJpMVGtfcoqkH9gvaXvNVWtSrtSsUUP4QUYI9QcKaVxZbt++XRK2rDI/iDWkRYvm0rdnW+nee7B06tpXI1QzZy8zg1WWNGnSRBo3biyNGjU2+01VmjZtKg0aNBTsMl2TbojeLz8uluSdewTSl2qmJYiOiP2rFAiw6Hrn5u1CpCAmNkbvANu1M/GU+e5Ga06mQmwQAckzA3mOIS1eb+X6Wc02EZ158+bLU089JU8//bSJzu3XCybHcQrBwpTg4MFny7vvvit/evRR+fjjj2XQoIFKolBMStoj77//vq7D+vHHH3X6DbL1u9/dYsjbOnn8iSeM/Wdk0qRJpo50ipyw8LvAFN9zzz0nf/vb32TlypVqMzjYL1yILV++XF/r9cIL/9DIOKSJd1T6/T75y1/+ImsNEXQr9/uDZeDAgeY3J1OeMD4iK1aslH79+h6RaEFKsfGeae+WrfnLF1x7dmsRKIpA5fpFKOq9PS53BLhFP8VMISbvSRYWov887Rdh6u5Ijnk8XmndurVe1cbVDJPk1FzZYaYBdu7cLTu2rdWIVvv2raVGjZoFJvi9d4VE9nnkw1bzAzd73FyNqGWaEP/eXWbqyS6AB6JyER4Qm7B9j6xfsaFA0lJTj+gL58nCaUtkuyFaPD+rYbN64nU8smbZuiOWKe0MN8pxNLsMzvXr1zdRj3o68Ho8hX82WccEoUg52NaQkFAzQ1eYpBzNfmnl1axZQ26//Xa90KlVq5bccMMN6jP2u3TpItdcfY0Em+k+j9crffr0FRauQ0BYo8V0HmSDCNEtt9wizZs1M5GoZrpOMj6+nraHshdddJEQSR4yZIiWHzZsmE41UkdMTHWNRJPHIvYB/fsrce7UqZPce++9eofgkCHnCGVqG/86dTpD7rnnbrVN+UDxGh9pS48ePTS5YcMGutaqibnwchxH11L9/ve/F/zBZ96NyjYsLEzO7NZNcRhifCTt0ksvVRyY2mVBPGmxsbFy5plnqs1Qjbo1k5tuulkog1x33bVC3TxWYvSVo6WTaQP9jv1rr71WWIvGYzT69OljfqtqiP0rXQSqmrXCvxhVrXW2PWWOANEjpuogWyxEXzTjF/lx8s96dclVX1EHzG+kxMfH6xUkP3g3XnuJ3HzzzXLnrVfJHXfcLrzn8ObrLjU6dQ/+APO8LeSQJaYEtpqpxh+/nSObV23QiNoe1vdYknUIpHLYSzJRxW/f/Ur+/ei/CuTzN76WvWZ6pTh3xn/+g8z4brpmNWndROo1j5etG7ZL4radmnYqPhg8j1UPBKOZIR5EU1u2bCmQGLdctchIIZ0H5RKphXCFhYUey2SZ5EMCIA/4EB4eLp07d9bpO8dxNOrUvkN7XRAOialfv56SBW5I8Hi8OpUHaWChO5Fkn9+vBAJC4b4Sy3EcvQmla9euuiA+0D4NgpByEYUNiEl4RIR+h72GNIEf6bxiq1GjRuLz+w1ZqqVRL/IpHyiO46j//FaQHhUdrf6y5Zgyrs1evXqpLn1DX/n8fmnevLn6SB6RdPQR2oMfRLewzTEYIA0a1Ncy5FPetQVuRM8dx1G/aRvHTCuyD974ZMUicCQEPEfKsOkWgeNBID09S3bvSlbSs2DKXPnm3e9kq4k4Fbd+wXEcXWDKjxs/ZgwK/PBxlcmPus/v13zRPyIDiB7I/v37ZdWiFTL+/YlKsohkQbKYxszXsJ/liUCWIbsFkuPILzMXyPiPJ+vdaYHEOy0lTSZ/MUnyTCSSV+/0PPtMiQyPkBnf/yhM/56qNpQkooUvjuPoOQmZaWSIAgOt52BkizvQVq1eLcFmCorBmwFdTunfococ59B3xXEK7zvO4ceO40h0dJTwHXQcR9voOIX1pMif4ziH6fE95vsLJrTfcQ7ZEPPnOE5BGcfJz3McR4mYHOHPcQrnO45TSNNxnEI2HedQvuMcypOAP8dxtIyYP8dxDqsf3xHHcYxG/n/HcQrpOc6hY8dx8pXsp0XgKAhYonUUcGxWyRAgqpWbnam36KeYacRMM3gSafrmzW9lnolw7UzYrdOJgQNtySznaxHBgmBxh9HkL6fJ+E9+KFiTZUlWPkYV8jMvRzg35k2fJxNNn+1K3FPgpscMUDGx1aV157Zy/g2jpF7TeJk3faGs+GW5ZBmyVqBYxjsQg+OtArJF1CfaRFk4Lzds2CCRJrLVrHmzQneuHa/d8tAnGsO03uDBgwsIyIn4wXOpWCvFBdOJlLdlLAJVGQFLtKpy757itjGoEqmA/KSkpgvrtuZOnCvjPhov82ctkg0rN2pkg7uSjkW6IFfcyZW4dYdGsGZ9N0u+ev0bWbXwN42aYZ81WScSyTrFsJz21dFHkK0pX02VxB35ZCso2CdDLj1HLr3jYqkeFy2LfvpVpptpRKahTyVgJY1oFfUJsgVJYduqVWudqmK/qJ49tghYBCwClmjZc6DUEWBgZfqH6FZKyj7hrjII1w9jpsjM72bLT5N+liVzf5VVv67W5+AkJSXpKz+IfG3atFnTF89cKj+O+1GmjZ0hU8fOlCWzlyhxg2BB5CBZpzLyUeognWYGOScW/bRIfpowT3hXps/nk3ZntpatqzfLD5/O1GnEHVt2aATsVEJzIhEt1z/HcXTNTmRkxElFg1x7dmsRsAhUTQRKQLSqZsNtq8oWAUhQWuoBgRCxdis5ea/s2L5DI1K6YH78TzLj25ky6ZOpOq30/YcThYjH1C9maPqcabNl2bwVug6LyJhLsCBwDNpEz8q2BdZ6aSNAtHPrqlVC1IpnT3368ucy5t2x8tPUWbLLTC+XR5+eaESrtLGx9iwCFoGqi4AlWlW3b8u/ZXk5ut6GgRWCRCRq965kSTaka1fiLiVeRLtYz+XK1vWbNV3zE3ZIwvadstsIhA2CBYEr/4ZZD04UAfoPQkVfLp23VBI2Jwr7J2rvZMudTETrZOu25U8CAVvUIlCJELBEqxJ1VmV1lYGVAZYBlagGpGlP4h4lUDxDKVAgVUwhkQ9BowxlsVFZ22/9Lh6BitCnNqJVfN/YVIuARaD0ELBEq/SwtJZKiAADLAKBKk7Ic6WEJq3a0RGwuUdAwEa0jgCMTbYIWARKDQFLtEoNSmvIImARqGwI2IhWZesx669FoPIhYIlWcX1m0ywCFoHTAgEb0Totutk20iJQrghYolWu8Ffeyn0RURJXv7ZKTFRI4YY4XqkZVyM/L7a6+IJOzWnGQzCr1a0njZs3lsN8KuyhPbIIKAI2oqUw2I9KgIB1sfIicGpGwMqLj/X8CAjUOrOrXHzzRSp9z+4iEWFBhzQ94TJodH7eOSO6Sc1o/6G8stzz1pELrj9XeNJ4915tCvtUlvVa25UWARvRqrRdZx23CFQaBCzRqjRdVbEcDWkQLy3aNzfSTLoO7Cztm8cJESW89DgRUrdZPc1r2DRWeA8a6WUtoRGm3qatpF6TuhIVFys+XwD5K+vKrf0KhkDJ3LERrZLhZLUsAhaBE0fAEq0Tx86WVAQciajVQDqe1U1q1wjWlPL6SE/dIF/89wsZ+84EmT1tqezdl1Ferth6KwkCNqJVSTrKumkRqMQIWKJViTuvNF0/GVtBQUHSqF0zad+mgfiOsB6LtVO9h/SWsy8aLI3io/Kr81aTZl07a1rfAR10qi+qXms9Rpe1Vi1699HjAcMGajl/iF8atWklHCOdOjYU0vIN1pS61fwSFOaV6tWCxOt18pPtp0XgCAjYiNYRgLHJFgGLQKkhYIlWqUF5ehrKycmR9PR0CY6uLZ3OOVPia0cWC0Rkq5Yy6KoL5dwrhkiLprVVp5o/VFr17SnDrxguA0d2lpox4VKrc1MZOXq4nHfdCLnivsvkhtuHaZkLbh4hN/zhGhl+w2i5+fejZdQNw4S0yx64SQae1U4JHlOH/a48V0aN7i+dz6wpwX57eov9OyoCNqJ1VHhspkWgPBGoMnXbkajKdGX5NEvXe10AABAASURBVOSAIVkbflsn+/btk1pN20mPnk1KxRGfzychuWmyeska+W3DHoHQRddtLN2N/S2rNsriRWskOTlZwsLDpUPvNpZUlQrqp58RG9E6/frcttgicKoRsETrVCNexepzMvbJ1uXL5Zf5myXPEek09GxpHB9/0q2EwP02dZZ8+epHMm7cXElLSzM2HUnauFK+f/szGfP2dzLv192Sk+tIREyM1Mwy2fa/ReA4EahSEa3jbLtVtwhYBE4NApZonRqcq3QtB3bulKU/L5ZVW/bpFOLwK5tISHDxU4glBQICt2dHmi5o37Vjt+xJzz9V9+1Kkz3b98m+xH2SmnigpOasnkWgWARsRKtYWGyiRcAiUIoI5I9epWjQmjo9Edi4Yq2s/GW1ZGRkSKNOnaVGRIXHwTpoERAb0bIngUXAIlDWCFiiVdYInyb2c9L2yaKps2Xt9jQJ8vnE7ztyw2uE5Ee7MsPyVMlrz0LFwX6cegRsROvUY25rtAicbgiUfIg73ZCx7T1uBPZt3y7TZiyR/ZlOsWVTUtPEa1hViyHtpcOZ7eXMof2leYva4hSvXqwNm2gRKE0EPJ6q8xPIDSNJSUly4MDxTann5eVf8IDr2LFjZcGCBeyelATaPF5DJ1qWchs3bpQtW7YUVEkaB9wZ/cYbb8iKFSs4PKq4ZdiCxZdffil7k5OPWuZImdhISEiUp59+Rl588UXBv/Xr1x9cc3qkUoenYwc5PEeEdKS4PJtWMRCoOr8yFQPP09uLvBxZ/d0MWbx8s/nyF4YiZcVK2Z6QLJlZjtRo0lFueuR6OW9UV6lXPbiwoj2yCJxCBKpSRGvnzl1y7733ysyZM0uM4M6dO+XTTz+VTZv4zubJ8uXLZc+ePSUuX5wiRGfMmDFKKo6XAEBCvvjiC8Gv4mwXTQs8hmh+9913MmXKFE3G1vvvv68kKTs7R+bNmy+7d+/WvKN9UGbJ4iWqsm3bNlm27DdJP5Chx8f7AcF7+umnJDU1RTp06KAkEOK2efPmEpvKyszUPp08ebLefR1YMDs7W6ZPny7F5QXq2f3yRcASrfLFv9LWfmDTVln162pZvXqX7Ngb8COUs0+mfDxZFi5YYfLXyMa1O3XdFtGuqe99JbOmLTHpq2X5gt/k5/FTZNbEuXq8dcUW1dufmi6rlxa2G5KcIdvWbFG95C0bCjBL2rFB1v22Wrat3qJp6ampsnHFKlm+cINs23LoKl0z7YdFoBgEqlJEq5jmFSQxIEOm5s2bJ7/88osSmTTzffn1119l3LhxMnv2T5KSkiIRERFSrVo12b9/v6xatcqQk3mydOlSQbfA2MEdCMDatWtVJ9Dm4sWLZfz4CZqeaqLYkC0IC9EhhH1IEeWxvXr1aoHYEO0h//vvv5dFixYVisylpKQKxIm7j7FHvbSHfTcvPf2ADBs2TAYMOEuI7M2ePVu+/368LDdRrAMH0tVrSCS+ggN+UF4zzAcY4Q9lZs+ZLYmJO0yqSFZWpmzYsF7mzp2rWLgRQ/x3fcb/vcnJqu9+kA9xRXr27CktWrSQdm3byqhRo6R+vXraB7/99pu4Qv0QTGzhH+0Dp7Xr1imRmjp1mmw3swakuXWsWbNGiSV5W7duUyIGHrQDf8EWf/GFfbdPwQcMOaY+cAcP6qQcGEFKwQef0MWGW6/dHh8ClmgdH15WGwQcr2yfMVPe/uu78vErn5orvs2SGzD9sGPVMvn8pf9p/piPpkribkPETLQrcf06GffWB5r+3j8/EvK+++BbPf74g2mqV5zdvVtXybev55f78ttlsi/XkChD6JbPyvfh/f9OlE3mijU3J1HrxfaUqUsldX823lopQMDuFEWgKkW0irbNPWZghlB9/PFH8t134+Szzz4XoiobN23SqbTExERZbCI4DL59eveR+Ph4mTNnjvzvf/8TphLfeecd+X78eB3EA20uMoTqww8/Up2PP/5YENdmQkKCLFmyRPbuTVZykG/rW42eEUGDFOwzxO6vf/2rvPzyyzJ+giFEJpoGGdi6dauSQUiVW9/WrVvUZ4gBUaJ//etf8u677yoZ++23ZfL1119LQsJ23U6ePElJDIQvMTFBCSPP+cvJyTaEco6MN2355JNPtH0QL7eOrKwskz/bEKwEcwG5WqiTvK3Gn0mTJhvsvpP//Oc/ig03/dD+zz//3LT/W/nY2Pv0s88KEdJ0M4W7cuVKSUtLN8RxsUb4VhlSSZnNZnoTcsOU4qeffqYRqx07dmgbsTVmzFfy6quvyoYNG9QXCB1Ec50hXRAy/EKYCnXz1pvf1+TkZJlgsPz88y/U3w8++FAJ4u49SUKk7pVXXhFs0yb67vXXX5fvxn0nb731lrz++hum/i+UnIItmO5PS9Mo548//ij0F3VaOX4ELNE6fsxsCUOacrMzJS0lTSUrO7cwJibfzcs8kFmIhHEcmOceQ4oga8XaLWLPrcwtiz3KyhH0XH27tQgUReB0iGgR0fj6628kJiZGrr76KhNRGamDN2QIYtW0aVM599zhUrdOHenQsYNERkYqSSK6de2118rZZ58tEBWiGy5+uTk5GrHi+Morr5TRV44Wv99vImKR0q9fPxO9aS5DhgyR2rVqGaKRJg0bNpTLL79MLrjgAp0+W7NmtUByk5KSjW4LwUZvQ/J69+4trVq1kuHDh0t0dLS4f9HRMbpL1AWSACkkEgQ5IcpDZvXq1fUtFRCmxo0aaXSrcePGgs2aNWqgIvXqxRsMrpaLL75YsAVxcdsVEhJifLxC6tevLz169JC2JvpEIdL79+8nt956q/o2bdp0JXIzZszQ6B/tAr8pU6bK2rXrKKISHh4uffr0NbhHyXnnjZIzzjhD2wxRhCzRLyiOHDlCLrzwQkPwEpXU9OvXV2688QapUydO0kxEsFevXtK1a1dTvpN06dJFcaYc0r9/f2FK8owzOknnzl2ECBckeeDAs4S+a9KksSFeEyU5OUn7sFGjRmq7QYMGOp1Zy/TP1VdfrXhDCuuZSBvtHDRokK7V22Gmllu3bi1ECauZ84I6rRw/ApZoHQUzm2URsAhUbQQY7Kt2C8VElfYKg+iECRPk+ef/Im+88YZGSojmhIaFCm9hCAsL07uFwSI4OFiaN2+uEZj33/+flmdA93q9ZKt4vF7p2LGj7N69S95++21ZtHiRnHnmmVInrraEhoYaMhAsEJQgn08YzIm0vPfe+yaaMsZEmFYL0aqcnFyj51M7DPCRkRFalnenQlIC64uJiZbY2FglR0yrQS7i4+sqIWRqizoCiQD1YgMf8MfjDRKvkXbt2hmyVU+FduKHNsh8OI5jSGaEBAeHqB/km2SJi6sjzZo1k7p16wpEBdJCe1auXGVIzAT5xz9eECJCRM8SdyRSRAX/w8PDTBuDDQHFbrCmB37Url1LOrRvr22jfdRBFJHpXIhe4yZNJNwQNkgsEmLIoOM4BSboN9qnecF+7VemDYlI0ddMg+7atUvxpj3YpA2hxg7H4I40NWQ70hApSG6c6cOGDRqaKdNsJa741aBBffH5/QX12p3jQ8ASrePDy2pbBCwCVQiB0yGiBZn0+31y1VVXyQMP3C8PP/ywIVzPy2ATqSquKyFeffv2lfvuu0/OOmuATiu+bqaYss3UmqsPbp0M0fq///s/jQ5B2t58803ZsHGjq6Jb6p40aZJGaq688gqNJrVu3Urz3A8Iibt/pC1EgqhYQkKiMI3Vp08fgfzNmjVL12NBFDxe75GKF6QXrQv/CjKPsuPx5Nv2HLxLNdeQRMjfJZdcUoDpa6+9ZiJhPY9ipfgs56BNon/XXHOt3HbbbUpOIUsLFswvWuioxzkm0giZvPPOO9WvJ598Qh577FGpXbu2lvMWwcg9pl0+X5B9rpyiVPoflmiVPqbWokXAIlBJECjpQFtJmlOsmzFmypCoBHe6MWWEMH2VaYgTAyxTbUxluYW5e5EIDdNqTLsNGXKOIUorZH96uqtipp3S5FVDLFiHBeG69NJLNQLiTuPl5GTrNBkFWENE9KRxo0YcGmKUrNsjfeBL0X5xHEfwm3VYiYmJ0sREeiAUy5evEKYPGzbMt13UZlbWIT+K5h3tGEyK+hCoHxUdZaJeYSait1vq1KkrDRs21Ls1c027A/VKup9jCNLP8+bJe++9a6Yjo+RCM8VKnxGJdG2g4+4X3bp5+EGEDwwhn/T9nt0ndxcpUT8W+rt1FK3bHh8bAUu0jo2R1bAIWAQqKwLH8BuicQyVSpPt9XqEaTcWnt977736qAcWW69ds1ZGjx6tC9/vv/9+QVgszV163GHI1BgLr7k7TsxfdHSUMEh/9dVXcs8995jB/z1hHRFrtky2/g8zU46sF/rhhx/kXhPVeuKJJ3Vqjakp1kqFhobJO++8I5C1wWcPloSEBLnb2GIx+Z49hx6xEBUVJd6AKEvt2nFqn8XurKHSg4MftczUYUNDaJiiZJorLi5OIFtMfcWYqUXUmEbzmelKx3EEPzIyDugi8K1btwg+gw96HhNFioiIFAggx4HSsmULYfpu+vTpB6dVQ42P+UMlkbWwsHCpWbOmDB06xEyDrpLf//5hjf599913AnkNtEU9TP2xJZ368ZEt04DgTzoY0DbIzDPPPKOY7tuXYiKKZ4nX41Fs589foIv9IcmUQSjHdKPmffONtGrVSoj20Z/087PPPivLVyxHVYkh9eqB+cAPsDK7gp2IiIiCiJbH61G8PKbumTNnytumL4laomvl+BHIP3uOv5wtYRGwCFgEKj0CR4taVLbGRRvScs/d98iNN96oi6tZYH3OOYOlTt060qlTJ3n00cd00fk111wjd911p4kQ1VfCcOONN8jNN98s8XXrapMhAEOHDJF7DVljkTrTg9dde60OxqpgPhiYmbojD52bb75JCVyNGjV0muqGG24Q6mHtVPsO7fWBnTebOrAJkTjjjDMkOjpKmOJq0by5sZj/n3VXkDuIYXR0dH7iwc+Q0FBdrE59EARIz+9+d4tOXbIPKRg5cqScbYgdRRrUry9/+tOfDEkcKXXq1JGbbrpJF96TBwm77LJLlZg4jkNSgVx33XW68J3HMUAmzz//fBNlqqb54HjNNVfr+rNu3brJQw89JCwmv86UYUqWKJQqHvyICA/XKbw4QwrBjLVeLMTn8Q7Ypi2kox4fHy+3m2nD2267Vfvpqaee0rVyPr9fBgw4y9T1oIAbbUUfgTgNNlPADz2Unwdm9BUki/6/5ZZb5KKLLhKmJZm6hQiDk8frVdx69OiBGcE/Fs/jFwkNTYQQvDjGT3Dl/CLPyvEjYInW8WNWlUvYtlkETisEGHSqSoN9fr9w1yB3/bnSvXt3XWjtOI4ZTGvrHXikQYhot+M4Gi1hwI2KjiZJxef36yDP1CFRI5//8IXQjuNIQxNhQgfSERkZoWUhDiyeph4iVo7jKKmjDhbZE3UhChUSEqLEIbBeyjZu3FiwFxYWpvbcD/Iyg5ZnAAAQAElEQVSwS1n2Eern2HEccRxHI3HoUMbnz28D/uMH2xgzjUoedUOkXBxIc4U06scuxInonhv54hj/qRshmkS70Cdy5dpwtz6/X+8UdPPwAwzCTfTIteU4jqo7jiNgAZkCUxalO05+HtiSDjbUqwUOfmCLPPwkz+f3S5s2bfTuT7aQMZ/frySTtjmOo6QZP/BfzB/+oYstc6g3BYAXx/iJbZ/fT5aVE0DAEq0TAM0WsQhYBKoGAlUpolU1esS2wiJQFIHKf2yJVuXvQ9sCi4BF4AQRqEoRrROEwBazCFgEyhgBS7TKGGBr3iJgEai4CFTFiFbFRdt6ZhE4PREoU6Ll9wWJP8RvxWJgzwF7DpzScyDEH1qiX3Qb0SoRTFbJImAROAkEypRo9Tj7THn2naesWAwq8Dlgz8+q+B39/csPSr9hvY/502gjWseEyCpYBCwCJ4lAmRIt7oDgbg0rwfq8FouDxcGeA6fuHChJtKokOif5G2uLWwQsAqc5AsdNtE5zvGzzLQIWgSqEgI1oVaHOtE2xCFRQBCzRqqAdY92yCFgEyh4BG9Eqe4xPQQ22CotAhUbAEq0K3T3WOYuARaAsEbARrbJE19q2CFgEQMASLVCwYhE4nRCwbS1AwEa0CqCwOxYBi0AZIWCJVhkBa81aBCwCFR8BG9Gq+H1kPbQIVHYELNE6dg9aDYuARaCKImAjWlW0Y22zLAIVCAFLtCpQZ1hXLAIWgVOLgI1onVq8bW2lhYC1U5kQsESrMvWW9dUiYBEoVQRsRKtU4bTGLAIWgWIQsESrGFBskkXAIlC1EDhSa2xE60jI2HSLgEWgtBCoIEQrz7QnT/JkjeTK51YsBvYcKONzgO+a5KXp9858nLb/bUTrtO1623CLwClDoEIQrTxZKzlylxlc7zRk63krUt4Y2Przqngf5MoVkuM8bL5zX5gfGy50zOY0/G8jWqdhp9smWwROMQLlTrTyZI35sb/TNPtrI/ONrLciFgOxGJyC78HHAqHMldOXbJ2uEa2cnBxBzElWIf/n5eVJdnZ2qfuG3YSERMnKzCx128cySHv27dtXgDs+7Ny5s+D4WOWPJ592Yp/t8ZQ7mi7+F7XJcXp6eqm3gXMTKeTPSRxgC1/ZumbAhjTa5aaV1bYciZa5ijZTF7nyoohAsNLN1v63CFgETi0C6w3ZutXI2lNbbQWp7XSLaKWlpcn06dPltddek+3bt1eQXjjkBgPh+vXr5fXXX5cJEyYcyiiFPWz/9NNPMnFi6dotiWsM6itWrJBPPvlEDhhi4pahL6ZMmVKqRAXyNnnyZPnz838pNbtLFi+RTz/9VN7/3//k3//+txw4cEDop6+/+Ub+9a9/yVtvvSVpqalus054C2lbsGCBnp+rV68WcDthYwcL7t27V8aNG6e+v/LKK7J27Vol8V988YV89PHHeq7Nmzev1LA6WG2hTTkSLZFc53vjzFwj9r9FwCJQngjoBY+58ClPH8qj7qoY0WJwys7OLn7gMJEicN6xY6dkZWWxWyEl1QzaDJCl5RyYrFu3TiZNmixnn322+Pz+AtMQMASdgsRS3klJSZEZM2YI0bRcE2PAvM/vl/79+wukaNnSZaVCKrCLeL1e2bx5M7snLeCydNlSCQsLk0GDBilRx/bSpUuF789VV10ls2bNklWGGJ10ZQcN0PeQroOHJ7VJTk6WDRs2yBlnnCGQUM4D7EOuOnfuLBERETJnzhwlXydV0VEKlxPROnimySrjWoIR+98iYBEoXwTmSp6zvXxdKIfaq1pEi6jCr0t+lV9++UUWLVqkUQemR1xow82g0rJlKzNohrpJFWoLQWjcuLHExsYK+6XlHIP2Nyb60qlTR6lTp46aBZeNGzcqTgsXLhRwy8jI0LzS/GBqiv6oW7fuYbjXrFlThgwZIh98+IHs37+/VKoFOzD0+YJKxZ7jOOpjx44dBXLVtGlTiYurI61atVLxeLwSHBwipfFdCg0NlUaNGklUVJR4jV0phb+6pr9HjRol9K3P59f+j46OlltuuUWtQ7qaN28uQUGlg5caLfJRTkTLEclzTyo7ZVikT+xheSBw2te597REwOMpp5/AMkCbAX2miSzMXzBfiKAwtUO0ZFMpRTaKc5mpyB9//FGnxMaOHavEjuhQcbrllUZEZs3qNRrhad++vTiOo9GjbWbqlKm7hIQE2b17t0yaPEkjG+iXlq9gsWbNGjVXv3593ebm5uiWD8dxpGvXrpKUlCy//vqr+kV6RZPq1atLcHCwQEogqrk52QI5gXT99tsy6datqzRr1qyiua3++Px+qVmjhhKt6OgoTeOjgekPCDj7ROtycw71C2mlKVXnV6Y0UbG2LAIWgdMCgdK4Cq8oQEF6ZsyYKV27dJWzzjpLp6W8ZgqJqA0Dfmn7ic1JkyYJkSKICtGOjz/++Ihrv1jXgx6RpNL25Wj2ss0UKVNftWvXFggDuvQ7RBTi0K9ffxk8eLB06NBBpk6dVuyUKyQW34uSMDcdLLBbVBi8f/75ZyVy8+fPF6atIF6Uc3XDw8OlZcsWSvLw1U0vugU3fHDJQdH8sjqm3rlz5ypRAScI4eIlS4R01jtRb+/evSXzKDcYgBs3AuA/+5Q5FUJdCQmJsmjxYmnTpo32Lf3B+sRp06dLkyZNBAI8ffoM2Wemd8vKpxMlWmXlj7VrEbAIWAROGQJVKaLl8XjN9FOavPb6a8K0IWtTWIcVExOja2kAlQE+OTnJ6KULxIzBkvSiQnpSUpISBAZHpOjUFramTZsmrHO5+uprZOTIkarP4MsAF2gTIrJq5Sr5/PPPZbsZ+ALzAvcph1+s0WJgTklJPWKUB5KEX66gTz2B9tiHAEA2maYLCQkhSQWy9dNPs2XChPGyc+cuXcfTunUrjXipQsAHNqZOnSrLly8v8AeMIE8QTLAIUC/Y9Xi9MnDgQGHajWkxn88nECvHMbM6kv/nNTpEhlj8XRTjfI38T3ADPxbVF9fOfC1RQkTfQ2zpwyPpQthc7NwtbXLtuNus7GwlgRDT9PQDupaJtixfvkK+/vprAQO21OWWKW5LdBX/j0Ym8TUtbb/Q/0nmPAX34mzhJ/W5frPlvOH8Kaq/ffs2IeqKPm3mHNize4/p9wnCOQPmQUHeqjh1mL9GK0+2FcXEHlsELAIWgVOGAIPtKausjCsKCwuVCy+80Ax8C+X+++/XO7e4Ym/dunUBeWANF8SgTp04IbKyc9euAuLgusdgt/CXX+Tee++V0aNHF8j777/vquiWNS1EiYjSeDyOTisxkNUw0zSqUORjf/p+2bp1qyECB4rkHDqkP3777TdhMCR14cIFR1z78/jjjxf4hp/PPvussX/4mJKSmiaJiYkC4QwypAa7Ho9HWrRoIQ0a1Je//vXv8vDDD+mddMOHnysQH3QCBWLRq1cv+f7772XlypVKNoiSbNmyxUSjWonfTE8F6rv72KpXr55A8sCrbdu2ihORLleHbVxcnOzZkyQpqUe+cy8j44Bp31adFqbMkWTbtm1KCLt06aIEaf/+9MNUISS0Bdxc+d3vficrV7FuurA6becGAkjJ7Nk/yRVXXKHRoazsLG0X66k4D47U7641FqLT/7kHb8hw0wO3+LpmzWpdowU5TkzcEZhdsA/Ju/32Owr1P3c+7i+yzs1xHGnSuLFGK5eYKFzLli0N8R0kzVs014gva+fou4svvlgXxRdUUMo75RPRytsvuc4/TVN4dpbZ2P8WAYuARaAcEGDALYdqy6RKBnWmQQYM6Ce1a8fJZ1/NkO+++05Jhlthtagoueiii3Qh8HnnnacLgx3HcbN1i53u3bvLO++8o8SCARlhIFaFgx9gN3r0VXoXWpuOZ8l99z0gEIlAYseADrFjEOQWe0jUmDFj5MMPPxRIykFTBRtssmbp+uuvl5tuukn69etXEI0rUDq488ILLxTy789//rMSp4PZBZtsQwg4gDB4vF52lXhWq1ZNo3EdO3aQFStWyf/+96GsWrVS8FmVAj4cxxEWs1933XWKKY8GILoF+YqLq632AtQL7WKPuiAotOnMM88sdNcjykS6srIyTaTRXbtMar5AUMCLaBD4jR8/QR+nwGMQsJ2vdeiTxeTUddttt8mIESMMgQg/lHlwz3EcJeX0qyufffaZtGvX7qDGoY3jONqvnC+XXnqpLoxnTRORTNrDonL6y52WPVRStD3jx4+Xt99+W5iyw3/OK85LolCBuuxHRITrtDc2r776ajOtV4/kw6SD6bMPP/ygUP/feeedGi0sqsw5zw0HnPcXXHCB+W7UUiIPNhyTzvoyzr2iZUvr+BQTLRPJyktTkpUn74hIuhH73yJgESgPBGydcsRoSWXEhkjGG2+8KQxQr/7nFXn6sTuVzPzwww9CpIk28Syk//znP+LKRx99JJQjzxUGb9IgRui7wtW/q8M2IyND3nzzDWGwmjtrrPzzny8IUQhumycqhg7CFN/Wrdt0WpEpIWxDsihPfqAQZSNy5vrH87TwI1DH3Wcqz/WNLcdEXdx8d5uVlSWIe8yWqaeZM2dKcnKyPPfc/1PfW7VqYfafM9NWvJoKrcOlWmSkPiZg9uzZhtQ1kNiaNQ9XCkghwhLYHtrFNBvkKUDtqLv4vn37diXM4LfLRCHBE1yLFgRX+pR6XPn2228L+t/Vp4+ZggQ3VyDAxfmFTXRce0fbFi2fl5trInV7TCRum0by8J+oFiQrKyvbdUe3nA8zZswoODfdeoprJ/XQLvxCIL7cOUq/qrGDH0zpcsODa+toW4hg0fIHzZz05tQSrYORrHySteeknbcGLAIWAYvAySBQllexJ+PXiZRlDU1OTrZw231UdLRcZKYRhw8frlNi7lqXyy67TG6//XaNaF1vokYcE6kpWh+DHtNtDLKuFCUx3NkIsSJCQ1SHu9CYPlplpp8YyLHpOI6wUPrRR/+kBBDdO+64Qx566CFhXRI6gYKNa665Rn3Ev+tMBOncc88NVCnYZ7B1fWO7Z88eXexcoHBwh2gRwrSk6xcECN8bNmyoC+SJ4D3yyCNKCljrc7BooQ2DNlNW1IVP1Ld6zRo52uBM5MdtDxFB2sNaNh7BEGgc3zgmmsg2UOgfpoLBDfyuumq0gCdrvxyncDSSacorr7xS8aO+aw2WRG6I5gXaZJ920hZXEhISzLTu4Y+3wCbnCeeNK0TLbrjhBrnZRB3dNLZF28XjRPDnT3/6o95wgP9//OMfBUw4Z/DDFe5q5Lli2FHfr71W2DI16eq4W85P/HV9h4gWR8iYrh0wYIDigV1X8Pu6664rlM454PP73SpKdXuKiFae8AJbpgvz5D+mAZWRZBm37X+LgEWgSiHgDnBVoVEMSAxA27blPw+NB2Oy8JqBmnUobhshG5AMHjJJtMRNd7eO4wjPYWIgZYB3hUHQ1WEbEhIqcXFxQnSHaSwe+rhjxw5hYHacwgQAfQZSBuJAX0gvTiAvCWBKzwAAEABJREFUTGlt2rSpuGxNY/B3fWPLOhvWYWlmwAckIywsXNc2EWEhiwE4JCRE8JdF45wHCNOeYIZOoOTk5OQ/m2zxIunbt68M6N9f1ykRFVq7bl2xBC+wPJjTFiI2LukNzCfiSL34GpgeuA9u4Hc0HVef+lhLxuM+aJeb7m4dxxHWcIGbK5AQ+s7VOdp23969uv6LR2QcTS8wL9qQf/z3mLoD04vbh+RPmzZNb9goLh8/b775Zl2LiP933XWXQDx9/mMTJbCZPWeO9mdxtssi7ZQQrTxZa6cLy6L3rE2LgEXgpBCoShEtyFGfPn3k22/H6t1948Z9pwu7eSI2pMIFKjU1Te/CYiowJ7vw9I2rU5Iti+8vv/xyva1/4sSJsmzZMunRo4d06dxZ6w20Ac6sHRo6dKguoA7MK26fSNGR1vEUp3+0NIhJjRrVdZrQJTkhoaHqKwSHKTOEu+eYdqVdRe1BYJlmHDDgLCWhPr9fnyPFmiYiQ0S7ipYJPKY8U5Vgnp2dE5ila8KIyEBCIiOrFcoLPCAf/LjBATw17wgfRNuYMqZPjqBywsnZ5pxZavp65sxZGgEsqaGePXsJ/nu8+evkjlSOaCM4uY+UOJLeiaYzdTl+/ASd5j5RG8dbrsyJVp6skTz51Mg7xjcbyTIg2P8WAYtABUGguKv9CuLacbtBRGTYsGG6gJxF8a1btRaiUFz9O05+hImr+fUmAsNgSYTkuCsJKMA0V6dOnfTOL6JJl19+hS6+ZtoyQE13HcfRu/6YGsRPTTzCB+t3mBaMjIw8gsbxJdNOSChTTfsPvmcQ37nrcNiw4UqYmEJkirNbt26HkURqwwYL37lLkWMEG7SHKBgRMtKKEzBfvHixPvCTMkV1eNzBqlWrNUIWGnro8RNF9cLCwtTXGjVqHHXxPdFAbkCoVavWMSNtResoyTFTdEzZFUdIj1TecRwBO/AqDgO3HJFDSCfElKe4u+mltYVYc5dsZGREaZkskZ2yJVp5aYZglR7Jys3OlU1bsmX3vtxCjdu3NUvTCyWeggPqnbsiWw5kFfbnaFXThvWLMg4rQ3pxbTuarcA8yo97I03wJzD9VO3Tplc/ziiXfqDd1H08baXvHn3pwGHnEjZoC3I8/Uo5KxUegcMcPFZk4LACFTwBEsOdf9y517ZdWyEKEjiwcbt84o5EHdRLoymO42gdDKAMpIGRsxOxD0lgOq5x4yYSZqb7TsRG0TK0v2PHjvrMJEicmw85ql+/nt55yB10RIrQdfMDt+iCbWAa+47jGD/DiiVn5EOyWLyOHMk+D8rcsGG9QOSOVD+2SiLURzQwzJAyCHZJyhyPDv0DaeQuPd4ReDxlS6LLOkCicUx3BwcfexqwJDZdHUjcakNoedQG4qafim0ZEq08M134vSFa/zHtOPlIFkRiS0KuvPDgfnn6uUMDJOn/eyVD/vFy5mHkxVRc8B+9RT8cEAbkokStQOk4drC3bkWOvPSPDElLF2FgPtLAHWg2Oy1XLrk6XRavLUzOUhNz5MJhqTJjQeGwcmDZovuQhVf+mKrkJjNPZMOGPNm23ewUVSyDY9oPwRkzNUut792dJzOnZMv2Iz8GRvVK+wM/aPeKxUfHDT23/9nfvTNXfv4+S9KKkHb8Wz4vW96akaf9yrGVqotAVYpoub3kOI4O/EUHbQaaKVN+kOjoaJ1GS07eK0nJyWUS9ZAT+IMksN6JqaMDB9Jl//40IbJFFOIEzBUUcRxHiFix+J4708DBzXQcpwArx8mP+kkp/hGtYq0ZEbVkgzUPYOXBma4PbH/66SepX7+BRqsc5+R8oA6IKqQQ7FJTU7Wvqac0mgWJgwjxvSGyRVsgX6VhGzsbNmxQf5niTTbnJ20oLd95KO227dv0TmMIHaSbbWn4fiwbZUi03BPGsJBjeVGCfE/QIVdnfZspn43LKkSsdpqBHjM6iJrBk+gQ4pIqCM5PhghABtZsyxX00HeF6AXExS3DljT0sME+upl7szUKgj9tugbJS38Llci8XGFwZuB2bVMOXewg2KD8iQi2KI8dBF8QiN7XC/NkwerCpIA8ty2uftF6i9rEPoIeeVreRA+PVD5pv8ikKTmy8NccxYNyrlAGwQ/SsMsxwj5pRbGhTgQdtxxb9NkWLYMeeaS74vpMOrbcdLYQWbf/8Z00BGKILcSt5+xLg+Xe6/xSo1r+OYc98hH2KWelaiBQ1SJax+oVohwshJ83b76sX79O16kwjXiscqcq342SsF5q3br1+uBNBvOTrR/SefnllwtTdAzmkLqTtVnS8hA8nh81Z85cxXzDhvXCA0vxgcc08PiBm266UUrjXAwK8uldlNTHTQqsR2IRfkl9PZYeBA4/eYQHi+1Xr14tROSOVa4k+Y7HI6GhoboAfs6cOQar9UI7wKok5Y+lQ4SMiCvr1rDLGwyYAj1WudLIzx9JSsPSYTbKLrJSo55XoydFo0K4sHFplnzy/H65+eZ0FaJfmwxh+G1+tkBKVs7Okm8nZkvgYMsAu2JGpjz+QLqWudtsiS5hf6Ox98zvUgsiUJM/zZArL0tTkodNdL8zZAfSsXtLjka4sE307c2/HFB7+PLiO5mHERL8LYm4PmAHeeeLLMHfd980Nk2dn3+UKRC8XgODpEtzR6a8k17QFle/aD2BNh95KkNoBz5CUJZMzzysfCDBgCSB8cyl+VEhSC/2d23OlY+fPIQ9frq6+IEQsYMQBWJDH4EXZBid72flR6doI3n0A3YCy6BHHuWoe/minAKfacu8NYcihrRp1rhMeeubbKH/XX8p99G7mQV99Ox/MrVfqQfbtBlf6X/qQ8CIdMpaqfwIcGVe+VtRshZANngA6OCzzzYRngbC9BwDT0nuAitZDSen5TiO3rHI+/R4gneLFs114TyPZjg5y6JrmpguuvTSS/RuMyImcgr+fH6/Pt5iyJChEh9fVzGHTFA1PsyfP0+ftB4fH68+kn4ywtqjAQMGSJ8+fRXLRo0a69qwk7EZWJbI4MgRI/QBpthmvVhQUFCgygnvY4dHkwwadLaw7o0oIHfSFjV4osfckcqaRabVmfrMn54MPlFzx1WuDImWG9E6Ln+Oqhzt5JO3M4f5JLaGcxhhYgrv+8+yZFWuR556IVTeeCNUnA3Z8saX2UL06Z4LPdJnhF9uvjCoIFpBhZk7cuSdybkS0dOvZR687Oh3RVAmUPp18cq1N/kFAvjcY8ESEyay9PsM+XGno348/4BPp6kgGYHlSrIPwXjp+Qz17dXn/EIbiMqt93jl7oeDtc677wuWbs080mlQiIDRxHWO6tN+9JlWg0zKwT9sglNeoyBt7zO3B0mtlBzNhYBB4FqeFywffhIu+L7y64xCU5r+qCC56aEQ6dvOI/TFdRf5tCwfbjnqxc+EFFJFatbP75NzOzsC6XGxoU300ThDrg6k5glkNb9E/qcbqYTUQpTcfj3P2MnXOPT5f38NE+zRll8M8XJziD4SpbphVJD2/yXD8/2lrlYdvdpO/F23NEd2JB4iaJTH19+SD/UjacVNN5JupfIhwNV55fP65DwOj4iQ80aNkrvuulMY2IJ8+d+Hk7NauqVbtWwpPNeKh6FGR0WVinHHcQQCd84555Tpe+2Kc5aF47QFzNu0aSNgDrEYYnzp1KlTqZCswHprVI8Rnl91++23SaNGjUolWuba93i90rVLF8E2WBLlcvNKYwtWEKL7779PeLYVWJWGXWw4jmMIb7w+R+7GG2/UfdLLWsqQaOWVuu/JefnkLb6WI9ed7REGxkDywgAIyWLw7N4qSBrUC5LBA71KcnLDim8q0Q7W6zDYd27v1TJNWh0f0QpsaPjB6SYiXER4iJhA4tBJDBjE60SQcmyBfBA5oq3//CRHp+uwW7QkZIK0kAhHzmmSp9hAMDdFBskV1/olxOchWwWbq9flSv9zfNre+MZead4kP5+1VjsivXJGJ6+S0TZdgzSPKcJAsgbZUmPmw7UNmXLL1W3iFfxkas6oSJN2XunYNL8OsOGYPmrYzqd9BBl0+xf9osK0X8uePrVRL85jfjzyzwVXr7Xxl/6uEetRf7fuyNPolJtP/zdqlF8mPDQ/FWI8vE9+O1t3y78qc/3N1xAhnXbRj3MMcR5xTpDUqp3fDlfHbisvAlU/onV43zDAR0VHC9EIBknHyf9eHK5ZfimQQfwjCuHz+0vNEa8hCbwOh22pGS2BIeqjLbTJxZw02sm2BCaOS8Xn92v/Uh8L4x2n9PoYf/Eb22DJ+XRczh1DGfvYde07Tun5TtVEcbGNsE9aWUsZjhilCw5AEK1hi0AARncTedVMz0EaSMvZlaMRLPZdYcB394vbugSluLyTTWOAhswgt5oIEIN6ULhHiKy4hKykdfQ104LY6XdLqGCLKcLiymK/z3C/EJXrGZojRKMgCYEkqbhyRdNKSgSLlnOPo0zE0d0vbgtZLi79WGn+EzytTrQcJBQsIa+5v2YJWDKVeSw/bX7lQOB0jGhVjp6xXloEqg4CZUi0yi6iBfxEVCAUbaLzhIgPadWa+DSaQXSEdTRMkTENRrTjSAMtES2iIJQn4gQhIcLFcaBwNx+63OEWmH6kfTdCBCFiuqxxbo6qQuxG3Bai04tSgj8iVEzREaEZZqIvgbaKK86aJe7CZGpx4HWhGi3i5gGmVV19bOLf9In5NxS4ES7yIUhMvTGVR3u3rs8RiCzEyI1coXeiAhGkbqYV6SMWqRPhiqzjEYg0USb6gbq3rcvHTMwf689YX0X7WMtFP7jTiia7RP8pcyzFovms1/pimQhY4gN1ci4U1bPHlROB0zGiVTl7ynptEai8CJQh0TrB0MNRsGQgDsyuFu/TdUpuGlNCwy7xaVRrSO990qtPqjANdt8dfoHgEN1i0fQjT2UULEwnPaK2VwnJmHczpU/nfXLrI5muSYGEQQyevTtNho1M0wXVBZkBOxAUDlkoDxmATEFYWFSPH381037kQ/5YVB24WJt0V6hnyLAUQUbfkia/bBdd/8Udjfg28vJ0XU+GPr5BNO+4JLXg+VlxkSJMkRHpQ/+xl7Jk2M0hOg1IGQSSCk5ggc4lNx0oIKvuVB5YnHnGPn0UBWvX3HVNlHeFadnv3zigj8xw0461BW/Wd4ENfTRwaJr2Eevm6AfWSr35bLpQN74z/YjNDv39uiYMPMGA9VqkH4+AC6STRe9MkZakLDi52N907wFhbSDkuSRlrU7FR8DjKcOfwIrffOuhRcAicAoQOMlfmZJ42LUkSiXS8dfyKrEKHPQbdwqWz94PFRahh/g8wvGfXouQN18MkZc/i9DHL7B2hwoYrFkszeJxSBlpCIP/0OtDdWE45dAhHYHMQQyog4XYX34foQuuqYu1XCwkZ/E79VIOHdbwUOfzr4apb4F+ENFBz12vRB0IJIM6qJ8F6Ah+NqvrERa5f/ZmiLYJ+48+EqJrq/CNBeCUQQ87kCjaQh2kU/eTtzh2HPMAABAASURBVB++xoEpMRbLo0Nd3CRA+aJYUP6Pt5n5/oNrz9BBiDixwJx8pkSZygULt13YxweOIZ0QKTCjLBiADWURHpEBXm7d4EA6WOMjNijnthV/mX6F9DAFi33INDrgyHFgfaRje6CJ8GGbPPwFS/qKfPx1/b/q9mDBntuvLvb45GJPGSuVHwEb0ar8fWhbYBGo6AiUKdHyyEXiyE0Gg65GTv4/AzWExn2+kWuRNAZq95h8yAmLrdl30xls0SUdW246W/KwQTkiRaS5Ankh0kM5dLBBHkSHfcpyzD46rm0IBeW6NfMURJTQRc/VoRxCOrrU70pgOeoiHfuBbcIf0gPTsEUdpKPPMXUECnfxsVieKUam6NybAdBB37VL+aK+ujrggo/osk+drm7gMfkI5RDsk09Z7ENoSEfIww55LHpHsMl0IQ+ldf1lOpObHiDM2Ebc8uwjHAcKdrCNTeqnbtLQ4Zg8jsGa8vhCHsculoE4k2elciNgI1qVu/+K9d4mWgQqGAJlSrTE0KzSJltyCv5Yw0TEpE7AnYHuoHs81VPGlZKUQzdQr+hxYN7J7hONY7E8z+DicRAssh/W5/jvtjwZH92y7jawTaS5QjpEiAXprCv7YJ4Ij5EgsgkxIv94BLvHo291qy4CNqJVdfvWtswiUFEQKGOiRTMd8eQNM5Sr9CJbUsZ/DOo3PBGm03NlXFW5mSdKwxTj+6+Eyj+eDpHz+noLPQKi3Bw7SsXDbw5XX/H5lot9BVHCoxSxWcdG4LTWsBGt07r7beMtAqcEgVNAtEw7nHDxyMWVimydSKTEtLRS/SeyEyiVwfnK5m9lwPR09tFGtE7n3rdttwicGgRODdE62JbKRrYOul14Y48sAhaBKoOAjWhVma60DbEIVFgETinRAgVLtkDBikXAIlARELARrYrQC9aHk0XAlq/YCJxyogUclmyBghWLgEWgvBGwEa3y7gFbv0Wg6iNQLkQLWPMXyPdjt8IKDxfdtCVbeGZUhXXSOmYRsAgcJwKH1G1E6xAWds8iYBEoGwTKjWidSHMgPBAf5ETKH6uMS6x4DQ+67rOmkvZzZMUiYBGoagjYiFZV61HbHotAxUOgUhEtHlq59PsMcd/DV9pw8l4/Hoq5IzFXTfMgz3VLD71vTxNPww/bZItAVUXARrSqas/adlkEKg4ClYZoEc2a/GmG/PPLXOE9fF/PzBEiT+sXZcgrf0yVex/Zr+/cc6Nd6C/64YCmu3mvfpyhZYhcjXsjTfMefemAvieQct9/liW8Cw+yxTHdxLv2Pnl+v+pSfve+fBJWnA3qxC428WnM1CxMWLEIWAQqKAI2olVBO8a6ZRE4OgKVKrfSEC1QrdvEK22i86RmfY90ae7I9mVZ8tLzGbK9dpDw1PAVi3OE18pAhpZMz5SH/5YlkXU8wqtaVn6dIeSnpYtA2HgaOul1ErPlpX8YG6kijRo5UqOeV/V5hx517t6So/ZbePIJ3owFObpmCxs8oZx6sfHtxGzZkpArGzbkyfdvHBBPe5/UreNgwopFwCJQQRGwEa0K2jHWLYtAFUKg0hAtHlTJi4CbN/FIk3Ze4X11y+dly2/JjvDSY14YfN3ZHmGqb822XPlpSra07uTVvBuGeWXwwPzXy+xblyWTpuQomRrSSqTXwCCplZIjvyzKEYgcJO4MU859p13Lnj7hJcS8WBqSl2imFVMTczSy1teUbd0tSAka9W43ZI138FHmuot8wvv6qtC5YptiEahyCFSViFZeXp7s3r1bNm3afJgkJCTKzp075ZVXXhH2S7MT9+7dK//6179k27ZtpWnW2joJBDgXOA9WrFhxElZOTdGMjAx56623ZMGCBYdVSDuWLl2q5/VhmQEJO825jY2KfA5WGqIVgGvBLtGj1oYU8RR3JKqGI7FGtm3PEwgPEasQn0eCwg81c+/uPJm5NFfefDZdLrk6XW6694Aey1H+iG4F2ti9M1eIdLk2HnspS1bOPjRNiA/UCzk8ilmbZRGwCJQzAlUlopWdlSXvv/++XHfdtSp9B14kl1xyqe7/+c/Pydq1a2XmzFmSkrKvVBFPTz8g06dPl337Ts4u5b/77jsdcHNyck7ax+zsbBk/frz6Vpw98qZMmXLS9ZSngQMHDsjf//532bJly2FuTJgwXj788MPD0o+UAAF/7733Tjlhpp/mzJmr9bI/b9487bf09HThnP7Pf/4jpB3Jb9I5d7DBluOKKIcYSEX0rgQ+7TTEibVarI+CRDkbsgum7LbuyNNpPhbRu6YgY0wP/vGlcJn/a7T8/Es1+WlWhBCBcnVKug20MWthNRvBKilwFV/PeniaIODxVPqfQO0pn98v9957r0Aexo0bJ2f3by9/+tMf5IcffpAXX3zRRN0bq15ycrKsX79eJSUlVYgaIAxSpEPIiIwVR07S0tK0HDpEEbIyM9UmH0S2KI8E2mUffYQyDKbUxz4RCPQZ5Ddt2iQzZsyQhQsXSmpqvl/YdYW60MfOJhO1g2RgB1+TkpJUDR1sMUgnJCQYezNl7ty5smfPHnHbQ5kEE+GbMSM/j7Lk4Se+rF69WvANP9VowAdlA9tJ3ZRFZf/+/bJx40YltNjHF/TRwR5kCN/dPOyQ7pZPM20mj2NsBerjC4I+6bR/r+nHDRs2COR01apVQhn8QBzHkQsvvFBuv/0ODsUtS/20kbo04+AHUaW1a9fouUIUDGzxgzrQR1ycDhbRjWsXv9FZa8g87UXYx0/qAgfaix772KYtpJkTUG2RRh2QKvomwfSfY76bjzzyiPTt21fbkGD6jXOAuhBsa+GDH64/9KVbD3hx3h5UKbdNpfyVYZpuS0KuDLvEJ7s258o7X2QJa7KYLsxrFCR1IkSnCn/+PktYNP/dwjydLgRlb02vnNfZkc8/yhQWq5PPeivuNISEudOIrPNCvziJb+yVG0YFFbLx/awcsY+BKA4tm2YRqLgIVJWIVkkQzsrKNNGCCfLyyy/Lc8/9WcaM+VIH6MTEHfLRRx/JP//5T/nHP/4h//3vf4VBPNAm5OWTTz6Rv/3tb6rDdOHy5SskNzdHMjOzZOLESYfZ3bVrl4myvVeg/+qrr8kvv/yikYoPPvhAnnjiSa1z3LjvZOrUqYK9OXPmCMSBgdetH9Lys4l0/PvfL+s05T/+8XfTjvECQcCnMWPGKJHasnWr8e+vAlmYOHGiMO30yy+LZNGiRTpQY48oCfWRt2TJrzJ//nzZvn27fPbZp+oLpPTll19RPwN9oCztefvtt1UPrN555x3FiQH/888/lxdeeEHb+sorL8ts0w4w+/LLL+XZZ5+Vt99+R/NeeOEfstIQo9mzZ8ubb75ZQAK/N9G3t99+y5C8XQbLiQfb+Q9j8x+yePFi2bVrt4Df448/bravygJDSD/++BNJS0uXyZN/UD/w0RXqxQ/aAJ6Upc/ovw9NX+Obq0v///jjj7J582b55ptvFA8wedu0j3YiTM1tMmQYAuOWgxjRhpdeekl9euqppxQbImnU9cwzzwjt2m8I+qRJk7RvMg05h0gTPSMtOyB6ST9BjOmbn3/+WSBiTz31tJJl6qIezk/3/P3k00/1HHD9we7bpn/oX+qhDX/84x9l7Zq1rkq5bUuHaJ0i95m+Y00VU3MLVucJhOf5B3y6yP2dybm6aP2Ka/26fuvsS4Plngs9Mn1ilsqOyPw1WkwDjrgtRHrH5mk6+Zsig4T0GrEeYQ2YLprfl6trtliHFR4qwjQg67xq1/boVCQkL9CGHPxDp1XH/LoOJtmNRcAiUEERqCoRrZLAm2kIUcOGDTTyNXLkCFmyZIlO2UyfPk3WrVsnN1x/g9x0000aUWLgZZB27e7du0+++uprGTlypNxxxx3SrFkzSd6bbAgMRCtDXLvDhw+TZcuWSYKJSMycOVP377vvPrnvvvslLq62IQWTZfeeJEPOMiUsLFRuueUWueCCC2T48OHSuXNnGTRokLRr104HUKJsRCe2m0jGlClTpVWrlmpn1KhRMmvWLMkwU2eZZuDOMtOm+AlphkD4fD656MILpVu3btK9+5nSq2dP8ZuIHzpBJu+yyy47lNerlzCorzGD8bXXXiuPPvqYNGhQ35DQr5QEUQYBi+lmivTXX3/V9t96661qc6OJYs01pIDI4RVXXCFEYNq2bWsii1OVsBAdgiRcfvllctddd0lwcLBG7Zo2bSpEFyEvtIFIDu3esGG98Wee9OvXT/Wjo6Pliy++lPT0/ZJliDK4X3/9daZd3Q12N0u4GZzOO2+UNDf9gZ+uZBlMIKJEeX777TdTPl2uvvpqFXDFL1e3bt06MnTIUNOnzWX06NFSv359mWGiizt27DR13KLthfRMNWQYHNxyOTm5ardWrVgTPbtddekXsH7ggQekT5/epq2/FPR3upkO1LJ5edr/tFuPD36ceeaZ2v/0W//+A6RaZKRkZBxQEo3K/v1p5jxrKHfffY+J2F0gkyZNLjRtGhERIfXq1dPIIm2EsFGucZMmbMpVPOVa+3FWDtnp0N8v993hl35dvOKPChKOn7rTp2n3XueX7q2ClBQdSM2TjGb5uvdc5lVixR2I5ryUBvWC5KaHQrQMtq67yCcsfq8W7ytIr2UIVZuuQXLJcJ+w3krMX5/h+fXiR+NOwQW62BjWx6s20KGMUbf/LQIWgQqOAINzBXex1NwLDw8XBrP4+Hhp2KCheL1eJRMQo01mOu6DDz+Qjz/+WAcqiBKDtVs5pAgiNHnyZIFAMaC1bt1agoK8wgDXtWtXHeSw7fUGKYlYtuw36dChg0Aq4uPrSqdOnQTitCMxUc1SvmXLlhITE2MIQ4QhIX4JCQkRx3F0fdGf//y8/Oc/r8jKlStMdCNZ2rdvrySolyFHEAJIkxoq5iMsLEyCg/0SGhoqwQdtouY4jqkrXOuCEIgZ9JmGaty4kbRo0UIgg9jfuzdZEg/6SblcE3mBDLVp00aaN2+uAkFs1aqVEtaGDRtK5zPOUAzwk0jfVhNho2yzZvn69evVM/bjlMjWrVNHatSoYdq2Unbs2KHEtGPHTkocVq1aaUjEJHnvvfdlzZo1snXrFkM4MhRn8GrcuLG2ISoqSske/erz+6nqMKGP6aucnGwZN+57JdQDBw6UCHMuuMpBQUESEhoiPl+Q2uWYKFqzZk2F+poZEgd5XGPIaOA5IebP5/Mf7N94AZvateOEfqVOJDMzw/h+wGge/T9+hph+CjZENNj0G+cbU4eBpcLCwqWJIU3169dTohxpiBhE19Xhoqld23a6eJ6I7E8//ST0ZUREuKtSbltPudV8ghV7gjxKlCBGmOC4miFIDQx5ctNIR7ZPzpCbb06XWx/JlB93OjLinKAC0gRJowziEikxf246aewH2qSewGPyKY+gb4pLUR3SrFgELAIVEwF+nCumZ2XjFQOaaxlC5E4FdejQXiNLrO258847haiPz0R/XN2wsDC54YYb5OLmhb6eAAAQAElEQVSLL5bo6GgTmfrBRF5+1ogWOi6O7pY0JNAGx0iOmW5keyTxejzSu3dvIVIzePBgqVatmuC3ayvYDMYM6hCCI9kocbohXuhi33EcdoU2ZGVl637RD/9BQoNOXFycxNasqb55PF4pSgzcskGGjLr77hY7kFMIDZGyZoaMxcbW1OhNo0aNZOjQodp+In4PP/ywkizKegw2jpPvJ8fHEq8h020N+SBa17t3LyV17777riTv3XusooZEBykWjuNoGyFrcpQ/fCObOtmWpQSZdvl8QYWqoP6mTZsYch0mRGQhYf3791fiXkixHA4qHdEqCUYsjI+o7ZWrbg+WV5/zy1MvhMpzjwVLt2ZVsrklgcTqWASOgcDpmX06RbSK62FIS7yJcBG9IXrRpUsXJVJMOTFwuWVY98Sam6ZmyouICNNF27ZtO2K0ArstWjTXuwhZjJyRkSHLly/XCEzt2rVds4W22dk5Qn94vF6NjnTv3l3OOOMMqVOnrg6erDXCDhE4yAcLwBnU9xrSQDoLrFmnE2g0x0Si8nJzA5MK9snDT6JRRGvcRfOs26pWLVIC/QwypLNjx466pos1Wei+9957Ms1MJ7YyUa2VK1fqGqcsM5XJQnD8gYgVVFZkB1LWpk1bSUpKls8//0IGDjxLsaljIl3Z2dka5YOI0XZsBfZFoCmm33LNFF5gWuA+66PGjv1GFi1aJNhjinbduvUa9QnUc/fBn33OhRUrVsquXbtkb3KyRu2IJvkMDuQfr0DU95gpY6Ys9+5LOWL92KVfiuuzTBMdY6E96+xWrV6tEUf6jjKuhJlIXbt2bYW7Som0NjURMDevPLdVknkQ5UKILjU2U3xMJxJ1Iq08wbZ1WwQsAhULgSMNYBXLy+P3xustfLVf1ILHm//Tz8DJuisIx8033yxXX32NvPjiiwJpCSzTsGEjqWmiN7fddpuukWGtUhszjca0VaAe+0EmguMxkZdzzjlHp8eIptx4400ya9aPMnjw2VKrVi3UNFqiO+Yj1ExdRUdH6XTZlClTJMsQFpOs/+vE1ZZ+/frK119/Ldddd7088cQT0rNnT2HqCPLDGqtrrrlG/vnPl5S4UMjj9eo0Hou7P/v8c11LRLorTGtxx96nn34qPXr0MLYi5MEHH5KrrrpaJkyYoNG96tWru+oaFTl3+HCJjY2Va6+7Tu688y4zrbdWGpnoE3fFde3aRe6551655trrDHH6XM466ywzzdlAIIIFRorsxJoIVvv27STTEIhOhsShS3uYevvrX/+qvtx33/8JxK1IUT2kzxqbacS//+Pvwk0Emhjw4TXnQIiZOoUgTZs2XX73u1vlD3/4g3Tq1FGYxgxQVWIXanTBljVdRNRycrKF/r7xppv0pomzzz5b8DGwHPv0NdujSW8ToYRwc35Bkt31U5Tx+YLYaAQt1uA7e/Ycee/9901fJmm6+8EaL0jpTeY8ffrpZ6RPnz7SoH59N1u3juMoOYdk0Qc+v1/Ty/sj/9tW3l5UwvqtyxYBi0DlR8C9gq/8LTnUAp+JOtx9911KIBzH0YyYmGh55Pe/F6JXjuNIw4aNhEXVjQ1RIIry2KOPCgPgPffcLdypxYJkx8kvi4HIyAh57LFHNQ+dxx9/Qog4MXX22KOPSf2DAx7rl1h03bBhQ4mOjlZ91+4TTzyua2YYrC+55BIZNmxYAdlievDyyy+Xxx9/TNq37yAer5dqVXx+vyFa/QQSQN3PPfecTmEyddjTkCSOWXz9zDNPC88Mo03Ucd6oUXrHH6SMqTo1dvCDPMqRR/vvvvtueeihBw2BukOef/4vBX4eVNdNlGnPU089pTg98MD9cv/990mzZs2EtUV333WX/L//96whW3ern4PNlCdEaMSIkUK7MADp4RjBP4Q87qQjEoMO666uu+46oZ4777xD8JG1YKznAjMIi0tsaP/TTz9tfL5TwJ3yrlAH/Usd9CV9d++99wiL9emP8IgIV1W3kOh7771XwBESCiZ/eOSRAn3KQdgc59A5UaN6jFx55RW67o96wgxR4xyDgGMU0sjUJ+cc9l999T+G6D1izok/6F2VAwcO0jVh3FwB2cUGW3CE6HFOPPjgg3qTBPaioqINlpcZon+3PGPazYWBz+8XfKVtnIN5eXnCdxoCTDSUchVBLNGqCL1gfbAIWATKBQF30CqXysuoUgYs7mAjOuBWwaDfoWMHYQqHNIgTgzMDruM4wpYBmYGubt26xUYuIBQMXug0aFBfIxA+v1+w60a2GBzVrpnCcRxHqDfQruM4Gh0iEsOA7jgO7mga/jJ1yYJ02qAZBz8gFZShbuy7+T6/X0kG6UxrMsjTFoqxxR7lXH3SEfJoi5uH/xxDZKjfcfL9QjdQwI/2YBfy4zj5ej6/X++WxA/XpuM4JqpVXzjGBj6AG+I4+eVoMz47Tv4xemBGGr64bSUNO+g7ziFd+gp/8EVEKK5CHZTlgHrBGmKM37SV9EBxHEcjgPhPHzqOIxBL9F37jnOoXsr6/H5dCO/65PPnnwsxMTFkazSTGwzAzHEcwVfsc27iGzjTr7QVGxRC182nzewHti0qKkqJV+A5RxlscH7yHDQilZBCCBg2K4J4KoIT1geLgEXAIlAeCHD1Wx712jotAhaBkiMA6WJ6tn69wlOFgRa4MxSiRdqQIUOEqVD2K4JYolUResH6YBGwCJx6BEyNVTGiZZpl/1sEqhQCkZGRMnLECGnbrq1GP4trnM/vl3PMlC3ryohoOU7hCFxxZU5VmiVapwppW49FwCJQ4RCwEa0K1yXWIYvAYQg4jiM+v7/YKe1AZZ/fr9PVjlNxSBb+WaIFClZKgoDVsQhUOQRsRKvKdaltkEWgwiFgiVaF6xLrkEXAInCqELARrVOFtK3HIlAWCFQOmxWAaIVWDqSslxaBKo1AVJVu3ZEaZyNaR0LGplsELAKlhUD5ES0nzLShhZE4I/a/RcAiUL4IdBcnr075ulAOtVfliBZP4U5ISBS2LrSlvd23b5/whPicnJwSm87KzNQyPICyxIXKUJEnzNMG/CqNasAb3EujfTwXClt7k5NLwzV9EOymTZt1WyoGT8AI5wrY8AT8EyheKYuUH9ESx/zrZEDrbsRGtQwI9r9FoJwQqG6+iwNE9OJHTqu/qhTRYlBmEGVgzt/fJF9++YVsPfhy49LuWOrg1S7/+9//pOjLho9WV+KOHcIT2XkX3dH0TlXeunXr1J+du3aVSpWbN2+Wr7/+SmgfGB2PUfSTkpL05dIQPy4EPvvsU5k9Z87xmDmiLu84fPnlfwt9cESlMs7YuXOX8PR/cDqRqiBqEGPeXgBeJ2LjVJcpR6Il5se9mRHzAy9txf5ZBCoeAqeDR5Cs68STN8w01jFyev1nIKsqLWYA+vbbsTJr1kxtEq882bJl62Gvn9HMUvrgPYMQiuPBkXf3bdmyRf2qCANlPk5bJDu75FG5o8GXvj9dyS1Rm6PpFZcHjrze6Pvvv5fUtDQBH7Das2dPcerHnQYh5pU+9MFxFy6lAl6vR3hcA28wOBGTPC9r8uTJ8uOPP+pT4E/ExqkuU65Ei8Z65CLxyL/N7uVGGhux0S0Dgv1vEShjBKob+13Nhc7/MyTrHhEnXE7HP4+n3H8CSwV2pqu+/fZbGT9+gnzxxZf6vj4G7f3702Tq1Kn6Kpd//etfQrSLChlo586dK3//+99V2IeokYdgb9KkSfpSaNKJlKELKWGqjbyFCxdqJAvdsWPHCu+fe+utt7QOCAJ648ePlyeeeFLrmDdvnhClwX6gpKSk6vsB3fLURXlXB/sMqh9++KG89tprWg8REfwiqvHll1/K+vXrVX3J4iWCXnZ2tvA+PfxBsP3VV1/JL7/8or5wTBvAgYKQogkT8n195ZVXCqJR1IFNsKMMTx2nDGSFevCHl0vzomnsuELb8fHPf/6zvPjii4oJ7QQnsKZ9+I5vECnKUdeypctMFPJLGTv2W42yYYf0tWvXCX795S9/Ecq7OFL2jTfeUEzAgZcuY8sV6iH6g4/4T3+4L94mD6zxgbzPP/9cXyBNWfaRonW6ZWg3ZT755BN9Lybp06ZNE+px7dFW+g3snjDnAPv0C2QPgs4W/9GnL3jdELo8dJQ2gyk2qMdtNxj+MGWK8A7LMWPGyLhx4wxBzhb6w/UJv10csAX+1IEtbNK+Uy2l+itzos6zNsSb97whXB+ZH/4XjLxqRSwGjsWgDL8HhmCZCxyNZJ2mJIvfK8gI28ouXo9H37sXG1tTX/vC62ggkYmJOyQ5ea+0bNlSVqxYIUxDMUhDQr7++huJjY0VXpny3/++Jdu3by+AwevxCFNqixcvlgPp6fLzz3PNwP+5rFq1SoiuQFgYLKkDksPA1rp1K1m5cqWZFvpBo1UMggxuXbp01noYABcYclZQidnJzsqSMWO+lIULf5G2bduYSNA2+f77ccLaL5Ot/3MMacKPCRMmaCSEV7e8+OI/zQC/y7QtWebPXyA7zHQkypu3bDa+/ix5ublKvvCB9Pj4uvLJJ5/Km2++qa/EwQbE67fffiPbtClJmLLD14SEBEMY3jdpe2T58uXypRnQeW0N/mFvxowZpu6dSmaZluVVL96gILXjfkCiIAXgvmPHTnnhhX/IgQPpujZt9uzZAoHC9pw5cws9wbym6b9GjRpJXFyctG7dWoj6QE7WrFkttWrVUvP0G1N/2ICYQERbG+zBYebMmYXIbEpKiiFtY2XZsmXGXitJTEyUzMxMtUM/MsVJuyk/x0xPTjKRIjJnzZolEydO0tfocOzWSb+89NI/hb6nDHbpY+oBy88//0LfX1irVqyS5zEGO/ABf94huW3bdu3bRYsWa58lJyfLV199bfpwvvGvtezevUcgs6TjC+S8U6eOeo5+9tlnsnnzJgEfXikUH19PX7+E/++++676RB9R5uuvvzZ4H9BzGlKGDpgW7SfadiqkAhAtM13BD70TpotxPRrhIsplxWJhz4GyOQcuNhc1FxsS10xO10iWHPyDKBzcrdQbn98vLVu0kNq144QXOvOyYxrEO++GDx8m5513npx11lmyaNEi2WcG34WG8ERHR8nAgQM13ecL0sGOyATlgnw+fffdrl27ZMfOncLg1bVrZ4EkQCKIOOjA5fUqcRl95ZUyYsQIfQ8d0RcICIP1+eefL8OHD5cLLrhQ/SKqQfSIOhB8YSA899zh0qtXb+ndu5eSG0gA+a54TT1du3YVXgZ96aWXavKGDflRrJycbD3mA+JMpIR9pGnTpqbuC+Syyy4z2NSSLl26yKhRo+Tcc8+VqKhojYTQ5tq1a6kevl511VVmQN8sa9as0faGhYVK//791b9OnTqZCOE0JSsM9BdfdLFiGBISQnUFQt7QoUO0rttvv02mTZuh5Ix3/NG2bdu2CeSxTZvWEh0dreVoY+3ataWRIVq8F7D1QaLF+wD79OkjLpZEKfcYQgLZJSI1ZMgQDItvRwAAEABJREFU41svQ7SbKhFmHZYaNB8QDAjdsGHDhPJXmn6KiIg0OaJEGvI9+OzB0qdPX+nQoYOZdp4l4EGdPXp0lwsvuED7LzMzQyA/+Lxhwwb53S23FOC1ZMkSbVtOTo4hS620nvPOO9/401xtUvfo0aMlNTXF4LpJp/vQlYN/kNjLL79czjXnSb9+fQViCqHr2LGjXH/99cL7EXv27KnamzZt0vMIfBo3bmTqaCZMtUL0aRvnOX27YMEC4dylUP369eWmG2/Uc7NoP5F/KqQCEC23mQcJl/n5FysiFgMRi4FImWAg9u8gAgzMB3er5MbrDdInZTOI8+43oiNMfa1fv8FMMY6Ra665Rm40gxCDMXkuCI7j6AuD9+9P1yk4pptuuukmjYwQwcIW0TD0Gbx8fr94PR6hHgZRBmWiHEQzSAsJ9utLhbFXiGjt22cG363y6KOPypVXXiHPPPOMibrskOIIsN/UAQFky+BMO6j/SIINr2l/UJBP/IY4hoWFa7QlyESffOaYcvjKlrTg4BDBVyJ81apFaoQLovLFF2Pk5ptvVv+++OILjUBBRvDDb9pFGWwESlCQV3g/H3m1TSQqPDxUmHZt3LixaZvXRPAW6oL3zp07a50S8EeZgEPNp734SJ3k5eTmaPmf5q2RW2+9VSCH3JQAvuS74mINKaY87fb7fZoNOZk/f6Hc+3/3atveeecdcUkqPlCnz+/XdlAgNydXyWf16jUkKjpa/aJ/KZOWmoaKSQsS6gk2uEBQg4OD9dhnMEdh//79bAoJ/oSGhonH6z1Ul4lIpuxLkb/97W9y9933yLPP/j9DIleL219i/vDRcRzFAdJMv5EGscrKylZiaNTy6zftII/j8pAKRLTKo/m2TouARaAQAqfZAYPxadZk8Xi8Zhoq1gzOV8rYb76RCePHy5gvv9RoUSAWDFgMlj/88INO0TRr1lynspiiYuomOioqUL3QPoM0BIwpJjIyzRQhkZxgMwAH+4NJUgk2A3FMTJS8+MKL6gfTRq+99qrEx8dr/rE+PIbcoQNJhPwci3yhW5xQPiPjgEZziKZAUMLCwpRUXXHFZWba8RMzlTZRvvj8c7n33nsLCEFxtkjLzs7RqBdE3o0wQU6Z/qtTJ05++GGKkpImTZqgfkISZfAf0Lu1fPjhR4odffnggw9I9eqsv8w3CbFij36ApGRkZBi/skgS2keU8r///W9++bFj5c9/fl4cxwQ9VOPwDyJJEOi01FQlPfQpdUA4D9c+8RT8/ODDD6R79+7y3rvvGL+ekxYtmhcySHtIAFOifEzVcg4QyfL5gpRUk18RxBKtitAL1geLgEWgXBBgICyXisugUseQjsjICJ0SYhHwkaoIDQmWVq1a6bQZ62B+/Okn+doQrt17kgoNshCluLg4XdvFtJLfREJamOlJIloQLY/Xe6QqzGBfQzp16iRTpkwV1jRNmTLFREPW6lRSqJmKcwsShejRo6fWP3PWLKM/RRd7p6cfcFWOuHUcR4kQZI2p0OnTp5tI0S8mKnNoKvGIhYtkELlifRPCOiwiJJCg9u3b6zof/GcR+veGlK5YsVxJRhEThQ4Z7H/++WfBp48//linVyGPYMr0IevAIFy0v1BBc4BOcnKSTokRLTJJxf6nT8gYO/Yb4fEPEyZOFNZJcVce6Ui0iTw1atRI/cCXqVOnGqKVQZZApGnn999/Lz/Nni0sSF+yZLHmHemjXbt2uk6O8wV7CPZr1KhxpCInlA6BZoqTKWjOT+rZunWbTjuSB2ndvHmzrglkHRznwMSJE/Rc445E+q5mzdgTqrssClmidXKo2tIWAYtAJUaAH+1K7H4h172G+Jx11lkaqYBoVatWTdq1ayvVquVHniBNrHMKDgmRbt26Sb9+/ZRssZ6F6R6iV4EGscfUFmteIGbosFamb98+0qhRYxMZ8wg2WfeErsfr1XVdrVu3MnVGCuUaNmwgLLJmEX3Pnj2kZ48eZqCupoQrOjpaQowvV199ldSoUV3XiLEAn0gLEQnXFxYwM3AiHkOugkw9Xbt2kZo1axpCV13XSBGBWrRokUBeOnXqKJBOfKP9QWYaz+P1KhYQROwyBUcex0SAiJwQIcFXFotfcMH5xlYd6da1q4Apd8eRByFDv4YhFvntrIa5QhJZLVK6detqIlZeYR0V06533nmnwaSaplEn0Zm2bdtq+wMLg2PLlq102nbDhg0CaUKvYcOGqhYREVGAHeu5brnlFp2SxDfWzhFJ9Hi9qssHGJ9zzjlCufnz55MkvXv3MdGeCKlnooa0k3ZDIlkoT5QMJerET/axCamjXXXq1DFTzTfIjh07tL/IGzp0qPYDBBJMKQO+kHJs0Gf0x1lnDZTatWorDmAHjpybnJOQf76LEE9sREfHCL5BqFgXCIbdu5+pN1VwHvYw5xF53G1IlI11d0TtaAfnBcecz+y75yd+lZd4yqtiW69FwCJgEShvBKpURMtxpEvnzrpmp1evXkp6WIhcJ662wtymTRth0bHP5zPEpoYuch49+iq54oorzKB2gQ6Aqhjw0dJEsFhkzKAOCcAGC8tjY2tq9IsBmQXIDKwMlESAhg4ZolNrDMoXX3yxUJ56GPCjoqMNQaohkDAGesdxBALFGiP08O9MQwIhYK4b+NvDRL2QIOM7wtoyyqHXs2dPXTR9+eVX6Joz/MPX1q1bC+13fWO/U6dOahbi4R5DYsCA8viAbQgmNsINsRk0cGCBXWxzRydrrWhnrCF7ajDgg3ZdesklMvrKKxVb1rZRL/YgNUSzmO7CBpgFFNXd+Pi6itnIkSMlJDRU2FKeTOoDb+rAXg9DOK6++mrVv/yyy4Tojtd7iGihQxrtA+NLLrnUnB+/0z7w+f26QJx02s1NBmBGPUXrdPsLexAj6qQceECwSOecA1PaRL9A5PGb/iKfdW7NzfRf7Vq1BOwaNGggnJuXX365RERG6vlEn2KjZs0awrlFPQhYXnvttdLeRNSw1UkXyt+gNwHQv93NFCNtQC435wF20GN7iekLdGhXeYklWuWFvK3XImARKHcEGBTK3YlSdMDn9wtX+EQGmE5h6/P7tQYiALGxsRpVIYHBkMccoE8eaUXF5/crKWPQIg+bRHPcY6JPHDuOowMlEQ7IFPmO42h0jagG9VAWG0QkKOPz5/vlOI6SPPTwz+f3o1Yg2GJKFHGc/HrQw3+UsMsxdRCRwbbj5NdN+ynvOI4+IgD/KEMaeRxTnn3suz6Qjx7i8/s1kkJeNRMlJI0ytNPnL+wreT6/X8hDwBbfHMfRR17w3CnWREFoyHMchyKFhLppA+XYxzf8RMnnz+8Pnz+/XvLRxTfq4xi9QCENG9RHG7FLH6Dj5lEeHY5JZ/9YdWIPPNwy7FPOcRw9x6KiokzkLFzPC8dxhP7hPPP5/YKvYOjz52Pr2ggxEU5s4J/jOHru4Rv6pEN8xfz5/H7BHm13HEcXvLOPLm0MtEd7HccxpcrvvyVa5Ye9rdkiYBEoZwSIaJWzC7b60wQBoioDBw6Sxx57TAYNGqRRv9Ok6ad9My3ROu1PAQuAReD0RaCqRbRO356s+C0nykIUhqlHIoEV32PrYWkhYIlWaSF52tixDbUIVB0EbESr6vSlbYlFoKIiUGGIFs+/4M4RHqK2M2G3WLEY2HOg7M4BnhWUnX38t8FX1B+yE/XLRrROFDlbziJQgRCo4K5UCKLFg8ZWLPxNJn0xVb59b7x8/fbXViwG9hwow3Pg+w8nytwf5kni1h36kMYK/jtVZu7ZiFaZQWsNWwQsAgcRKHeixbMvpn49Q8a8O1ZmfDddfpm5QJb8/KsVi4E9B8rwHPj5h9ny7Qffydj3vpUNKzeetmSrKka0mB3gRcNsD/7OF91U6WPazewIj1Ko0g21jas0CJQr0WLqYu7EuTJ74k+SsDlRMg9kSm5eXqUBzzpqEaisCGRl50paSposX7hMvnrrG+G1GpW1LSfjd1WLaEEyeC3Ku+++K7yAl6eyb9q0+WQgqnRl6VOe5D59+vRjPsH9RBu3NzlZfvzxR4Px5hO6SIEE4h9Pci/qA8GH8ePHCw8gLZoXeIwPPC6C1+EEptv9iodAuREtfhDWLV8vS2Yv0R/8igeN9cgicBCBKryBcG1cs0HmTJhzQgNGZYemqkW0iOT885//FB4wyhPOp0+fIZs3bzqubuLp5xC0bdu2aTkG/K+++kqIkmlCBfyAuPB0dJe4dOzYUb755ht9RQtjTWm7vCcpSaZMmXrc2Lp+8MT3qVOn6Wt23DR3m2xIHESL9cpuGlvwnzdvnvCUfdqLDx988KGkpKaRXSUFMsvT9St748qNaHHVsWHFetm9K7myY2j9twhUagSIInPBczpGtfgdqtSdF+A8hIKBiffD8XRtSGRWVqbwgl5XGKDdIuxnZebns6U8aZTn5c6805BZB14F89Zbb0ty8l4l4+iRXtQm6dhBAvNcXdKx79bvbkkjD6EcW2yRz5ZjSAZbdElny7ErlBs/foK+7od9nko/YMAA+eKLL2V/2uFEpCR2sYN9dKmTLceanpUlYEvbyAsU1zfXZ8qRzxZ9ykOCEXTdPNc26fv3p0vguUlZvp+8q5BX6WCDcpmZGZKdnaV9nGX60rVHHvvoIeyTFiikUQZBhy31oIOfCPukkYc++66uuyWd/KO1F130sMcWfVewSV2Ud/VII/+778YJkT/2A8uiRxp6gemkYYu0iiRlQbRK1D4YfWpShqSn7i+RvlWyCFgEyg4BLngy9meVXQUV1DJkpIK6dtxuMVARJYFk8dRtDOzfv1/GjRsn9913nwqDFgNRmiEfkyZNkkf+8Ae566675YUXXzTRmS2yfft2eeedd4TIyWeffWaIyhfywQcfSGLiDnnhhX+ozubNW+T1119Xe9gdO3asUM+uXbvkpX/9S55+5hl5+OGH5fbbb5fPP/9ceBI6dTz40EMya9YsQwwK3+0KObz3//5P/vz8X7QMvuAHg+iyZcs0/Y477pA/Pfqo+sVgiu+33nabPP7Ek/LyK69oPXPmzNa20l6eWcXrgPbuTZaNmzYBRYEUZxfy4trFT3zA/7/9/e+yYcMGnYJcuXKl1kdbaFNCQmKBTXeHPqCN+IrPz/6/54T3N5IPPuBG+ef/8hcTmVpJspLXQNtvv/2O7NmzW/PcD+4SBucpU6bI2LHfChFH+hFS9uGHH2of0pdLlixRX5lWpN/oH/pizJgxQpprDwx4NyRtpc/wCSxdX/Hziy++UFsbTPvBAR/pl1tuuUVefe01rZPy9DH5v/vd77SP0MM+hP3tt98uOE/Gm+lQzpOZM2fqeUfZ9//3P+G9nP/+97/l7rvvUd2vv/5awOqjjz+WhQsXCOXYZ4qUcwU/8ZfzhbroN/qccwgMvv32WyWeblsrwrbciFZebp5k5WYIV9MVAQjrg0XgdEYgy1yhc/FzumEQGDWo7G1nqikxMUF4H6HbFpdM3ikAABAASURBVKYSea8e79vjfXBvvPGmIUubZcWKFTqA8X662267VQfUV199VaKiovW9h7xEeOjQocL7CXnPXUxMlPCuufDwMJk8eZLs2LFT3//He+QYxJm2y8nJVaLm8/mF99PxHr7XzIDMa1fuNESJB3X+8MMPwtSk6x9bIjWJiYnSo0d3ueGGG2Tjxo0ybdo0napcuHCh8O4/XspMlGrSpMmSvHev8JJhIm49e/YQ3v13zjlDhOnC/v37C4JdXgkTEREpmwzRysvLI0mFiAqEpGHDBoJd8IHA7EtJUbtgw3v28AW/Fi9eLBAdSENQkFdoC3VlZBxQe4EftGXt2rXSs2dPufXWWyU9fb9MmDBB8YVgQBxHj75SBphoGzgFkiVw+t3vbpFWrVoGmtT9iIgIOeuss+TMM8+UgQPPki5duggXCWlp6VKzZk2hXIRp6+zZs7UN3xlyPXfuXLnuuutk8ODBhrD8IksNaaXtatB8QAq3bNkivLbmxhtvMGQ5TdedmSzZazCmzezjI+dWdla2Ick5ev5ERUXJzTffJNHRMfLVV18L58uDDz6oBIdoKDhMnDhR+5pz4aKLLpLXXntdSSckn+lo2kKbIEv4Ba48MR+/6TPOu3bt2knv3n2EfQjzeBO1bNeurfZBdHSU/OMfLwj9Rn179iRJnz59FCNe4YPvFUXKjWhVFACsHxYBi8DpiwCDVVVpPQMjg2L16jUKmsT73xjQzjjjDOFFwQxyDGyQlLCwcDn77LOFvAsuuMBMu80W8nk3HHm8Ww5hIPf7g3XdV0ZGhqxZs9YM9J2Flwv37dtXX/4LMcrNzREG+/bt20mnTp2EPByh3rZmcIS8ZGfnCH6S7grRJwb7XoacQM4ghJAddDt17KTvy1u+fLkkm6nL3bt3GfKST3CaNWuu/jdu3FhqVI/RuiEA0YYEYJvBNiws1ESH9ijRIQ1xHEfatW2nr8DBLqQCwpFliAT5EMIBhgh17txZ3xuJvxCu5ctXCC9e7tCxg+Bjw4YNUS8k4eHhSnSJ3BCpAS+II0rgDiGBDPQ1hAC/8RHSyNqy80aN0pc8g1v1gD6kLBhFR0cL7aNPIJGcuxDgc845RzoZvFu3bmWwSTckaZ9MmzbdTG1mG4K1UCNGiYaAE40qejHFWr6BAwdK5zPOENoNAaK+owl9PGDAWeprhw7tpXnzZnoOQYpo3+bNm3UhP+1lnR9EFSwyzTTnmjVr9D2I9B0vnW7UqJFQDiyXLlsqRMGSkpJNG/ZK9erV9V2Z0dFR2m7IV05OtiGag4Q+4AXZa9asVnLv9/sVd9rCOxjB62htONV55Ua0cvJy5UB6xqlur63PImARKAECp4tKVYpo0ZbMzCwzkBX+WWdApj+ZTvT7fRopyszMFAYnn89HliEpEYZkpQvpmnCED+pgsINQMJghDP6QEfI4RijOljqCgvLrII2y6LF/mBgCRFqEid5Asg4cSJdJJnoGUQkJCTHEyE92gfh8QeI4TsFx0R2PycOH7OxsycvNLcjmeMrUKRo5wy6RpIJMs+MzmDiOoxEjMX/oI2ZXqlWLYqN5Ho9X9wM/du3ardN6ycnJgm0wJ5+ptPT0dKEuj6dw/4BHpum3yGqRBe3xmbZRriQSiC/6Wbou74DExERrfRAWyBiExuMt7LPPtJUyHm/hdNKOJh5PPu6U9/n8Bo9D5bNMdByCmZOTY4hSuPpAu6+55hoTrWtVYBYc0CHSt3DhL3o+cl75jtB2InAUDg0JZiPuFlxJCDLRRq+nMLakVwQpF6+yzJd8+dxVsnX96XXbcUXocOuDRcAicAgBfuwPHVXuPQYziBTRFLclDHh79uwRfnM3bNhgiFSWmYqLF6JWqakpZgpwh5kOypalS5dK/frxQvSAgT/HRA4gB64dtqRTB1EybFEPD5smKkS06mSw3L8/3Uxd7VcSSNSjVq1YE4XKlfnzFwhREtadNWnSBDeOKe5ylGwz0GeasSYsLEw83kNE4IAhPL/++muB3YYmMuU7SDiOZByCBQlYvHiR8StHUvYxzZhSSB28kpOShChOHzPdxTQYWKHkOI7ExcUZcrdJmOZKTUsz7U0jS8JCQ01/1NQ+oJ8gaUS5NLOYjxzTLuoqJkuTIHfx8fUMMQ2Wiy68UC6++GIzldlLI5Il7SOvwYvoJgQTEg2ZyTERS62gBB8RZhozKipaGjduJETqLrvsMo26EUGTgD9I2UIzPdzQTOOi1759eynaF7TXcRyDEedEjmzdtk3P2RUr89e41a4dF2CxYu6ecqIFaL8tXCFTvpkkO7bsqJioHLdXtoBFwCJQGRGAPFRGv4vzmchFhIkGMQ3m5jNgs4bq8SeelKeffkY6deoobVq3FogRJOAvf/mL/PGPf5R3331Prr/+ep2mCzNTivxOs8iZRwlgE3svvPCirv9hKnLBggXy5JNPyqOP/kkYLCFCHo8XteMWyjMF9Le//U0ef/xx+eWXRdK7d28lfUxL4dujjz4qrAVifVeOIYFFK/F4vVKjRnVhDdj333+v2ZBMiCBruzwBkY4QQ2zq12+gbcbul19+qWuJuHtPCxbzUcNMTV500YWmzLumzY/Ja6+/povkA1Udx5HomBgJCgqSf770T23LrFk/KmboMVWWkLBdHnvsMXn22WeFdWIQGfxhevXDDz8SFtH/5z+vSmJiIkUKid9MjyGsfSIKRNlCCgcPIFqXXHKxmTJcI3/805/kmWeelTfffEOn5Q6qHHPTtm1bmTv3Z/WVtVXcAHHMQgEK9AVr7ubNm683Rzz55FN6AwX9EaCmUSzq4u5C2s46Qc7fHEMm+W7Gx8frYzQ4F5s2bSYNDSl+8cV/Gr8el1deeUWuuuoqQ8BqBpqskPueU+3V2t/WydfvfiOb1m+1C+FPNfi2PouARaAQAoEDcKGMSnhQrVo1JVDckUbEg6jVDTfcIPfee6+JaPSQG264Xh555BEJN2SMdSy333abXHLJJdKtWzdDmp6Q4cOHm2lHr9StW0dYPM/6LUgWkaQnn3xCOnc+w0ydVdO1V9zNxoJvFsw/99xzuqC6WrVIY2OYrrkBVxaZ33XXXRIS7BeOW7RooQvtSQ+ElwgGa3YgayzOf/zxx4R1YyFmuvDhhx5Sv1ng/tBDDwp3vNFO8omSQGqw5TVEi7ZcccUVUr9+fY06QVYyMzOEAdpxHNRUICL333+/2j3rrLPksUcfkxtvvFEiIyO1XuxAaLA9dMhQwSfIEOvYIKXgwDQYd/M1b95cbbof9evXkwceeFDOP/98GTVqlDzz9NNy0UUXaftbG4L7wAMPyIABAzTK9LTJA0N8P9dg/8AD9wtrv1jYTj9BEF27bImoYQv/yKsVGyvgC+7gy5q5wWcP1nZ06tRJXjJkD3LXs2cPbR/1O04+Do7jKC7Yot3YBwvKs3/O4MHmvLlHzw0Wvf/hD49IgwYNBMJ5++23mWnJGG0T05HDhw8z50UkxRSrK6+8UqdNWS/18MMP6QL1rl27KPGMj68rbdq01fOEKWfaDsHHPuchNxCwqJ5zDoNXXjla+4k1fLGxNeWG66+Xa6+9Rs/F+++73+xfq2SN84FzkX6jXEWTU0a0YN/rV2yQD/71sexK2F3RcLD+WAQsAqchAlw1V5VmM2iNGDFSWEjO4mMGUO5OYxAiYsLdZ0z9ue2Nio4uGPQhQY6TPwhDMFq1aiVDhw41pKuuki9sMAUVYyI21MPCacgEOhAfbIaZKTrqa9y4sa41YiDlbjGf36/HDJY9evQQ0tEPFBatM9BeeOGFQt34QD6kEL/xHx+IdNWoUcOQhKYCiXD10I01xAN/8IHpwVmzZunAX7NmDbILSWRkhN6Nh38srMYWftEu6sAu7SQPf9hH8AEcIET4C2H9/+z9B3xbyXU2Dj8XIMACsPfei0RJpCSqUL2teltpm7fZ63WJHSd2nMT53u9N3vjL+0/yT3Ps2E5x2953taveJapQlRJJiZTYxN57Bzu/eQa8EEhRElVX0l78MLfMnDlz5pkLzINzBvcqihU3NqAoCgIC/OUfD0g0WJ97RVEkjsSGuBEHtqMSNYPRCNrN/nNPYkmsMebF9thHEhyOH+0n7oqiSEzYnpMgqIpiDbVRH7GjJ4j226ujnbSB8iyjTtanjMFolKSPfWU/aS9xNwmSzvZJ+hRFEaHBSGk3bWA9YkWd1MdEPNlf2sH+MC8sLFTWoQ7WIdbUr7ZFbFmPshwn1ld1sn0eU5a2UoaJ8hwbg9FIlY9c0j0Mi/p6epGbcQXv/OJdtDQ0P4wmtTY0BDQENARuiwA9AbcVeowE6DGgF4u3FFAXDz/q5nMC5kTJCfN+2Epv3uWcHKnqqadWylCePNE2GgJfEgIPnGgxTp5zJg8HPz6gebK+pEHWmtUQeHQQeLQseZI8WkSWZIW/+LkQ+3Ehkbwn1auvvCIXb7MP9yPR+/LCCy+IMJr5fqjTdGgI3BMCD5Ro9ff1Ifd0nlz4XllafU+GqpV1wl3JpJ6P2it63LRslOD1EydvP0TGRsLs4nA98yEd0daAUH+ERQbD4KC7q1Zpf0JSPNx0Cgxmd3j6ekld/pFR96T3rowZqcQ+jYenydEbtHW8spGq2k5D4KEi8LiQkTsBhaGYyZMn31ficift36ksQ1fuHh4yvHindceTVxQFDMkxlDheuZanIfCwEbi72X2CVhZdLrSRLPUvtxOseqOYIFEkFSu/+RLWb5kHT3enUTJ+8dPw4o9exLy5kZJ0jCq0P9G7IWJyAgJ9rPVDI1OweGUSXL8EogW9AWEzZ2Ja6jQ4GscfCnvTxzv2TpqKjc/OgpdeD7+YeKxcPwvB/q4IT0qQehUHh/GqPbA8nUMQVr26GclJYaPbEOPn4OuHZS8sQUTA9fvqjBbSzjQEHi4CT5pH6+Gip7WmIaAhMBEEdBMRuluZ2ppm0JN1zySLBgwPwtHZG6GTwpCYmoSAQA+b90rnYETC8hRMnRGHkGB3St80mVwDsPjpxQiPNNpk/ALNtuOHfeBkMsHH0xHDese7btrs6Snr1hfl49ihLDS2dEHVKwse4mZosA5H39+F3CtjPJhi/Hz0Znh4WG19iCZpTWkI3BSBJ9GjddPOagUaAvcHAU3LHSLwQIkWbbkvJEso0gl38EDnIDo6euDuYUJsYjRcnPWiBHA2R2Dm1Ah0tnXLc27cgkKw+vWX8Wf/+EN876+/hQWpUWA4belrTyFhUijWfuPrMo+ycPfH0tc3SdlvfXuFzdsly0Y2TiLEuOilZ/GDv/u+TZ9BhPsYrpu9eS1e/7sfyrLVa2ZIAmjyiMO657bg+T96TpbRhuSk8BFto3dm/yA886dWW59/bZWt/bFtpiaFSN222sJLZDsWB/RoLV6RLIibSZxdfwcnz8brf/UaWJ/2Jq1Yjq//7+/a7GU/YPcicY2bv0CWEz97m1QxP+FBfOX/+yIiSGyFHTEpM0C5AO8gLH1xPeJtV85rAAAQAElEQVTjBJEV+ZR7/s+/I3Ut3JwIg8FBqmAbwcIutWzj1vlQvZT2Y/dHP3oakxICMJ6NbFPtx9Ovb8Gf/K/nESH0s48cE44VE8eE9SWe3/8mXvjjF0aNyeqR60Rti9cahOdzrA4t5Ikn7qV5tJ64IdU6pCHwyCGge+QsuolBJGwOZj0cB7pQ19CHoFA/G6EIWhQHz6EGVAoPGsRr0OCFeWuWIMK1C3s/3IfckjYkb14FL8duZB49j+Lablw5elJ6XVzcXORN+gbrW3HkcA5coxKxZEbiKEIjJ+7Vi5EUpkP2kZPIuNKOeS8+jcTEUESK0N3UeH8UHDmKcxdLsWTrckyOdBJWAEGzE+DnqSDrUDoquhyx8tmF44Y13b3c0ZKXg927LsAtcSaWPDUHJlcTZo+0eXzXCdmHJa9sRFiQm9QtN8JLJPfqxssVXsGh6pnch02Zgq+9tgBd17JwIb9e2jtPhFfrLp7HieP5SH12PebMioD9K3BKMlaumoai02dwfG86zJEJWLxk0iiy095YCyevCMRF+8NgMiMoPhq6nh50DDjDKyQYvn5ecAsMxNL1c+E52IDTh87BIjyPDno9+HINiMbqLanQVedLO6JTUrBgQQBIcBY9vwmxfv2y7dIOEza8vAIMh7KemnyihU0bF6KnulTq9goPRXC0NVypjklmerYckxkbVyIlMQhGRyPiowLgYeiVY9Js0eHZP/8WQnS1si2LyQ/zF06Bu5sjZm9YgNmp4XK8iVNM6lwZDiVh49jcLBmdjKqJ2v4xQEBndyPLB2buQ1bMmz3y7uS8pc5DbvqOm+M/BPl8ve7u6z+S71iJVkFD4BFHQPeI23eDeUpnL6oL8tDv6IGQMG+5AHzJomkoz7qKpm4HKa/o25B3OgOnThXJ866KEhiGjHB0dERraSuGurtQWnYNLW096G7vRld1Mc4eOINsQcKuFjXBWTie9HpF1uXG2c0VkRFeyE/PxJmTOTi/fR/OnCmHMwbRVl2N80cz0NDSi6rSRrTpghA5yZ/V0NfSJOtcOJ6BzOw86J3c5FoqWWi3qbp6FScOXUBB+kmkHb+EUEHgQqNCEBQTisbSWvT19qG2tAY9pgBMTfa8XlN4jK6f3HjkGh6EDa9vRm/5Zezacxk6kweiEiIw3NmE6qZ+9DZUorJ5AAlTokaRqI76akleSqu70NXWgabadpg9vWG/jqynuQmFF+sQPyscXr7e8HI3o7KmBZbOTpshTq5e8PQalrgSg6O7zsDS0yvL42ZPFfj1yzq0o6ZHj+DY6fCLicDkKCdk7EkH65zam4amIW9J6KSnCQC9YYGhvnCx1Mpxo9y+NOvfuUUxaktK5Zg01TaiubIWFrggPNaXRaBHtPhiLjJPXEDmmSvQ97Xjs49PIvPUJWSdFmPv4w334AhMEmPQU1Qox3W4vR4NbQMIjQhFcFwcUlfOw8rnVt2Qlm5YhKj4yFFYyka1zSOLwJPm0SLJysrKwgcffAA+QqVLfB6ZmP+oDALJVUtLC0iuiD/vcr5z507QzkfFRs0ODYH7icBjR7TY+bbaBlQ19kuC4Dc7BdEe/cg4V8gimbjeyS8uCrOWpiApNQnxMydB72L1pEiBcTa8DcU42TLL2dEIR6cB1PY4on9gCBhsx8mPtksPkau3h2wnecF0zJqXCNMtHBrDziapb7xN39CIfdVDkpA5hRnh6uoE70mJmLFsNmYkh6A6OwcN9Xb3IRvr0cLol4+PD8zog6V92Fbg4OYOz5BATJmfDNrcUVKM/MJ6WzkPSJBiZs2Q7VImMtSN2VDDfvJEtH3lwnkMu8di6gwRxnXtRmPtaD1urg4Y6B9Aa++ArOIq8JMHYmNycoVngAeik2ZIO9BYjdL8Mrj2OIJeho4O601tLXymWJtFkESzqGV9Dw0Lj+GQJ/otfRhv3PyC/Gz9mzI7CR6O1vYx8uoWNo0cChLbg3678wG9K9zMBjg4OsEpNE5iMHlWItDViorSCnQ2N6CyqBzXLhfekMqLKtHa3Kqq1vaPAQK81h4DMydsYnl5Of7whz9g2bJl4F2yz547h1OnT4trvH/COh60ID+zJFZ83iDxnzdvPgoKCnE+I0M+w+5Bt6/p1xB42Ag8lkRrqKsTxXmlciJcvWQKqq5mIa/SYsNO7+opJv9YdGdewudvfoFzJ3IxOOb5WA4OPjb52x1YhEeprVWPIG8DDCPrsqYuWYjJ8YFgyGywswWHPjuIozvOoKlj9INGb6eb5U4GBW6Og9JT4xFmxmBPO3rK+9Be04jy7Gzs/cMn+OytvTi9Px05ud2sYk238Wg1FuZjx2en4TFlGhYsnibrDLS3oSG/AKc+3oFtv9+Go3vOoSinwEogpQQQMSkE4Z7dOPrOJ/jiwyMoqWgfKRm9Y/iwtEXB1JTJGC6vRW1N6yiB9o4BDOvc4O3pInHT+fpCr7deci21beitL8fZ/fukHWk7jiIjswyNg50YGBiEh3+gDN/SW2Z2d0ZnaysYPpYNDHUBuhbQq+nh4wEoeriYnSFffiY5Jm7DnTjzxV45Jq29Vk+nLJ/Ahh7ETkHueioKsP1327Dz7Z04tvsYcq9Uo7muGXnZ+bh07vK4qbaibhSWE2hOE/kSERgaEj+cvsT272fTAwMDOHr0KAICApGQkCCfpbdjxw588cUXoJeLt9vhs+aOHDmC999/H9w3NTWJ78ZB8E7yPGf66KOPkJ6eDnrE7O0bHBxETk6OrLdv3z5Q7sqVK+LzKj7nw8NoaGjAwYMHpW4+BqitrQ30XrEO5ZmYf+rUKdCu7dt3IDc3F3ysS3JyEs4JUkhPl32b2rGGwKOBwL1ZYZ317k3Hl1K7PK8AjYNOiAj1wJnPLo2yQensASdKn5kxWLRuMeavmgVHETY0j3i1ugb1mDInSS6yHlXxJif0qpRcq0TwtCSsEiGj5c9vkLeR4C+znq4umP2DMFd4nZZunAtvV9ebaLl5tkdsDBZtWIxlmxZjwaxAlGfloqK4ErLNSZMwf91SrFy7HMvWzrKtS5PahFdJ7m+y6WjvRdHZMzh+NA+xS+ciIcRZElRdWDjmrJwrsVn/3GJEBPuM0tDa0I5Bsw9mrlyKNZsXIG6S16hy9aSvrRV1ZQ1wcXVBU1UNOrv61CK5JxGrKmvC1OXLJG4zFofAaDDIstqSi6izmDBnudWOZc+sREKkO9pqqpBzqV7WWbZlBZZvng9Dczkqy5tkPbkR/a69VoLOAYOsv2LLMjB8LMvqu8Ax0fn7YcrieeCY+JgU3MmLXqm87GtyvR7DgQwVLhbXUXiE/52o0WQfAwR0usf2K/AGdBl6u3TpEubPnwcHvV56hilkEJ85RVHQ19eHN998A7xrfKv44ZKefgrbt28Hj+ld+vnPf4G8vDzU1NTg888/x4kTJ0DyRh1MQ4JokQy99957KC4uluk3v/kNysrKYLFYsG3bNpw5c1bq2717N04LTxrbvHjxIv7zP/8LmZmZMlxIXQaDkTuZHIR9kZGR6BRhTj6fUGZqGw2BJwgB3YPsi6OTEUaR7ksbwmsx0FCPy5k5KLhWB64RytidhvSPdyKrsgGDvb0oOJeNvMJm8WFuRtq2Q7ic1SCbLsrIwYkdp9DU0g1LZylYr6iiU5bV15bg9KFL6OgeEB6UHhRlX0FBTov4lXc93Nbf2YbMQ+nIOn0ZPSIMNtBah7RPd6GoqB6XTmSAi6WZ33TlAtI+34OKSlHX0oScExdQUW/1BnUWVOPMrgtoFl9WsmFuBvtRnX9N2lZX288cZOw/iv0Hr6Kro0vqPnc8S7bZO9iBrJOZqKrrkHLqprG+CRlHLkq9bCPn5Dm0cR2b0Hvx/DX0iS9A2n78QL6sUnUpE0e2Z6Kp3fpLvuDsBVwurJVl6qYk+zJ2fpIh2+1o7UD6rjMyvGgfYqPs0EAf8s+cQtrO47h8pVx6coaEJ+nyoRMouVonx+jU3jRcOn9V6qrMycWxXadE28NoqKjEvvcPorTYik9FZrb0GEGEZdO+OIBTZ0rYBMquFGPfJ0du6Dfrn9173FY/v/h6HzgmZ/dekG02XCvA0e3HUVnVJkKoHbianm0jbVxflyGw6+2zYlFTVQDi3Su8flfOZGDnZyekDhpy9eJVFBVWXfeqMVNLjz0CT5JHq1F4p+gRImkheYmLjQUfJMznGCbEx6OktBTHjh3Dc889h5dfflmEF5eK77BrIhXJ0KKvr498yPRLL72EyZMnS2JEffaD3N/fj4iISGzZshWvvfZNWXT27Fm557PyXn75Jbz04ouIiYmR3ir+GGUKDQ3BSy+9jMWLF4PPpAsODsKMGdMRHxcnb1Tq5uYOgyBf9fX10gsmFWobDYEnBIEHSrSSUqdIr8l9IVvCi9HV14oLJzJRXi0mZ3FedCEbB/ZlygmeZKjg1GnhLrdO+HUlxTi+7yiObT+M0wdOyZSfXweSA9ZjPs87qvKQfuwyOgXRUss4ydvCVCMDTf1sm/WYrubVynZ7muqRfThNtkM9h7YdkTZ09TbJBddsgyraKq9Ke9qHBAljhkhso/hCprRNtZU6Wtp6RClA3fZtXrpk7ZssHNn05mRhx7YzoF62odZnH3PO50gbafvlwyN2CQLHNmkn+0F59n1EndxRvuhUuuwTZYjfeHIUbq+ulPbXNFptJlGi7pxiCyDGiOXpB85IXdRzZNshUJZYyzE6eFKWUb99v2mv2napIElybRwbHElmPz8Eh3qj9NIFHNt/ToRendFcW4Oq4aFRuKltckzZL+rl9UPsG0pLsHf7aYkR7akvyJVjRjsoS5xoAxOxHIvTiCna7jFG4MnyaImQuhgLNzc3SV4chKeI/dML75aDgwMKCgokmSHpogwJmbOzMxobG8UPy0G4Cm+8h7s7vLy8BJmKEN6sQellEiptb+pzdTXD09MD/sJrTBJXWVkJg9Df3d2Nn/70p3jl1a/LxfiSNI2EZt3drfJsz2g0QrWJNlI58xwc9GhtbcWTRH7ZNy1pCOgeJAQmkwlLNy3CvKUL5O0K7rktMXFz8uYkKXWJc9sxM8acs4wTNPdqohh1jJvPwjE6mGVLooz1mGx5PBjJZxvULfcin3smcSjf9scyQ2yYpybq5bHIvv4e0T1umSolZNRDW32RZzsWhTxmEoeQe1F+K52UYTkTj5lYd7x0Q5nQPUpOnN9MDwmOWmZfhzrHy1dluI5K7xOEp3/wDfzw71/H1OBh7Hz3kCRNUmZMm9THfO6Z1GO2wWOZRB21jOc8ZjkTj5n3YJKm9ctC4Ema1HV6nQgP9gvv1MC4cLq6usr8HuH95wE9Tf39fZL08LxfeKu457oqrsfise4moVXKEDuGDEmSamrr8OGHH0pP2Rtv/EHuzWZre9RzuzQ0NCiJHcOclGX7bIPHWtIQeNwReKBEi+C4il8/y59fhFkL5ty/MCIVa+krjQC9fWc+2453fvEu3v3X9/Df//Qh6GX8g/zC0QAAEABJREFUSoOidf6OEbgZkbhjRY9ABQ8PD7i4OAuvUIvNGnqOuCi9qbkFDOcZjQZw7dW1a9dw4cIFKRcSEiLJFtdH5QuvV15envDKX4KHh7vwXHlKGXVDckUPVlFREbKyspCfXyAX3g+O/NlocHAQVZVVKC0tFYSvT602aq8oimjPAWyvubkZfJH0ce8uPGpDQkduTq7oRyuztKQh8Ngj8MCJFhHih2fFC4vvWxiROrWkIdDX04fG2ibwn34tDdYvbA0VDYE7QYDE4U7kH2VZT09PEc4LAP8JSDv5x5OoqChBWNpw+fIl+IlwO9dmcXH6++9/gKtX87Bw4UJQhvKdnZ1yofynn36G7m4LFi9aLMOJLFOTJFJV1di5cyc++2wbJk+ehJkzZ4p2/TF37lz5r8ftO3aI+t0yBKkIj5ivry9CQoKh3gePHrCkpGlyMX12drZck0XC1S+8a4GBgegTnrV9+/ehqqpKbVbbawg81gg8FKJFhLgmYMWWJZJsmVxNzNKShoCGgIbAl4rAk+TRcnJywqJFC3H8+HF5awaD0YjZs2fjtde+gaSkJLCc99f6zne+g00bN+LrX/86lixeLP+RzUHgLSG2bNmCLU8/jddf/yYSpyTKtV4sUxNDe9OnJ2PTpk148cWvCd2vgffrc3FxEecvSp3PP/8cfvSjH+FpocdZ2DR//nysX78BOr1equF6sbVr1+GVV16R3rC+vj65ID84OBhBgmjRzq1btyI8PELKPyYbzUwNgZsi8NCIFi1wdnbBko0L5J21NbJFRLSkIaAh8GUi8CR5tBgmTBVeJX9/f+zduxf9gsCQAMXGxgqPUogI1+llYqhwmvAohYWFwmA0wp5shgiyw7KgoCApO97Y0CMVHR0N/suQ0QpFsd4+hWty+W9FLpBnG+Hh4VI/PVpsi/ap+rikhPXpwWIYk7eLoHfNxWSS7VI/ZVR5ba8h8DgjoHuYxvPz6OrqioXrUjWy9TCB19rSEHjUEHhE7LEnGY+ISfdkhpu7u/Qq0UvEENxElaWkpMhbO+j0Vq/TePV0ej1IhlasWAF6pcaTudM8El2GCKkzNibmBg/anerT5DUEHkUEHirRIgCKosDDw1OSrYTpk5ilJQ0BDQENgS8FAU70X0rDD6hRRVFAL9GzzzwDerMm0oyiKIiIiJBrrOy9TmPrsozeMd6bi8djy+/mnHqWLl2KGTNmSO/X3ejQ6mgIPOoIPHSiRUDE5xomEUZ0cnbk6SOfuIjT4KCzLeZ0CwpBclK47fwhdOCBNeEXPw0Rwe53r1/Rg9jcvYI7r+nk7YeZi1LGt1vYw/G6E63EYPWaGTC7ONxJtVvK0sYVW59CoI/TLeW0wi8XgSfNo0U0FUWRpEVRFJ5OKJHwMN1OmDJMt5O7k3J6x+63zjtpX5PVEHjQCHwpROtBd+p+63f38cS0eTPgF+InVfunJGPu0hkwT/x7TNZ7FDez1y7EtLlT7ooskWDFzEzCpBmJD490CiLl6OyN5NSpCAnzHgWpzsGIuHmpmDYtbOL2CH2BwXGYNn8yXO8X0RI6hwODkLpqFkLM7qNs1E4eLQSeNI/Wo4WuZs2TjYDWu4ki8HgRLTGBubv5IDI2EglJ8QgI9bcRBN593j8ySuaHRQbbvBMGMdFRnnmsw72nr5dNB89VTwYnauqMmJwgyz3dncD6YUnTsWDjXMyeHQPm1WVk4czRi7DoFPgEeIM62Ab10ztE/aoOlutGfllSlyrHOrSZAzU2X7WHZUz0jrAeiQ3PiQHtZP3x6rI91qEM6/CcdvCc9e1Tzv7DyLpYikE4SDxpuyzXu4F9kLYI3JlPG9hH6iFWXqERmLk4BYuXT5YklG3JumKj2sV+Ug/rEjtRJN/Up+bTNrWuWk9tR7Yvatjyp8XAP9wbRoNe5Nq9hY1hcVGYsWI2UmbHIizITV4bxIHtqPrUdmw1hwdth/JA6KFttJd1VNt4bTGfWLLv7Jfsz4g822AdKQPrI32kvjEblrMus6mH+pl4zHxiS11q22yPslp6MAg8iR6tB4OUplVDQEPgbhHQ3W3FL6Oek5c3kjYsRer6BUheMB2bt85DTIzwMonJbtKChfIBxEmpSViweRkWLJ4myZaLRxA2f2+DfCAzy556biVWiTR7+SzwfN1La0QYUHhAhDckcEoylmxciumpk2Ubq9fOQaCvGYHhgTA7ucIrwBfuZkfQo7Vw7VyYTUZEzZ0D6qC+GctmY8Orq4WOJZizaJrUsXxNCvy9HSVhS920EotXJmFSSiLmCU/S5PhAmT99xXzMWTlH5tM+2m5PCOjBYR/iwxzBCTlidhIWr0iGl68nWHfZliWyrtpvdzdHhM6fLWVo4xB0mLx8GZYuSJDkA+pL4DZl1XIkz4iA0d0Ds9YvxpTEEHByN7kG4JnvrkVEgAHEferK5dLG5BHc42O8EBAdiSAfZ5i9vRETYoKj8frlpIuIxLJXNsp+EgvaOCspTLZP8rPgmRXCK5gsdRKjYH9XGxbzts6RY8OxiIkNBgnl5LkpWP38ctnPeSkx8PAwwv6l0+vhJ4hWYIAHvMIDEOgjxis0Aks2r8SSpQmy3rJnViIxMVT2D+pLYKAecu8fES7Hj+PJvj7zwiLQtvh5M7Fw0SS4OOvhE50AjlOwtwK3wEDM2bhWjjfHcOX6WXK8qeuGJNoKE6R90wsLZJHeyVleP/PmJ8Bs8ETqlnVYvWWNvP54La3fulASRimsbR4IAg/To/VAOqAp1RDQEHjkEdA98hbaGejmE4DY+CA05+Xi6J5zqKzvgYejA0zu0UhZNEXmH9t9DLmXqxGTOhehYT5wNBlgNptRffkK0vZnoKkDiIz0Qv7ps6Bsi/DcJEyJgp+HP2akRqC7tgKnD6Tj0J5sRC5KRbCbgqLsK2hqa8S13GJU1XVgyMsLXoJgOBkAJ5MJDoMduJR2XNZxCEuEv+swTu9PR8a5EngFhyIi2AeRSVMxbZoPzh4+I/VXtw4ifkYCgsMCMXVGrGz3hLA940I5jC7OcLZ7JmJ3azU6h8yYIuRdXdwQGRcGS3snzP7BmD0jAhWn0yHrivYiZ85AeIQ/PBxchPfNBerLxckRJrMwWM3gXnhzAoPd4exm5hlcKePsAL1ekecuXsEwexvgHRqBafG+qMq9InGvqFbg7tqN8uxMlFS0o6akGrlXqtFtGe0d8nTXo7W4QOJc1diPKBFiNDo7Y+riJYjwUHBqzwmcSC+GU1AE4qL94RcTj0WCFJUdOyfHihhJ79SUKZi9eg5az2VK7DJzK9DRLU20bfgon7xzl1BYUIcKUZ5X2oiw6SmI9eu3Yc7rZaEgyCS+tooCA/XY0dER4UkJcHcakuPJa2wwZBLmpkahp6tLEm0fTxPc48PgoutGVdMw4ufOk23I8T5bIPsSHRukqhy9F20Z3bzltaMW8PpxHsHf7O4Mh+5K2cdzJ3Kh9w9HwrRoSU5VeW1/fxHQPFr3F09Nm4aAhsCNCOhuzHp0c3o6mtFU2y5J1JIlsWirrgInVI8ZofBz6Udl/lV5l/CijApYYECon5vsTH9/P6orK1BX3oiSvA501hSirLROylY3tMLB5AqTKQB+wjuRsGQunvn2Vjz30gKRZ4Kruws6mlox0D+Ajpa268/Sk5qtm/raVlQI3XwoMXNaK0tRXlqL1sZ2dA/r4eDphaDwePj7+WHJM+ul/tmzhc0BHlD6e1FV1oTolBTQg+E20IBLZ3LQOUxN1tTf1YmsU0UIS05EeEIg3D2NaCgqg1dIgJjw23E+u1zeIb08rwAVXY4ICPK2VrzdVtHfTkKWd9RXo6FtAEnLFoC4t9cXIb+gD10dnejp7YdDXyc6u/qsz1CUNayb/v4+NF2tkjg3NzXD4GwU3ilHRM5MRXB0GDa+tglPb0lBlCBZXn4mOCUnIEBglLxmNZ59bTUWpsbA2UcQE9HPUOcO7Dubi9rKRpTmVcPSZbE2Yrftaa6XZ8P97ejrMYkQoy+6GotQVFQvbcjLyMewhxc8fDxge9lh4OzqjMjoEIQKYrf8xS149rXVCPT3hm+4D+oLijHo7gK34DDMEESqobAALZ1GRE8NsfVltQgvy74EBdrU3+lBXXWRtLUs75q8LtwDfKE4ONypGk1+gghoHq0JAqWJaQhoCNw1Ao8X0RIT6Zmde3B81wl0O7kjZeMSMByl9r6z1ygPB/Wtcu/oOvpZWzqlR+bfbDPQ24O8tDPY/c5emX73f/8gSczN5G/IFx6Lzq7rbfR2CRIyYLXBybkXHVXXsO+jw1L3Z7/6HJ+8m4b62npk7N6Lz9/Zj4YGHeKWLcWKtbNGL7QXegvOXYaDdwhmzIrGwGAbSqsabc33CxJoO7mTA6F3IuIkMMc+3o59O86gTeeL2SI0a4/7zXTcahIrOpspcSDWb/7jO9h/8KpU091chZOf7ZZl7//iQ4lRa0O7LLubfna3jF4vpSiK1GXbjINBwbnzsn3a9s7f/QqfvnUCtXXNaKjTYcr8ZIR7diM7p8amoupqlk2efTlxyPoMOZuAdvDIIqB5tB7ZodEM0xB49BC4S4seH6IlPA++CclY8Mw8tFeV4+DHaSisGERIvCtaL1ag3+AEhp+MTkaEJcTBxakfRdeuk57b4dOvq0ZPzzBMRge01tegsqYZji5G2E/uQ45uo9f33E7pSPlwbydqymqg8wyEabAWZSVVaBIkzOjgAFNQtPRkOQ+14sC2L3B8RyF84+Ng8nIcqS12ou9tVQUoru1DdEoShoSuxtY+VInwWK+TB6bGBsi1WwzxRXgOo7O1Fa0D3dKDJMObXt5w93ARisa8hV77nO5eB3h6uMq1Zx4RHsJbZsUvYuZsLF63GAM113D4o52oatFJ3O3r2q/Pss8fe9zX04v63By5jqqnpUYSTVVGl9MIxcULzhhEVUWVDSN6BjuHjJiXEgWjox5mH1cY3G708gw7OEtVisENir4N7fX18I2NA9dY8boIT0wAWpqEp7FVysmNHQYtXcOoqW2RIdfh7mZpw7DBOg59ba1yDP3jYmFpqUNtjdAx1AV6RJ09/cG+8JqROm+y0SmKHBe9k6tow0mEbF3h5W6GyaHRVsM3yBtGcQ07u7nCP8AEpaMewwMDtnLt4P4iMDQ0dH8Vato0BDQENATGIPD4EC3heWAISy88Kstf3oItr64CScXVc3XoaruGY8cqEbdiBZ753vNYuWoaGjNzZTiPXiU+LNXWb10LLO3DttOq7gEMdHWgtawamWeuwH1KHNZ881k8++2NWLphIXw8TbD09qFRRKXmzYsB/82ma26GxWKd/Lh2p6tXZ9PX0WElJxD2MrOr08Id8jMvIy+3ERu+/xqe/dZmPPvKU5icICZoEQ6t7THLkOKWbz2DRRtjUXohFyRSsiI31CXS1RPl6OruRumVa+gfGEJ9UT4yM+swc+tGqXP1llQRqsuV66Xa8svR7RyAVS+9gE3f2Nd3sesAABAASURBVIzQMDM6BvTUdj0JneoJiURJQTm8JyUK+RdkSM9isdreVl0NmDxA3ImLj74HxJ3zP0OCrlGJmD57MtR/CKo629sG1UP0dgqPXnuvPL+Yth9NQ97Y/EcvY9O3tmD188sREOghQoLpuHC+HCkvbcSW10XobgSj/toCHD1agZkbV8h89tNt2GqbVDiyGeyxoK6sAR7RsUhOCkP+qQuo73OXdlPfnGQf5Kdnoq7JaoesJjDobu8Woch+KJY2MLxoMfnZ6jz9irjOgn2AwX7UVDSgvaEJhVearARc1M3ecRp1FhPWvv41EBsu+mdfqLuzs5M7WxoaHkb9xWsoa9Lh5e9vwvrnlyIyxhWWTrNNJiJ5Hp7+xmY8/do6uA214szpYjnWNgHt4L4ioHm07iucY5Vp5xoCGgICgesMQZw86u/Omipsf/MLHDucjZz0LOx4YzvOXqoCSc2FHV9g14dHZP7h97dh5/Z0dAoS1d1ajUPvH0FpbT+GBgdRciUf6Sdy5Joi9rfz2EkcOHQVFp2CorPn8PnvDksd1P/hL99FaVUbOoVn5PTeYzh1qghtgjDUZYi2PzkvyVD5hQu4dPoSevuGqA5nPtkjJ0eesO2zB87iWqHwljXVY/fb2/DJh2dw9eJVHNmWhpPHLqG9ulJ6iY7uPCHz0z/bJ20nkaIOW6LnRZDErspyYZPVA9Lf2YaTH20H+02dat2Wth7UF+Ri1xs7cfH0BWQfOgaGKk+n5YyetKlTNKDr6QEXk185kyF1sQ4x/Pw32+VarLrSMol7+r5TEptd//OexJ11Mg+l4/DnR1BW1mTDQKjEUGkJzu5KQ1FLG08l7scOZKNPkDf2+b1ffIB0gU1OehY+f2snuI6K/dnxm/ew880juHI+14YR+8Px/fydwzKf/fzkrXRJKKVydSPI0OVjaSCW5bW9aK4olXafP5oh6/F6OXSiECQ8ahUIDOqqL+HQ58fkeNbnX8Lnb+yGWufzX72J09mVsk5LVRmOvLMDZ09dsS38p6fxo//+XMqzL9vf2oH8/DrZ/71v7bf1X22P8hyXY4ev4OKRc/jiv3bi6Mk8dPZbSfCVoyfldZB58BR2vr1PjLUVP7W+tr+/CGgerfuLp6ZNQ0BD4EYEHiuixQmyRxCWooyLuHTuMspFCI557BYn/dIreTL/an6DJFnM5+Sdl51vPRceiHZBbK7m1doIR11JsdRDYkMdPKduJk7w1GGfzzzqoE7Wqa2os9WnLG0gOeMx2y4pLEFNYw9PwXPV9rKiUqtNooT51Mc2uSdBFNm2t8HsjpkLpyN5TgwKswpHeWRoG9u8oa7oq9oX6qQdxMumVO8mdZpNThjuH1kDJYibqosYUSf7SyJL3AsuFeDS+Sty8h+C9dKh7ZSjbuKh6mc+25X1RSYxow2qDPWxHhMxVPPZn/Kr+WC+PUbMpz7mc09dbSMeMqFevnkt9DU3gOWqPfbtMI8yUljdCJxoG68Z1Qaesx0mdSwpzj6xXfbJpkfUt2+jsbaJonKsaQdlZYa6EfLquBBP6quvrLeWim2XpUX2fWzbokh7PwAENI/WAwBVU6khoCEwCgHrbDkq6wk4EZPZo94L20Q9AUP1jo7w9PVE3cXzyBZE507qjqteeHGY72pyQ+GJ0zYPHPNulWS7Krbq/lYV7rJMtiPqqntxOO57vPLx8satPDbzPvZnojaoctwPDXciLz0Dd7KucGwXtPM7R0DzaN05ZloNDQENgTtD4HEmWnfW08dYuqe5CacPnMKRozk279g9dYekYqgL50+eRdoXB1FebfVo3ZNOrfK9IcDxOHYeDKHemyKt9p0goHm07gQtTVZDQEPgbhDQiNbdoPaw6whi1NXRhb6evvvX8ohOhinpUbl/ijVNd4WAGA+Orxq+vCsdWqU7RkDzaN0xZFqFWyKgFWoI3IiARrRuxETL0RDQEPiKIKB5tB7tgR4eHn60DdSs0xCYAAIa0ZoASJqIhoCGwINB4MvWqnm07s8I9Pf1ITMzE4WFhRgcHERHRycaGhrQ1taGOyFL3d3dsh71VVdX49SpU1BvM2Nv6Xg62S7rNzU13VGb9nq1Yw2BB4GARrQeBKqaTg0BDYHHAoGvokeLJIWkhOl+DVJJaSmuXbuG0NBQ1NXV4fz5c8jKysLu3bvR3dUlm2G7TPJkZGN/TnJ15swZHDlyBN0WC/z9/dHb24uLFy+OIk6s09jYCMqPqJG71tZWpKen45133pFkT2be44ZtESe2xb2qjsdj89Qyba8hMBYBjWiNReSRPn94xukUBU7efgj0cXo4jSp6+AR439ieyPf09QLT3RrCfgSE+oN9GqvD5GqCweHR+xiwv8RjrL3a+f1F4Kvm0aLH5/Klyzhx4gTa2+/Pn2BIOkiQIiMj4eTkhIqKCumVSkxMRE9PD1oEASJhaRferbq6ekmCeF5ZWQmSI44oz+vq65Gbmwt6pDguer0eMTGxyM/Pl3oop6bLly+DfVHP7fc1NTX2p3d9LG0S9ubm5CIrO1sSQBI/eulIIi8KDx773TXmxsR33aBW8YlF4NGbYR5xqO92AuSEzsn+fnePj2tZsmYZJiUEjFatd0PSiuWYO8ttdP4tznQORkl2aOsQdIhPWoSpk8MwHkEZq4Z2sH9j7w4/Vu6m5zoTUtatQcqc0f3Q6fWInT8Xc1IiJmQH9dMWkhT2g+eh82dj/eqpo58fyQKB0cLnnkZKYhDP7imxLbbJtu9JESsLchkr+jxvfsKE+8xqWrpzBL5qHq3hoSE0tzQjLe2YjeTcOWqja5B8FBeXIDg4RBa4u7tLwvSrX/1akjkvLy+ZPyBCimVlpSgvL0dxcTFItGSB2NDrRU+Yt7c3zGazyLG+3d3dJDEj+bLmWLd9IlQ59k88rBscHAxHR+tjs6yS97a9ciUXGRcyRCi0A++++y4YziSRTEtLQ0tLi/DY7UGFIIz31spjXlsz/7YIaETrthDZCYxMgMvXpNhlTuBQ1AueNh2bt86bgPCdiehMHohdPhehfqMJlU4xY9L8JExOjp2wQqO7BxauW4zoSVHQ6fXwDHCHt5PrhOo7+0Rj1vrFmOTnfVfkgPZ6hPiBz/qzb1Dv5AynoAD5DEa9XrEvGveYpNDJy0/2IyzYVcoMiS/64IQQeTxqM9SFhsI8VNk9kmlU+R2c+IqQCbELCPS9g1o3ER0ehJe3F4JC/W4ioGXfLwToOblfuh4FPfQukcCcP38eV65ckUSHnhnVNheTSXiJYuDi4qxm3fOea6gslm6pk21ZPVExMBqNct2W6mHy8PAQZCwYFy5cAD1SERGRYB5trqquBsdCJWU8pi4HBwdJnOh9I7HJy8uTJK6srEx6uthHhiy7RsKT99yZMQqio6Mxe/Zs0A4SQGdnFxnSXLRokfTeOTs7S/vGVNNONQRGIaAbdfYIn9DbQg/NwiXT4KZTwLul05OTmiQmUEFkYlJm4OnXt8i0IDXK+tw9vRtmb14LnrNrbkEhmL9qPiKC3eEfGYXnX1sly1dsfeqG0BTLVX1s093NB0nLl4j6c5GYEoeNW+eDYTXqX//iGjCpetV6q9fMkHpjZiZh4aqZCE6aJtuMMDiAng/VZtpBj5ROhOvYTzWfOmkb7feLnybbYJsQ/Y2YnCBsmQ8/NwN4d3f2b6LJvg3ampwULu2cvXoxJom+LVq/EHMS/dDV04EmkfQmN+kdoyxtYj9pq9oecV26cS5mzIzD3K8tweRIJ/mQ6+Dk2XI8WI99MLs4gC/2nbgxnzhSH2/YyTIm2hcs6rLvgb7Xf91CvFhmjw9xM9iF/oxevpi3ZgmmpU7GkmfWY1aEv6gF6AVhnLFqqbRHjou7k8w3hUYi2E0BMWU/2Obzf/Qc7GVg93IS4VTaThkVC/eQSVj89GJMSZmMZWtnyeuL+lQ7Ob7EmHY6TkmW45gkvI3sP9uRY2rXBuvy1DMkEMu2rJA2LxTXvdHJiOBly6VtEktxfcfNXyCvb+pmHS3dGQI63UP/CrwzA+9AmsTk0qVL+PTTT6W3iuGtL774AlzPpKpRFEWQBoN6et/2er31s01PEz0+JCh/8ic/wNq1a2XIjcSJjdH7RdLC86GhQSiKgv7+ftBurq86evQoTp5MR7YI1ZGAsY6aSNzc3Nzg5uYOV1dXsXeTyWQyiz5Z21dl78deURSEhISINtxx9epVTJs2DZ6eHiAZDAwMlF658PAweHl63o/mNB1PMAKP17fMkCeSUyfB5OUIz+BwTElNwLCxHX5xiXju9ZVwdxqCBS6Y+8JmJCeFCc+KGVFJCYibYv0gOLl6ISZliiBIrnBw90GKmHiXL4gQNbrhNNwN9WXyiMOLP/mG1NfXASm3+Kl49DZUoqa2FRbLIAqKGjHs7I6kBcmYPT8GJschOARG4/WfPAdvXTs6WjsQv3weFi6ahL6mOjTVtmO4uxlXc6vRLFzoETNnY7UgJ0bhVYFXODZ/awv8vR3hE52ADa9vBvsy4OyN1BVzkDAlCr1d/Zi2MEmG8gziiyUhNQWTwpzRNzCgmj2xvaJHzJzZ2LB1IQZbhV09eqz81jNIjPFAbWkNLK0WdNZVo6axAxc+/wSHTpVi8twULFs+Bf0WC7wjw/Dc9zZIW9kgCZelvUO41OvQ1dWNxtJaNAkPUeCUZHzttQVg/ywC4VkbNyAmNhgkSnO/+TLWPxUtMXKOSMTqZ5chwNOd6mQiBmtfXgGH7iY0NbbKPHVDvRtetOp18AjABiEX7O+qFmOwtxfNTc3o7OxEc1UFKjutzwp08QpGQrw7OJ6TnlqAWeL6MDrqET89FuGxvnDy8sai5zdhUpwXmhpaMGX1EqxeO8emlweS3G9eiZlTglBX1ojAGdMlFp7D1SgpbUZ3r2iztkE+DzN25ip5TTqJPvQ6B2HlswsRE+OHsKgQpK6eh0WzfGT/Jy1aiEUbFkMSJ1x/dTsa4eLti5AAE4Yd3bHomXWYGe8Hl3ZHTBceTB9PE9z83ZC6JBEugrhfr6kd3QkCnPDvRP5RluWapX379mHLlq1YsWIFnnrqKQyI7wd6j0jCHpTt9OpQd3e3RXznKjLUR0LFfF9fX0RERLAYDQ2NoCeKHqJ58+ZLzxY9VU5OTnj66afxx9//PlJTUzF16hRMnpwIesZoP3V5eHjAJLxxQUFBCA0NgUp2SIQCAvylV4nEjLIy9fRIO2TD97AhbsHBQXjmmWfAf0CePXtWagsICBAkcp30ruXk5t6XtqRibfNEIvDYEC0+666mqgC9LmZExwYhYlIIFEuTfOjx7LUL0VF0AZ++sQsH3voY585VYMqcJJgNg7cctAHxS+qDf38POz5LF8TC+jxCVhgIcYGH4wDyT2bg1NE07PzsBMqLKnEttxDVDa3obGqSz9PrHjSI2H0PTn60H9veOYj66nrs/+AQvtiZiXOnryL7ogUM/3Q0N0kiMtjTIZ9jZ3FxQ9zsJDSUXMO/Hf4rAAAQAElEQVThvRnY99EJNMIDKXMCkJASj4HyXGz7r+3yYdPHLleDr+7afFwq6EBYfBi8fL3hJbww5fnl6O3pZ/GEk5OXNyYnxaL2UpbAqQiXDxxGeeOwJHO1JaWoq28W/SxGVV0HuAbCQfxQNLp5w1JXjpxjp7Dv/YM4fCAParOU4TMAS69WoqVtEEWn8+SzGDsFUTvwnpAV/bt48hKaO3sQEOQNZ3MElqQmYs+bb+HItkNIE6muQ4GTnwl8mdy8sOnb6zGcfw6n9meib1gYwAKRBuGAhZsWoOPqFYnbqcMXUGcxIS7aX37BCxHQlrLsPLS1tklSW9NoHdeO6jzs+/VOHD58EkWFtXASE4DBYGAVmfSDHvB2GUBZQSUuHDqBL95JQ0VphSxTN3pHRzi4uaP1WiFyMrPx8c8/R/qJEkmsqvOvyTYLc6+hpb0fS15IRv1FMbaHLkO1MzwySKoa7KjHzn/9DEe2H8ORwznwC/BAaJiPLFM3Lr19qMq+JK+D3W9vQ/a1diTOTsC1rCx5rUxN9oRfkB8cBvpQUd8uvuiH1ara/g4QeJI8Wj2CXJSUlAqPkHWh++DgkERC9SDxhGSEYb5ecX2RkPCc+WMT8y3ih1V3d7dcdM49/2U3Vo7nXBOVkBCPiopyGIxGzJgxQ1yPgyDpo4dr2bJlFIOzkyNmirIgQZZIjhaJ8BttYCHHgYvhSazoubp2rUjqaGtrl4TL18eHYrZEGf7Is2WIA677IqmMiorCZ9u2CbstIvfGN9tgf9TEfjJvrCTx/P3vf4+PPvoItJM4lpaWYvv27fjVr34lfnB3Sxubm5tH/StyrB7tXENA9zhB0N5Yi/qaIfhOTkZQkD8aCgvQN6RHYLA7GoSHobdvCEPCW1TTYYHB2QgXk/GW3VN629E5eH0iV4WHSktw+PBVzNy6EVu+uQmTw53R2tgqPlQ3n8wGB4fRJ768fGMT8Oy3nsazrzwliJO7VOlkkDvbxuysB22OmTlDyr74jflw7G5Fb4cRbn5+6GosQvvQjW3li0ndGBWNqTOipS5OsJ2WQdDL1t0/IPNutyGhcHQ2IHzBbDz99Q144btb4KPvQX2zBS76/huq9/UOoiw3D+2KGWteexZLVqXAub8ZnV19o2TbDLpR58NDHYhKSZH9W/NMKsLCveE5qMDk7wSTvleQ1X5J5OpKy7D7vV0oL2iX9YOSF8HPaRgkkRadIvOub3xEyMAJYcmTpN6tz86Gq/BKTbTv9CTS43Vd3/Wj/p5SZJ0tgmfCFGz5o68hIc4fTS3d1wXEUV9bKwrOZcMYlSDbX/1UGLpqK2/AQqf3h48IYdJO4qvaOdTVKbRcf/NabRSE9HrOjUed4jIY7LEID1oDnAW5xmAN8otrERw7HfFREeisr0ZtTavE8sbaWs7tEHiSPFpuIpw2a1YKfvGLX+Jv//ZvsWfPbtn9uLh4SVZ40t1tQU5OjvguG5S3YxiPJNCLU1VVjR07duC9996zJf7LjjrGJnqe5s+fj6qqKpC0eHt7g+Rq48aNWLVqlWybMu7CK8Wk1nd3dwc9XjxXFEWG6Z555hl897vfBfUxv1R8FycmJsJgHP1dPnXqVLi4uFDElmJjY/Hqq6/K+ty7upptZfYHJGQffvihrV+ffPIJSkpKJCb2cvwhRp2uAleuDYuIiJSewsjISPiJ7+mioiJECVLHkCL7Z19XO36yEbjT3unutMKXKc+JrqSgHFFTwxAX1I+8wmbxwe6XXiWzpzccjTro9Hp4OLiIMFffKFN14oNscHYalXezE2c3V3RVlODT336GrNOX5eSbuigZLs76m1WR+aGRKZg3wxNpn+7CJ8LDlXG2TeaP3fT19Eqbiy5cxOdv7cSH/7MNO97YjvPZ5RhobwO9OuaR9Uz2deuqL6G33wmzUmNF2K9eTrCDYhK+eOgcKsub7EVvejyoF4TO0o+SjEu2ttnPE8evgh66sRV1er0gYH24eOQc9m47ibZ+IxZuXQ37cB3ruPdbfz3zmCl+7jw5RsRi76enUV5mta9XhEC7Bh1h9jaAY+IkPGxR8ZFwNlu/FFvK8nEhswLR4tcuQ23UpSau4+ro6EF51lV88rvPJW60PfdK9Q1Eo1/YqdabyH7YwRnD7fU4/vEBHDucLUOkK9ZNHVVV7+QMXWeDlDm68wTadL5Y88q6G7CgnT29HSjNOjXKTo6vvUKdXi/CIUb7rFHHBv5YENcc2/X2vC537VQOzOLLPnKmP9pEqHIs6R2lRDu5JQL0pNxS4DEqdBAe2oULF2LKlMkoLi4B/yXXI7xcer3O1gsnEZKeNWs2vvOdb4MhPJIIRVFs5eqBTqeAniqG69REj45aPnYfFhqKqMgoNAlvP8v04tqmvKLcqJvlE0m8bYKzszOSkpJGiSuKIgmawXj9MzFK4DYntI3hSrVfJGy0dWw1ys2bNw8zZ85EeHg4vv/97yEwMBBTBPFbsmSJJFnPP/+8JIiKcvf9HNuudv7kIaB7nLpED0BNRQPaB1xgERM2vUzMu7A7D65RiViweBqmLlmIyZM8UZpfJshMNzrbe+ETPgnTF87E1JlxCPLU37bLXMu1aPM8JE8JlrI9PcKtII+sG7P4xZacFC4ISL81Y2Tb7dYrjxgimjo1HLEz/OU5Ny1DOrkge9rsqTDqBnHtciW8gkNlG1GTopC6ZArczY4oziuFLjBe9mX2/CnCaxHA6jJ11tfjWl4n3D1MaLlWYvOkODs7wtnVWcqM3ZC0sU2mhKR4cPF8dXUdfCOjZduhkcFIWTgD4UGu0iM3qHNGUGSgjTwwdOibMA1zF0xCqJ8R3YIkjm2D5yRQ3MekJsDf2xGtA92iv24gFgyHBod4shgDDfW4eLEYyfOXyzFZvnyB1G32tHrkGsuu4tTeNNQ0D2L+winw9nSS9bgxKJ0SN6eYWKRMDwdxSxG2EzeWj02TEoNww0LzsUIj5yTXkxamYm5KGNxdbvxY6MQXKUOHESmzMHtBHIyOo7GwDDhgWOeG2MRoeJr7cOHkZfjHz7HZOWX2NAQEesjWhp09kbBiGqbPE2nuZFgam8BrWRaKjQ5D4Bot3xA/eR3MF9fupBhv5J8vk4SyqaIUlc2Aq15BWUk1+gdGk1yhQntPEIEnyaPF+1QdO3YMmzdvxl/91U8wd24qePNPLjLv77P+8KRXircsoIeGYTb+A7CttfUGtEiy6G2yTyQmNwiKDK5bOnHyJKprquW/DNnm6HRE2nGneSfT01EvvvO4NupO61Ke97hiCFSYOOrtLMibfb+43ov9HSUkTni/LC7KJ1ZlZWVygf7Ro0fBvtrnEXOSQlFFe2sIjIvAjTPKuGKPSObwIHo6mtFQXCPX0jS2dAEirzQvHVzr4hwUgahwd9RdPI/s81dg6WvG+S/24mpVH8Jiw+BgaUJx7jVwofdAWyPyMgsxaOm6oXMtVWXY/dlFUB/rNZWW4PTxLHRbBpF3OAPFRY1yvdGACNcVZ+fJNTJUUn8uA7sOXpP1PL3dUH0uD9UV9XI9U11GFjIvVoGT/2BHLy4fS8PVC8VSlm20Cc8E+1OSfRlp+67KfL+Q60SN+odEWLRaeHzKSltkm5xg6e1w9/eCh6MDRWyJXpXqogp09JgQPTVWppjEKHi5OaAw/QxOHM+XbbBM19uOuqo60GOYeeYK+nQmQVBcpS6GDsszM1BZ2wWf6Bh4Ow3ixGf7wDVcUmBk091ajcsXC9Hj4g1vEeKqSD+H9EwR7gqKgNtwJ65lF6OiowV9gy04/tF2VFQrckwUBwuyTmaiuaEJtLehugntNTXISjuN2i4DPLw80FNdi6aqGuHaH5a4nTtdJm0nbgMtdXKN1IgZckddDAOyH46Ojugpr0JBRoks46a5uAqlFe3y304VV8tRWdUmQnD1uHAsAx2Ki7SrqaQch3ZfprhMXItGfPJOZ6CrVyfxtMeC5If9H3J0A0PF5/Ydw+GTpTY7ubCfIT4q43oQB09/2U5XTQXST+SgsdU6EbKcqa2gTF4vlPMM8sDV4yekx5Nlg729qC1sQ0tlDVSdzNfSnSOg0z1eX4G36mFBYaHwZBWDYbu5c+fij/7oj+Tict77iXdaZ12GvLhGSk1c1G0UnxGW2Sf+mYQ3Cs3NzZULvrkn6bGXUY9VnREREWCoTdV9r/vo6Ggw3a0ef//R35+qva2trbY+sV98bBDz1HJ1bxQeM7Vvt7OB3kS1nrbXEBiLwOP1LaPo4eTqBRfHATQUlUniww5xAfTltBM48PF+mY4czRFkqgecHOtKy3Dk3d0y/+jO49j16UlJEhoqKvHJ2wfRJjxe1GGfqK/0wjlZhzpPHziF8up2qa/xWh52vbdb/KrJR1tjC3IPH0NRUb0sG+xqR9a+Q7Ie20rbux+HD2TJNkgeqIvtc91NT1M9Th09KWWZT5s7uwdAr4lDXxtO7D6G9JNFGOruQmdLkzTPYDIjICJQ/puuqqAOfPV3deLCjj24kF/P0+tpsF3ms4/Uz5S++yiu5NegpaEZV09ex2vf7vNWvAb6oPbbpk8Q2TqB4XFhD3UwnT1feoMXhZipfc8v7wX7d+az7bJ/xIKYZYnQKMlhe3UliA11sSw3twJqP44erbSS56uFYFlxfonE+FRGscSYetV2WJ+4tbT1XO+3OOI4qP0jIWw4dQI7dmWAuLOd88fOI+9SPgZ6+3Hi489xLrMS/LNFcVaObJN62XZ+vhVjoVK+KVM6YhdlmFQsepqb5NizHkkT7czYZb0WKKfa2d1pgaG/AzmfHLRhw3aIi2wEAK9b1X7qs69PGV4j/oF60Gs73vVLGS1NDIEnyaNF7w0Tw2AMewUG+CMuLg4eHh5w0OslIFxflJCQAK6j4ppS/mvPWXh4ZOHIRlEUhAQHY+uWLXjllVdsKSUlZURi9E7VSb33mmgXf4iEh4fjXnXRLuIw2lpI8mbfL64LI6EbK0tcqMPeDhJJ/ngjQY+Pj7fZyLyx7WjnGgIqAo8P0RIkK3bmKrz6/RVyfVJeaaOceNWOcBLs6uiCpbMbfT123gFBFJhvnzipqfKc1FQd9nvqsK+jyqn1WEY96p51KcN6tIH5amI+PW+jzkUFyjKP8jwWWTCKkFTyivl45Ycv46VvLIW3rglnThdD7+6DrX/+OuZP90X5xdzri+VH+qfWpw41qbqpn4mERJXjXi0n4VDrqPncq3m0nTJdnT1gHfbbVmZ3wDpsRy1Xz1mHqVMQSVWc52qS8iP9sMmMnFMH5Wz5QoGax7Z4LLJGvYk381lO3TymDuazLzxn4jnzeUwF6tiyHvNZzvxRacQuljNRvywX+dRjn0d91MXEMsq5mJ25k4myTOO1Q3mWqYnnrMT7qX3vL74GP2ObIIvXRn0GWK6lO0OAE+ad1Xh0pScJAmU2u4L/lCsoKMDpM2dQWlqKSZMmwcmOTDGMyHDi7j275e0fxuuRwWiEuyBoJD5q4lqm8WTvKQ/5rgAAEABJREFUV15PTw8OHjwI2tYnvLb3S+9YPSRFap/UPfPGyo13zttRvPXW26AX7Eki6eP1Vcu7fwg8NkRLhyFUlGTgs199jgPbjoGkwQrD6O14k9ZoiQd/dqc22MvT8/XeLz7A3g/3yfTOzz+V3rSe1h6c+WQP3vv1dmTkVk+4E9StpvEq3arMXp5yJCn2eeMdSzm7grHndkX3fHg73bcrv5kBd1tvPH3UxaSWMaT6xs93oWr4ztdVcZ0Yw9q8Nj544xBKRchT1avt7w6BJ2myJDH64Q//FAEBAdizZ48kWatWrcLYf8XV1NbJMobGMDx8d8Dd51r0xPFfi2p40v4zc5+bumt19LRlZGSAni+mu1akVfzKIfDYEC1+8PqaG1BWVHpTkvVEjJ7wjDDslJedD6aaRmsIFCIUWHolD+UlVTeE7Z6Ifn9FOsGxLSksuasx5GeAIVpeF4211nDyVwS2B9bNJ8mjRZA8PT2xRYT8fvSjH8lbHTB0aE8Kurq6UFRUCN4ywT6fdb/MRE9RY2Mjxgtlfpl2qW2TCJaUlMjT6Ogoub/lRivUELBD4LEhWrSZEw0Tj7WkIaAhoCFwrwg8SR6t22FBsnD27Fn09fWBxx0dnWhpbZXHt6v7IMvpKeI9qVpaWqQtzc3NNzyj8UG2PxHdXCx/+vRp+Pv5y1tY0EaGOidSV5PREHisiJY2XBoCGgJPJAJfWqeeNI/W7YAkyWLIsKKiQhCGRpBA8Aalt6v3IMuHh4YkwaKHraamBvX1DfIpC48SCeaNWOktrKuvQ01NrcCuCd3d3SLy+miEXh/k+Gi67x0BjWjdO4aaBg0BDYHHFIFHaTJ/0BCSVPKGptHR0dJj1N1tAe8VRe/Wg277Vvp5awSuI+M/DUkE29pahaet5ZEiMVz3tmjRInkTV9rH218w3apfWpmGgIqARrRUJB6nvWarhoCGwH1BgOTjvih6DJQoigLedDQoMBC8ozlvasq7nPN2EF+m+YqiyMfpkGi9+OKL+Iu/+AskJyXJRedfpl32bRMjd3d3JCcn48c//rG85QXJl6Io9mLasYbAuAhoRGtcWO4u0z8yCgtSo2BwuHtYqWNSQsCdG6Dooda9l/bvvOHRNZy8/TBzUQrcdDd+AdE+3lF/dI0v58wtKAS8W77RyTjKAJ2DET4B3jCP8wikUYLayROBwFfJo6UOmMFolIvO6dniPxUZslPLvsw9b7HAxfCRkZGgXYpy43fIl2kf23Zzc5P34aKdvM8W87RkRUDb3hyBu2cEN9f58EseFMkQennfopf+Py9AJT+coF//ux9i5aI42U8Si3XPbcHqNTMQNj0Fy59ZBEfjHcCqdwMfjaM+KiZ+3kykLrQ++kc2cIsN22ZdT3cn6PR6TEpdCj6fz2waTR5uoeK+Fw0HBmHza+sQFuF0g272beWzC2/I/zIyAiIjsO65hTA5jh4r14BorPzaWsTEBstnMeJLfJEERsZGIiDU/57I+5fYhUe+6a+SR+uRHwzNQA2BJxSB0bPMY9BJTj6evl7S6yAJhvjV4+TlLUnG4tWp8PEwygmSngmbnJCnl4d5JlcTmNSy23kuejqa4aB3R6ifm9TrHzQNURE+iJ8VLic/dzczzKE+6LIM2NBzcnO32jfSriwQpI3t0lvCttkPnfCeOE6KwsJXtmLJjESwP5TtbhkCy+zlaT/L1MT6oZEpWPfaGiRODoKzs0Etks9MZDusrxP4yIIx7Y/Vh5Fy2sbE+qo9qi3MZ5J1hby7m4+tn7RHtjOycR5yu2kZRWiXwewO6mNSx4Ft8Zy2SxsEhtTNPHkuSKVsn0rsk7DHJjNSRy1mO7KuyKdetq2Wyf1IXfa3u7Uap3edRFlpHaA3SPtYR61PW9Q69vlsm+f2unnMPCbWUfum2s981mPiMeUpJxNtCgxB6voFWLwiefzr+mZYQHtNFIEvz6M1UQs1OQ0BDYHHHYHHimhxwpy0YCFWPbcSK7Y+hZVbFiMsyA2h82cjdoY/PEMCETMlDs5mFwROScaCZ1Zg+eblWLl1BebMioCrixuWrFmF9S+tw5KNS7BSeC6WrZkDTrAY7zU8CD6moq62C97BgXBx1iNwdgA662tgDoyVk5+Duw9cXfvR0dKGvtYh6J1csXDdYqt9ot3ExFBJmiImxWLZy+tkGe1ftnQK/AI9kRQThCAPHXxmxiA+zojq/GsoK2yAb2iItHW5sH+NqLd0XowkdqqZnmISTpztDzc3N0yZk4SwYFdZZBZ2zdmwSvZt/TML4O/tCJIov7hE2T71EQ/apU744EtnQsycudj04kao2Gx6eTUigt3h7mmWdbd8cxM2PbcI3oG+oL6lL2+4ju/cBFu4TdHpkLguVZaxr7Onh4yync0ZvXwxfcV8OTaUWbB4mhwHepQ2fudZrHxulcRwlRjrRQJP2sQxp00xMX5UcT0JUkJ7KKv2b86IPU7efkjdtFLawn4v3bAIvGauVwbUuiSsXr7eSJyVgIBAD3EdReD5H20F61Av9at9cQsMxMLnnpY2Ui/HKHleMhwcrxNeHs/cuBYzZkbL5tg3ysaHOYLXMsuok2n5ymTrWElJwGAyIzwpAUERvvCNjEZ0bJDUPXXJQnn9054lz6xFYmLoDdiOqNB2E0BA82hNACRNRENAQ+CeENDdU+2HXNkzOBwpi6agu7YCGWcLoPfwQ0iYN/jA5pqqNnQ2NaGisAx6V08sWJ4Mpb4K5w6fR0ltJ6YuX4bASG/pffJ06sfVjFzkXq5G3KI5mJUUdtOeDPb2ormpGY5envCJiEFsgCsyD59BIzzk5Ofj4wqH1la0NraCL6OjEyzVpdI+mDwwaXIE3E06MZlHSXuyjmeiuKodEQtmwtOkoPRqJaoFQWu8UISykj4UZVxExrUOMMwWFW3A1YtXUVTShPj502EfEmxuaELuuTrwXjjFF3NRXtXB5mWqzsuTfQtJmiRt5KQ9e+1CuPS0Ift0Nmo6hrFw7dxR+ljR6OYNP98BNF4rwrkTuTBETsaytTFwdDIIUhgIQ28rruUWY9jBhA0vLYVPf4XUR3zj5sxETGww1UCv06G3uUWWVbcOYvqSWRhFjhS9JMdT4/1l/67mNyBmyRwkRPjAR29GVLQ/BlvrJIbDTm6YlRoL2pR1MlPalDw9ftQaMJ1ej4SUeCjNNbJN9i8xORo+niaECq/fvHkRqMrOkG2Z3FzlNSMNFRvfKSmyL6ybe6Uaw0Yz/EMD4OHoAAezHuHRk+E63C31tvY4IGbGNPh4GBE/dx6mT3JD5cVzKLpSDGdPL4QEmWHUDQmt19+BAZ4IEYSaOY4mA3x5DXoLPGPiIe3KvYKLWZVwCQiFh48HVK9Wf1cnyrLzUF3agIaSa6gsb4JHeALWbZ2F1uICaY8FLkheMB3B/q5Ur6W7QGBoaPR43YUKrYqGgIaAhsAtEXisiJbS14nONgu8Anzh7+2MnPQsXCusFh6menTW9cDS2ITGli64+gUhNMws5eidiBGTm8nXDd4BPhKMqsJMQRgKcTntBPJKexEWHzZq4pZCI5vBHgtaG9rhZFAQMykULpZa+Yy5/OJaTJ8XDXd/L7S0daOts1fWsLQ14OSxSyjKLEJxSassdzIA9QXFGHJ0k96SoCB/eArPh7trN9obazHU3YWmng7wLvBUogxY0NPVhQG9K8JiQjDYXI8Te85gsMPaBmV4h/C2jkoMdg+iurICFks/s9FZU4iczALRt6tobR+Gp9cQXDyCMDPRE34BgvilJIKTv2+Inwwxykp2m+ayWhTlFKDoQjayThUhNGGqJFYDvT3IzbqG9GOXQS+ev68zzhxOl3evzzt3CU0dQECQt9TEGxBePntO4FSEvIx8dA+5wNvTRZZxo9PrER8dLkidM6KnxiIq3B2eguSFx/qyGLx7dXHmRRuGap94R3TiTsyl4MhmaHAQ5ZmX0aG4ICYxSvbPzccEZ1dndA80ore9D8EJsXD1dJMEhdcMqw47m7Du5ZXg8yTTDp4V49jD7FFJP9wD9qUgtwQ1ZTXyOjAORQi7Q1CXfxanzpTg0sVCVJU1oatXN6rurU4aB/rQK0h8UGQgfM3DuHI+F7U1rdefXSi8qW3tnejo6YVF7BvaBxCemABDdy3Onroicb948hL0Zk94+HjYCNqt2tTKbkRA82jdiImWoyGgITAhBCYsNPGZYcIqH5wgvThn9x5HpQjlhU+OwvyVcxAR7HNDgy4OPpKANNc2oKayAWXC43D0s+OoqmgaJTskJrv2XsuovLEnlGltbEe/owciU2dBJXM152phikpGlI8JbaKdzq4+jH31CU8V8xwdHZGQmgIfT0dpT3V1HXp0DiwaN/X1DoLk5dzxLAwPOGPKwpmYu3QG9K6O1+UV/fXjmxx1DVpl6EmhSGNpLcoLy1GZk4uDnxyzkUOW2aeefnEmJvrWgW5xMPrNO/MTX6ehLlsBw6uDw10wujjb8uSB0NHbRWXybNTG7OYoPZD1lXXSpiNfHEXOxbxRMhM9MZjMSF6SihA/J4lvZ0WjrWp9UT52fnYCTe1DkNfM6nnwD/aX5QadwLO1CWbPOyMrDmLsTPpBcC0d8ZDK7nAzVFqCne+ftNm1ePlkGa5UPVpU59g/xJ0tmZxc5XF//4Dcqxuzi3Wc1XNtP3EENI/WxLHSJDUENATuDoHHh2gJYsHQ4ZTkSBSdOYdtb+9Hs0WHSbOtk6Z99+nFGDIMorm6BpdOXRSemSxUlVSgpV2RYiZnT/nPQK6TYSiwq7MfncOA0ck47nqXduF1qutzQVSAC8rzy9HbN4S66kvo1bkiMNQFtdVN6B9UpO7xNvSshEU4Ci9asbSnqrQRt/qCJ3FImD0Nzv3NOLV/Dw7tzkRwchJiPN2vqxckxrVHEIXrOTc9Itnp6upGS2sHLgvvU9apLBReq8N45NDZTRFeG0DnYAS9Ts2NFjjiuieNjdCT1qMzwcM/UHpS3N3M8BKh1Z6GBhZD0engPOQGiDHzDXCG0aAXxPc6EaUHqrqhFf2WPhRfuIDMU5dw7UoRSmvHJ2W4zUsviGzk1EgwhMr+FVbV22pMnpuCyeHC+7b3KHZ9dBT0vNFL6OzsiIGuZnz2m09xpd6AFU8vhlzPZqt584NBxwrUtQzAN9xHekLZvpOjYdwKXUPWfIODDgZnJ+iFNw/ipdp14dAJ7P4kAw3GYMREO4lyRZRa372G6x9PZbAXhbWlcHb3hY+nCcTWw8dNYtvU0g3tdXcIaB6tu8PtrmpplTQEvqIIXP8mf8QB0MH6694/IQ4bXl2NTc8uQXiEKyrzO8CJu0uE3nzj4zB99mQ0VZSirLgLC17eii2vPIX133kJT399AwK9rTomL12Ap762EVv//HX4ufTL0JA5MBhPf2MzuGiekyLsXj2tPWivr0d/Wx0q6oV3a2BIhHM6UFPbisGedtv6LFax2P37kOdMXb16tLXqsWD9Aqz/+mY890stBGkAABAASURBVN318HZW4ODgg742BzAsl7xyNubOEuSEFUQa1pkxa+MGrBR2Lty0AANNpajsbBMlI29Fj8bBTnQaTEhZswohob4gBhYRLhzr8eiovYaMs22YuW6V7OMzf/oynn15CezXfI1ohd+UeVj1/GpsFJjNnxmIzLTzaO29PvlTrvFaHk5ersfil57Hpm8+jfWvbYDbUCsKBHljOdOGv3wOz393K5a+sBqWlkYRor3uZYIgiddO5cAcGYlnvr1JtvXaD7diamwAq8rHccgDsekb8QqKw5u+uY6OY7Hg+VWyf89+baH0UrFC4xAwZcVCPPPaeqzZOA+RoW4gIbRYrOSxo7kJe377MXq8o7F4ySS46K8TQtYfe9fsnn7ByEVB5tHz8IiZgxf/dDM2ietm1twomBxFY6JMfQ8Ix1NdWQNC56Vg63efw3PPpyLQw1kWNzZ2IGnFUmx6eTXWPZuCSNceVFQOi75b9VOI/ervMyIsKQnJSWFoyr6Ma60GfO3PXpLYrls/E63XClFR3oih4ev1WFdLE0PgVj94JqZBk9IQ0BDQELg1Ao8N0eJEUl+Qi0/++zNcvFiJpoYWHPjdpzh6qgicuC8fS8Pxg9lo6x6Gg6UZu9/ehm3vnwZDRgyVffHf76KizDoZ5WYUoKO1A405l/Her7cjp9giidNVLjyv7Bo12RE+3VAH8k9dwKdvpYHraJjHxcpnPtmDfTuy0VzTzizUllzE6UPC0yU8XjqlBzVVBThz9CKa6+qw/c0vpH1s9/zbb2L7R6dRXtuLoYFq7P30NM6lV0sd3HD9VdaB/daQl+hn7bks/OYfP4S6hosy7DMJ1NEP98lQqq6vE2W5ecg4Vwh63IaGO1F49DhKrtaJNvpwats7+OjN/RK34vTT+PS329HS1iNV2W/qC/Kkvs66Snz0L7/FydPFGOxoQebBU9ILRlmGU0/+5l2pj/0pOHJU6iutaoNSI/rz/gG8/Ua6bCtv1y7s/2ifbIvrqE7tPkUVqMq+gHd+/gUuZzWAbX3xu23IyK1GbVsbzuw9j6omMVZDXRLTE4cKoJJHEjRiKpWMbIjXZ//2e+zfcRF1ZY3Y9/FBiW9Daz9qjh7B7//5Y1SKcDOvmaMffiGvmdqSUpzcdRJdvUNor67E9t/uQlXjIIYsHTh/NENg3YGO2jYc/vwYmgR5HRocRO21Elw8f02GXGtysvDB7/egqKITTSIMWJxbLHSN/jgRJ47jFx+eRWNtE47vTcfud/eDf3pg/3/zz++jtLgd1XlVYP9zcyvsCRN4jZ3am4bM9Gx0dg9isK0Rb/7019izL19ie/jzI9i5PV2UCUY3goW2uzMENI/WneGlSWsIaAjcOQKjZ4Y7r/9wawhPCCfF9P3pOPTZQWRll6FfeJdoRE9TPZh/6dxlOfFw8i1IPynlmF/TeJ1UdNfn49j2w7KsvKSK1UF51q2tqBs12bGQJK+upBgst5ETYUvplTyZ1z4kSIE4p8yJtEvSJk6y9fmXpI2d3QNQ7aPdJC8XjmdAbZtyaXuP4Mx5K2Fjm7SH/0CkPMvs7Wc5E9tQZUhyGgsuy/YkJoPtYBs5JVYPTV9PH1TZE8dyBZG4jof9uiCuQWM4i+0SX7bT1dkj+0lseM5k37a9PrWftrYEHqrtxOvkmTJWl+SYeLFvbOtqXq3Erau1QI6jxJmYlpbJPhFDVqzKOifPJebMGEkkJRxn6mO/mUhu1LFjG0zsE/HhdcSxIi5UwTHgOceE40w8SYJZR9pPW+yuAZ/oBBmSrCwqF4TZggERam2rrpIkl/rUxHFUr0PaxDbs9dFeJrX/aj25F2121lRJPFS7qS/7kPXapZ0qLlJe29wxAppH644h0ypoCGgI3CECjxfRulXnJlA2qG9F3ZUiGaKZgPhjJ0JScYPRYrK+XZ5ar62uGpWVzTbvka3eeDpsheLgduVCxPa+E1lWmqj8ROWo8z4k3sh2UO+PSSmJSEzwQ0teDvhvTZK4+6DepkIdG1uGdnBfEdA8WvcVTk2ZhoCGwDgIfKWIVl9bK86fPIuiwirpPRkHj69slk6ER0uyL4O3Dui2DH5lcZhox+kRO7DnME7sPibTkb1nR3kJJ6pHk/tyEdA8Wl8u/k9661r/NASIwFeKaDHc1dXRhU6LCPWx91qyIUDPCcNSDNnx2FagHdwUAeLF8CSTFsK7KUyPdIHm0Xqkh0czTkPgiUDgK0W0bCP2kMNMtna1Aw0BDYFbIPDwizSP1t1hzpvtFhQUoK21dcIKLBYLyssr0NXZOeE64wk2NDTgypUrGPuP4PFkn9S84eFh1NbWgWPwpODAcb127doTOa5fTaL1pH76tH5pCGgI3BECN/No8ekGTU1NkhhUV1eju/vGe5VxsmuobUJdVb2cHEgkKisrZR0SCjW1tbWBsndk2F0It7S04P/+3/8HH330ka29np4eef7FF1+A9t2F2nGrEJv//M//RE5urq2t8QSJW2FhocSHOG7f/gVKSkvHE51w3rlz5/Bv//Zvt2x3wsoeMUGOF3Eab6yYxzI+OYNmHzuWBo5Bf38/Tx/rxM/HmTNn8Jvf/EY+McO+M/z8lJWVyWvIPv9xOtaI1uM0WmNs1U41BDQE7g2BsR4tfuG3t7fjyOdH8Ou//i/8x1/9Cj/781/gzX9+GyV5paO+7Lu7uvDuz97Dzrd3gZNdQXYhfv6Xv8Qv/vznsh7rMl08cenejJxg7d7ePmRnZ+FnP/s5rl69KokI+0fyxwmax1RFEsnJi6m/r0/K0UOlTuD0kHBSZxnlub+dF4q4sQ49XCRX1EGdJEXf/e53UVNTI7EzGo3gkzJY3tHRCZJD1mM74yWWUYbts854MrSPY6b2R5WhPPtEm6iHNqpl9ntb/dZW8FgtY332he1zr9anDPUyz163zBfeOns5yvCciTZQnnnUzTzqYT6xYB+zs7PF+P0M58+fB8dJtYXHly5dwi9+8QucPXsWA3bkqleQaeqlHupU65C00Xa2wfbUfHVPWY4R67J9exkej4cp61Af69ysPXtd1MN+ERvWoU72RbVB5osfIsynrJqv7tnGwYMH8X/+z/9BQ0OjvIZYptrNMWc92sX+0ja2z2PqZts8ZtvURVmWExfqoK6HkR47osU7lptcTfD09QLv5M5kcLizbrA+08MAeNw2FD3YvtnFAfa3VhhX9j5nEi+2PV67xPZ2WFLmZvVva6rot8HsDk93p9uK3ncB0TbtJub3Xbem8LFFYKxHixPY5dO5OLrzOFxd3bBo3WIkTItHwaUC8L5l/NJmZ/nFXlVSg9bWNkyelQgHBwcRErOwCJNmJGLlluW2FBETKvMfxsZgMCI0NFh6BhobGyWJsm+XE9HRo0fxxhtv4O2330basWOiD63Iz8vHu+++K4lGa2srPv/8c1y4eFFObNx/tm2bPLbXpR6TwFVUVMo6v/v97/Hpp5+iuLhY6kxLO4auLgsOHDiAPkHqoqKiBNFywkWh+5133sZvf/tbfPLJJzIMRkxVnTxmGIllf/jDH/Due+9J8sjJU5XhnhPpiZMn8dZbb8k+sT/sIydUkk32iTaxP+Xl5Tf0gZMu66ty+/bvB3WSDNATx76w/Q8//BA8p958ETJle/QSUvcHH3yA5uZmVFZVSTuJO+VOCw/N4cOHpYeGbbMvlKfO0tJSicf27dvlOBCLg4cO4aToS0FBIY4cOYrGxiZ2UY4hj0+fPg1ikp5+CjUibMjCurp67N6zB9TLPvKc2JFcbxNjRtvp4czPzx9F3Fi3UVwfO3fulHXZfkZGhhx/9p3eJWLC64SYqkRoLKbsB/tKIj/SHqiLRJGfFZKjt8R1dvjIEbzx5pugPRcuXJC2EHvm/+53v8N7YnwLBK60yz7l5ORITCoqKnDsWBo6BZFliPGQwIr6aB/tJnmlzRwXtp+VlSW9rb8WXtddu3bhf4SnjON0TFzvn3zyMf77v/8bHD/2y769B3V8ZwzlQVkxUb1isvQNDcGSNauwcNEkBIsvFH4RBvu7TlQDSBRi5szF/OnBD53kqEYaTGbQBt7t2zz6puuqyE33JEhuQSGYNnsqZi5KwaSEAEk41QokMglJ8bKM5faJ+WFTpmDhgni4uzmqVeSe9aKSpyAxMXTcxxBJIbHh/aOWr0y+ob4ouv1bZwIfPbNggfUO8LevcHsJlTgaxiHbahkx0+n1Nsx5fnvNmsRXAQGSBPt+9glPAW9s6xfgh2VblmDNcyuw/OllcHA0oL6mHpw8KM96ecKD5Wp2RuyUGAwNDKKzpQ0GgwHRU2ORNC8Zs1bMwjJRNyI+HIpyhx90NnIXyWg0YMuWLbLm3r17R4c8h4eRlpYmiM2nCAwMhLe3Nzhh0UOi0+uwe/ceNDW3oKqyCjt37pJeFU5s6enpMuyo040/XZDYcILj5B4XF4cqQTj27dsHo6MRkyYlwGRyxtSpU0GStWzZMvT398lwJh9HlZiYiDxB8k6ePDGKBHHyPiImZxKYhIQE0HNBUkD7ZOfEZnhoCAUiLLljxw7RhgleXl6yP5yUWY8TOMkdbSoQ5IVEpLOjQ9S0vtnGhQsZos5hmM1mREdHS5KYIYhAdXWNJI61tbVgfZIShumol9452sZ+R0ZG4uDBQ5I4Oju7SDLG9WMsI9kgAaDnhHVJEKirrKwc+wWha2lplfXosfHz80N4eLhsKyAgAFOmJAqib5aGKooij2mfl5e3kImFu7sb+Kqrq5XXJMeT48T+tLe14f333xekrBjEjmSCZKO+vp5VZCIZIzE5cOCg7DexYJ9aRd0ruVdkfQ8PD1Avbc3MzBTjWo1f//rXkiBa+1EmsDskPU0kZTk5ucK2ODg5OUnsLl++jPb2Npw4cRKsHxsbK8d4+/YdkkSeOXNaXGc74evrK34chKJMhAelcXab4OBgqdNLjO2khEkQrFPgfVDglomIiAgQN2JbUlIiyT3b4meQttfV1YHXIa+BkJAQnDlzFh9++JG8Vngtvvfe+yAhs2vugR3qHpjmB6CYBCVsegqiog1oFh8ES8+N6yZu1+zQsBPc48IRFh8Gvf7hfPmNZ1Po1ASEBLuPV3TLPKOXL5KXpmLW0hTETI7CkmfWY2a8n60On7vn6BuCwBBfxMyagVVfW4GYaG957uvpCJOHJ/jF7252tNVRD3SOLurhTffuriFImB4pn4d4U6FbFLDfEQmxt5C4syKP8AQs3bAIwYpudEVFD5appJDjzrbjpnjiyxz30UZqZ182AmPJA8NayYumYt0raxA5OQI6vR7tre0YHhiAh5cHjEbr54YTKW9WGxoXIfJdMTg8JIhWr+zO1YxcMJy44809yDh1Cf0ipCcLxts8gDxOSs8++6yYjC6Ckx0nUTZDErlHeD9mzUrB1q1bJSGLj49Hbm4uODGZTCYUFOSjorJCkBZPOaEWFRWBE/QU8QNNURSquSHRW5OeflJ8rvToEESGIUx6Xkjw7BhvAAAQAElEQVSkOKEZRbiQ7bi4uEgZKmAZJ0BOlFu3bsHkyZNHkVFFUZCSkiJJgBry4cTZ0dHO6rZEwssTehRJ5jZu3CgJZIHwjtC788ILL2Dt2rXYtGmjJEGNTVYvEeuQNNNLFRgYgM2bN2PDhg14/fXXJVGoqCgXfemUddevX48XXvgaqI96WZcT97p164TeTYgUZKu0tBSenh5gPxniI+ns7rYgJiZG4peWdlz2nSErEk3qaWxsoCosXrwYTz/9NJKTk6UuHx8f2W+OhxQQGx6znYAAfxBTEkORLfTH4plnnhG2b5REjWvnSOROnkwXnkOjJKjEjySG+LHO2ERiNG/ePJAEuzg7Y9/+fcJD1yIJHK9zEkTWv3z5ksCgDi+//LLE5bnnnpPjxn5kZmbhheefB7FiX4gPvZYcY5L/dWvXyTpso7u7SxCtBhAnEu2t4ocBx2jRokVjTUNQUJDsr5cgmNHRUWhr7xDh8Wzh2eoQJK5desZIWIknr4Hp05MlHhwHKvMSBO1pgS3tmjp1irB3ElavWoUtIs/X1wccN8o96DRmdnrQzd2DfkUPv5h4TEsOhLPJIBX19vRjoHtQHtMjQy8P0/xV87FwybTrISpR1z8yCsyfv2Iqgnw9ZJ2xG3q7IiYnWOWEjghBhOj9oO6YlBnSS0QdgT5Oo6qq5Sxju2p4ivps7Y7os6+oGNzgHR2B5KRwqHXcQyZJb5WbToG9XvaLHhr+SjT2tOLCviPYu+MUmi06TJrtb1Pb19yAq+LXIUMfeZnNcBrqQu6x4zIUcibDeld2g7MRweKL097ewR4LhnqtxFVxcAD7GxkbacOCnjPDGK8R+0c52j+2zMnbz4YXy9X+qYbS08b27fWq+pjPchVnevCIq2xjZCzpnaN9CctTMH3JdEzbOAeqPCgTEY55y2ciZdkMLFwxE55eDrJpk5sXps2bIfsVFhls82raYz2evbKytnniEFAnarVj/LIOCwtFnPBKubm5yUcnpe87JYt5c1oXF2fxo3oYtWV1aG1uRbj4seMgvFj0EDi46GF0cgQ/oxCvvMyr2PvublzLLZJ1RNZDeZPETJuWJLxJk4TH4bCc6NkwQ0KcbAMCAmSok6SSfSQhcHAwYM6c2eJX/xnpGZgzZw5IkBiW0esdJAGgjvESvV6cUNkuJ2Y/P1/Mnj1beGHcxhMHJ2F63TjB79u3HwzpsJ69MB95xTBPVla2zKYtPFBJI48V4WGjl4TkijZ88smn0v7BwSFJCFxdXeHh7g7a5e3tI4kDSQfrMjFM3NPTIz0c1E/SnTp3rvS+dY/8+cHDw0MSQE9PT4GHQXhvGqQ+FxeT9F6yjrMgJ/3CE+rg4CAm8smoqalFVlaW6L8ZwcEhkhCwPdrR29sL4p+amgrqZj5JFMsUReHpHSUXcT3SdgcHvbSLY9zR2SFIci9oF3El2eB4EgN75XNFX1evXiWJ9scffwyGFweFl5DEmnqJNRMJLz1YxJi2mk0m2RY9cCwbEngbjQb4COKiKIpsl3KUZxnbNJlN3EnMeEC8GDokBrSfOLq4uLDolqlHzFPEUC+uSY4lj9mH4OBgWY99pj5FsWJpMBhlmxwbJ+Fpo106UZfXDnWwvqz4gDe6B6z/gap3dDIgdvlchIR5w8UjCHOe24BF6xciREygKauWYutzC2AQ5MA9OA4b//gFzJgRIr8Y40NvHFA5yYsvmvUvLJP1faPj5MN74+P94ezmioSFqVj93FNISI5DiNnd1i9O0MkrV+Gp1TPgF+KPBP76eWmJJE6BU5Kx/rUNiI3xRYhwBfNhwFOinG11eWDwC8bCtXPh4ykuREWP6YvmYXaSP/TenkjdtBKLlyfB09sNK196ClvWJ6KnuR6nD5wSH44KVodiNqO75frDjHkPLD5WhvcL6263Eic+q4/nfEwNK3mExUosaO+S5zdi/dqpMLp7IGh2Mib5+0Bn8kDKuiV4/kfP2Gxf8fRixMT4sbpM/JKeuXEzVm+cK9cgDA4Oy3xuSLI2/+BlzJsfLTFZsHUd5qVEwSS+zFkelLxIfJmFyLFY/uIWpCQGgfgveH4Tnn1hrqxDb9yml9eAZDcgMgIL1i+A4uAgPQxu3gmYu2AS3F2u95t6J5KCJyXLtmNSpuCF15fC39sR0Lth+fMboI4h7V2weJq8dqC9nmgE+AV/sw7S+7Dv44Mozi/B7OWpmCtIPSdETtCleSVwdnJBZHSInIj5Bb900yL84O++j2e/v1Wm1JXz0NbYgkvnrz50r5ZZTGyq9+DEiXQZsjEKzxJJTnV1tSR+JEf0gLi6mkVfHKVnhZ4Qei84CbsLknLq1CkRnvEFicbNcKJ3hbpJHl782tfwyiuvYpPwLNFjMB6+9PaQAGzYsBF/9EffBb0PDAvSHrUNhrBOnjyJp55aAXqOpk+fLjw04rOqCog9Q4f0prGN54U35Rvf+LokifS8BIuJt7m5CZ1dXbKvdSLE5jQy0Yqq8m10dJTeK9rS3z8Aku6LIkRGT4urIGmDgwNobW2VsrwWKBcoQq4yY5wNrw2SD2KRlnZMht08PNyFd9BLSi9etBjEhx6h9cIb5u3tLfPv94aExSg8r7MF2WV7L774kvCYbRHeoUBbU+wr11uFh4fjm9/8JtasWSMX2TNUSrs43puFl4/1X331VSQnJ4MEkd4jiyCn/GHBEDGJuIPBQRC7fuEFa5b6iRPDldTBMpk5ZmMN77mD1x89rbRnIqTHyckZLi4mJCVNAz1qtO+ll16SPyrGNPFInT4+RGt4EPVF+Sis7UBFbgUunS1Ba/cwzCYnG6CO3a0oOHQI2373KY4crIJXeAB8PIxIWjwFTk3X8O5/bscnv92BC7kttjrqgdnPD9PnTkZ5djZ2v70NO37zHi5XKZi/cAqcHY0wuzmieMcBfPTLd3ChrB7qy1mQsOAAE6quXsXBD3Zg+293obbLALP4EM2al4jOkjx8+sYubPufj6S+pU8vUKtiuL8dbeJLr9/sJsmiE92jCWaU55fDOzwCsSFmnNq+F3s+2Ift7+Qhcm4qvM06kDTp3X0wb80ShBnqcSztKm54CdJ2Q95IRm9TKQ59fgzb//C5iJ/XwDc2DmbDoLXU22zdi2191hG89z87kLbtENp1HvD2dBG51vfUjavEl2AULny2A1fzakGCZy0BjAKvxpzLEu/P3zyES/kNCIsPg9HNSsZayvKl3m1v70dRWTvCZiQiKnkK5s4NQ9o7AkNhF9u0mPyQMC1aqnV21ss9Ny5uLiJ0qaCuqg7X8srQ2dSFSzvOXr8zu7hW6krLkHuuToRzWnD+2AW0NA+wKorOZsrx2PvpafS7eEnSHCzCuPGTPJD26S5sf2sXzl0sRUR8uLi2jLKOtnlyEeAX/Hi946/tAx8dxuVzl8Q1GI8Nr64FyRRlOXmXF1UiKCoIZg8TsyTZchWExTfAGyQo9BSFx4TIsqbaRvQP9Mvjh7VRFAUR4eFYvnw5uEaKJIa/6r8miBDXYvFv9L///e9x4cJFkMSYxA82Ep6+vl64CM9CaGgoOAlz0oyIiAAnxpvZTq8SJ/Wf//wX2LtvH/7rv/4Tv/3d7+TES8xaWtqEZ+2QDGNRBydUrpV57713kZ6eDnp/fH194aC3+4wLGwwGIz788EPp8XrrrbdAEjB2vLh265133gEXmJOY0Yvi4eGBKYmJoN3/7//7/8r6v/3t78AwFUOVtIHJSRCvadOmgWHOd955Wy7I/tu//Vs5ltHR0aCeN998U64n+9nP/k3qmzp1KqveNJGk0CNKksf2iVtYWBiWLFmEfxM6du3eLdc5/eGNN9DScuM8xDFiaO3YsWOShNg3xDISGGLGReb2ZfbHDC2mps7F3//9P8jxePPNN/CrX/0S1dU19mIg4f2P//gP+UcF/juUhRz7F154QYSQC8E1brT3H/7hH0DCzfBxaGiI0Pv3oAeMa6O4Ho2kduHCBfiXf/kXOQ7EjCHZucJjxv5T79hEcjx//nyQqPEPEVyw//bb74wVk+e8hjj2JwTxdhfzLdevMQTONXe078c//rEcQyn8pWxu36ju9iKPj0Sf0ot2S634UhsCvTl6JzdpvJe7GV2NReLXTR8YImvvtch8+42ic4XZQbBycTH29g2Bd5GvLymBs483ho1mDHd2oqmnA7JseNhW1dLegZKCcoQlJeH5P3kFM6IckHPsFLoHDXD3NKK7Ph+8a3h/ZxvqyhrgG5Vgq8sDS1kJSostSJgSBe/QCPi59KPgWh0UBCAoIhirv/48vv//+x7Wb42lOPodTIAgUfHTpyIy0Ak73z2EuqZe3PASZOOGvJGM9sYuWDoskhy11LbJUKyD+FUyUmzbWcogsbSMrDFRHK0kzNE7QnirpqGjvASXC2tt8upBZ309GtqGsPEHX8f3/tdzWJgaI7yCiloMS0ud1DvU1YrmpmbA0R0mtyjoxbiUVjVKu9raO8UXdQuMLs5ighv9S9am6C4OhtAix7CrrgedQ2bofS3w8QqDn5+/Fev/8y0sWpoAhleFw/QuWtCqPE4I8Avf3l7+Um9vb8fR7ceRdSprhGSth1F4gxiWGRwcRENlI1obmqVHlp5d1uf9tH73j38AU8HlQrkIva7C+tkwubvCQYQXKfcgk7OzE7jWRvW6GIxGLFiwAN/4xjckyeBEzVDP3/zNX8vwFknKN7/5GuaIMCHLnEUIjN6LVatWgSQkPj4BXOtFckFvjb3tJkGEZsyYIRcyE5s///M/x4YN63HxYibc3d2xadMm6cmJjYkRHpNvgGu9LJYeqYKE7kc/+qH0svGfdGz/61//+iiMOOH/wz/8vfDCBMn7ktEmJtrIdTucxHV6PWbOnCn0f1OERxuk3Ouvvw6SJxcR3uIETNLBRdrLly8DvV4MHUkjxEZRFMyYPh30iBAL2vj3f//3IEZcJ/Xaa9+UurKzL8n9//pf/0t61fzEj3J6VJycnIUWCA/5FHDROU+cBHkj6SRZ4fos4sZr7H//7/8tSS91ER+uGfL18RGRhRkgqWNdJpLb1atXy/VhXV3dzLKliIgIsIwhM65VoyzHQK/TSZJKIsk2uc7qBz/4E7z66ivyDw28ZrlOKTg4COqLdm0QHsVnnnkGtInn3/ve96QXju0Qe+Zx/d7SpUsxR3jHvLy88NOf/hRsl3VmzZol10O5ubmB1xjb4B8A2MYf//EfS08l/7nLa9BkMkNRFEleiQ/rkOCzzdbWNrkQ/vvf/57Eg+1Sh5o4HuvWrZXeSv6g57VFryDXV9GOH/zgB7KtCIEPx0GtHxQYBBJARVHAPOLMHwUGMdcpioK5c+eA53gIL91DaONLb6Kntx86eEo79CMfDnkyzsZFDIKaPawzy8NB19ELMGXmyEYZsKD2WgkOfXYYeVkFCE5diOe+twHeJgN6eobRP+QFnRhUnYNREIZhDAqyNlLVtrtcUgODfwQWLE9GZ00hyuusRLChakjk7gAAEABJREFUuQ4Z+49ixxvb8cUfduC9X2+XoQgR24PF0osS8Wu0orxREhObMvVA0atH933P9RNZJy/B6B8oQ4IMz9o34hOdgHVbZ6E4/TS2vXcEFzIr7Ittx8MOznASX4jobQN0LTLf202Re270iiCVPBhJRt31UCGJ0Ej2Pe9Iyjvra3B+x06J9We/+hzbPzyJxta+e9atKXi0ERjrIWFYMOfcVRmep+Wunm64kpmPE/tO41zaBekFqCqrhV58ngPDvUGCQjkXVyf4hQbg2tVi+V2w6529SD94Fs5mFySnTpVEjXIPMnEC5z2r6HlQ22H4huSJEzRJoV6QE06QP/3p34LEYa7wOpAcUF5RFLz44ougp0FRFAQE+EtywglKUa5/Linr7uEhJvJXwbU7iqJIcsW6nKBpQ2RkJNiWwWgEz3/yk59IfazLfC5+Z94//dM/ST2ceBXlehuKosh1YZShrdTNRL2coL/97W9L/U6C2NBekkfKcUE1+6koiiRpbJs2kWTR28T27ZPBaATxIBZ/93d/J4kb7VMUa/+JHeszvMb6LCO+1EcPpqIo2Lx5MximpV5FUcByEhjKq3nsn6rr+9//vuybwWiUeC9evJhiMpFIcqzYH3rGZObIhn1lGW0lQeDYUafBaITBaATL2H+D0SjXh9EG4vujH/1IEkHaDrsX7d+wYQPYPxJl2k0ZRbH2gdgTE+qlx1NRFEmsaT/rUD+vL0VRpBeUOLA96uL4UhevIY4V92w6JCRE9pl7fnbmiuuP48Y+sR3iyvGjrJpIjjmObJft8fypp54CbaMdvB5IzNl35hMn1p2WNA2sQzuok2O0ZMkS+SOCeRxTnlP2QSfdg27gUdBfU1YDp9A4zJkVgfCEaMQGuN5gVq+lCVWN/QiaOhnRibHgovhpyYFoKCyAQ9PNYXLy8sP0ZfMQEWRCdXE1CvOrYfb0xOBAH2pqW8AQ1LRpYWBoLDY+CPmns29ouyn7MvqMJkxODEDmqWsgkWnrqISlW9BDb1fwS13v7il+SXhb6w51yZBjWUm19M5YM8dsb+HRGiN5x6f9rRU4u3M/TqQVIGbNUrl2i2RSVWQQv6z1eitmrt4e8Ajxk0X6kX95egUFg4vZORaREV6wCO8VyWp9twFT58wGF7nHC4+d6Lr8d2ljYwe64YTkpDCExUUhMsFV6rPfBE4OgNnFwT7Lduwf7A93k9F2PvagvrYEPf0GeAUFglh7BXrDy218XWPrauePNwI64Q2w78GA8Fj19vTB28dDpoqCUlw4clamrJOZqMyrRnlhuQwberi726ryi37O0hRwXRYzWc8/yBcrn1uFhOnxUJTrJILlWtIQ0BD46iBgnQ0fo/72VNeipbVDWqzv60J1UaUIzQ1ioHMQDaUtaOtwkWXdA42oEUSEJ/mZl+U6oZAZszE1KQIDvT3oKmvBoN0C7p7mJmQeOYW2Hh3476K5S4V3qSRPrn9qE0SApKmjrXtUHerm4vTivFK4h8cgedF0hPg54dSudNTWNCD/1AVUVCuIT52DlDlxcr3WsZH1VAwjNtd3UQXY9qWsGjQW5uNaYTUgSFJLVRmyzhbBJSBU6mV9KSw2Or0e7kFBCI8MgqPxJkOo6EEMqgsrRY3r765WgVFds1zAztzu9m40i1/oA/0DsMe2tbIeDJVSRt/fjfbaBnS0tEmd9TWdsn7moXTk5DQjNjEa7m6OFJWpqaIU58+WI3R6ksTb1NOCxmoRthV4s99l5ZAYs0891aW4dCYHDRWVOLbjBJSAMNnfhBhvVF3KRu6VatQX5ePUqVLEzJiG6amT4eI4gPraVtlWZ0E1Sira5TovV3uiJTAkgapsEvjPSIDBZRjtDGlWN9nGsKG4RuroqL2GI4dzYA6Lkm3HTI4SpE0vy778jWbBg0RgrEeLYbApKZOx9TvP3JDWvLAavkE+cHJ2lGFDFxE+U21TFAX+wX54autSbPzWemvdb2/BknULwF/Tqpy21xDQEPjqIXCTWfrRBIL/mrt0IgNnT11B5zBgsfTj2MfbUVRYBUtnKU7sPgaG0mg9J+d9O07L8A+JzIUde3BqzwkREkjH/re/QNrF3NEhNzEx15WWIW1Hmvz1StkD247JBdZ9ba24cviIXI/EGDH1q6lP/PotvXAOh784LOsd+fQATh67BOZT38l9x3F6f7psW9XHfhSdOITz2eWyHyRWl4+l4ZN302zrrbimi7dpSNtxVOrl/szJHOvaJvGru+5yHs5mlN7So9V69Rq++OyUxEC1tyY/HweP5tjyqi+fxRc7M9EuyGth+hmJLfubsXuvtI/12lo6JbaFxY2S9Ki40sZz+47h3LkidPVeD+v1NNXj8Ec7cfKLIxLv7W/tkG12dXSiSPR7lyg7fSDdismu8yivbgfXxBVdyMaBD/bI/h4TY0kcW9p6wHZObz+AI3vOyzLKHN6bIfvQVlWAk9t24HRaDjq6B2iuLUkCJcbjtChj/y4fOIyTJ2vluPN6ObNzD3Jyu2Xbl9NOgGNH7wXH8lxmpcTapkw7eCIRGOvR0osfMb4B3sJrGgF6oyMTru95HBoTgiUbFmHqjDiMt+6KoR+GRShL4qUomifribxwtE5pCNwBAo8V0SIh4STe1t4rJ0tOzrUVdcKjNSAny8baJnDhOfvPyZll/QOCAAgS1dXZg/KSKjCPqabRujCTsrYk5FoamqUcZTnJs4ztNNa1ynZ4PjaRVLGcdahbtYH2trU33qCP+WyH+lXixn6xrnrONqiXeape2RcWCDuplzpsecwfk7p6m2R/bTKiXldHl7w3kJpHGeLGtqhP2iTCnszjMVXK/tc2yX87jsJVFKp2s744lW+GESmn2k1dTJRhGzxW+8VzW5+FfePiKLQOdrXbcGR9JtkH1hG2sS0b7kKeb9qttiPbbmyDfZ9Yptaxl6VuylOHlp5sBMZ6tOx7qyhWkqQo1j3LSKRIoNQ1K8zTkoaAhoCGwK0QeLyI1khPbBPzyPmEdmJCnpDczYRuV/925TfT+wTm39X4qDjcBMd70nkb3Wqxtv/qITDWo/XVQ0Dr8UNAQGviK47AY0m0vuJjpnVfQ0BD4D4hcCuP1n1qQlOjIaAh8BVHQCNaX/ELQOu+hsAjh8BDNEjzaN072MPDw+C9mu5d06OhgX3p7u4G71fF4/ttFXUy3W+9mr5HFwGNaD26Y6NZpiGgIfCAEXjSPFq9vb3o73u4939rbGyUzxjs6Rln3esDHr8HoT43J1fekZ53mu+xWO65Cd7olqSNhJRjw2cK8tFBGtm6Z2gfGwUa0XpshuqmhmoFGgIaAneJwP3waHECvcvm72s1TtwHDhzA6TNn7qve2ylrbW1FTk4O+h4ywbudXXdTTiL09jtvo6qq2npbDrs/QtyNPtYpKCiQjwHizXAHBgeF7ipUV1ezSEtfEQQ0ovUVGWitmxoCGgI3InAvHi0SG4aYqqqq5CN3btT+8HJIELKyssBn/u3YsUMSH9W+S9mXcOTIEZSUlNw0xNfQ0AA+X+/48ePgMclje3s78vLy5KNt+Hw9JvZ3bK94p24+Fod3+mZdki4+A4/6+BxB2pGZmQnq5vP1eM5nSdKu2to62e6FCxdkqI7tkoRQBxPz6RGiLefPn5c6WE45JupjW5SlfpZRP23kvry8QtZhOb1KzC8sLJT4MI+YUA/ziWHasWO4ePEi/Px8ERoaKh+FQwxoK22hTj4ImVgwsb9qfdpJ2bS0NIkbvYvUv3fvXvlsQBLgPuFx9PDwsD2km3XZB44P+0dcaAu9g8SM+tnO2bNnQQxUefaBtlD20UyaVfYIaETLHo2JHit6ePp6wehknGiNu5IzuZrAxNsl3JWC8SoJ292CQhAR7I6xj84ZT/yWeUKXT4A3AkL95WOGbin7mBfyEUr+kVEI9HG6oa+8DsIig+VY8ZjXxn0ds8ccu0fZ/LvxaHGya2lpQXNzsyAuQ5KYMBzECZhlX0Z/+a9c2tPV1QXVNnqaPvzwQ9BDw8n/X//1XyWpsbeRxyQc//7vP8fhw4exe/du/PKXvxTkqlx6Xd544w387Gf/hv379+Ott97Gm2++eUNosqamBvv27ZNE6fLly/j7v/8HvPvue9i5cyf++q//Bv/2b/+GTz75FNu2bcN//ud/gSShpqYav/r1r/Hv//4z2e4f/vAH6fXp6OhAbm6u1PFf//VfIMGorq4Rbb+F9957T7SzH//8z/8sZUg0SEL42JePP/5Y6v/Zz36G0tJSMS6DIPH8j//4haxDXewbydbBgwfx05/+FO+88458BqNKtgeHhlAj+tLVZQGffdjR3oHLly/hX/7lX/A/v/kfaQs9Xf/4j/8ocNqDzz//HP/93/8j69CWL774QmJ34MBB/O53v8MB4V2sr69HU1Oz9PbxuKOzUxI5kkM+AeTUqVP4u7/7v0hLS8NHH30k8H0DJJ/E4Ve/+hU4ZsT+7bfflvh0i/ElAWMfWP/LuNa0Nu8cAY1oTQAzTpqcPEkqSE6cvLyx5U9ewezpIROofZciejckLl+M9c8sGHXX9bvUdr2azoTkpalIXZSMm95V/rr0LY90ej0mL1+G1RtT4eBouKUsC/3ip+HFP3sFkxICePpYJbOfH2ZtXoOpk8OgH3mUkNoBz8AQLH1xPUKjQhAxczZe/tZTE8JDra/tvzwE1El2ohaQmLS3tckH3HaKSdPFxRl8kC3vr8UJnmUT1WUvd6/HvKP9/PnzER0djeTkZKTOnSsJDSf0Z599Fn/1k59g+fLl+O1vfweuqVLbY//Zj/nz5+Ev/uIv8MMf/tD61AfhgaKHhmV8ftxf/uVP8PWvv4oTJ06iVfQfdq/+/n7U1dWBukhkvLw88eqrr+Cv/uqvwOOysjL82Z/9CH/0R38ka5FoMcxIMrFlyxZQ99atW3Hp0iXQA0ayaDQa8Md//Md45ZVXkZ+fJ/N5/pd/+ReIi4sThORNsF16jXx9ffGd73wHfDYfbaYnjfmffbYNfJbeX/3VT/Dcc8/JdWQkw+yTv7+/7OuiRYugkm3ewZ/P/vP39wOfPzg5cTLoWXJ1dcU3vvEN0f+vC69SG/hsxD//8x/LNmtrayQppVeK7bEffG7f0qVLwZBhcHAwiK2/fwCIo6vZLEkcPYNNzS14//33sWTJYnB8+Ow9erDOnz8nSGuPIPCNoB7is3nzZjmejU1N0jaOqYPh9t+5EnBt86Uj8NgRLZIeehfoOSDpsSGo6MF85t1QRiFRznwm6mAWRvJYh8k+j3Jqnt7khjkb12L91oUwm4zgndMPf7gf1wqtcXbqY9v2dVRd1MF0Q5kQsK9DHSLr+nuoC3nnLsk7nnd29dn6NrYOz6nfVlH0yXYujtkuk5pncLbefNFkNsBgcADLbG0Lecqp59TNcvs8tqPmOzvfwQddEMeElHhMnRmPFeumUo0tSf0ORrCt27UtK41jJ3WwjPV5zMRzdYztdct8++vFR08AABAASURBVI3Qx3ImW72RcrWvI6fQmczWQ1FHLXN2Ngpi5QQn9KA8rwAH92RheGAAbJv6mG6lW9VD26G9HioC6iR7q0ZJrhhWYiKRKhYhOHo8WIcTOj0LERER4ERdU1sLyrHsYSZFUWBwcIBez6SXTVdXV8Pd3QMxMTHgDVZJOkhiSAqkgNjwTviJiVPAPb0n9AiR7DBMJYrhLuqHh4fDbDYhNDQM/f19kgSw7GaJdUh++ABg3iWf9b28vODh4QkSQhIs1iVJJRFxdTULG2NlOQkbywICAmR7RqNBeqgYmoyKipIhtwXzF8jQH8NwlGV7fIBzYGAgpk2bJrxU18B+njlzWnrV/vZv/1Z4w94XxKfQFuKlXdTJMVMU63eioijSPuqkncSEx97ePtIWhkhpA/vyy1/+Snjn/hNXr16VOlVMp06dKh/oTIL00ksvy4cwUxf1GEiMRBs8ZqoRXj2SPpI9kyBgxJd41IprqLe3B2wvPj5eYu/j4yNsc5T94gOqia+iWO2mLi092gjoHm3zRlvHCck3IhLLNi3GupfWY82mVDAExgnKLy4Ra59bjsWblo8qg3gZzO5IWr5E5q/cslx8GMPEl5IOwUkzZd6q51Zh+VPJMgSmylE/80wifBeZNBWTYrwRGBmEOfMmw+jugbDpUxEi9I61ibpok8FBB/+IcPBctWnLK09Je6HowfBdyvoVsn3mx8f7jwpJ6fR6BERGIDzcG/Q8Ra9dKXWpfadtfL5gzJzZ2Lo5SdblZB43LxVzF0wB7Y6YFAv2l31RsRJw2N5GryA8/Y3NCAtyA20ihvOfWiLPnbz9oNrHPtA+9olYTl2yUNq9dMMiREZ4YSIvN383KZuVWY7gSclgCI712M709avl2NFO2sI8tQ37tinP5OTlDdpJm4g/Zdk/XgdGL19ZFhPjB9pqP57z5kbKcacONbF+zMwk2R+2T1ylbSNjtOD5TbJs+ZrZ8Pd0UKuBWG36+npZNj11MpzRL8sC/L0wfXKAPOb1RfvV8aeN1E072UdVN69bti37oyiyrrZ5OAjQC3O7luilyRHhrEsiLHY1L0+G5tQ6LLsiJluGjvyFl4Tn3ffhn2qq/nvZq31T96ou+3N6gHbu3AGG/lasWAF6SkhCVNmHvVfJjX27tJf4kvDa53Nhuf352GOz2RULFizAunXrRL+eAb1QgYFBY8UmfM72z5w5g3fffVd6qZ5++mmEhobK+sSRJFSeiA37QSLJvTi96buvr1+GOSkwPDzEnfQMygNt88Qg8FgRLbMI3yzZsgIhASbUV9bBOSIRG15dDRIOQ7Avpi1MgrebTpb5JqVgxdpZIPmYvmI+5olJlnUGnL2x8tmFCPZ3hY9XGGYuSoKPpyOqm/rhHz8FiVODZP2W6lbM2LgS06f4o038MqxutKBTuG1rq5vk4MdPj4VnmDvsbSovLIcpMBTPfW+D1O8eFCRtUu11S5yJDS/MhtFRj/i58zBzSpBsq9c5CItXp8LF2fpLlA0MDTshICIQ8bF+MAjPk8/0BZg9PwYu6EZHawdiUucicbL1S2Py0gXw93YU3hYPTE6KhcnZAR7RiVj/wjKYHIdAu3T+cVj97DJ4ezpRvUw9Te1wE79256ZGSZsiJoUgIsoNPTonLNm8EnMmucq6xGzF04vFr04/RCxbiGXLp2CwtQ6dLb3w9TNJXbfcCNISOTkebkOtOLfjIK61GpAyJ0CSQ0dnb0QlJWDyZG9QJ/VMXbxk1HixbY4Xy9TkERmO2MRoif+k+UmYt2aexMDNJwDR08LBX6oc90WzfCTGVU09mP70aqQkWjFT9XD8Vm+cK9vmmAenLkTSrMkwmZ2wSJCs+dN9ZX2LQN7X2yirOfsFYcNLS+HvOizxGXZ0h6Obtcw9KBhxKZFQHBwgr69lM+Etrkm2H52SIkOPDo4GzH5+PeZOcpS6ie+UOQnwcHSQ+rXNw0NgIh6twcEhSa7oxWLIZ6x19J6wTPVc9PX1YXh4eKzYQzl3cNDL0FR7RwdImEj86HWhx+XEiRPCw+KD4OAQmy0kCDU1NQgS31UR4kcsF7R3d9/7LQ1sDdzigO0wvEbP25UrucJT1g1/P/9RNWgPvUhN4rv3Su4VMAx5Mv0kkpKSpMeHwk1NjTK/qKgIDJUmJMSDD/yOi4sFSRpDjREREfD08ATxYZ27SdTF8DC9SbSJtvUJokRdYWFh0h6uCyPWXDt26NAh0HtHskUS1tjYBOJNeSaSPn9/P7lujhjk5+ejpqZWjpujoxNFxk0ML3KRP8nnuAJa5peDwC1a1d2i7NEqEpN1QGQEvJyHkLF3P04fOIWju87ANSwS8XHWSa6lqhG5x44j/cAZZKRVITghBEHeznIidxjskP3p7umFzjMQAUHWL8L+xhKkfXEUORfzUXutBGVXitFj6UVHVzs4uYYEu6OlphI1tS2or21FWWmd1KNuVJvOHj6DzBMXsOv3aej3jkNctPULgzaxjDblZxbCS0zEww7Osjpt0vV2oDgjA2eOXpR5t9o0FOch7fNTOHf6KppbOqA4mlFbUooKi6ucwN18AuDtCpSVVCMoKgKKpQnHdx7DheMZOHX4Avq9whA7YhfbGRxoRdapIvjGxiEg0Bf+gUJfcTmGXPwxZZofLOKLgXL6jm44uAXAxS8E8dHhaCs+iSN7z+LU0ZPIuVRPkZsnMW4GkxmRcWFoLK0VGNaj8GIdIqbNAQmyWjHrwDns3X4atT2OSJ4Xg+HOJjkOHC/noBDhARMdGxFm6La6ug7ObmYQfzeHNlwT5G3q5DAEhvpisLMFrf3Wce+39IEvF+GK79F5IDzWVxI85jH19fYh53QemjqB/qFeDAi5kBAv+IpfqvHhBlzYcQjp+9Nxam8aSorbWEW26efSj5M79skxz0o7jdZ26/UkBew2ltpSnOX1uCsLJRXtCIl3lYR45tQIXD190nodn81BdW2XXS3t8GEhwMnzXttSFOVeVdyX+jq9HomJiSJ0VoTz58/L9VpTpiSKify4XAuUnX0JL7zwgiRbaoMGEc5KET8AmgSReeutt+QCboPBASQRTAzrqWTUQZA4Ly9vUaZXq8u9QejwF948ynGtmoeHu23dk9lsBhMF9XqdDKuRBPGc5CNDfPd98MEHOH78hCRP4SIKwJCZh4eH+JwCetGnqVOnITY2Ftt37JD9qK9vkP3Q63SSuNTV1UuP3HvvvS/achXepvlwcnICPU5lZeWyDv+NmZObI+QHhcx1m2iHfVIUReLDPjGfetgfvbBdJ9pLmZkidAwInR/gyJGjFJGJRHXTpk04Icgs111xEb+rq6u0I1R8lxgMRhw6dFCE/rrh7u4uiaC3lye4Ri0vLx/0ku3bt1+Q4CBMnz4dRqNRrm/T6x2kftrj6mqWuGZlZSEt7SgYspaF2uaRR0D3yFtoZ+BwrxtITprEpMZ/2bQ31koy5OYcYJPq7DUCw4Pobu9G37ALnF2dxYfb+uvA2ewCt+FO5KTnoFN4sNRKvb298qJ1F7/qwidHITDEF56+nmoxjLoh2/HYA2dnR2mTpcMC2tTVUStFvEY8PX39g+jqFV9MwiaLRYHeyRX9XZ0oz8zA1YJmBCdOxqylKYL4eeNOX/Rc9TTXS+ISP3866JGSJKOxVXiujOho70VH94BU29PRjK5BvfR2yYyRTcG5y4CnN5JnRMDVyREkaa6C7DjqHaUEcVAcLCi8XIDWMgUmXT+6W4bQ2zckvnAAEiEpeLON6LdncDh8owLh7u+FWQvmwMNjCMHRYUiI8JG1HAe60N0/IFzowzA6GmE2OYEvts3xunL6CmoaO5glE79gmitroffwQ8rsSHRcKQIJIzEIDA9Ec20DWtqFrfpBKc9xd3DRo+ZiJvIKm2WeumF74TNiERJkhpQb+SXp4OICRdGh3WIdT8p3DRm4A6/DwZ52qNehZYTMycJxNvL6EtddT2+/LHUUXjxXswkN9c3ymnFq7ZX52ubhI8DJ83atcpLl5MikkgT7Om5ubnLytFh6QOJmFMRDURR7kYdyrBekZOXKleCi6ogI8aPUywvr1q7F+vXr5KJwLlBfsngxKKcaxOM5c+bg61//OhYuXAAuBuei89TUVOnlIlnh2iFFUcA1V9/97ncEAfBSq8s9vTvf+ta34OYqfvBNnYqNGzeKz7BJtrNWtL9q1SoQZ+LEstmzZ7Oe9ABxfRLXjm3dukXaShkSK7brKMgSBX19fSQhWb16FSj/9a+/Cq6FUgTxIRkMCwsF7X3qqRV47bVvgH1nv2bPmiXPWYdhUdrh4uIM7mkXdY9Njo6O+P73vw96qBRFQXJyMlavXg3apSgKJk1KkIv6Fy9eJIjcZvzkJ38pvPGJIDFas2YNnnvuOYk1Sdf8+fPh7OyMyMhI/PjHfyaJJDGkLXPnzoWDuE74pwXazHP2b8uWLSBp9fT0ADH18fGGoijSHmISLLyRkyZNkm3o9GJeGdsB7fyRROCxIlqKYzt6Xczw8PGQYLoJD45Z3wP7yVAWiI2Lmws4GZIAdXT0gN6ZC4dO4OjO4zhz5BwKqq2TsBCVb3pdohIi4NJZgwsHjkpPQ2dXjyy71cZi6cWA3hXOrs5SzOQaADdDH5rrb+6hYFgqIDoSjUUFOPTZQVzOr8P05XNFCNMkddzJZnhgAKcvXYBPbDymCsJQKzxSja19aGrpg6ubI1xdHKQ6J1cv+LhY0GUZkOfqpqP2GkpqFCSmJsHY14FWQdIaBzvRO9iLuuoiiQMxSz94FuVNBSDZcPG0XjYiOqaquemea6BIAM26TrS0dcNBEJ6B1lrpgYqYHA1Hk2FUXXqYiHtrZamtbY5XdZNdOEOQt4ZaCwZ1zkiI8UBTVQ3KcvPgFR2L4HBvNFfXYKBzUBJL6uG40wPKPhQVVoGEWG00MmEuooOM0ut0Mi0bVWVNsmiwrQVt/U5wsyPxJkEyWcjrUO/kBn4p89zZ2cjdhJOutw4dnV3w9fOCTnyJTriiJnjfESAxup1SjjMnNyb+q4+ES63jIgh5nPC2KIqCxsYGmEwmME8tf9h7T09P6dHhPyFJNtw9PKSHhGSDeQbjjdcqvTaTJ0/GkiVLMGXKFEEcJktyQHLBOvSksB/OgjTMnDkTlOe5mtgmvTAGo1F4g3zBOgajURIE4sWkKIr8vNAzRe8PiRdJEsObJCTUS1sVRUFAgL/UwXK2wX74+vrKf/tRlsRFLWO52ewKLoJnWXh4uCR4zDcYjdITxvxZgnRxwTx10R4myoxNLKct7DvL2C5t5jXAc4PRKG0jnsSK/aa9iqJIUsU8lhFP9TqgrWyfeokl22a/FUWBwWi1kXUoo9rI9qhb1UF7iCvrsy7DobSVNmnp0UdA9+ibOGKhmFwZJmtr1WPF04uxYutT4DqZ1pJruJDZKYX8IgKwZPNSWfbUpjBU5FagvLodV9Oz4ZM8HavXzsGSNavwzJ9sQVyQXtZRN/2WYelEHhDfAAAQAElEQVSd8Y2Pw8yVS7H+Oy8hOtBKfPqGrDD5RkaD66KMwuui1qNNzRadtGnJmmV44cdrwHDR+exyVeSGfd+wAzz9IpC64SlMmZ6EyOgQSQp7e+/Os9GfdwWVzQNgOCvv0jX0DwyBnqpuQRI2vbwG81fNl1gN1NTial7VKHuGBvpQcTkPRg8vkKTVNfWiraYK5/JbMf/pZ7FwQbzEbP23VyMmxBmZ2YLQTFmMZ55diLlbN2GxKKdCnckDi156FisXxcHgYMWL+fzjAPtXez4bB7Ydw/Hdx8T+MNKOX4KHIEZeUQaK2VJPcxPonYpYugLLVyaD4/W111bIELBNSBx0t1ajrbUbFssgKurb0XgtD9WtQxKDa4XVsHSWoljYGrZ4GRaumClvlfH8j7YiOSlM1L7+bmwuh8HdH3NWzhXXzkqkzo+Sha2tbdJTuOzVTdi4dT6WbX4KcfE+soz/LCzpcALX4nHM5z67VrYrCyew6eroxMmDOZi1dgOWbVmB1c8vRGS4l6zpGxGJ7/31t8A/VMgMdaPtHwgCnPBvp1gvPAec8Ji8hJeIHhyVbBnFRCkYBYoKi8S1aJFeIHoqbqfzq17u4eGBxYsXS2J6t1goigISjhkzpsNBjNHd6tHqaQg8aASuz4gPuqX7oL+9pgZ7P9iD7PIh8J5WDdkZePc/t6N/UJHa+Zdky6BRlhUcP4t9e85K78XltBPY9v5pDHsFwuzlgDMfH0B+eS84yWaeKrSG1wbbcW7fMRw+WQqzpzt01fnY9km69EzRa5R/6gJKcmphFl8Q9LpwvVVLeRvaqyulTQwDBiUEo/tqFn77L5+K0FU/uIj+2qUy4b2wSPtayotw9eQl9He24cz+nbiQUw3WQXMZPv6vnahpvO5B0yk9qM6/hvzCevSLsFpj5kkUXmmCRafA0t4h15KVVndJvSRLxz4/jszDZ1BVZw2xtVUVYNcbO1HXoSB8chSI1Udv7EWzCMHVltZIvSqBLLmSj/S9Z0GSJr09AovTb3+Gbbty4ZWQCKMrcHl3OoqK6lFz/AR2fHxOYuntNIj9+y/iWm4xBgVJHGysBkOA0qiRDUlpU2kJsjLz0SZCmX09fWCqy8hC4dUyGJv6cFUQ4qaWbmsNQaizDuzH3s8vwiUgVIQgunBiz/V+WYUAhl+Lsq/IPleUN8rQr4pBo/DoEZOMXYfwxYdnpZ7IADNydh3G2fOlqgpA0aMq+wI+fPMoFBdPuA814MTu06isbAb6upG+41OJAe0YEF640/vPg3+G6GtuwJ7ffoxLJUBAlB86C6/K66a2uUeMeRV4TQ0LTyOvr7zMEuv1BaCmrAYFOS1gGfu46+A1ea32WvrRKoidEIGDuw/cAz15qKWHgMBEPFr2ZpB0kSSQbJnNZnR2dCArKwv9A/2IiYmBq6ur4F3W7yP7etrxaATo1Xr11VdlOHJ0ycTPOBYMufFfhQajceIVNUkNgYeMwGNFtCAmYRKb4+99gg9//SF2fJYuwlHXyUlPczfO7tzPslFlnHQL0k/K/I/++2NkZZeJL8YhVGWdk3Kd6jqmpnqc+2KPlPvgg2Py+MCJa1K2rqQYuz/ehgP7MsGJljacH1kYT5sObTuC9//9HbBeS5uwSdjKOml7j6ClQUzcYmCLMi7KcnGInpG2WOejN/aDnjedcv0LmjYXXcjGibRLoH2FO3Zh396L0hYStfT96cjLzpfn1Mf+qeU8J1Zs//Pfb5N2qVhRL2Wpl4SHstJ+EcIsrWrjqUxsg1jQPupQMVPrE3/mUyb92GUMdrXLPyGcPGPFVioRG1X31bxaSXpFlnyr+ZfOXZY425ez7exDh+U4EBu1bVlR3Qh8iSf7THzYX/aL5/ToUYy2Fp1Kt+oR437qTIkNL5azDpN9W4cEDtTBMaQd58T18PF/foQ9H+yTYV7aQjJK+/f9/l2pe9f7e2UfaivqUHolT15TtGHU9SXIK9s5ebpY2uAXEw9jXZ7UWVJQjs7ODrT2Dsg/MTRmZaK5pl2aqG0eLAIT8WiNtUBRFEkQ6N0yGI2Ijo4BF6GTgCnK9c/w2HrauYaAhsBXE4HHi2jdbIzEpIvmDuGteQCTE3XbtctJlskuy3o4Rs6aOfEtdTKNqnGPOkfpeoAntJuJpEWmB9jWnaqWdo1Usj8eyZrQjvWYJiQ8QSGTyYiY2YuwfPNyTE8MRfXFKyiv6kDRiUP47OOTaB8anqAmTexeELhTj5Z9W/SoMJzINTpOTk6aJ8seHO14HAS0rK8qAk8G0RKjV1+Uj2O7j6GxxRpOE1naW0PgkUWA3rdtnxzCucPncWTHQXm7jK6OLun9pDftkTX8CTPsbjxaTxgEWnc0BDQEHjACTwzRYpiHoRsZRnrAoGnqNQTuBwKdNVUoKypFeUmVDA/fD51Pko6H0Zd78Wg9DPu0NjQENAQefwSeGKL1+A+F1oOvGgIMRzJ91fr9KPVX82g9SqOh2aIh8GQioBGtJ2ZctY5oCGgI3CkCmkfrThHT5DUENATuFAGNaN0pYpq8hoCGwBODgObRemKGUuvIo4iAZpNE4IknWjoHI4xOX849Vni7BiaJ9CO2IS72NxYdZZ6in9Ady4nrTXUIhez7rcqFyJf3Fn2k/bSRRtzWTiGvylLePtljSRkm+3Lt+NFFQPNoPbpjo1mmIfCkIKB7Ujpys34YEiZjztwEuOnGub+NmDztJ9ub6biTfOpTJ22jly/ipsXB093pTlQ8cFkSg6jkKUhMDLUSKjscWBYxKRZhQW63tMNgdsekBQsR7O96UzlzYDCiE2NhHnkM0E0Fv4QCt8BAzFo8C3ywtezLjMSbj5PAh/Icy7F9IV5hcVGYJOpTT9ik+Ntid6vu8voJiwxGZGwkAkL9H0nsbmX/41b2iHm0Hjf4NHs1BDQEJoDAE0+0QlKmYdmGGeNCwclz3tIFcrIdV+AuMpNXr5AEBmJydnczIyQmDO5mx7vQ9OCq6J2cETQ7GSmzY2UjxEElHSzzi4tCXLS/lYRJiTEb0Te9oyNmr54j5caUWk+FjKtfkOy/weBgzXtUtsK2Xi8fzF41E8HeCpzdXBEWE3LTcdLp9fDyMCMgKNj27EiMvBxE18KmT8WMWdFw0RlA7Dx8PG6O3Ui98XYkbSSv615agzkr52DZMysxffZkGOweaTRePS3v7hHQPFp3j51WU0NAQ2BiCOgmJvboSJlcTYiYnICEpHjweXA6RXiq9G4yT/UcOXn7IUx4BdQJqm/YBVFTw2QdegmY7xYUguSlqVj49FxMmR4HT18vWYeeBOqmLk58/pFRsh7z7b0ZbINyTHwcED0RtGv+qrmYu3QGwiIC0NfZivqKWvAZhtRPHePpU9uZNnuq9GTQduqUfRsLvSAJtJ26mNg+caA3hcdMal3aSBn2FyP1qNuoXH+wtKurt8Qhde0ciYPZWY/mylr5/EA2TXtZh32jbokLhlhkS5RRcWUmZQNCfDDQ1ij7z0cI0WbqoT3sJ4+lXaICbWc+9TOf9dmOKBr/PdKXBHENsI5NduQ6oK5JCQE3eIPUMUqYFoOwqBCo3gw+UqmmskG2xfY5VjzhuNCWMH9nNLd2ormpwfo4Hbv2o+Ij4eJkJdIDwxb0VFeguV3gqzdA1hXXIfeqneqYss/MY6K9bNfo7oHIuDBUXb2KswfOorK+B4nJ0fDxMEJ7PRgE1GvgwWjXtGoIaAhoCACPFdEicVj43NNY8tRczFg2G8tf3oL4eH/oFDMWP70Y8XFiQhKToHfSVKQumQKzSZyLUXbzD0TykqWyzroX10qPk5OrFwIDPGE0GODp7Qr/IF8krZ6Pzd/ciPmr5yEg0AMp61dg/XOLkZSahGVblmDB4mkg2SJp2PSNzViydDKSF0zH+q0LwQk3ONQbTo6ucPMxwUMQN3dfP4TPnAR6OMKSpmP9t9dg+eb5Nn3JSWHSWxEzZzZWv/iUCD9NQur6Bdj42iakTA+HXq8I60e/dXo9IhPmYt0ra6TXI2nFYqz/7kt49tsbQVtmCFxoD0N/3qERWP/MbDlR6/R6uCbES1ycTddDmY6BQQjxc4Kz0QUhgZ4wmj0QkyT6FRYs6JQOszavgfSwLJqGOeuXYOtzC+DvbSUWtExnMiMgOhKLVyRb23EIwvIXVmFapDvcvBOkp8dVhA4TZk+T/Vq8Mkn2kzoZuiThmL5iPogvcV764nqsf2GZxB/jvEhUgpNmYs3X1sr+zl2Sik0vr0agjxNMrgF46ptbJDbzF06Bj6fJpoGkid7GNVsWSPwXpUTD12yQ5cMCg+TUqXKc/KfPx5yUCDnOJD7UF+jjCmI3KTFIerT84hLx9GvrMHfBJBDz5BmBUo9REC6Od3i4tzj3kTiwn3OXJkvsVgsyq4YqV337ZSzdsFDW51iuXDEJZsMgzuzcI29eWlLcBIvlxvEXirX3fURA82jdRzA1VRoCGgIYDwLdeJmPap6bTwCCxSR2Lfsidn10FFWN/Qj1c5Pm+vqZ5J4bF7MzPN1d4GSdR9HfXo+z+/fh8BfpaOqADJn1N1ci88wVdHR2ojD3GqobuuDi4oGO4lwc/PgAKsob4WQyIf/4MRz47BAu59chIj5cTt70hCUE9WHfJ0dwdM85NA0ZERFkwpWLV9HT24GK3ArkXcpHv9ENXl6eNAmOInzoa9Ijc+9BYcdhaXtwQiycRXht+tzJMNRfk+0c2pMNCwzwMI3/CJahYScYPXRQLE3IPpyGtG2H0Cvs9nbqA5/Td+5ELpwEaQwJ84aLgw+8fJxl+9youJj1wuPCDJFay/KQca5E3pE8KzMfbe2dcHBzFyWATq+H2c0R/XWl0uZDuzNhik9AdGyQLOdmqKtTEIJeuIYHwcPHA4FTQhDuPYSCa3VwcXOBq6jvKMKMLi6BIrTWjrOHz8h+tujdMGlyBILDApE8MxBVl7Jl/um0XJi9TWAd6h+b9CY3zJqXCNf2Ypz5Yi/27LsIvX84lsxIlKK+piE0XjqNL3ZmoqpODLbMBcx+fkhakCy9RRzP4xnX0No7Uih2bv6uMLT1oK+9CQFRYXKcSdijPfpRWtUoJCCvKdo1Y8E0uA21Iu2Lo9jz+UmUFLfJcr0gxi4uHjA5O8hzN19viR3HJetsETyiYyWB9JudggWJLkj7dJesX1TWDgeTaH+gC/Kmu5ZhxM2dhjnJPii+mIvG1j6pT9vcfwQ0j9b9x1TTqCGgITAaAd3o00f7rKejGV2DeqSsWoolqeG4cuQojp4quq3Rgz0dqCqoQ0NFJUryOuDspgB93Rjq7Ya+1wJLh0Xq0A9ZkF9Yj5qKGnmn7qyjp2GePA8bv/Ms5s+JhX+oOxQXLwTFhKIi77KYgNtQV1qGk58ewtmMUnS2tKKzqwfD/e3o6x2UOu03tIMPT25v7UBzUzOcXZzhF+QHXz+9IDuFkuy0VJWhqXYCz2zsa0ZrYyuaG5rQ0dGDhsICNNc1o6OpFf2DLnAxkCKRogAAEABJREFUWCd7+/bHOx7o7Zc4sKyrV4/BXjv2wUyROlua0NbYgpqcStTW9CEk2F3kXn/XlpQKGwwIjwxC9LwpaCjOG0VyVElLS50ksC2NbagtbINJeJTcg4Lh2N2JspJq2X/qGhi4ETtVh9HBH94BbijPL5f41xeVoqqsCT5TvaRIb28PSsuuobG2CXyws8wUG3ow3Ry6UZx5UbZTXlwpQ7qiaNS7pkKEEB08QNI4KyFMELMs1LUO2WT0vaHwCPGTePNB4D3N9aipbbGVjz2oqy6StjQ2dqCvf1ASyNiACDTX1oDXQmd9Pa41tKKnf9hWlWvmFj+9SBLGUxnFo/phE9IO7gsCmkfrvsB4D0q0qhoCTz4Cusepi5zUjr79Bc6lZcAzYQpe+PELmDMrAg/ixVDT8z9+FRGuXcg8eAoXcqphsVz3BNnaHB5EV0enTIOD1ydLW/mXfMD1aQ/aBEt7hyQbAXHTMDveA/nny9A/KMjsmIa72pvH5AAOfVZv0A0FN8lwMOtHleiUHuu50Uq0rCd3v21vrEWTIOGRKTMRHmVCxqGrd6/sNjUZBh1PhKRwuLMGZ04XS8I/noyWd38Q0Dxa9wdHTYuGgIbAzRHQ3bzoEStR9PAIT8C8ZcloFh6Lz9/YjbLSDsRN8ZSGtvU7CS9EDHz8PRDo6gyDsxHqS+/kiuA4f/iGhiAywRWWdishsgw4YNDRGc5CHje8fGA2OaGqMBPV5dW20uHuZlQXVcAnfBK4CD0g1B+L1i0GbyHh4GiQcmZPb+GtcZLHt9vQA9VQPyjDaFyE7RkcDnpsWM/o7Cz/4m90ut4X5k80dQ80yv5FBIu++PkhUHhixqtLHJjv5eYAvQjz8dg+sT/uPp4yLOjr7oDKqtHkqF+ED2tLa+AT5QU3h35cvlJuX/2Wx11tHbA4usAnwA/sPz18RqO1vwazu8j3luvYMPLqbq2WHj/P6EhZ5hOdAIaTGy8UjUiMs1P06BHe0FYx7iHxk2S9hABvOI7T157mJpQXNiF6WgQce1qRe7lqlMJBxwq0VtYLr1aEvI2DZ2AIAgM8R8nc6qRXeAwLa0vhFRAIri9kSDPa10OEua8T05aqMpz8/NS4D0i/lW6t7M4R+Kp5tIaHh9HW1oampia0t7eD53eO2oOtYbFY0NbaioaGBvT33d+wOfXV1tZhcPDmXvMH0Ttizv50iB/lKua0gXm06X62OTAwIPHjGHd1dt4X1bSR+qqrq9HV1TVKJ7/TOF5qv0YV3uEJMaF+tkWdPL9DFTeI0y7iwHFvaWmRY0+97AvzOAbMZx9vqHyfMh4foiU8R5wsB4wOSFq+BMvXzIZZTOpXz9UJKBqRn1mIyJkzsFCQnsgIL/Rb+kQ4BtA1NwtP1KCss2RVCrxdIcN0nV196BThnKaWAcQmRiPI14SOHvuwWSMuXC5FyPQVNp2Wrn7RFsCQYlmLC5ZsXorUlfMREmAS4aF6DIgwXH5xLQz+EZg+xR+GvnY0N1vDSr2dvWhutIYoxecAPLd0W9DXXC3Xipnio7By/SwsWzEZvt5WohEYH4+nXlkONw9htGzZuukToaz6Zp3sX79lGJ3tvVDarUNp6e2DpaUZ3f0D6CwulmQ0Ze18iVdsgCsGujrQOegACILDkCA18t+BHb2DkuwFepkw0H6dSA0ZQ+EbHycxWLw0Hp111bhWaCWeHSJk2dHWDYixqRXhw8pmoDzrKpo6h6gW3e3d6BC28YPYJcK3MnNkw/Ouzn7UVTfgUlYd4ubMxJKNSzB/1Szo4YAhRzdMnpuCzRumw8fDigerktSdP5ULvYeftGnF2iQM1pUh7WIui8UXzHXbZQY3wj6G6C5fvH6NJCRFQ7F0obPXqrtDeOUoyr6U5lWjob4L5Vm5aB+yknKWtYi+si8XT16CxeQnx3+eIP5md2dwLAeFR7O7uxVdI57PdhHWZT2mfksPujqt49+UfRlnLjZixdOL5biETgqjiC25eATJBfuuLmKcbLnawYNA4Kvm0aqpqcHBgweRk5ODQ4cOoa6u/pEiW5zsTp8+jZzcXBw5cgQnTp6UE+P9GHtOrufOn8f58+dAMnI/dE5ER4uY3C9cuICCggJkZl5EY2OjrDYkyF5WVhbSjh27b/YMCyKdl5eHk+np4H77jh3ie+feyBZxyxe2Z2dn48yZM9i+fTu6u7tlH4hjRkYGjqalYaDfOj/KgrvctAqCffbsWbAt2l5VZZ1r7lKdrNYuflicPXcOFy5kYOfOnSgvL0ePIPNvvfUW3nvvXZHew969e9Ek5mriJyvd5411dr7PSh+EOoZZOmuqcGz7KVw5n4trlwtxavteZORWY2igD+f2HUP6gbMy/+yuNOzfnYXOrj7UZWTh83cO48zRLFy9eFUudL+SXwOu3+movYbDH+5HQVEjGusakXPoPK7mVYkP9rBV50e7Ruk8uCdLehnaqyux94M9uHj+mmxv347TKCqqx5C4yLO+OCDrlNf2oqXSqrO2phUlV/LB+sSGH7CqnCycTstBV+8QaktKcW5PBq6KvlQIb1lDUx9auxSYPDxhEmRs0GL3C2KoCyV5Z2RdkkWGznL2H8bp3CLZ/mBHC07vOinJUEdHk7Tz2OEr0s70z/bhgAiF9QgilX/qggxN0WauXTv2+TFkXqlFa2sbMo+csuoTXwS6vgo05BfI+jnpWdj12QnUNfWir60VZz7Zg9KRheLs17D49ZSXU4xhMklBbuqqL+HYgWxJvMozM8QXey16+4YkMeN5+pkiGXIty87D+aMZso2ruRXoHbASEqObt/iS6JeEkvplEnprBHaHv0iX8hePnLPZ1NVRC3qC8gv6pKj9htdI5qF07N0msBHXTvahY/K6aGzpwlBpiaxX1NImq1gar+H4xwdwLM0aNuR4kRydO1kgb+9QX5CLfe8flON/NSNXXkNyLMWv1ZyRawhoBPHOOFsrddJLxVs28FogdjnnssFxKS8sR0NxjejjsEhSFL38o8PpbNmWNUfbPigEnkSPFicLTo7cj8WtsaERJFtubm7Izb2CUnHtj5X5Ms/7hAersLAQ7u7ucg3l/v37wc/fvdpELKg3XRCQadOmjfJm3wyre22T9dnulStXUFlZicjISNmnmuoaFsFgNGLSpEmCvJyVxIKysuAeN0VFRbKdgIAAED8SiHtROSC+z4kbdSQlJeHw4cMoKiySBL2+vl4Q1/Ogd4hzCWXuJdHLSqw4/hcvXkRFRfm9qJM2Vgkv3KVLlyT+tbW1gnBdQIsgdP7+/khISAA/C3q9Hs7OTlAU5Z7au1nlx4ZocRCZ2gXJuXTuMpi4mJiEiZ3raaqXeczPy85HSWGJJFOU53nplTxZXllajb4e60TMyZf5LOfiadbhnu2Mp5Nynd0DLAL1si0m/lNMtUPNLy+pQlt7o7Sjpa1HyrO+rCzIAtuhDBfNR06Ol7c8cPV0g2tIJJzRLxeH9zZUCoJ4ESRUsh43oi7bYF22qfahtMpKEro6BBETfa9p6pfEi7K0kYntsx77UFdSjNLqTmqEqoPlLQ3NkGUj+ihAz9dV4TGiDtpNfNQ6bIf30Zq3Zgk8BxtQWd4kcWc9tk1MiTd1sm3azDL1fNjBGeFJCeCtE7y8fREZHQJLdSXqa+rRUl4E/hNyVP9FZbbN+rSHNqs2YbAdPCfeQuyGd39nGzjeaj3KEgvm81itR3tLisrBvkklAnNeX+wL5SHO1fYLLhVIneybrCewl/YI8k+dNY09UsVgV7vtWjC6e0jPXUSoGzx9PYVH1Bm1xeXg/cYozLZYV7bFDC09MASeNI8Wwy6HhKfq008/BT0PZWVl4ofj9TBZZFQUli5dKjxZdXBxcUZQUPADw/ZuFDs5O2P16tXguJSVlWPWrFnQ6fV3o2pUnZ6eHuzevRtxcXEICQmRZf2C1JEEff755/j444/lBEzSJQvv00ZRFHh7ewuPyT7ZRkdHB3x8fWzaAwMDMX/+PFnGkKmt4C4PFEXB3LmpmDx5siRvMTGx8PSc+NKG8Zp1cHBAqtBJ7Dw8PKT3bXBoEN0ihKiSdicnp/Gq3nEeyc/8+fNBnDw8PBEgyOIdK7GroCgKqHPx4sVyT0LFMXZ1dcXWLVsEVnMRHR2NxYuXSMJlV/W+Huruq7bHQBlJwqNmZn7mZVQKYubp7YaB1jqc/Gy39JAV5JaIX50VNuJyR3YLMnBb+QnIXMgsQF5hs/iyvh5Cs9er0+sxbDRLu88cvTjuvw3t5cceMxRIj1ZdbT/Mno6wlOZi59v70FTTgOKsHImDSs7G1n2g58SG6TaNTPR6sskpeukNpAeR4VEnRwdkHzmJs6euaAvfb4P1gyh+kjxaJA4MhxQXFyM1dR649uSXv/wlrl27ZoPO1dWM0NBQee4sSI1Od2+/4DlpnRfhuPfff1+GJLkWSSq/yw0nQhIhrp90dDSO8jzdpUpZjRhUVFRg6tSpYBv0Hl29moddu3aBniZfX1/867/+G46JMB7LZKX7tCHRio+Px5UrV6U3iGRYVU1bZs6ciZaWVly+fFnNvqe9v7+fJHcGg0GS6XscYolX4pRESXqIT0pKiiSstXV1ICH2F54h3KeXi4uLbMdJEDeOP/Xfq2ovLy/Qi0lSyGt+xowZklSZBdmi948E11eQX0W5t8/CrezU3apQK3sICIjJnB6M9ANnsP/j/Ti2/TAuXSqX5Iqemy+FZKjdFraV7tkj7bERBbVsZE8bGwsuj7J7pGhiO9EGvUNpIvTL/u/dfhr0zrHf1M39xBQ9JlKiv+xX6dVC7PrggBzz9GOXoXrTHpNePEwzH2hb9+OL/IEaeAfKW9vacOLESaSlHRO/3v0QERGBgoJC5Ofnix9Kg1ITPVwM9yQnTwcnmOPHj9/12hqSrN/97nf41a9+Jdv54osv8A//8A9yob1s7C42XPtDe/38/KXn7f33P0BVVfVdaLpehQSUYSgSAk66LKHtRdeK5DowkkOGkPr7+7Bjxw4bVpRTE+WZ1HN1T1LGfO7VPPs9w27btm3DK6+8jL//+/8HJFW0hXVUObPZjPj4OHBtGm1V8+9mT73Ej3UXLVwoQm8V92WdGz8nFy5cAMnbq6+8IkOFXJvFdP58hpgjLsnE9tn23SRiyEXwVVVV0iPHP0WRCBPDu9FnX6dOkEKGJFesWAFXVzfwB1Z/fz/OnTsnzl0lmbSXv9/HGtG634jerT4xAZNUMN2M1Nyt6nupNxF7aO9E5G5ph13/byn3pBSK/jIEec+4PSl4fEn94Bful9T0fW+WIaIf/eiH+PGP/0yShebmZphMJvj5+UnPA8SLYTImi6UbXA9FD4LIvuHNyY3/kCMJURPDb/aC1H/16lX84Ac/wN/+7f/Bn/zJn8h2uRaKk6a9LCfgzMxM/FJ42Ej27Mvsj0tLS/Huu+8JglAuw0dGowGccO1l1OOuzk6otnFPTxHbUcvVPfvJydvHx8fmIaMnaRx0fAMAABAASURBVO7cufibv/kb6eViXzqFvsTExHHX6VD3e++9B9qu9o0YXb50GXvEj9Gx2Khtc0+beJ25CA8iQ3q+wnvGfDWRxDB8Rdy6Ldb1qWqZ/Z5tEz96EKnTvkw95iLvt99+B1y0bunpBckEx5htqDLqnn/sIW5q4voo9kktV/fsLwkVSQmJ1kERmqbssmXLsGTJEnF9+QoPmo8g9wG260ytq+6p46OPPpLjfzMySYzo1fvss8/AtVTd3RZ5/SrKjZ4m2jn2+rQI7NiO2qa659gynM4fGDk5OcKzmAuu++OY0tNJ75kq+6D2GtF6UMh+WXq1djUENAQmjMB4E9CEKz9iglxLM2fOHERFRckFypyQly1bKhdcK4p1slq3bh3Cw8Oll4tyXA9jMBpH9YSTeEFBAf7rv/5TeqjopWLivxXtBT3c3fFnf/Zn0nNGgsRkNDrCw8PDXkwuSObE1t3dLcOZnODZxniTIm1btGihnGg5Cb7++uvwFWGdUQpHTt56++1R9r0vwpecVEeKbTuSF3pKSEQNDg4yX1EUBAUFgWEkhlj5bzR6tbZs2TIuWXAVYabU1FTs27cPDDexL1dyr+Bq3lVMnz4dN5usSejWr98gvVUXLl6U5FENX0pDxEZRFNFHX/kPda5NElmj3sSJeBE32kqCQDyZP0pQnHCN28aNG8QRcOFCBji+DPUpinX8ZYHYsC7JE8dVTT/72b8LglshSke/+W9CkryamlocPXoUOTm5CAsLg5W4Osm+M8xXUzO+55G2k0S1trbK8R8YHJSEnDbYt0SsuA5sypQpIOkMDg4C1+sx316Ox7TnV7/6pW38/+mf/hl79+6VfwJguZrYBkkh1/vl5uaC/2jkWOr0ejiIxD8jjL1e1br3c68RrfuJpqZLQ0BD4LFCgBPAY2XwBIzlhExiYTa7ypBIt/AMcMJh1djYWGzevBkkDVu3bpUTPPPtE8lncHAw1q5dixdeeMGWSCjs5QxGI0iMGJKhF2rbts8FyXJHaEiIzSvEdun1+uTTT0WY7qiYQIukB4hetbq6ent18pgeuKeeekqG2F566SUsFOGv8SZaCjMMZG8fvSucRFlmnyyWHhkmdXR0hKIbPeXR49PS0iK9Zt7ePvJPAuNdE4qiICYmBvTiMMRHwsHQI0kMF7QrimLfpO1YURSEhobgawLHpGnTZDjUd4xHi8Ikav0idEmvDM/tE8kj/9hAz1lhYREYGiae9KYRX3tZYkWyTTsXLFiAr33ta6BHy16Gx4qiyHVW9vhtefpp+I1jm8FoxDPPPCNIzd/jn/7pn/DTn/6tvG4URRGEKxTf/OY38ZOf/ARsV1FG40BP34kTJ0BvFv/5R/s/+eQTuRaOxIu22CeS39WrVslxf+XllyUZti9XjwP8/bFhwwbbtfnss88gJWWWDG2qMtwriiLX4P3N3/y1tJ328w8WxMnN3R2vvvoqIiIiKPpA0+ir7oE2pSnXENAQ0BB4tBAgqXi0LLp7a+g5aBNeA18RItu0aROeemoFDh48JCa1NNsvfXq5SBQYxjt58qT8hc/Q0dhW29raQQ8Aw0VqIqEaK8dzejfWrl2DlSufkuuzCgoLpReLZUz0wNTU1IiyRvC4vr4B9fX1wqYeFo9K9NjQRtrHdrn4OkeEe0YJjZxcuXJFrrGhHBO9cL09N+ocEZeeKkW5TgRIAhRFh3nz5uEb3/gGSktL8POf/wLMV+vY7xVFQYTwBvJ2AEeFZ4cEhoSUk7a9nP0xw2SnTp1CukiZWVkg5uwbw572cuoxx1A9Vvf8NzJxqRe4Eb/W1hZ5u4iOzg5VxLbn+BMLFUPidyn7EmiHTUgcDA8PS1JJWTVlZWeho7NLlI5+k4jSE5SWloa02ySG8+xrsz8kihz/5uYWOf4MC7I/DP/Zy/Kc9/4iVlzHxj3bG498trW3yzVhqu3EtKKiXIYE7XWyfeqknrGJ2LBfJIIsKykpkZ42+/r36/grS7R0DkZ513W38f6SoejBu5QHhPrD7GJ1Nd8vwB9pPaLfJlcTPN2doBNfKo+arU7efo+sbRPBitccr6u7vdP/RNrQZO4MgfG8F3em4UFI351O/tvw3372M/AGmJz8eS8iekkYZqGXi1q5GJwhH5Zxz3Ouu2GZfdLpFLmeif/SUhN12svQa8aQG8kqF3nPnTsXer2DJAEqroqiyPAc13ExLMew0Msvv4Rvf+tbttss2Os0Cu+Jh4eHvI+Wl6cXaON4XirWoRdItY171oVoj2X2iX3hOW0iweBxtwhjcqH1O++8LW8gStLE0GK2ICUso8zYxEk7R4SfGIqit49yxJz5Y2XVc0WnA/91yH6omHuI/ulHQpiqHG3j8Xhj4e/vh2++9hqIW3JyEjZu3Ig//dM/lbcmUJTrxJH1HQwGcEyJndqeu4c7aAfL7RPHjbipiR4/vV5nLyKPiSt1sg9qon4m9VzdOzjoZR11Q1ylvX/yJ8JLtQC0/4+//31sFd5U1lHluFcURf4bkPmq7TxmiI/l9kmn08uQpWo7rwWGzu1l1GMSY+pRE+2216/mm81mtcp939+I6n1v4v4p5EQ7e/NaPP36llGJj8K501ZcA6Lx/A+fRXyY3w1V/eISseVPXsHTX9+AmNj7f58ZkplHZrJV9KA9BgcdoDMhcflirHpqElycR39gbgDpJhnsF4naTYpvn21vzxjp2c+vx+q1c2BWxhTch1NiQNvvg6qbquA1t+bldYgLujtsb6pYK7hrBHRiIrzryo9YxebmZukx4Z6TPz1VfX39kqxwEqW5vHUC70xO7xTlGKrhZMgyNSmKAobD1onQ4fPPPw81jQ0dUp43rzxw4ID8Fxo9St3dXTLcY4+rXq8HJ0FOiq6uZkngDEYjmE8d9omTHfP5LzGG5mg3PWb2Murx8mXLbLbRxiWLF8uJWi1X92yXekmMhoeGZHZ/fz94ewd67UhCWUYvS1RUpPjuc5Yy9hviydAXPSjLRLsLRViOa624eLu0tPSmnhD2OzoqSpJPFXP+OYHEwF5/X1+fCHsZQVvt8///7H0FfB3H1f3Z9/SemJnBIJllZmZ2HHKYoUnaJG1KKX+lr9+/aZOG05CDDtgOOWZmloyyLVtgSxYz43/OlVd+kmVHZkle/TRvd2fu3LlzZqU5797ZHZ5rmiYvNyUW7AfHi4SMOLHcNjH0SlKUfjpd2uQ9QK8b7bCV0zQN0dHRTfBjSJl1beV4Tp0MOZMkc00TideJpBNgGx6KNPIBApYxNbdf0zQZexJA2s7Ec9qjaRrVNyb2h+1zbIgVE8feYrU2yugnvr4+4HpDjjsTiVu/vn0FJ12GR+rkPU7baKePjy8yszJB7xXHnf1hGZOvCptSnvWudDJdaYVXS59JDYq51gPdeoTC3aEOWacyGxMBu9h2Kzzs4efnf241sxu69x8Ib1MuFrz8kXKfn7s48NxKrc9hP2b+9DEMHhLT+kpXUdI9uCse+Pl9iA3xlVacnALh5Hnpt0VE/0H4ye/nXbIn0C0wEPN+/jB6qHEWg2w+qn27wtnFYpNzZU5Nyrs549G7MGX6wCujsCUtmhn2zhZ4BbjAxfvK9wHGzyUhoHsSLqlyG6vUvXsP8XaQPPCFpVwLw/UokyZNkm//NJfhNvZ51KhRvATJke7lkYwzH5xwLFarkCJO8EycHM8Uy4GT7B133AESrbvvvhv//e/bGD9+PHr36qUcS5rI6B8kXt27dcN9990HTvx6fvMjn5qjTXzvET1kDOmQ5DSX47XF2tQ+i9V6TruUI6nx9vZWoctcVCmCxTxO+Ayturt7iP1vvfUWqhQp/c1vnoeTszNFmiR6sUiquFaJ9lusVvBhgkGDBoELt883BxHbPXv3guSImBP744ln32vGRijD0Jq/8lzx1QPMaymRJBPnHj16gni2JENdDLtFRERgzJixQrayVJgWLfxwjDmutol5LYg2ZjGsyicaJ06cCH9/f3kwgHmNAhc4mTp1Ku699z4hXucT45cAhiqHqXAuCRe3y2lJlnba2s1zi9XakmhjHhf179+/D1xrN1n9TfBhAH7ZaBS4iieXPqNeRaNaUs1XCNi5mKGVVCJ9/yFsXr65MZ3OqQAny4juMZhw80RJEcHuEC+NUuagQk7DJw+X/Ng+4ThfOJA6gnvFoEs/f/XNwg7dh/SHi6cHug4fAdYfM3UcRK+Lu+SxLeYH+jiABApqMvWL7i3tsKxbTECjDcoMZWMQxs2dgMjwUMQO7Qa9nG9Wp27WGTE0qkkd1mMKHjceLGM7FtV+70G9EBYZLO2yf3r9kWN6N4bXKEfbqVe3k7r05BYUgqGT+8M3xAd9JvZCZJQ3+GN1DsOA0aOkH9Sn40h9/UcNkHzqa+K5OtP3vkO6w8GvE8ZNHQziQi9R5wH9GusQP/aBdrE/HAv2n/pi+kTL3n8RYZ6I7hcjWFOWNunJ0ccb/SaPFX22Y8mxo069r9KOIlBsm31giJj295kwvhF30amI9aiJI9Cpsxdi+kaCOtlf3ks6pnqeyNt8sE3qZ5uU1ceT9wGxZR7LOFYujs0mHmUb7ZUyJzsbrcbppSNw8TXPN2FdvKbrX8NVeYv4ioVHH30UgeoLy5NPPolf//pXTUJ09NzwXVFc98RzTlCXajknOy6Afuedd8B9CT/99BNZoGyxWs9RqWma+pLkIt4uEp9zBM5k8Im0PXv2ggSL5INtnCm65APbi1JeJa4NYp+piHpp+y9/8XN5vQOfbnvnnbfRs2fPFskaw4r33nsvSNg0TaMKUEdkZCRYl0RKMlv4IAmbP3++kFqusbKz2DWRIpEkWaN3xdHRoUmZ7QXHit4ZjrOmNdhgW66fE7cFCz5DRsZpWRNF75dedrnHurp67NmzR57wI/mkvtb8DWmaJgvoAwL8BTfWaynxFRubN2+Rp2ZJuOg9a0nuUvJqlTeToV6GjLktT5XyIl5J/ReyyXShwrZUxgm3pqQW9S72YhYncCZOitDMiIrtiRnzxsHbzQTviEjc9qOZCPZ3BUnI7PvnoFc3P7h6uGLEzdMxbECU6Gj+wUdmmVen3N88miqLYe9gQb8JgzB5Vj9ERLnB0dURw2fdgkmTe4Nv9e48oCcm3z4F/t72CO7TH3c9NqbBBl9PjLllBgb0CKIqSXX1JSgvKUOF0ltdXoXSSjM8O/XEjAdmim7qi546E7fcOvIcshU2ciL6DuskYTNHN1f0HB6L8HBvuAQGY85Td6NXrC/sza7oM24EBg/rDkcXJwydPQnjx8aInSE9e2D23VOF/Igx6qOqsgplFZWoUzdgaUk1amuqVC7gFR0t9lDfyNunYfDACJCkUF/s0F6iL2b4ANz9xOwmpFWrKkFleTW0yiJUlZWj2s4Z3UaMxMQp/QR72sBxcXdrGMNe48eh76DuGDp1NLp09kVlWRWKC4rFHjGkhY/gTmFim4t/iIxlbJ8wWB2sGHH7bNx8U2+xLbz0WCBIAAAQAElEQVR7FGbeOwXRijyV19hh8E0TMGREF0WcB2DkqGjRWlt79k331XWVKIcTykurUVhmQuTgYXIvcbyJwdh5czB+Yuw5YxI4aiRm3jxS+hYUE4wJN41W35b84OzeCQ/97lHERLtL2agZI+Wec61o6DcN6DRtEibN6gXnynyUldcyy0jXAQHe+9eh2avWJCd/ej7oPWG4p7kXiq8wcHJyBh+Hp+eL4ZKrZswlKOa7pgYOHIBvv/0Of//739XfU+cWic/FqCYm3KOPxIDryvS6mqbB3cNDtvlhWNTJyUkvumJHTdOEyLm6uuLPf/4LWsKc4b2kpGR5FUPz8bpYQzRNA71s3HvwZz97DvQKMfR3sXrOJ+/o6ADeW3xXF7ctYr8u12bbtugl8/PzBV+ES6wcHBxtiy/rnIST2Ozff0DWuPn5+TV6ei9LcSsqm1oh0yZEdI+Wnb0Dovr1wKjpoyWRBJjMZsSMHAqtPBeHD6Zj77ZDqHXxQddO/ggdPgg9ouxxYHs89scnI7uwBmHRYS33qb4WafsTkJtRhLz0NGxctw8FZfUoKarE4U378PVHy5Bb74dhI32Re/ggEg+eUO2dhEOQL3yjumDE+FiUp55E/J5k2cC6yuoM387hZyfo2iJsXbEFJaUVSD6SgtTUYsQMiIYlLxXLP1smbwrfuHw3/Pr3QnSYfcs2NsvVTK4IDPBA9rGjOKRc1Bu+24j03Gp4dOqB/j2DkHb4MA7uTEBC/HHYhwQrL5GPeMGohm+kj19/APwWkXzouNjD/OLE3dLXpYu+w4mMKoQo72BwWCB6R/siO/Go9Hv/nmNwDYtEaJgPq4Av3+Qb3g/FH0NVZQU2rd+Hkmo1Ln06oTw/B4d3HWywwTsCMRE+SIrfj6TTFRigvFNdg6oRt2kvUhKTsWPrYRQXl+DIngTwDfF19WcJERtKO54qti37bAlOZZQjNCIUHuEx6D+iF3Z/swrff7oM3322FllV7giPDELB8YNYv/4U+s+aICQrces25e7OQqNeNSZ8K//pjALB8NTpPETFRKDi5FFpZ8kXX2PTztPoEtsFPh5WNPnJK8beDfulbwf3p6Pe0Rvenk5w9neAm6UKB+OOI27DXmxdtQNZhZVS1VJnRfjoSbh5cjfEfbUcu9T92miLSBgf1xKB1nwbv5b2XO224uPjMXToEDzzzNMoU1+G4uLiQI8K2shPbl4+GIp67rmfgeGpZcuW40qEd8LCwsB3NLH/fLrtWnWX2PLJtunTpzdivnv37kbMaQufSgwNDUV0166XbRafLuRTdg8++AAee+xR0INz8ODBJk+BXk4j9DLl5uaCL6glkad3q6Cg4HJUNtYlVgwdkmzRM2tvb48dO7Y3YtUoeIknDEtz3ddDDz2IBx54AHz6lmu1LlHdRVUzXZT0dRTWPVq6CTVltWDSrwMVGeBE16lXF/SI8cPplFyUVdcgMMQPVkXOfLvHolefCGgVRSjJz9WrtfqYrzwttcWVsChGb1GuX3svT3Qb0AORAS7IP1kIa5k73AJ94ObjLPm0ozw/D/m5xXBU7taWGjJpLvByd0HBqWQUl9UIWSlMT4dJERQ7V7+WqpyTV1aQrkKo2wD/aAydMQJhnUNQXZQNZ2crzE5meAX4InZUX0SFuyMjMQsFlaqdc7Q0zSgtylPfhGrkUVmSTM3iBh+TDywWC4JC/aR/wd4OSD6aJl45vTbHSD/n0V4RDxd3R7i62Usd2pCenCY2cI/DEwnJgIc38lIykJKceZb8sPJ5UnlOLjgOFQUVyCssgbOLBR4+bvByrEP6qZOio7yoGIUFZfD0cIVWW4mjO/ajwjkArk5Awr7jsr2RrXqLub7x0qz+uN09nFCako+SUuXhU+Q7/UQy6j284O2mNcrpJwFRfujTT5HHzt6Cj5O6N/LTUrB27REE9+iOwZMGI9jXHgU5BSh2UGRL9Ve8CqjAqdTcc2zR9RrHa4NAR/No/RBqycnJCAgIEO/J8OHDZBLTF4j/UN1rUV5UVAiSj4iICHkHlIeHOxh6u9y2GSKaMWOmrFlKTEy8YsTjh+xilITEh+uCuO6IL2MloWC9evUlkhN9XFw8br/9tnMWclPmYhPXoPFBgpCQEEyYMAF8l1ZLL0G9WL26fEFBgRBhegi59o8hVb5+Qi+/3GNBQYGooOeJ5JThPcm4Ah98cW1ZWRkCA4Mw96ab0K1bN/WlvvgKaP5hFaYfFmkbEvzWb+diRm1uIU7sOYh1S9dI2rT1hBhYXFyBksx07F6zXXmNNmPTV2tw8FA60hSBoYclQcV9t67YjHXfrMWqTalS51I+qssrwH/OXCdGfeuXrAfT0TxFlpQNJA3MZ1rz5QocOHgKJWfn8SZNMpRYUVkNF09O0nZSZufuA9jX/+A/F0drgzzDiJbyQmz5fiN2bDwIN38f9B7aR3TV1yvysf+Q4EF7aOfJ1BwQSxG4iI8ChzJFvqrFS0NdTMQ443R2o5bmeuvrilGjvFs5yRmNNqz8fAWOJ+fB4uwCd/8gmKsKwHVXAYEejZ62RoUtnDieITsWRw1ODvaoQz5KFSHiP2d9kTnJkoO9BfXVRaIhIiYITrXlqKi2iJezOSGsrtVETv9g+BPeLrC3nvnz8HKFU3UxSiptPFpmN/QdOxC+DrlYvyoOu3clIq+kQlR4+XqjPu2IjMmeuFNwjOiBoaNi4eZqBxTkYu/StTiUZcGEaQNlPZ1UMj6uCwI3mkeLE9jJkyfBhcAEnAvo7SwWnraJRBLo7u4Oep5o44ABA2Rtz+Uap2kaQkNDMHnyZJBsVlaqLz2Xq7QV9YntuLHjQC8WE6twHRjDmSQRHIspUyaDW/Cw7HKTg4ODrDMjfny3FK/5dKSmNf0fd6ntBAQEysMMfB8Y17x17dIVnp4el6quST3+LXJtoUXdj3y6k96zgQMHnnfhf5PKrbhgmJME9MiRBOzYuRPh4eHo2qVLK2pevsiZmeTyFV1PDfzWcCI+AZ4h4ege44/gyFAMnTwc7i72KN4ah6Iai5APv0A/9B86HP26el+yuUU5GTiWVoHYSYNAfZ26d8aAkf3gZK7G8f2n4BvdFV06+UsZ88ODXJsQmzo0QB4S4gUfXwvo1XEI7SrrqrgweuTsERJ+JCGyNTIr5RBcArugz6heiB07FL5hPlLs4OqFQZP7Y1h/PziZqlFrcpR8esZOnSxD9PC+Yot/dE/QHh9PZynXP7juTdNMCO/iiwBPdz37nGNJcraEXXvEdmrUR4yd7Rv6Y1vBqjyIUT27wVxdhiRFqjw6dRFMaMOwaSMVhzHBr3M0BnR3w65lcThZ6ITYvtHgKyWqKqtQa/UQz1yTxfZnGvCNisGwyX3Rd8JwdA53w6kjxchKPILdB/MxavYsEMNBU0Yj0MuMhGN5cArtjkFTBuP4umXYvP2Y4BEW5HZGW9ODR0gEPJw0JB1NhXe3Hhgxuje42H3KmJ44efAkcvJLz1aoazj3CgqW+61zn+4IPKOXZHnwTRPkXnSoLoSDgyb16rPNqDZVISt1P9YsWAXn6BhwPZ2sMxQJ4+NaI8AvTde6zSva3kUq47f4YcOGy9uy6ZUIDg6CpjXcnxep6qqIczLkInV6fZmGDBkCe+VlvhKNaZomXgxO3pzMr4TOH9KhaRp69OwB9oML54k5J3vWs7Ozk+17uA2Q2Wxm1mUn6uE7zbjmjOFSElUfH5/L1qsrcHV1AV+rQQ8dSXpXNd9dyfEh0SJWDEuyH8RM067M/UnSSVz4mgfqHTp0KNw9PPSuXdXjubPkVW3u8pSTFGSfLkJxYVlTRSq8s2/jLplI/fsNxKBRsShMSZSJMevoQXz14TrAKxzDVRjHxbkUCSdLYZ+Xg5SU5KZ6zlylZZQiOyXnzBVQlJWFkoIClJs0cF3T9//9HPuSIPq6xHRBQdIRlKi4ddyK5Vi9KRk9RwzCwLEDYKosQmZaZqMeOVG2rtuwD/VeoYiJdEfavr1YsXwfaDftq089iK8/WooS5YkT+TMfad8uw+ET5aI7xM8BqampKM4vREFKApYs3AP76EFij4rDYd/WeGQnJ2HdolVILqiX/AH9w8TOJmRB6S4tzsCOHSfhq76Z+EV5ID8rWYXg6lVJwy/7nq/CprkFaaIvrdLSqC8tfldDeK1BVD5TE45i7+FC6b+7tRZxa7fiYFKh2E0b0g4ekjBppx7h4Pqx+C1bsHPLQYVHILjeq6qwALs37YdXSBeER/jDZPNHRrJ54tBJeMX0kPVnqfHx2BmfitrSIqz64IvGMYlS4dv9q9fg2IkcRHRTodSkQ1i+8jASduzDMeVJCu0SDoudSezVP/as2gHNxVsIYermOGzccATBvfuAC/nLDsdh3crtTcdEjePGL9Yg/rgm95uHQw2SlW0MV5P4rfw2HpH9+wlWFenJ2LohDjm1JchOylX3SjVyjidg3bLDcA/wRbC/q26GcbzGCPBb9DVu8ro2x4k4IMBfhU8CwSfoeH1dDWrWuKZpcHNzE/uCgoJwpReos7/Xut9sk+SKJMK2beZ7enqCx2YwXNYlCQWxY3vUr2naZelrXpnkJDg4GLyPHBwcmhdf1jWxIEa0nQ9qkIxelsJmlXk/ERsmd/fzOxaaVbvsS9Nla7iGCkoLjmLJ54uwNf7UOa2SAO346nvM/+ubeP0vb2PZ0j0NE6OaEBN37cFnL7wl+Z+9txypSWkoSj+Ft373DnYmZzbVVVuEnYs+x4Iv90o+9W74+AswRFldUyd5JafTsOydj0Tf+y+9L2UkRtUlhdihbGD77/zjPXyzcDP46gmpZPNx7JvvwPIt25JQWlyKo5s3NdpN+zJzz3VrV+Vl46vX3pM2P/n3h/jkH58hbt8pVFVUnVP/cEKGeNG4OP3b1z+XOmyPfaCdNqYAqr/s38t//wwHdh4ACcqKZXsbsWMZsWTfW9LHfFt9xItYsz0uZifO1KFjsnn9ftHNPOKTX1iBtLgdWPDqAojdNVVgGXGNi0+Rfuj6k+Z/iPdf/QrsP/Xp9RmyJD7Nx6RUYcvxYB22U5R+SsZt47p9TddGqXvk6JatghPL8stzBQf2ge18+un6Fsex8NThxjH5/LXPpA/EmPdB/KrVoo/1OabEgvKfvfE5DijCXKf6SZnP3ldkOK1Q76JxvMYI3GgeLR1eTbuyk6+u90odNa1t23cp/dS0a9snTbt67Wna1dNNbDXt6upnG9cytSuidS2BuVBbnNgvVN7asvPpaSm/pTw+6dfatlojxzb01Br5S5Gh/kupxzoXqnuhMtb9waTIlq3Mxeq7WPnGtpq125hvnFwTBG40j9Y1AdVoxEDAQKAJAhcmWk1EjQsDAQMBA4GOhcCN6tHqWKNo9MZAoG0jYBCttj0+hnUGAgYCVxEBw6N1FcG9SqoNtQYC7Q0Bg2i1txEz7DUQMBC4YggYHq0rBqWhyEDAQOA8CBhE6zzAGNkGAh0DAaMXF0LAJCSumgAAEABJREFU8GhdCB2jzEDAQOBKIGAQrSuBoqHDQMBAoF0iYHi02uWwGUYbCLQrBAyi1Wy4jEsDAQOBGwcBw6N144y10VMDgeuFgEG0rhfyF2hXf0mnyc6KgFD/67dNi2aGf2QUXJzsLmBt0yLazsRcq4MVkV0iEejjwMu2nVRfdbvbtqGGdVcSAcOjdSXRNHRdJQQMte0cAYNotbEBdAsKQdfeXeFm0mB195Atg2IifJq8If2amWxyxtCpo9G5S3DrmlRkxTciEtHR/mKvxSECo26bhAGDA1pX/zpJmTQNEd26ICQi6DpZYDR7vRAwPFrXC3mjXQOBGwcBU3vqKj0knr5e8AnwFk8Pj9xKhXlhkcGSz2u9T+5uPiJHr5DulaGXiPWY9HzmUQevmW+rQ9cFRSJsZSjHvfj0utTPCZvX1KProM2UZR7ldX2UY76t3Q7efogeMgw33TMe0WF+sK+uw5ETyTidU9zwhvRmNlA39VEX9dv2Vy+j3dTLcibayTqtSSatAicP7EdBToGIW1zcBU/abNsXKVS2uQUGYuCcqZhw02hwP0E7F7MUVdd5Sb3m7dNG5jHp+vS+EBsmyjCP52yXRx1bUW7zwfGhDPWdr596HygjbSq7/UL8MH7eZIw7s8mzPo5si/p4ZJu0g20wsT7TOe0ofZQX3bRNXVOe19R7TvvNZHjJdqjjHN0sNNIPI3AREoZH6yLAMkQNBAwELgmBdkW0HH06YfStszF+zniMnj4aM26fidGzx2PMrDEYOnm45PfoESreFL/o3hh11ziRo+y4qYMlhOXoEoEB06dK3TGzxsr+emFdo0QH5ah78MAI0dGIqJos/SPCMeKWCaJvpGp70h3TMGJEQIPXaVR/xPYJg9mswTWgEybfN1H2r+Ok2m3ESLGLumffPQURwe7gRNp58CDJp90zbh4J2h0SGYJOvULg7uEM727BcPe2R3RUBAKC6sUev649Gm2gnePG9pSwIvs069EZGHfrKLGP/RrUN0T283MP7oqJt41pzB8xurfUQSt+6mpr0XlgP3j4eMBBkcC+E4aLHtqs90VXYzKbERAZgUDVPxdvb8T07gQHSyXs7B3Qe3h3DJ00HONumQS2rxOO2CkNeBKbSXNHy/jQizf6ttkgvkPGDUJAoC90rPqPG4wJN08Ex4fER2+bZDI4dhAmK+8ZZaiv76DuaE5UHGz6QIzYZoB3EML694ebrzcCI4Nkf0U7e8s5bQ7oEQQXPz/0mjRe2hl6pj+8r2zbMZnNiBoyGFOmDRb8Hby8pU6P7kHwVd6+SdPGC4a0ke3L/WD2b5Rhv4jBAHWP9uoSAOPn6iJgeLSuLr6GdgMBAwHA1G5A0Mywd7bANyoQ5dlp2L5hH8rtrBg6eSCyD8XJNZw90K17BNx9PDFsfH8E21djx+qd2L0rEZ4xPdFnYHfYuZgRHO4N1BQgbtNeVNQ6InbMUDiU5Yrs6eJ69B0zEO5u9tB/LM4uiB7WoO/I1u3YH58M5+BQ+AZ5w1zrARf/EHh61Yl4hYc9oqKi4GtxgF/naPToFYT0hASxr9zBDzPnDYKjowV9h3QHKgulzYwKF7E7NyUZx/efQmFBKXIPp6Gw2g0+XXzh6+cFs7Mbxs4YAm9TldRJSMwFNy0Oj/CXdjt16iR9IC4FFXbo3K83fDys6DO6J/p1dsK+dRtw+Eg2PKK6KvLiAZIdqQic92AymxHUOQR+7vZw8wlALxUSLExJbOzLkKFR0H9IyjKSlPctrRAlublI2HccFdUNGGadLsHhXQdxLKUSfccPQZidGZF9eok+YsPxcYmMkfGx2lulTaeS0zi+Zy+s3v4YOqYH2O7uNduRXlCLnoP7SN/0tq32ZnTqEY6yjJOI27AXSRkl6BHbCT6ezroISMbYh0FDw2U8dm0/Che/IEQG1yN1926czijA6aR0pCRnwiM8BiNHdIFtm33GDoRfkJ+yLRQuVTnSzsH96eg6ajBsCRFxyK8zoduIBvzZZmSEFzR7F7mHojpZEL81XjCEVziGjoqFo4sLAgM8G+8hqJ/QbmFwdXdSZ8bv1UTA8GhdTXRvbN2VlZU4evQoysvLBYha9cWVqb6+Xq5b80H56qoqsA7PT506hezsbLluTX3KsB4TdfDaSNcegfZDtM5gU5Wfi+zEFCQfPoak46dgqS7G9p3JSEs9jczTtbD38oR3eARCwh0Qv3Ynko4lISXhOJKS8xAQFQafCrNoSt9/CMcPHkOpyRWRvSLhExGA2FF9ZcLzDfFDsLcG/cfRzVXyk4+k4MT+VCTuTURxcYVefN6jj1cYwjoHKBIQhb5Du8Mt0Ae+UTEiX1pngZcia9GdPXFkw2Ys+347CnPyUVBThtqKImSn5aKmpFZk+WGKiERklDuObNqFlMRkHNm7H3nlakL392ExOGEkJe5F6tETOJ5doLxJGuzt7dUfuYY61yDE9o2Glp2IVQtX4rjConFvPrMbBs2Zhpsemovhyivo6e4g+lr6qFHENiI6HKF+VmxdtATLVx4+K1Zfi5KsLBRVlqM8JxdpmcVif01lBXKT43B031GkqzCopgijS6gFQeHRCA9zQVBMDHr1iYCbrzdCQrxEn7mqAAkHTuBIYp7izp7wD3ABCSK9VYEkJCGBCFFhTBFWH1WVtYhbuxVlcJIxjOwUAjcfZzi6OqrSM7/KPp5Vmj3RqUcUnEzVWPn5Cuw/loGMUzmoLylBZV4+8gsrEBjqC29lC+8X2zY9Qhv+QaYeScWppBTsX3cYp/KAcEWGof+odtI3HEW+yRe9uoeJLsfSLGTnVyJSEa5jccfkvuP9u+dYutx3AQpXvbpxvLYImEyma9ug0doNgQCJzaFDh4QU8R4j2Vq2bBm+/fZbrF27FqWlpT+IA2W+//57fPvdd9i4cSP4JU7XW1xcfE59ljHZFpCUUcfixYuxZ88ekLTZlrfd845lWfv9L6MmNH0oqmvq9FM5ujuZYFbemILKGrmurSjH6eJyIR9wbph8i8ozwHoWRwfY1xUjS3k08tMLFClIwvJv9iC3qGFSpSdElKiPutISlJs0dQaUFFXK8Yc+tPJS5GVkg7qTtu7Elu82o7S4FKs++AK7D6QjeOhIPPj8vRg8rPsFVfmoydhisaCmsBokSRUFFagsr4ZjeEO1urp65Umqbriw+dz9zVf4bP4G1AVFY/aP78Et80YhyLsBA5z5qSypFPsqys/fp6yjB7Hsk5U4lG2HAbffgid+cycYDjujQg519Q5ybOmDNjvk1zcpKi+vRW62IjcK9/2rNmLXjmON5SVlZ0hmnSfMiryV5BeKjZmHErHpu004VVLYKAuTM0bdPhvDhwUj61Sm8giWnS2zOcs5noBvXl2A3Dorxj9wKx5+bi4iAiw2Eg2n9i72qK6uRo4iRxw3vc2Ckxrsa0pRVl2D2tp6NQ4lch84eZoaKp75LC08jmNHMxE9vC9i+nRCYWYe8osaxqa0vOGepGhZSTlqzK48NdJ1QqCurun/jutkhtHsdUSAnh4SkLKylv9vXIppBQUFSEpKUl8eQ2C1qi+mW7cqorMX4eHh2Lx5C+Li4n5Q7ZYtW8BIxdSpU0Hv2BHlHQsKDESuihikpqY28WrR/uPHjytil9Ool3lr1qxBRkYGvLy88P33S3EqLa2x/FJPSOaIVWFhofo/WCt2kNAx71J1dvR6TWeIDtLb3Bw1AZaZERsWDKuDFe6eLugR4qu8FWWoafZNoCSnGNm5Vcg/noQtazdh64otOBKfgMzcM6RDEbqqyiohNd7BgXBxtsLBwwEuNqFFwsYF3ywjITJpGrMAk/JQFVTh2MHjonvnyr3YtTdFeWm6YsSYPihO2IMP//Y6Vu48iS6xXeCiNVRr6bMguQAZRZC1W+yTf5iP6pcVp44UtyQueRWVbhgwYwIizFlY/Or7ePuVFSh39kNImPfZ0GFtEeJXrca6pWuwe8MuhVHLnjq/rj3QLSYCqetW4JWfv4C4k7Xoq0Ks0tCZDy6e56mjmwZ7q4mn502lFcWKGOYicdsOwSZu8x4cO3H2nwQr1ilXe3llBkrUXHjq4CGR27lpOw4npJ0dHyXI8ejS1R9bv96CHZsP4ERCsspt9quZEdgzFoP7BWLTJ9/gnT+/hZRcE0Kiu4kgPYx1Dg7gGqmC7CJUl9SgeZvZGeWotHOGk8UOTo5muPm7ITDYHdnpuaKj8UPdM3uVN9VP6Y4KtEPyoeMoLCpBYX4VQgI95R5ydnFAp0Av5UnLRSkKwfadHT0FN3tH70ZVxsnVRYDehqvbwrXRbrRyaQiQNGzfvh2fLliABSo988wzrfI2/VBrp0+fFhEXFxc59u3bF5MmTRTCZGdnhqenp5AUtn3s2DHU1NQIgdq9e7ciRplSh16rjz76GPSMlSoPmKOjI+zUl21/f38kJiaiRn0ZFMEzH5SpUmHGM5cwmc0YOXIkBgwYgKKiIri6usDR0UkvvqQjSenOnTvx8ccf480335SUk5MDEroZM2ZgypQpkl577TXp3yU10gErmdpTn2pdi1BRUS9eHdpdqTwxtWrC5jkTJ28eC7OzsGvDAXgM6otR00dj2Ngx8FaOgyN7EpCjvsEynEU5prKCdBw7ko5Oo0aJ7KTbJmP81AFNSE9VYQEOxR+DR6cuGD59LAZNGY1u4Q1/QFU1mcgrLEFw7z7oP2EkJkzvC0ttwzejpENHcDqvFoPHDxHd0x+aigkjwlBrLoCLf0hjfqSnBTnJGeItK0vNQrWTF7oOjYKLZ430l3aWFx5D3JZEcF3WpLnjwdcuaAWZOHo8k8WoqqqUIz+cyspRUV0PB/si1Jtc0HX6eGl/UP8Q1NQWIje/jGKtSiWlFeLBobB/984YPGkIRk8eBB9zBY6pMBjz9STEKKMEjp7+6Duou9hfrb4lVhZbRaTYoVL9o2kgcql7d6HI5IExc8aKbZPumIa+Pf1FrrDaQY5QhCU14aganyKMnDZEjeMIjLt7uoyPuw3Rra2sFA9S7KRBYtvIyf3VPxS7Bh02n9XlFbJWj4vQR44YBEdUozA9SyQY8vQL8ECPHqHIPnoIiSln2+Q9MZEPHrg1eOToqRoydSymKpsdco9jf1y+6Gj8UKTu9IFTSM2pEjKZnJaDirxcuYeco6PAe2jopGHoHe2LA9vjkVeSicyUbGVbf1Dv2FlD4Glf2Yh7o17j5IojYHi0rjikbVIhCQJTc+OYR0Lj7e2NQYMGISEhAcXFJc3FLvq6pKQEJPFWqz00TRNiFR4eIWu2SJSYzIoI9ezRA/RE7d27V9p2c3ODr6+PtEdyVqjmnn/+8wUkJyfDR9moaQ268vLyRKZaESuSqALlXaJHqaSkGIXqvPRM+2yHZC89PR0RERFwc1MTodS8tA8SU4YgQ0NDMW3aNGRlZYPetZCQELzzzjt4+eWX8eSTT2Ly5Mlg/y6tlY5Xy9RuuqQm3dKkMiTu3NMYNspQXqg131MFafsAABAASURBVO6RLjA8mJ2wD3t2Hkd1aREObduFlcsaykqLC7Dl66U4ePAkSIwObFTfGtI1qVetQlA7lq3Hjg0NrlyGnrav2IYiFYoTAfVRV1OFpPj9oq9ChSNNatJMPVWoSqDaKgHXByXEHZVr6v72iy1iY5H6VrN16XocS8yWspN742VdEyfdNV+tbMw/sXkr1q3cLqHMrMQjWPP9QUW6HKCpMBX7u19N5Ay9xa1YjtVrE0Abso8fVXI7ZS1UufqjWr9wi4Q7SXaIC3HIyS8F66z4Zr+0zzDYnq/WqW9DWSrs1UAapOA8H9R1aOV6nErNRY4Ku21fugGZGdUiHb9mEzat3yfnjR9qjI5s26K8SumSVVVSgAOb4xrJYFFOBrYt3Sl2Zp88JaHI5BPKTaekKRcXn4ryomJIm5klKheoyM3Cuq9WKLf7Kdg5mZF3Ig0cn0Kb0C3HcMNnXze2m7B5F3hfZBc02CqKlG0FKQlYv3g9MjOqUVlbjLily2SNFgndkaXrFGFqGKeS/AJsUdd79jS0yXtiq7o/8osa7hmGmakzNzkJq5S+1PSGPjBPkmqrrr5E/cOuQPaxo8hRXk22kbh9B1Z9vlXGj3KbFi4B+1xVUYX969dh387DzAbHdvN32wR3yTA+rhoCnAyvmvIOopiTOSfY9tgdEikSj4MHD2LHjh3YF78P5WcWp7M/dnZ2GD58OHr16q3+x+zB6NGjFSnyYNFlJXqWSDRMpob/GRkZmerLcJWQufz8fOzfvx/E1MnZGd2798C2bdvU/4tiCTWyHu0+cOAA7rzzTtx3372qrAR74+IkTEebWZdzQpGK0JDocJF8ZmYm0lRo8OTJk0hTxIo20LPmrNro16+favOAlF9Ox2jbjBkzERvbV3B0cnIE9cfGxiIsLEwRrywEBQUhQpG6y2mno9VtP0RLIc9Jl+Gt0zkNXpHM5BRsXNcw2ZMMJR9KwL4d+1FSVgNOvom79sjib4bFDidkCJFhPnUkpzUQJaVWJnPmcaE4Q4e2ZSxnYr1GfSt2ITO/htngBFqUfgqbl2+WtvYqEkcdYqOacDOTTjSW0VYutm5eZ+P6gxB5pZHtMJRH2YyTmRLO0+1h2dHNm6QdtpealCZ9qqtJB/soOs60aYuDXocyOg6qqR/+Vbo2r9gGtq/jSx3EifYR5+ZKiAVlWJ6fnSfjkZx+ljTRbtpJfcSGstR3YOeBxnGjTE7G2XAcx515lONR7Gn25I7eri7D9m110E4SGi5C19vctPWEtMky3Za4+BTBlPrYlq6PbVZ42MsarbSEY1izaJWMA/HkPzzq0JNbUAj4lKK/axUOKC8q1wKyrE6FQnmPUicT29IxbN5Hts02Wc9IVw+BjujRIpFgeGfz5s1ISUkBw1KXiiAn9GXLl4P6LlXH9axHb8/atWvVl+yDEhJc8Nln+PTTT4Uk6HYxJOfs7ITAwEAhNPnqi5ZedqlHq9UqRKpOfWEnaVqhviTv2LEdTk7O0kZBQYGoZtgtMfEYRo8aDXrVuK6LxLZORV7o6QoNDcP4ceMUGRym6hVLHRIoPuhkUt4tN1dXRCpSQ5JD71VwcDDCleeMR+pYsWIFjqnQpJMKGRYWFoCeNtojii7hQ9M0RahCYbHYgYSOYUm27azIXJ7yspEwkmSRkF2C+g5bpVVEq832XhGBK21b80nzfPozVajnnLU5Spj1mdRp63+vQj9a3/gPSF4J21qh46Ix+wGzz1vcClvOV1c7nY6k5DxUni49nwigmeHqF4SYzt44/M0KHEmtROPPZbTdqMM4uaIIdDSPFonVn//8Fyxe/BWWK4L05ptvyZHk61KA45eDrVu3yTqhS6mv1yF52LBhgzx1x3M9/3KO7777LkgmL6QjKysLK1euBInNwIGDZJ3SRx99BIbSWI/hNuJ04sQJ8Tbt2bNb9fUgiy4rMQRIgltRUS56oqOjQU9WfHwcoqIi0adPH8lnHhe89+rdC5SxWCwoUx43EhV62nbt2okdO3eKN4yhRFYiofHz84NmMsFitcLZxQUkXE5OTnBxcZU+kvjYqdBkhCJhvCcOJxzGkCFDFEkKk1AmLuOH91JCQgIiIyMREBAgBJbq6KUrVGFL2sJrI51FoH0TrbP9uLZntUUqvLUEa9eeurbtGq1dVwQY8t39zfeIO5V9wdDr6QNxWLFwFdZuSRTv2HU12mj8ggjwW/8FBdpRIUnDBx98KBY/9NCDePjhRzBgQH+Q4NA7QoLDcBTDTFxgTW+PCJ/5oPeK732i94qTM4nCmSI50DOiL9amLDN5pBdGX9TNNugx4VNozKc+1juuiMz69RuwevVq8Ly5bl6npp4E9bMe9VA37aYutsXF3rym3QcOHFAEapUQLdYjYeGRJICyevLx8ZG1RAydWa2WRk8WPUKUqVeeI5Ixemdoq4siLXwykGWXk7hmiW2Q4PEe69+/P+bMmQOSvdmzZgnhIclnW/QIaZqmCJLyTinyQhvYdqwiY8OGDUenTp0xVJEketw4xiQzJGckY5RjMpnN8PX1VTpceCnJYrVi2LBhmDRpMkaPHoOpU6bI04dSeIkfHJNVq1bh3//+N15//Q18/vkXYB+pjmPDo8ls5sFINggYRMsGjIs55Ssa9LDPxdQzZNsxAsojxXHXQ4Et9kTJMCzKsOkF5VqsbGReawQ42V3rNq9We1yfQwJ15513qMm5k5rMQ+WpM074JBHZOTl47rnn8Mwzz+DVV1+VRcy6LZxA+STZ888/j3/84x/4/e9/r75IrkWtIiKUWblyFf7yl7/g73//O/75z/8ndVln8eLFeP753+DFF19Sdf6AL778Urwv69evl/znlb4FCz4DCR69OfSE0Ea+roB6mUiySAZ/97vfiv6f//znWKfqM/+dd94Fn2ijHAnYW2+9JaEwhgMzMzMkJHjkSAK4mHz+/PkgiSTRozyTp6enLMyOiooSmWPHEvHEE0+IJ4blXCPF1ydwXREJA/tILxDLmie+B+vRRx+DnogliSFxaC7rqkJ69FCRwDHUx3VVJEIBAf5w9/AASZKmaeDYaFrDOi5N00A5llGfxWpVdvpLYh3eqxxjerMYGtS0hnqUZR3meSjdvNaTg4MD2CYTPV+adraOLlNRUYHPVEiVi9ht+8ax0mVsjyR5xJD32ezZs0DsWE4P3MyZM3lqpGYImJpdG5cGAgYCHREBo08tIkBvQ4sF7TCTnhmaTc8Hj0wMJ7m7u8urA0huOOnPUh6VF154Ad26daOIpAoVrvrkk0+EhDAkxwmT4TR6kSgQHBykPBiv41//+jesVnsVXjskT8vxBZxPPfUkPvroQ/z0p8+KhykuLk7IFskGicuvf/0rTJ8+HWx33LhxILFhaIt6meiNWrhwIW666SZ5bcBjjz0mL+jkeqLa2hpZ60Q5ptraWiEnTz31lNjPp9smTpwoYbHHH38MEeHh54TG6LViX77//nvl0fFETExMowz1EaNevXqJ94dP0xEn5rM920TiNG/e7dAT7aU3igTIVo51qSMwMAj0WNELRRwvN/HpSAcHRxV6jJJF8c31sR2m5vm217TLlojSbpI7evxuvfXWxr5xrEgMWd48sU+DBw9W3rmB6Nq1qxSzDeZ3794dJG70LBIHKTQ+YBAt4yYwEDAQuGERaD5JtncgqqurzumC7YTn4uKK2D6xcFCeDnpBdGGr8p4MGTIUq1atVmkVunbpinm33y5rfyjDCZSExNHRQcJTJEH0TAUEBMhkS10RERHy1JweQoqMjJAF5pzINe1cTwr1MjEUmJeXD5IdenhGjBiB++67D2yP5a1JlCUxsFitTcT1vpNI/OlPf0Lv3r3xk5/8BIcPHxY5hki/++47fP31142JnquysnIpt/1wUWFFH28f6IkE1mqx2IrIOUkHF4V/++03YEiVa8Bs9V/qOe3ctGmjCpmubLT1YnXR89f8/VuapsmTg16eXo194wtOHeztpT+2HyTkrWlzlQovZmZm2la9oc8NotXy8Bu5BgIGAjcAAh3JoyVEw2IFH+nXh66srEyeNOMTbVxoree3dLznnrsxatRIZGRk4N333sUS5QFi/ZZk9TydyOjXl3PUx4KLuLmYvDkJrqutuyj1tC01NVW2sElOTpa6Xbp0wfHUEnmVAzNIDufMmSPetDnqePPNN2PmjBlwcXFmcZPExd4ff/Ix9MQHDk6eOgXdbl2Ynrzhw4aBui43zZ07F7Nnz74iumhL/379ZAG9biuPDNEyBMonMm37ln76NIubJIZaqcc2ETfaaZs3ZfJk8CnIJpVv4AuDaHHwNTP4tnUmNP85U2axawaVynd2dYbkq3Me+bityc4K5vO8uaqrda23ebX0tzu9ajw4lhyTdme7jcH6uLb3fth0qc2dNp/M25yBF2EQQ1X0PH3yyaey/QufrONTeQwXRUZGws7uXO+Lrr6ktBQffvgRglS4i+9JYliR3p5SRdR0mebHzp07y+JyEhBuC0MvEY9cw9NcVr8uU54iesNIgvQ8kip/fz9QT0ZGJjZu2iRem6qqakV4XGXdFfNTUlNQVNTwigPWJXFkOI0epMKCAqSmnpSwFcuYGCI7cuQIPlEhUYYO2WZeXh4CvM3g2i3K0BPHduiFY/s8mszmxtAiZfTENUjP//rX0NPTT/8E0Sp0Rh26DI+apgmZoXfuchIJHDGl51Ds0jQJm16OTou1qceP9lpV3oQJE/DLX/6iSd94z7DcNmnaWRvY7wxFymkjsSNh022zWK1guW3dG/ncdCN3Xu+7xdkF3UaMxOAhMXAzNXVxO3h5y5vLe/QI1cXlyHy+pTzY3xVugYEYNH4owoLc4BsaglvvnQh3mzeXS4XWfmjmBvLWSnmTuvG5tQzbNCbkBtA4Hnx7fkhkeEPGFfgkztcSX7bn4ueHsTNHITA08Ar0wFDREgKczFrKb4959MJw/ZCrqwteeukl/PWvf8WOHTuVl2qUCgV2gdlsgtVqgUkdm/fP0dFRhfkCxJP1r3+9IAvO+ToBdzc3VceqSJqdVDGZqKNhEuUC8/Hjx8vrI/785z/jm2++kXU73bv3kDqcwDVNk3p2dnYSVkxKOiEkiut4pEB9eLi7g2u4GGb73//9u+ijd87B3qpsHwmSJeavX78etbU1oA2qmoQBuR8gF8sfTkjA0qXfIysrW9YvsdxsNoNrqHr27AV6tLiAnmn8+HHKzkEUUfpqcfToEfH6kXyRmJIISmGzD5IIdw8P6IkE0WI9l7g0q3bJl/v27UOZIrruCp9U5Zk7lZZ2ybouVFHTNHD82Y5t3zhmF6qXk5Mr72lj3aysLIXj0QuJ39Blphu692c6b1axaPeu4QgJ9DyTc/ZgVX/swTFRcPV0P5upzpgfHRMCDx8PdXX2187dBzF9u8Ds6IxL+Rk0ezLm3jMRnGhbU5/vn3IK80NU96ZEsDV1O6qMoxqzgK4BasxcrkgX6VnqO7I/ps4JmgwrAAAQAElEQVQeCk93hyui84eUcFy9PFzgH9MVXm4Nk9wP1THKmyLQmit90m6NbFuX0TQNJD+PPvooHn/8cdkKhUcuQHd2cREvDp8obMnjxDVbd991l9RhfT6BNmrUKDBU9PDDDwkRYv85Gd91190YrwgWJ1gubGcbrPOjH/0IM86E3caOHQvK6YveSXq4gPq3v/0txowZA7ZHfUwWq1WejuSTbNRDfdyjz2K1gnX45CLzaRPr09OiaRpuVmG1XysPE1+ZQA8cyZqfn2+jN0rTNHRRXjfaz/VfbOvee+/Fs88+A3/lQeM1U0pKCuLj45X3zAU5OTlQTI3Z1z0lJyfLG+MdHBxRXV0t6bobZWNAcXGRhGCLiookfErPqU2xcWqDQPshWpoZ/pFRCIsMFhLi4O2HmD7RcHGyk2uWdYsJEG+QxcVdyvqPGoDYPuGSB1Wfb+ymDOsQA7/o3uA1z20TJ9aI7jFg/S6dA2yLWjyvqqxCbkYOCksqm5TTDuqhzRYVeuR170G9RK+e11hB2UfZqD4xiOrRSX1bCwO9a6zDftIWHnXb9XrNCZkuHxHsDvaXdSK7REqbPLetT8yolzZRnjpZh/IMvfGaGLGM7RBzltnqYHu0m4l6mFiu62abtuSE+m3bpF4db8qyvrRnZ5Xx1mWpk/Y0SQoz6mMdyrGeXl5dbYVfaABYxmRrA21mW6zTOP5ndPGaY6XbRJ0+nWIQ3b8bwvr0QY/uQXLP6e3wqMtSH+833Va2w7bZFlOjDaot4sO22H/KsZwhZ+pjn3jNcybngJDGftjeE4E+DiwGx4XyeruSaXy0CoGO5NFih0louB6LT9Z1795deXRCxVvBMnooSLJIkHjdPJGMcQ0T65HMcIG5pmniiaJOylMHXxXg6ekphIa6KMs61E1ipWmavOWccrSH9TRNkwXX1M/XAej5LGNycHCA/tQa9fFaz6de6mc+E9tkmbuHB9hPtkMCyHdX6fVYzmSxWsX+gQMHguSPbzKnt0zTGjxtJNo9e/bE7t17cPfdd4NPFhIH1r3eafToMdi1azfuv/8+8F1ikRER19ukJu0HqUgOx5tEmN5Gjm0TAeOiEQFT41kbPzGZzQjrOwDTZg+Cv7c9ovv2wtzHb0KvLooImS2InjoGsX2j4R3oi+n3zsXUeVMQO7QXJj18C265dSSs9mZEdo/G6ClD4ePpLL3tNO9OTJjeC46mGrnmR62zE/rPmoN7npkr9UdNHY6wcG8WnTfVBwZh1C0j0NnG6+Xk6IC+E4Zj6twR4pFw9AvC3Mdux6gZI9FTeUdufvQWDB4YISSRik1mM9yDguHq6gB3D2cEBHnDKdgP42+f2diXGQ9Ox8zZw5tM9PR8sD6Ti6eHyE+cFstL+Af1xq2P34rp90yVvrD+uKmDYXWwIjh2kOrjHAwaFYuBM8Zh6gO3CikNiIzAlNvHI8jbETC74a5nbsHMeYMkFNp75ACMntQHrorc4syPo5srJj44F3c8OA4Dxw7A7Adm45HfPYnbfjRF+jnr4RkYOaG/2Bys2nzoxzdLm8MnDcaMx+7C4N7BAHww5NZpuOPp2zH+pnHoFeuJzoMH4c5HZ4os8+bdNaaBMCtp+VVkJbhPf9W/m0FdsQrrO569CyRGLLezd8CAcapvyqZJd03E3U/MFm+UW1BI4/3BcZj71AOYMrUfGD6OjBnScH94WGF19xCbhvboDHfXEPj7ecHF2xkuHh6wWOzYhCSSLN4vtzw2TWwdO28OaCtJjykiEuMfuBU3PzIXQ0Z0g7uLPeSnvhZuvbpj5t0TBNfIPr0w59FZ6NvTH9Q36vbZmDghTETdfL0xamIf9J04TLC95aF+IOaDZ4zBwNH95f7huMy6dWATu6Sy8fGDCHCi/UEhQ6DdI0BiR5LIo21n+AQeSczcuTfh9ttvx/vvz5f1bbYy1+v80KGDivzdhYcffhhcrL57zx7lbKu/XuY0aZfr33JycxEQEKA8hM/KW++XLFkiodgmgsaFIGCSz3bwwZdApp9IRrW9B9yDwxEYHihWdxvkD7NyrXYJcEVu2mm4hXVBoJcZy+Z/hnf+7wN8/M5GBA/pj+7RDfJS6QIfLj7+6B0biGMrluKDF+bj4/fXIj3jAluu4NyfarMTeg0cjEH9IrB/9RocPHgSMYN6IyrQDqs/WYRln6xE0skidO7XWyZaamD/4levw5G9x5B2PBXLlsVLXzqHu2Htgq/w3v+9j0/f2wTvbj0ayCUrqUSPiDooIumAXpPGIzLQARu/3wZ9o2NLXaG0+cGri7Bjx0l4BfjCy8UfI8bHouDAPrz9v+/i45c+xem8WgwY1AXVWWkoqzcjJMwb9t2i4GFfg2qvCAQEesDL2wt5GdkoLmsgpnrbxcUV2Lt6Gz586WMsWBoHvxAfbHttIT55aQHWrj2JoFA/ePn7o+/YgajJOYQP//U+3n7xCySmFCF6xAD4eZjZBZzcugXv/++bWL+3Bn2HdEfGvjgsnv8t1qw+gMCBgxAdZi9y+oejXQ3Stm7Eko+X4rv3vkWFcwBienfSixH33WoZww9eWwW7sB4Y2CcMJJL6/fHhP97D5yv2Y9iM4Qh2b6x2zknKgVXYvP0YMg4dw/YthyD7VZ6Rcg3oJPfLvoXfCZaff7YVXr37oGcPJ5EwVxVg5+cL8eV73zWOCQuy9hxHrYsPYiJ8EBARiEqTK0IjQuHi54dAZcyRnSngT11pFjZ9twmfvvAelq08itCYXjBXlyEpOU/G0i/ED0FB/shJOYzCokpWMdJFINDRPFoX0XVDVCHATZn5GoKoqCg8+MADKkQ6TfbwU0XX9be2thZco8V1cnyib86cOY3bBl1Xw840zr+bjIwMWCwWCSM/++yzsmE1F8SfEbkyhw6ipd0QLeJdnJWO8qoadO6hCIBDDfbvOwGf8G7wDA6Hk0M1TmYVwcPXDeX5OSjIKVCx9lrknkxGYbUD/NybTtLU11JyqfOGm0s9DuxJkO1TKorzUFNZ0ZLoefOs9vYYMKk7tPJcHD+Wjup6FyEpjo5mxAwfhmHK0+LtCpSXlTfVoTwdjRkmZ+mLVngMmWmZqKuvl74UV9bCPcivUYz5vLC4+mD0aEWUMpORktwgz/zaimLBoraiHKeLy+Fg0ZQLPwBugT44ELdD+lhVWICkhGI4+nijtqYKhflVMukPHtUPOQe3Ij9PQ5cenZRnTkNe+mmUlddStdgkJ+qjpKBA4VQNLbcAWmUREvMLwTarCupgcbTCyc0F/p52IIHgG/VZdjrldIM9aGA5memJjSQmqHMIPDp1wdBJw2XfQK4DUM00+c1Kz0KNkzf6jxssmLLQs1aDk109tLoipOdWS/9yjufgdEYBQqJd4e4fhHJ1f2ScLgDJLQmP5uyNQB81IFRwkcnH7CL3S/qpk9JWVuIR5ObXwFd5wKiKe53lpxaCfa5TY8g8psLTaUjLNyGsXw9FtjUk7U9StnmBRNDTvhJHj2dSTNUzo1hhWVWhxiUzHY7uvkBVGdKPHIfZxRMxPXuA99LhHWfHXCoaH61CwPBotQqmDivk5OQEvjOKpCE5JQUeHh7o3LnLde8v78tOnTohMTFRiB8JTdeuXa+7XboBtI+4kRAmJ6s5trAQQ4cObXxoQpczjg0ImBoO7eOzvKgYp7Iq0GVAFzigAvvX70O+QxjGTegOZB4DJ0/2hGSCx8tJLt6WS65Otp+y9wAqnVzQq3sYnO0sqCi3R0l+Pg7vOihp87It2LruAEpKq862o8Jh+oVJO0PurF56lhwZEpOTMx+6V6m6pgYHtifA4h+BGOUl4TqjMyItHurKSqGTAQrYu5WhurwK1cW5OHgqG6E9QhEdFYBdqw7jRFKBrE9yqy9BakZlI8HS22b91iaTs0ujaJmTY+N585OS0goUHD8mWMVvjcfyD1ciLbf+rJjJGbFjh6JzqAuO7z+GvVsPKSzPYHZGys181hPJkGxZfp2U8P5wODO8FR72kndJH2q8ih2aepHMimSbnJx/UB3H9/j+U7Iez9tUhRO7dqHc2U88eeXpp5B3uuiCOkgyc4uBvqN6wVJZgOS0nAvKG4UtI8C/1ZZL2mWuYfRFIuDo6Ii+sbFCtkpKSsA1XKGhIRep5cqLa5qGcePGgfbxC3lwcDC44F/TtCvf2CVo1DQNEeHh4Bo5LoJ3dXHFkCFDYDabL0Fbx6/SrogWvSCFmXngY7WVefnIPnkSR05koOegbkhOOKYm2iqkJedAc/FGn4HdZeH8oCmj4YMC8RCUl1dKWYgKi3Hxdk/Xcyez0tIMpKdVIHb4eKnPdV1e3hc3GWsVhVi/Ih5xu08jdOhwpceC/KxkCRWFudejIK8Azu6u8PBtSqJwxqPl6GyBl/KwsC8ka+xLQKg/uBbHWlWKlKR06D+NXpLyAmxcsh4HkwrRR4Xogv1ddZFzjrU1R5GWkouI3oOVbcGIiu2JbopYpZ/MQmleJQqPpKLO1Q+hjsVIUHgyZOvu5Y6a0mIU5+U26mtsuzHn/CdlRSU4diQdXWK7oFtMAMK6RqFflyBwPDNqbMimUsGHC7JPnBYPj1ZZiIpqDV07+6C2uFKVnv11cmgYF5PyoLkHBcPF2aGxsN7khuCYLojsEokBM2Lh7ViNlGPZYF94f3Tu2RX+kVEYO7gnik8lQicqLPMP9kdYTFcEBng06uOJWXmQXL280Uhi1XjR43m60A69Bg8SLDlGvN+SDmeyynlTnQoN0BY7Nw/YVZXg5JFjSMqvRvceAcg+dhRFdTaksgUtFXlZSFMhbe8gLxScSm4M57YgamRdAAF+M79AsVF0AyDg7uGBHj16oHfv3qAXSdPaBpnhQnMSvx7Ka925c+c2R2IsVqs85RqriGqv3r2aPEl6A9w2F9VF00VJX2dhhnpOn8zGsYMpOJl8ElXl5TiekAJ+E+HExk18GbrZsi0Jwb37YPpdU9Ej0h0bFy5DWmYxMpKSkXS6Ar3Gj8P4mUNBr055UT3qKhUMhcUoVWHJkrLT2LQ6DtVeYVJ/QP8wFCtPWn1lyTm9zy+sRWVlw+RfkneWLBQWlIKPvibs2Ie0nGrE9o1G5pED2LjuKLpOmICb7puJXr1CQILQXOlx1bdKBw8MGx6DulP7sH19svRF6kT7y5qvxMSsJtWcysqRl3EaRQXFOLJlNzKqPBrXKuXllDfKlpWUq9Bcmdi8Zek6nCx0kj5OnNIPFenJ2LftgEzwRTkZOJlaguS4LbLuhyHbg4cycOpU3jlkh8orsvNRW1bFU5QqD12h6n91dY1cw5SP4qJKmBSZiFu7FceyLBhzywx5SAB5Kdi6IQ7l6pskdTRUACoUmduyuqEfjbKqsNxk8w+wrhSJ8YeQb/bF0JkTwXEqys5FvVsdymo0FR7Mg4tfEMbNHSNr5Q6t2YL9xzKQpUJ7uw+ko+vg/ph71zh08avGtx+tQk5Blbo/9oBr1UbcPB0jR3QBCnKRq0Kv9wKSlAAAEABJREFUVSpcm3cqA3B2w/AhnRWhsyprGn6LTp/GriXrUBcULVj2UmPENVVHUhvui/K8igbBFj6J69EjOThyLAv0bB7fcgBcmMuwNcXLlYexPD9PxovXTOWF2TyANpGoZaRk4lRaYWM4VwqNj1YjYHi0Wg1VhxbUNK3NERmoH03TxC5Ns/nfh7bzo2maPH2qaVrbMaoNWmJqgzZd0KSc4wn48vXPsH1nsqyJOb1hI17+1Ws4lNQwoVWXFGL/uo1Y8Nrn+OClTyXpspwU13zckM/yBf/vbXzw4QYUFudj28KvsWzJTnAtTVr8bkiZqk+5T1/4HFt2nmpiV8npNJEh6alOOISv316EOBVyO30gDv/503zkKc+b3t7CxVuRdSoLu75bhff+33yx6YsPVsoieZJDW8Ws//af3hNbMnMrm/SFtuh9sa2zX/X31X8sBtfxZCan4Pt3P8aatQdwPG4V3n3lO1CPkFSF1eJP18p1kQpPUU7HiPn6AnoSncWvvo+PPtwvYUL2g7LUWdTM06KX7TqYLrK0n/3nOi62Sds+eed7WQhOWR1/tqu3WVebKTYvX53e0C3lKco6elDyKMfEsWmClZJJ3B2P7976WPAkNhyzRd8dRN7JZLlHJE/dB8R86ddbZWx5f3AcWEa97yp8jhzJlHsp8wx2lGf5W397G+t2JMtavxNxB2S8v/16M5osOm/Bjm2bDog+3hfUw/uioWM2n6oe7yHar8sTu/f+8kHjvZx98pTcV7zHWDNx+w78849fNLbv7GxFjrrPTqXmCvaUMdLFIWB4tC4OL0PaQMBA4OIRuBiidfHar0INTt4kFPqky+vS4tImE42ex3wmXZahOdZlnp54refLOW1Wk6Berh+pk0V6qquvB8uom2XNz1luq5fXuhxlmVhX16cfdRnacrF1RIeynXWZdF3UwzJeS76yndc8px1MPNflbO2m3DnXknnm40x7el/YBvU16qqtFgIo12dkWc7U2OaZfF6f0SrkhteUY+J5Y5l+ouqxzDZRjrbwaJvPPL2abqNeLraxUOlrXo/XLNLrkIg3yrOASdXTdfGot6XX0a8papuopyV55lOueX392s7egj7jx2DS5N4oOKHCwMpbS3kjXTwChkfr4jEzahgIGAhcHALtjmhdXPcM6euNgE4arrcdHa19u6pCxK/ZBL5u4nxErqP1+Wr0x/BoXQ1Ur6VOoy0DgbaPgEG02v4YGRYaCDRBgF623Rv3YuO6fcgvbAiZNxEwLlqNgOHRajVUhqCBgIHAJSJgEK1LBM6oZiBwXRFQ4cpLad+o0xQBw6PVFA/jykDAQODKI2AQrSuPqaHRQMBAoJ0gYHi02slAGWYaCLRjBAyidcHBMwoNBAwEOjIChkerI4+u0TcDgbaBgEG02sY4GFYYCBgIXAcEDI/WdQDdaPLyEDBqtzsE2hfR0sywOljPvpkbV//HpGnSprOr80W3y7pMV99KowUDAQOBS0HA8GhdCmpGHQMBA4GLQcB0McLXVVaRLLfAQEy/awY6d/aDyc4KT18vuDjZXVWz+M6i2CkTMPPemXDx9GhVWxYXd/SZMB6zH7wJ0+6Ygtg+4RdN0lrVkCFkIGAg8EMIXLDc8GhdEB6j0EDAQOAKINB+iFZ9LbgH3vH9x1BeXA7f0BDM/fE9GDG6d1OypQgZvU/0fAk+Z64tdg1dZT4Ty0jWKMtEwqZ7n1jOvIbkQtHGpNehPDNtZXnOvIiY4Rg3vidqCzJh5xGAkdOG4EJ7D7KOkQwEDASuPQKGR+vaY260aCBwoyHQwD7aSa+t9lZ4efvCwScA4X1i4O/rCNmk2M+7sQcmsxmdBw/BoL4h4kVyD+6KsTNHCdGhp6nXoN7oHh0IkqLOgwdJGcuHTB2LsCA38ZRF9B+EGbeMkLLBAyLgZq4W/WazJhswj58UCx9PFUpUnqtuI0aKHHWMG9tTSF9ZTQ5WL14Dbvuyc8tB1Jhd4eHjAZ3IibK2+mHYZSBwAyFgeLRuoME2umogcJ0QaFdEy8HVC+H9uiDMvR7c5LeqqgpZGQXIrm760kZ3fy/E9IyCi7MVXQf1wuCJg9Ar1hOObq6I7t8Nfu728I2JxcxbB8BUWYTTp7Lh4h+CwZOGwNXJDUHh0eg7vLeUpec2kCyOT3DPWAyfPJCnyMkvhV/naIwcFS1yWWUaOg8dgogAC7hX4uE9B2F290GnHuGoL8lFQU5Bk22CRInxYSBgIHBdETA8WtcVfqNxA4FWIdDehdoV0dLBLi4sQ1Z6FvILa5GedBrJaYV6EbgfXEbyaTj6eMPVyxudeoUg+WQBgrv0hV+QHzT7apzMKkKnYT1hLsnBxlW7sXfLPhyKPwYXvyAEBTWs+crLOI01S7fj+OETKKq1IKRrECbPjkXViQSpU1JeL206uDvIMfvgYSz5cCnSclW+CnNqdnaI7tsLPSLdEb92J9KM/egEJ+PDQKAtIWB4tNrSaBi2GAh0TARMHbFbaQezUOnkgqiYaAS61+DI0m9R7RWGXn0iUJOZj+yCarjZO6I8PxO1xZVCzgpyigQKe3t7ObKMGwhXVzd4tDw9PcHk7GJBdXWNbHqclXgE33y+Ay5hUZjz4CxMnh4LB4tUh8UhAjF9OiHt8GHsOpgOYz+6BlyMTwOBtoRAx/RotSWEDVsMBAwEOiTRKi3OQNbpOgyfPhg12ZnYf7AImfk16BIbicKMbFQUFaKoshyOnv6oczADmhkePm7gT2FZy5CcOHgCi7/cAo+evTFsQBRYJzgsEP6WInz99iJ88ta3qA3phgGDA8Cf6opk7PhmJXau322QLAJiJAOBNohAR/No1dbWIiEhAcuWLcPmzZuRm5uL+nrlZW+D2LdFk4jXZ599hsLCs1GSy7Hz0KFDeOihh1BdVXU5an6wbmlpKdavXy9jz3vgByv8gMDf//53fPvtt+dIZWdn45e//CXuuONOub+u5L1Fu48fP441a9aguLjknLbbc0bLrKId9IhPINZUViC6ix8igt2bWlxbhIOnsuHgYo/kfdtRXqWIVko2XExVKCkoQFm5+me0ehdMnoGYOXs4+o/si75DuqMs9QTymoX4apTzispLCktxYtt2dTOfQv9ZE9At2hdWTx/0GTcCI0dEI6BTpNJfgpxTDRXq7RwRFBWkCJwHqxupDSNgmHbjItCRPFplZWV4++23oU+S8+d/gBde+BcOHjwITmIcZR71xOvmiWX65MljS9d6HZYxUU7Pa35kuZ5sy/Q8HvV86uG1bdLLbI8s12V5ZBmPzGfiNRPPmc9zHnnNcyaeM4+J53pitOLEiRPg+t/U1JN48803sXv37kb89LqUZ11e2yYSni+//BIkayRXNSr6kZ2dI+tzWYfJVp46mMfEc9synjNPL+ORSc/TzynH84yMDBSo+U2/5pFJl+c5E2X1xGs96XIsox7eT3oZj8wn+WI7v/nN8+jZsyf4RYX5TKyvy/Gaidd6YjnzmHjOlJGRid///vcgIaVcUVERMlQ/qqoqeSmJ8kyUlwz1oV/zyGRbporb3G/7IVrK61SUk4G0hBM4nVOMqsICbF13EGUugejayb/JE30mTUPmrjjs2bgP++PyUVVZi5SDCdiwJgGnUnNRp77hZR09iA//ux71XoGyQL48+SDWrdyO4rIi5GclIzslp3GwuPD+VFIaastLsX/9Ouw9XIRQPzek7duLjRuOwCumB3r0CsLhlZuw/1iG1DOrEKSjixP0UKRkGh8GAgYCbQoBThRtyqDLMCY1NRUrV67EE088gVdeeQV//etfEBISLESrsrIShWoS3rZtm8jwSO9N8wmKHoVjx44JscjJycG+ffuUd6FYrpnPck5s9GxQB9vbv28/qL+56fQK7dq165z2OJnu2bNH8umFyVCTLe3IzMyS9mzrNPdssO3Dhw+D9Vk3MTER5eXlYB49IZs2bVITdabYy7y0NPV/W3n5Tp48JTK0U9fBPKadO3eC9Sjv6uKMUaNGSVf279+nSNYe0J68vDzReerUKfVle714XY4cOdKk39R79OhRUB/tS0pOVtGMhqUnJBK0j5gROzZQo77F037mM5HgMY9lemK7rEN9xJq2JCu9zKPXkvnsE+eZXr16qfEOEbJFbyZxrlaeNPZL1817gPbpujhGbKu0pARxcXEyJiwvUdfM1xPHh2NP0uni4oK62jrQVt4ftGXjxo0oU1419o3X1E/bqJ91iY3eV44b7WHfiHFcXDxYJzMzE4GBQejduzecnJzEE6vjTX1xyj6SP7ZL7PkFgv1kGfvIvur2trXjJRCt69SF+lpU5GZh1cKVSE0vAhe9H928CZ/8+0Os2HBUyJNuGYlUUfopLH5nEWShvKqbdWSf1JVrCqq8tLgdWPDqAtHxzcLNisBViN74Vaux4Mu9lJLrxF17sHn5ZuQXVogNy975SNosLS4FZWkD07Kle1BSViP1dFvj4lPk2vgwEDAQaHsIdCSPlsVigbOzMzgJcTJ2cHDEjBkz0a9fPwldLVAhscWLF2PLli1YsuR7fP311+BkB5sfTuSfffY5KhR54eT34osvij6uVX3//flCOjgh0rOxfPly0fXue+9KPidUXRUnbupftGiRmkS345tvvmlsj5My69MO5r+n6ldUVCivxkEhiEuWLBG9r7zyKlavXiUTrq6Xdnz++ef4z3/+g3Xr1iFZkQ5O6AsXLgL1fv/99/jgg/koKS7GqlWrsGLFCpSVlWPp0u/x73//GyQCvKbn78iRBGzdugX//Oc/JUxGIpChJnvKcYJnysvLRUpKKkhaTp8+jffee1/aXbt2HRYs+AwknyQRtK9OEbr09HRF9DIksS2SgpKSYiFmtO+TTz4RMsP+7t+/X3Qwn/o++eRTJCUlNekv9f/5z3+WfmzYsBFvvfUW/vvft5W+tSp0t0VwINmhfcSA48dzetSWLl0Kkr358+dLSJGkZ6EaD2JE7Dk2xJpeuI2KoH788cdgGxs2bAAJKPukJ34hyVCepry8fHXP5ONE0gkQD+qm53Tjxk3IVWVfffWV3FvUT31bt24VMsp+vPrqqzJGq9T8yjE8cOCAjB/x4TjmKTK7X5FbluXn54MkmXhTnvq++OJLdT+sBvvx+edfiPeWRGuVGmfiwr7q9ra1Y/shWjbIkUjZXBqnBgIGAgYCl4QAJ5BLqtgGK4WFhuKOO+5Qk+oRcPJ7//331ESWhICAQDUxJgl5ufeeeyVUc+uttwiBoldAJwrsUs8ePZGbm4OTynPDiZWTcEpKippc84QExMbGKv0J4nkaPHgwbrvtNri5uYEEjuE26mDipLd9+3Yp/8Mffo/77rsPJEkkAR4eHpgwYQLmzZuHiRMnioeIEyvrubq6Yvbs2fjdb3+LYcOGiqfJ1j7KMHXu3AU///kvQHs42drbW3HLzbdg7Nix2LFjh5CjHj16qP4nqwn7lNjPCZrkIC3tlNgSHR1DVeIFeoqW9KkAABAASURBVPjhhzF92jToxNvX11ds7NmzF6ZMmYzw8HBFbtYoMnhI7Js1a6aEF0ly9H5brFaMGT1a2T0MxGbAgAFwVGSXjcyaNQvPP/+82Hf8+AlkZWXLOrrq6irBaPbsWYpAFIinrnl/6UG6+eab8etf/xrdu3dXnrUaPPDA/fjTH/8gD2iRaLINPYWq+4DjQkJF0uzt7Y0hQ4YIFsSKthF74sPrBi/cLiHkv/3tb/DYY4/B19dHVydHs9mM4cOHS/t9+8YKBo6OjrCzs8OkSRPx058+C29vL3WvBaiyWdInf39/uU+KFenl/eHt7SPru5599hnBk164qVOngvbedNNNiIlpGA82WFNTq0jfBpCE/exnP8VvfvMbDB06RBHjbSDRpwzrPfPMM6KTdhxRHkbmt8XULolWWwTSsMlAwECg/SGgT6ztz/JzLTaZzTKRP/bYoyr8NVIE6DHarDz/nEz51HRkVJRMjgzReKsJOCsrC/TEiLD6CAwKVGEbZ5nwq6ur1eQ2VJGWFNDbY7VaEBwcLF4hensYsqEXJjc3F1arvSIAtUpDwy/10sMWFhYGTdPQpXNnzJ07F35+fhJy2rx5s/IyLZWJmESF4S/W9PDwhJeXFyxWq8gWFRWjvq6ORU1SeHgYXFSYj/VIBEkYFyiP3dq1a8WrV15RjoiICOXNKkN8fLySdUH//v2xX3mRGMZj33UyQULgq4iVxWpt0obtvUEbEhKOgMSTniMSB4ZWWeF8ZJ1LWFju4uKKCEXUSAbc3d2ZJQSCGNJ2YkjvEkOgLGRbPOqJXkra6+joIMQqMDAQrip8Z7FaheSSQNaqUB7O/GiahkGDBiEyMkp5vTbJPcGxp7eNshy3jz76WMbYRelhP9h2uLKR5Ic2+vg0JVpnVDceNE2Tc4b4aA+PVuVRLSsrU963laC3MykpWeFfrkK7FULOe/Xqqe4tJxlfEqweitTbYqxpDTqpuLa2BiSkUep+9fDwUPeXVfUnkkWgvSR+ISEhku+gyKyLwpj3ggi0wQ+DaLXBQTFMMhC4yggY6s8gcL5J8kxxuzrQu8KQHCeg0cqzQq8FJ0+SkFoV1iJxqqtrIEM1NdUqpFMlHhzNdHYaoEcpXJGYdevWg5PZuHHjlIcrT3mdNqBv375wcHCQ/K5do3HPPffg8ccfVx6FX+EnP/lJk/WonLAJnk4A2AYn1dzcPOWp2AhOoLfffjtmzpwpkyVlLzW5KLIwfvx4seXJJ5/Cn//8F/Tq1QucoElQGL7ikX0hyWIYiuFUqyIqF9OmnZ0Z3brFNLbzW+V1oxeMmFyMHl2WRJTjRAxpNz1WU6ZMgZ0iLLrMpR65xipJhfeIDclcvSKrxJ+kkt5FtvnTn/4Mzz77U/EosW81NTXSXH19fRPSLJmt+DiVlgZ60UaPHiWe1f79+6l7wqruMU2Irq6fqmiLyXSWWDHPNrHcXnkped/q+SRStYqA8b7U89rL8exfWHux2LDTQMBAwEDgCiHAf+hXSFWbULNgwQJFitaLLSRWJDYkFCQWeXn5ElbjomF6uHJViLBr165CnKSC+uDkH648G4mJx+CoQkMM57i6umDt2jUSfqJXhkSusLBAhboKERjgj/T0NMTF7VW1z/5Shu3r+SQ3fBry5MlU8eawHXpZSA7z8wvPVrzIM4Yt6VFp8LhZQVu3bt0inieSDHpmEhISVCjMV8gXPWQMtZGIoRU/dYqYkiCYzGYJCXKheGVlhYTJkpOTlLcvFSQmzVXVKmJ7oSUuLsoD06lTJ3BxOW32VaE6jsnJkydxueSf9nJ9lIsioD/+8Y/V2K1FUnIyONa8B+hJCw4OUmSqBjt37hCvGGW5vosELU0RpqNHjzXv0g9eV1ZWIj+/QO4bk8ks2NBTZm9vL95EfgkoKixUodx0/Oc/L8taN72v9GraNmBWeDP0yrVfaWnpyitWLh44s9kOvD9tZdvDuUG0WjNKhoyBgIFAh0RA/0ffETrHp7XoWZo/f76sfXrwwQfBCWvGjBmIjo7G00//BO+++x4mK68JZebMmaM8NN0ktKf332QygeG+IUOGysRMbw3X9Pj7B4gs9fXp0wf0vHBRNnX997//lXVOrKvrIdG6//778emnn4KepHfeeQdchzNo4ECMGDECn3zyiXizSHpCQ4OFGJHEOTk5KpvtRA0naDc3Vzm3/SApYKiKea6urqLXZDLj/vvvE09Krgpleri7i6eM/WYYLUKFEUkchwwZLP0ICgpideVxsRdvi1yoD7OayBmqMykc/FQ40VelF198SYXgNmPMmDFgn0heuGZq2bLlcBR7zapmw6+DIqdRKty1cuUqfPDBB2AI09PTQwo1TROb2EeS3zvvvFM8e9RFbDZv3gJ64cyKZEgF9UFCyv7SHnUpHkX2gx5CXrOM12azSUgmx4vkde/eveD6pVg1ViTLa1VIld6sp556UmH/qdwfzz//G+VtMoH5bJ/r13jkeqjQ0BDBhm3YJldFutkm80wKI55z3HjdSfV7+vRpysP5Szz66KPIzMyAxWJVhK4O99x9t6zBun3ePDz11FMqLOwrxJVEmGvF6M1btmyZkrcIUbOzs2C08srOnDlD6XpEws5cg3XvvfdI+JQY6vcAHWO0i/cL7WiLydQWjTJsMhAwEDAQuBYIcLK4Fu1cizbMaoIeOXIkXnv1VZlMP/zwQzz33M8QEREhZIqE6c0335Cy/7z0EijLOra2aZomBIsTX/9+/aTeSEWMXnnlZfF8UJYTO9fYvPZaQzskIpwsNU1jsSTqpRft5ZdfbmjvP/8Rj5jFagXrkpzxybg///nP8q6qLl26yLoihrSCggJFx+TJk2VRvJ1NKI2TKWWmTZsmMpqmCTH8xS9+DvaX6ZGHH5Y1XrRh6JAhCoPnhNBomiZE7G9/+5sQFpZPmjQJ99//AEhwqJBt/+tf/xLy4aw8QnzZ6DvvvA1iRxJDcsQ2mLhwvHPnzoIR6zJR5xhFEN57713ceccdiI2NBfWxD7zXqOfRRx9THjYfWatE0kEcqI9jRYJKPXrqrUKgf/nLXwR76p49ezbuvusuWYdGGWJB+7mu7aGHHgbJYM+ePaVNEj43RTjZBz4kQQI5bNgwvPHG6zImHD8SZuplP/70xz9KPseM3kfizzb0RPvZxn333itZoaGhEkbtp0LKmqYJ5g8+8IC8Q4z9531Bcu/j4y3h0Od+9jOwnyy7//77hTBxPElcP/mkgZAPUeP15JNPCj6063YVXqZ3jvX+9Kc/CVkjwSKGDBdTxsnZWZGxx+ThBTGsDX6Y2qBNhkkGAgYCBgLXBIGO5NEiYJqmgQQhQIX06I0hKdK0BgKkaZpM2Cxz9/AAJynWaZ7s7OzEO2KxWqXIYrWqUJl3E0JBGU9PT1AXvQma1tCGVDjzQf0M7VGGC6x5zSK9rm4f109xwnVwcBD7WE452k47Ne2sbk3TRIaTraY15GuaJousqY/JYrWyuiSL1SryetuiU5EPTdOknHpov17OtmmPfs1y6qR9rMByXjOxTNMa9LBMTxarVfDiOLAe9WmaJvixj3p7mqaJ14i6mGibrkM/WqxWISS0R9M0IVjUy2vKEF9dH4/UTz1skzKapgk2lNOvORYcE44f86hH07TG+4ayTNTDMj1pmib3BdtnHrGgnMXaFG/2he3THpZTTtMaiJheRlyoQ9M08WDRHrZH+1lHt4tH6mI9EkW9DnUTf9tr1ud1W0ymtmiUYZOBgIGAgcCVRaBlbfyW3nKJkWsgYCBgIHBlEDCI1pXB0dBiIGAg0A4R6GgerXY4BIbJBgIdHgGDaHX4Ib60Dhq1DARuBAQMj9aNMMot95FPBjK1XHrlc9kWnwhs6SnFS21N18mjroPnfLKURz3vco+0mW+z13XyyGv253J13wj1DaJ1I4yy0UcDAQOBFhEwPFotwtKhM0ka+IoDvrhz/fr1IGm42h3mizy//PJLLFy4UBK357ncNvnqBC4U57Y3XFBPnXzikq9R+Pa77/Daa6/J1kHs7+W0RdLG13N88skn+Nvf/i7bDvHFrZ9//jmefvppPPPMM+ATjCkpKZfTTGvqtlsZg2i126EzDDcQMBC4XAQMj9blItj+6pNc5+XmgcQgOTn5mnSArybgi2P5dObhwwnyhvrLbZgvX+WrHPi6Db5Fne/k4lvw2adhw4arNg7ItkuX286Ro0fBfQn5hCJf2Priiy+C78ziqx3Gjh0rW/d4eLiDr9S43LY6an2DaHXUkTX6ZSBgIPCDCHDS/UGh9ipwA9tNLww9PEz0vth6dfgkGwkDX39wpSCiV6ywsFC2JyosKADbt9XNd1lx/0G+EJTvgOJWRLbll3JO0nbXXXeJ14pvdg8KDAJfyTF9+nQUFOSLyivRR746gnr4pCDP2QcHB0d5PQhfjxEeHo558+4AXyUhjRof5yBgEK1zIDEyDAQMBG4UBAyPVtORJmFISkoSb48tOaEUy/iW9YyMzBbfhk6ZtpAYUtu6bZu8ZJShwY0bN4JvO2/enytlK/XSY8VQ5DbV7tfffIONmzbJS1j1NvjqAb7BnvsN0hPk4eFx2Rg6ODggIiICJ0+eBF/Z4OHpCXcPD/AloBwnvpSVbWmapptxSUfqmTBhgryxnh60W265RV7zQNJ1/PhxCb16e3nK6ysuqYEboJJBtG6AQTa62CoEDKEbEAHDo9V00LltzqpVq7B69WqZWG1LGS764osvERe395wyW7nrfc6Q2s6dO8EtXAYNGoysrCxwexkSsKthG3F56623VHjtILgfJBeIz58/HyQ7JKdsMzX1JDIzM5VNA2XrItqjl7H8YhPJHXXybe7sJ/vGrYdIfPLy8sCQHrcP4lheTju6XUVFRTh8+DC4+wBfiEqdXAzPPMrYK9LHo5FaRsAgWi3jYuQaCBgI3AAIdCSPFic/hqx45CTIc07IHEZO/rzWE/Mpx2vK8pxyzOc1E0kXSYRtGSd05lOWSa/PI+sysS0m5lEP6zNRFxPPWbd5Yr5tHeqiDI96Po+8Zj7bYOK5baJ3iQTEU3l3+KZ3hulIFJrYXVMD3Tbm6zpt9ejn+fn54h0rLSnRs8458iWbHh7u4k3iyzW55x9DiRSk7l27doKeNV5XVlaBdmvapXua+AWBxErXSeyI7fbt24VUsp2amlrZI5DnLSXaRQ8b13ZxXFuSYR7L6K0jeWUoltv5ML+4uAR8qIDnmnbpfWH9jp4unWh1dGSM/hkIGAh0eAQ4YXWUTnLS+/Nf/iJPmz322GP4+S9+gR07dsh6oe+++w7/+4//wzPPPos33nwTfApuzZo1ck1ZPqGmE4mqqipwwv7Vr36FRx99FIsXLxYdzXE6duwY/vq3v4P1f/u734EEp6y0FHwK7u9//19p/4EHHgSfjKOOH//4J2DipE1SYKtPn8xpH+vQnuLiYgmvsR32i/l/+OOfxLNCYsG9BJlIvmx1cT3Rxo2b8YdKrj8MAAAQAElEQVQ//hEkBVz0HqFCbE6Ojo1iXJhOkkGyRa9MTXV1Y1nzk5ycHDAkWKi8Os3LeM21S9wKh+ul2C96laKiItGpUyfZS1DTNPF0MXy4Z89ucH0Yt5ppTvJJfGgrnxrkE4p6omeM7dgm1h00aJDsDch9DcPDwzFmzFhZmM41aJtU6DI8PEz2k+S1bV39nPc+Q6rcb5L3g57f/EiiSaJKzHmPeSgCy/YtFjuEq3Z9vH2kn83rGddnETCI1lksjDMDAQOBGwwBThgdpcskK3Fx8bJe57e//S24WHrRokVITkmRsFV8fBy4gfHs2XPA8NqSJUtkIv75z38unol333sPdbW1subG3t4BJA7cI48Tf1x8fBOYGAb7+ONPhDT8/ve/B/fKe/vtt5FfUCDru0pKinHffffh8ccfw6uvvg6u7fnJT36MESOGY8OGjUhNTRUSRaU6wSBhoH2/+91vxStDbw0JANt3d3fHH/7we9BrtHDhIpAMkmgM6D8AJrOZaiTxg+G7J5/8Eb74agO4Zx89S926dZO9+FjOFNunD+6++248+OCD6Nmjh+zFx/yWUoQiEw8/9BDoGWupXNM0cB0TMfmHIrOHDh0GcQsODm5ctxQRESHYT5wwATNmzIBtma6TxIfkMjk5WV6hQILJVKAw1WX0o6ZpoE7uBThu7FjMmjULoaEh6NKlC6ZNm4ZRo0bjnnvuEbtwnh8SsF69eoE6SJ7OIwZ/f3/pD/cgJKHkYntN09RYeEi73brFNPbzfDpu9HyDaN3od4DRfwOBGxgBTm4dqfvcD27cuHEy4Y4ZMwZms50slmYfSUxGjhihJk4/mci9lSdi1KhRQshuuukmkHiVlZfDarUiNraPeEeoIzg4BHFxcVQhiZ4NEoDs7CwhZfTCsN3s7GwwZMf6JHl80m6Eas/T0x2DBw9WpKybpNraGnlSTpSpD03TQM/IvHnzZC8/rqki0Ttx4kTjBE6ypESFHD300INiI9cK9e7TGyQMLNMTPVUJCUfw7//7FSIjI7Fw4WKQcOoeO3pouFieITMmnpP41SqSqeuoUaHFZcuWKYJxJ2YqEnO7so0EiQvBmU9yqMvyyOvorl3x7LPPCJn89NNPcfToUcGHZSSNbGv3nj3iZdy/b794FVlXT+xHN0UIH1feSG7ArKeBAwfqIo1H2rdlyxboOhnWYxubN28Wkrp37x450hNHPBornjl54YUXMGXKFMyZMwd8GpLk6dFHHxPCfUZEDrSdxI/6pa3du8XbuWHDBgmnMp/48frQoUNSx/g4FwGDaJ2LiZFjIHCDIGB0syN5tPTR1PtEssJwFb0/LONErplMILmkl4SvGbDY2QmZ8fb2Fi9ReXmFEBfKso7FYpEnzBhi47We6D2jB2fduvX45ptvhDyQWJFw6TKapoG2WK32opPnOPNDG86cimcrIyMDH330Mb7++hshD7wm8WFYjt4aPj33xhtv4JVXXkViYqLU0evbHmnnggULMGjQQMyePRt//evfFJG4RTxqGZmZIko7iItt0vsrAupD0zRZ+P3UU0+CIdRfqDDsr3/9a0WknpV8JdL4yzYZfixSoU6uzyJZYoiNxIehRAratsVzq71VsGGZnthfEtq/qnDsr59/HnqiHl3G9sinDqnrQon4cQxt6/GcxOp51Qb7xcS+kcB6eXmxuEmyWKy4UBt6WUvtNFF0A1+YbuC+G103EDAQuMERsJ3wOwoU+nqagvx8WQzt6urapGt2KtTGMBi9RCQH9I7Q++LvH6AmVAfxwrCMJIG6+LZxEjFbJdTJ0NVjjz0KekcYomOokGEmW7nWnHMM+EqJwsICcLJneKpr1y5SlSSR7d966634zW9+g8DAACF2tI0Eh4RPBM98MJ8EkB4ykqeAAH9MnjxZPGZsh2IMQ9JL1K9fP3A9V1fliWIoj/IsZ+I5w4HDhw9HTEw3IaGxffqA18zXNI1iQvhIshg+5XowZpLIVVVVS536ujohsnwykG0RY+LGEB+JEuX1xHphYWGYPXsW2F89sX1dRj/aKYLcv39/sB+2ibqjo6PB9pjPMCrJn15PP8bExEhfdJwGKF30Ojo5OekictQ0DWFhoY3tUC/b0PtBDNkOE/sklYyPcxC4bkRLM2mwmOxhUgN5jlVtNMMwy0CgoyLAb6Mms7mjdu+8/eLkdt7CdljAl3NysTm3ZOH7nLy9vYRk2HbFTnmpGHYzmczgtipcUE6ScPPNc8GJtqqqSha2czH2u+++K0/IcULVdZjVfdKpU2dFegLx/fdLZbE7Q2UMZVVX1+hiF3X09PSUdrgeizYxXEU7mBieordr6dKlKCgoREhIiHjI6OlZv3691NMb44J3hi2Zz/AmCRwTCYWtt4YhMRIyhkvpIdPrt3QsLy8Dw2/lFZUtFYNeIxaQlKamngQX2nt6eoB2WFUYVsoKCxEfH6/CuKlSzhAr822TpmkgKSI5IunRE8mirdz5ztk+8eNDCTqpPJ+snl9aUgp6D6su8DCALstjQUEB6HVLT0+TdX4t9YNyRmqKwHUkWia4eNrDzt7S1CLjykDAQOCaI+Dq4QJ7pxvvb7G1E9I1H5BLaNCkwoJWq0UWbZNwhYc3PHUWEBAg662GDBki3hVN09ApKgpzb7pJFs4zZMUXUk6dOhVWRcLoteE5vSZ8bcG8efNEnmVjx46R9V++vj7K63IbunWLEa8ZZUne3N3dxPvBRdbMYzfmzbsdfAKP54GBgfKOJx55zUTi1rVLF1lYzTAUw4/05tB7wpAhF+/Tw1VeXg4eZ6uQoEXZSYJDeerQk8VqxcyZswQDPk23d+9eEBeuT/Pw8NDFxNtEL15KSqq85qGxoIUTepn4YAD73LxY0zR06dwZTz31lCwO5ysX6CHkQvuBAwc1LsBPS09HQkKCkF6+ToLr2ZrrusRrqcY2U1NThfxw7CXzBz6Ie4+ePeQ+sMXmQtX4lCKJJDEhWWU/eLxQHaMMMF0vEDjIETGR8PL1vF4mGO0aCBgInEGg56DeoDfjzOUNc+Ak3FE6S9JosVgxdOgweWKQi5xJcEh4YlXYa9DAgeIJYn8tVis4yVKGJIJEiwTHYrWCcrNnzcLcuXNFD8NCFqtVnszj4nk+Ycj/3wwpzZw5UxaoUw9DVgyHcRsYeZJPhbc0TQMX2nNRuqZp4gUbO3asHDVNoymSnF1cQN18Uu7mm2+WyZ+Ej+3wabo5c+bIU3Q8MnTF/KGKOA4bOhTsnyg58+Hv7wfKjRw5Etzzb8zo0SAxYJ0zIsjMzAKf8GuNt4j1SOp41OvbHi1WK4YPG4bRqh22SUzYpqurS6OYl5e3eLJee+112abH39+/sexyT0h0+AABCZa3t7cQy9bqZJ8sVqsQ8NbU8fLyUmTusKyVo5eP/dC0s+PYGh03osx1I1qapiGiSxg6de8Mq4P1RsTe6LOBQJtAwCfAG8OnDj5nwmoTxl1pI5rpIzlpltWuL61WixpHs5Bmkh5OpOyQxWpt9K7wmolllCHBtiUrFmuDrF5GOcprmiZhMltZEhASNMpqmiYTtsXaUJ91mOh10utQF+vwyDLbRBnawnKL1SptsVzTGtrVyzRNY7b0x2K1yrnth6Zp0n+upSKRclYkzrY9ruM6ciQBXFPEtlj3cu8Di9UKkhy26evrK7ZRLxOJkL29VdorKyvFunXrkZOdI+u7WH65iWvVGAb1VOFXd3d3Ucc25eQKf9jb26N7926ora254v24wqa2KXWm62mN1cEeM+6egl7q27TF7rqacj1hMNo2ELguCHB9ZECoP+7/9X0ySVwXI65zox3Jo8UFzvPnz7/gu5OuM9xtovkDBw7IW9r5tOT69evlNQUkKleLnLDTXDtFb9ff/vY3ef3D0WNHcaGXpLJOaxJtpmeJ6/KWL18ur15Ytmw5uP9ha+pfjExtbS3YBj2Nf/jDHzBp0kQcTjj8g6HXi2mjo8ped3bDbxt3/OgW3Prju9B7UC/wH7+nrxeM1CYwMMahA96L9GBFdonEuLkT8NAvH5QXHeIG/blcT8YNClu77nYfFUb92c9+Ji/2ZLizW7duoDdI0xo8ZVejc1xrxlAl32LPxfyhoaEwmS//4RNNU5GhiAg8+cQTZ0K0UejTpzf8lFftSveDX0roVZR+VFdL+Jd94VOsV7qtjqbvuhMtAkrP1uCRfXHn0/Pw2B8ewVP/84SRDAyMe+Aq3QM/+sOP8PDvHsS0eZPgH+wn4R7+Hd6IiZPHjdjvG7nPEqJ0dJRF/Ay1cXF6yQX2MbwSWI0fP17WhPGFpQy/6evcroRuhkUdVH/4RGBwcBAYGj3fdkGX056maRg7Zoy8bJZPHtLD1bVr1yZh0svR3/q67U+yTRAtwqZpDXF1xrl9A7xhJAMD4x64evcAF+pywuHf3o2cDI/WjTn6FqsVAwcOlH0aueif66quFhKapsnTnXySk09+8rUNnOeuZHskW3zq85FHHsG999571cLH7h4e4GJ/PhE6bNgwXE3criQ+11tXmyFa1xsIo30DAQOBGw+BG8GjdeONatvsMb/YMPTGY9u0sHVWkdTxAYj23o/W9fbKSBlE68rgaGgxEDAQaIcIGB6tdjhohskGAu0MAYNotbMBM8y92ggY+m8kBAyP1o002kZfDQSuDwIG0bo+uButGggYCLQBBAyPVhsYBMMEA4EOjsBlE60Ojo/RPQMBA4EOjIDh0erAg2t0zUCgjSBgEK02MhCGGQYCBgLXHgHDo3XtMb8GLRpNGAi0KQQMotWmhsMwxkDAQOBaImB4tK4l2kZbBgI3JgIG0boxx93otYHAWQRu4DPDo3UDD77RdQOBa4SAQbSuEdBGMwYCBgJtDwHDo9X2xsSwyECgoyFgEK2LH1GjhoGAgUAHQcDwaHWQgTS6YSDQhhEwiFYbHhzDNAMBA4Gri4Dh0bq6+BrarxUCRjttGQGDaLXl0TFsMxAwELiqCBgerasKr6HcQMBAQCFgEC0FgvFrIGAgcGMhoPfW8GjpSBhHAwEDgauFgEG0rhayhl4DAQOBNo/AjejRqq+vR1FREbKzs8HzNj9IysDqqiqxt7S0FLW1taioqLig7ezX+WQKCwpEF2WU6lb9sv3U1JNISUmR9ltV6SKE2Ce2cRFV2oxoZWUliM2pU6dQXl6O9PR0sC96ny4GZ9tOsR51ccxt89vjuUG02uOoXXObjQYNBDomAufzaNXU1CA/Px+ZaVnIzsiViaMlBCjDck4qnHAo3zwVF5e0VPWK5x04cAAbNmxoJCAZGZlYt24deGRjtO+rr77CiRMnEBcXh5UrV6KmuppFbT5l5+Rg6dKlOHr0KPLy8vDhhx+ipKT0vHafPn0an3/+uUz8zYW2btuGb7/9Fq0l2RzbdevXY/78+Vi2bBmIY3OdF3tN8kCiy/uMhGLfvn1gGyQoF6vresoTi7Vr1wo2a9asESJK3AsKC3HkyBHpU3FxcatNLCsrP0H16wAAEABJREFUExJMHDg+n376KRISElpdv60KGkSrrY6MYZeBgIHAVUeA/8ybN0JitGPdbix8YzE+eWkBvnjjCyz9fJUQL1tZTjIrPluNrau2gxNmetJpLPzvIqnDeno6uPdoI/mxrX+lz+lR+Oyzz8TbQ3Jw6NBBvPfee+CR15mZWfjoo49QUFAAEpHjx0+gtq7uSptxVfTRU3LiRJKMAcmxs7MzTCbtvG1ZLBa4uLhA086VoZeEJOC8lZsVEK8lS5YgIMAfw4cPh9VqbSZx8ZeHDh3CokWLUKgICWvTXnt7e562q5Sbmyvks1OnKAwaNAhVlVXqfjsMEib2ycnJCWZT62gGCWfisUTBhcSa1ySgJNYtgtKOMluHQDvqkGGqgYCBgIFAaxHgpG0ry2/S+7cfxKqFK5Gemg5XTxcU5BVgw5L1WPvFJlRVVDaKk7gciU+Ag70dzGYzMrPycOJIkpR7BXpDT45WO8m72h9hYWHK25OPrKws8bocO3YMmZmZIAGrUqG3pKQTsFisCAwMFFMKCwtkknzttdewffv2xpBYaUkJ6J1gPr1eJJ4kauuUd4z5JAhvvvkm9sXvE4IpytQHZXSvGnEsLCjABx98IJOubRkJKsvoVXrxxRfFBob5lIomv5Rj+7RjvfIosQ8UIDkm+aFOevB27twpRJY6SIjoAamtrRNCSXmSYNr13//+FySiDJsyn4l2sh8se/fdd8WbwgmeZUzs+/Lly8WrkpiYKMQoX3k66RlkYh/Yl6SkJFAHbSWW1Es9JIjEjP388ssvRT/tW7z4KyxZ8j0++eQTlKlwKPtKcsI2WXf37t2gLurUw5WFipSxv5s3bxZcWc4ytqP3kX1gnePHjzeOJ3XaJtahLbSNbW5THj7iQzzpZaMOYsnEvrAdyrPMVg9xWLVqlWBz4MBBuRdM5gZKoWkmuQepv0aFeokxsaJHkPrYB7Zvqy85ORkffPiB4MJxzMnJlWL2m+PGe+6A8trSTvaZ40i7Xn75Zblf2ZZUaIMfDai0QcMMkwwEDAQMBK42Apy0bduoViHDkvxCuLq6YcbtM3HXM3fgjifmiciJhCMoLi2Rc/6jP74vWc5jBndDvfIMlReVKiJjwaDxA3HrYzfhzidvldRzYA9o2rmeFal8BT9IoFxdXSW8xkns9OkM9OvXX8hBYWGRTIiRkZHw9PSUSXjPnj0qhBiP3Nw8/PWvf0NaWrpMjp+pkNvChQtFZsGCBSrM9g1IcjZu3IT/+7//k5BQSkoq3nzrTQkV2XaBnrL16zeAoaMDBw/i1Vdfx/79+8XLtmPHDhw+fFiI12uvv45NmzaBnqkvvvhCCAcJhq6Lk+nHH3+Ml19+ReygZ4OTLMv1CZbkhKSSkz0n2bS0tIZwqBrDvLxcfP/999JufHw8/vOfl6V/JJ2ffvoZ1aBOEQCGEd99711Zs8aJ/ic/eRq2oS47O7PyZAWIdywqKgq+vr5Clt599z0sXrxYZA+r0Nbzz/9GdBD3d955FzsU+SNRIdFkP9zc3EBC88Ybb0rIMjAwQPoeEREBs50dSOJ27twlOK9WITiSEWKeo0Kmv/rVrwVz2vXNN9/glVdeVYQ6T0LAv//97+V87969ePvtt4VYnzx5Er/85S/FaykdbeFj4cJFQsBJxDnGxLBEEWwSvG3bGkj3OkWsaT/tYHiQ+tknXZ1Vefb8/PwEm86dO8HDw0MvkiMJ3a5du8Aw6eGEw/jLX/4G9pHE6a233gLJM8dZhNUHPZDh4eHq/vQQzB0dGjx8bJfjxnuO5xwn3gP//Oc/lb6d4mHk/fqVCouTcCpVbe7X1OYsMgwyEDAQMBC4RgiYmoU1GOoYP3c8fvL3J9FnZE8hTram6PKcfI7vP4agsCD4+/tJCK64oBhWNTlkpuRg+5rd2LlhL8rKy6HXsdVzNc45mXPC4+TGcEtJSTHGjh0DTqBZyrNFsjJo0EDYmc3S/JAhQ/Gzn/0MTz/9E4SGhqjJPEEWMnOiveeee3Dfffdhzpw5IEGiDqifcePG4TlV57HHHhVsSARIOlWRePX8/fx5KpM4CU7Pnt2xdOkyRUhKhASQrJAUFBQUiP7bb78djzzyiEy6uXn5UpcfLP/qq6/x058+i6eeegpPPvkkYmP7sKhJ6tqlq+gmuWA4ztvbRzx2OoEm8aEd3bt3w49//JTS91PV7j2ig+3RG9a7d2/ce++9qvzHQgpIQEVAfTg6OiImJkaNsT8GDBiArl27qlwgKioSzzzzDO644w4pe+aZp6UfvGZbtOXY0WPYvXuPYPzggw+KvIeHu9SnTpLe/v37w8HBQcgkSUdWdja2bNmCmTNn4sknnsAvfvEL1W5/kBhVV1crUuOKO++8Q8p+/etfg/0muc3IyICHhyduueUWPPvss5g7d26L69PYeJDyaJKQ07NGokrPFO8XnnNshgwZDBLXDRs2Yvz48aDtDz/8sJBBtkcdTCTJXbp0kf4zbBgSEsLsxsQxqKmplWv2rU+f3njuuZ8JDsOGDQPvxwJ1H4iA+vDy8lJfDPohODgEPXv2hLMK/apsPPDAA1LngQfuB+9x2rB161b1BSFX6XsOt912G6ZMmQK9P6zT1pJBtNraiBj2tA0EDCtuCAQ4GTTvqPkMETl+6AQ2LtuKpQuWiUj/cYOVp8sVJBac2Aqy89CpVxf5Rs2JpKasVkKL8bvisHHJeix6ZxHe/ev8C3oWRPEV+iChI2nYt2+/TDre3t7o1q2bECB6FPIUkdGJAvtIEmGx2Em5xWIR7w+JU2LiMbz00n9kwmZohuZxkueRdUxms5AsXtco7xGPevLx9VEYuYgXixjdp8jagQP7kZycJBM/iRZDUIcPJ+Af//iHtPG68m7RU1RX1zApU5c+AYeGhoo3kH0zmRoIIsuZTIokBwYFws/PF/R2caF8t24xioy4sFgSvV70qHASJzHQNE2IDQtLlXeSkzYJ3a9+9SswWa0W6H2lzPmSnfJCcU2VpmnSHj1B//M//yMev+3bd4iO/IJ8hZOdIkANnp5ARXBIWPQxaEl36ZkwIvGwU2NiVlhTPjc3R3TymsRMU33nkV6lOhUmJTFxcnIEw2tcQE7SQ+xaaoN6SaZIAukF7NGjB9zd3cFwY1JSMkaMGKHGqkJ5Ro+Ip5HE7cUXX5TQIO9zW50cA9vrC51b1L1GedocFBQk5JLjc6E6LOPYsd/E3GKxCg5cZ0d7n3vuOSFbvE9Z1tLfM3Vc72QQres9Akb7BgIGAtcNAf7jb6nx2uoaJCckIU55pU6eOAU3D1d4+bjLpM/J5lRCulSL6NxABKxqUuzWPwpjZ47C3AdnY94TtyOmdzRSEpOxa02cTFJS4Sp+aJoGehjy8/PEQ9RNkSwfHx9w0qXnhl4Mf3//C1pAIsUJ+sEHH8Bvf/tbSU8//TQ42V2w4plChiUZTqJXiBMfbWCba9euFUISEBAAEhR6hH70ox+Jfoa/6LHyVbaeUaMISsOCc4aISGw5gdoSMV2OfWL/9uzZKyFSeok4IevlZrMdOElzQq9WY0pdOpGiffQCTZkyWUJt7O9f/vIXDB48WK/+g0fq4xqsgypM+uijj4pXrG/fWKlHIsQ22TYzeCRBKC+v4GWLibablc30KLHPvNfy8/MFM03TWqzDTGI6bdo03HvPvYLz66+/AdpE+6iDR8oxaZqGAf0HICnphPJiHlEeswESEmVYj+XhKnxnMmniqZo1axaef/55cIyIT0REBEUaE21svGjFCe1gyJb947iYTE3JM21thRoJu4aFhePnP/954z1Ej5e/CmW2pv61ljFdoQYNNQYCBgIGAu0OgfNNFGb17bvvyP6Y8+AsTLptMspLK7B52RbkZRfIt/1TSWnw8PWCV0CDt8JitaJb/x6YeMtE9BnSG116dkb3gT0Ej6yTGbL2Ri6u8oefCt15enopb8Qx9OrVSyboTp06KY9SsgoPhsLN1fWCFpAUkQzt27dPwogMxyQlJcm6ogtWPFNIcsH6XFMTHBwkk/6oUaOE+HECZzk9NBRneI0etBMnGib8uvp6Zkvy9fVR3rgYfPfdEgmlMVRE7wua/VgUwSW5Sks7pUK0Zgk7mZUXSBdzdHRAVFSUhL3WrVsrr79gKJTl7u5uCAsLVWHONFlrRhK0ceNG8ZiwvLWJ5IBrl1if69H0JxoDA4PAJxVXrFgha4m4ZoypuLhIEUmLIoYF4nm0XZtGL2R4eBgY/uWCca5j4oJ0kj97e4cWTaquqRY91J2jPF/0nFGQNhFfroUrLm76ioVQ1W/KcJxiVGiU9wjHg6FnkjZ3dw8h7Vw7lpaWBo4R+9b878VkMlFNqxI9UMR346ZNiI/fp7AJUKHAs/cjdVnV31FhYYGMF8nY+RR3i+mmPGI1En5kH/ngB/Xb3kPnq3s98luP0vWwzmjTQMBAwEDgKiLAf+626hm62bJqO1YvWo3KmnJERIcjdnhPyNqr9GyUFBQjJy0H6SfSJWzo6OAo1QsLC7HiixVY+eVKefcWJ6R6FdKRQvWhaZr6vPq/JBZTp07B0KFDFOkIFg8ciUafPrFguMhOEROGnUioOKGbTSaQmJD80GvFxDUvnPDWrFkrBM2Jj+gr8kL54OBg6QQnY07O7irkJBlnPjRNA4nP6NGj0adPHwmrDh8+HFyUz2u2xXq33nqrvKqBi7BJ5jw8PMSOM2rg6OiIhx56CAyHbdiwQZGSQnTv3h30mLGMIVKSLOqjl4XhroEDB8Dby1NUMEzYvXt3OCk9XAfVr18/xMXFy8RMPZ07dxYSOGHCRMTERDcSG9ajXlFy5oN9paeQ3jNmsX1iSllejxgxErGxsVi3br3gRf0kTD4+3iCWXM/HfnIt1cCBA8Eytk+dJLTlFRVCOqKiIlXY1RVTp06TsSPRIskaO3Ysxo8bpzBxAMfAy8tLxpX3LkOGHgo7jh89e5QnSeM90FOFBE+nn8by5StknR5t1RP7MnnyZBAbP+UF6tSps/Js9ZfXV1CGuE+fPr3RDtrJ+4BtslxPxIZETceCx+jorjLuvr6+Yq+Op9VqL4Rt8+Ytkj9y5EjVp4a/H+rTNE28r9SXnJyMsrJyNTYxYP9Y7ujoJPV43aVrF3BdHRfcE1sSQbFP6aBsW0sG0WprI2LYYyBgIHDNECAhat5YTkYu1n67Acs+XIEtK7ZhxWerUVpcAlcXRzi5OuH0qUypEhweAIt9Q4hL0zSVn91Q7/OV2LB0C3as3ily+jouubjKHww9zZ49G1wLxEmQzXFifvzxx8AFyJqmCaEZOGAAOJGSeHEiJPEhWSBx4fHOO+8E11fNmzdPTcADZOKkPBdHU4YEi2UkDJrWlESGKDLG+lz7Q1l6WH7yk5+gk/IsQf3QLnpoOFFSjnpIQGi7Km78JRG5//77cdddd4MyPOckzBAj1+ZwUqcwJ97bFHEbo8idxdowHrTh8ccfh4MiWgyfzpgxAwwt3XrrbT4miokAABAASURBVIINF4uTNISGhuDmuXPBxf+0hflccE29emJf77rrLjXJh0sWdRMvLirXNE15CkNk0ueicco9rAjipEmTwH4ydEq9TOwD+8l8YkJZEjH2Y+DAQTIeLKNNN900V/pNu7gw3l2RKZJMjgF10nar6utPf/pThIWGCiGarcJ8lGfionguJj956iQCAwPAPojxZz44LsSEfSfuvsqDSHxJvCjCcpJJLu4n/jyS7Dk4OLC4MXEs2C9iwkweOa4kmfSo0l4Pd3cWCU7si9xXt9+uvIlhQhil8MxHYGAgiNXMmbPgrUjzAw88CN5HLOY19fGadowYMUKN6YMiz/Ho27cvLNaG8ad8W0oG0WpLo2HYYiBwHRG4EZvmhGXbb/4D7zOyBzp1i8Lxwyew+P2vsHP9Tnj5emLibZNgdbLgZOJJ8P1anip0qGkNJIOT5aipwxEaFYKEvYex5OPvkJWRhaGThmHA6L5CbmzbuZrnnFR9lTdB0xps46TJa9rIdjVNkye66FnRNE1ssy2nPMsYVmM+J2JN08A86ob6YR7LiJe6bPJrsVpFVi+jPobQLNazk6BePzw8HNRDmSZK1IWmNbSp28H26U2yWK3i+dDr8EgiQmKhqsmvxWoFF1yzTNNUf52dpQ7tYB+oS9M0mehZj94gJt1mUXLmQ7eVJIhZFqtVbLZYG/qjaZoQGd1O2kJSxLaZ2FbzfjKf/dZtdHV1Ecw0rcEmXlMfbdLbpR3URc+NpmkybqxvsVrP6YcuQ/JBcslr2PxomqbCdm6grcymPdRt23/mkXTSDr0dytomi7UpFhZrwzVt5f1GnSazubEKr6mP7VJ/Y8GZE+ZRhuNksVrBo267xdpwX/Fa0zTpP8t1bNkm2uiPQbTa6MAYZhkIGAhcfQSae7T4j57/uO/4ye144Of34ZYf3Y57nr4LT/3lCVl7xRdY5mbkIKxzCFw9nBsNZD2GGe/+6Z1S787H7sSjzz+MWx65CZw0GwWNEwOBa4QA70kSJJIRTdOuUavnNkM7hg4dCnrM2jIZOtfyK5djEK1LxtKoaCBgINDeEWju0dL7w2/jXXt1wZBR/YRg8Zs9n5giaRo+ZRj6DIuV0JAuz6OmNXgJWK/fmD6IjImQb90sM5KBwI2MQGRkJBg2Jem6EXEwiNaNOOpGnw0EDAQEgeYeLck8z4emabIYm08V+gf7SbjmPKJGtoHA9UHAaLVNImAQrTY5LIZRBgIGAtcCgfN5tK5F20YbBgIGAjcGAgbRujHG2eilgYCBwLkItPr9UC1UNbIMBAwEDARahYBBtFoFkyFkIGAg0BERMDxaHXFUjT4ZCLQtBAyi1bbGo21bY1hnINDBELiYNVodrOtXvTuFBQXgSzf55vTmjZWXl8vb0leuXAmeNy+/3Gtud8MnRPkAw+Xq0utzj8b//ve/sH2Tu17WmiNt4Yttt23bBu6NyHN9i6HW1KcMX6i7L34fcnNzZc9N5rWUKMe3ypeVlbVUfE3yOK5M7Pc1abCFRjhmfIlraupJ8F7LyGh4B14Lolc1yyBaVxVeQ7mBgIFAW0bA8GhdvdFJSUnFv//9b9TVnt0smq2ReH300UeyqfTy5ctxJcgASR03lS4tKQH1f/XVV+BGyDxnm5ebSNpefvlleRiitq4O3JaIW+5cjP6y0lJ88MEH+Oc//ylvol+9ejW4EfXF9D83Nw8ff/IxuOWMbZ9oB23iljo8z8rKwt///nfk5eXZil2zc27/88UXX4AbXJeUlF7Vdi+k/PDhw3jrrbdgZ2cG3za/fv06kIReqM7VKDOI1tVA1dBpIGAg0C4QuFSPFiezmpoaIQn8tqxP8Ne707QrPz9fPB6cwHVvAo+cYPgNn14UytFW5nNSpIeEiX1iPhPP6XVhPj0TzKM8z6mLeljG+ixjol49v7KqkllNEutnZmYiLi4Os2bNwu9//3vwze4kSiQzrMt2mdgP2su2WI+KeGT7zGc55ehh2r1nj0yoBw4eBInd0KHDcNNNcxqfDKUM5WkvvV3URVupm4nts4xyLLNNlFu3bi1Yj29Tp/0fffQxvv32W5m0aRNldKyoj3m2Onh98tQpcD8+vsWcb2/nFjR8O7yDg4N4ydh31qUdPFIndbAur5lfVlYqRJL5eqIcCRVt+uabb1BQUKAXic2sR9uIlV7AfhIPJvaLbehlPFIn7dET6+p5xJ726HV45DXziSPluNsA+8etmBzsreDYctxoB+3hPcN6lGUe71XaQruYx78nyrEe5WgTE+2gTSxjHb2MdShLG1iX15TXE+8xbgV1UN0fJKR6Pb38ah8NonW1ETb0GwgYCLRZBC7Fo8V/4pzYODHU1tYpUpODo8eOifeAZders5wwGapjeOu1117HggULkJqaKhMzNwf+7LPP8MYbb2L+/Pmy5x9tzczMwnfffSckhd/8uW8cJ01OYlu2bMHbb78N6qJngt4STpCUoQ7mvfTSS/j6668l/MdJkgSK7b/zzjvYsGEDSpSHyRYP2rhjxw4hHHsUOWJYp6CgAP9+8SW8887boCfq5MmTWLt2LajnjTfeBO3mPoG0Ny0tDYsXLwbzWc42jiUmqhDlFhw9egxr1qxBbl4+jhxJANvhhMpxWqFClJRnX9gGJ2S2S9s/Ut61Dz78EOzLalWfk7mtzcRj69ZtmDBhgmQT40OHDqnw3x7QY0ICwXCgjhXtJd60Vyqoj5rqaqxfvx4nTiRJyPTIkSMyNswjMTxy9Khq/z9YuHCh4E18s7NzVE3g5MlToI0cnyVLloC2S8GZD+6lyFBkfHwciGd8fDzYB+ZT/ztqLGjb/v37JZ/9YT+JBxPHs6iwsEkokvf3G2+8IWPw5ZdfIj39tJDj+fPnC/bsIz1EbIdHXr+hxupt1Rax4H1CjJi4l+OCBZ+Kd+vjjz+W/n3//fdCCDkGr732Gj5U+FN3UnKyGrsj+OiM3Pvvv4f9+xrs5r3Dfr777ruig7p4X9CGOEXcP/zwA7FtvvIanjhxokl/CBVfROzu7g6SLWLDvGuVDKJ1rZA22jEQMBBocwhcrEeLkycnIU4uJBGOjg6y8S1faEoiwomDk/v16GhGRoYiK+8gICAAQ4YMBj0ve/fuleOCBZ+Bk9/o0aNk38IFioSlpaUrYrJaSBe3amFatGgxDhw4AE7Ky5Ytl61mhg8fJmEXTvQkYOx7XFw8/P39ZR+6jz/+REJpmSpcReJCjKirpcmMng7uVxgWFo7evXtLfRIVki4eu3btKl4i2s097diPxMTjWLZsmeSTaJBQ0Sbus0gPDj0cvXr1lL30BgwYAHd3N3ACJpmhDVsUYdygSB/lqY/nDd6oMiQkJEgYjvsqRkRESLiRHhbb8SOOhYUF4N5/tJ928wWc3Dw5PDxCkacT4OTPLXVoF4kdyaBOlKjLZDYjNjZWbOQG1xGqLd5Hhw4dBkORPN+8eRNF0a9fXyFMcXF7xdO1aNFCIXTsm4uLi+BAjEVYfVitVnD/w65dowXPzp27qFCZnSoBaAvtpbdnvSJ6hYWF2Lhxo3jjiG/nzp2FpNIjaKuzvLwCe/fGgfLR0dGK3GUJUXJ3dwf7mJOTIwSdBIwhQl6PHDkC3KuQY0KyzL8HHqsVyeRYbNu2XTDs1ClKSDjHmGNO8kRiRDsrVLu8h/i3xXb4gtOX/vOSED16or7++hvwZcIcx6SkZPB+oK0klw7KM8g6KSkpsh6LYy8gnPlgOckW2yJpO5N9TQ6ma9KK0YiBQDtFwDC7YyPQGo8WJyBOOAyLcNJNVt+6i4uLBRj+ky8sLJJ99TgBsLz5P3gRvAYfnJQ4EXPSJiGgB6ZXr17KI3ISh5QHhn3ghMdykrJDhw4qz9IJNbH3w9ixYzF58mTcd9+9cHRwFK8C34I/c+ZMKbvtttvEQ8SQDSf22Ng+mDhxImZMn66ImwVcE0RPC8tvuukm8f5MmjRJldk36TltJEFzc3NFaGioTMwU8PT0wPRp0zF48GCEhoSApIL2kjAxXEZSSGw5SY4dOwajR4/GzBkzwDAc9XGCd3f3QHBwMDihUicTvTckUyQLU6ZMEbvYp82bNytvWzEcHR0VKR2C8ePGgfn5+YUgcWNdPbFPPCeZpv1sy8/PV0iot5en4OLj44NbbrlFsBqndBUUFCrcUxu9KqxH23QbPT09qbIxsZzkc+rUqWJjZ0WWiGlJaamQ3ukKZ44nMY1QJI3yemWe+/n5wdvbC7SDtrGM4zRnzhzR179/PwnflZaWCWklkSERooeQJIn3NAkR6+nJS/WN98SwYcNA8kIZjgnXh7F/DIMmJh6TsimTp8iYzJ49G7RV359R18UjyRHvGZZzayDqY5v8u+E9wzEtKy9DgfJwst2x6p68++67hezFK28d5Wtra9Q4zZI+PfTQg+jUqRMsFjvwPuf4sE8kUbSXni62qyf+rXt5eSkPdK6EVPX8a3E0iNa1QNlow0DAQKBNItAajxY9QZysE1S4h9+qdZLFDlVVVaqJJhkkV5w8+U+eXh+WXevkrybbhx9+WDYLppeAXhsSKpINq9UCkjBOgJzwp02b1rCwu7ZWiAkna03TMGjgQISHh0kokBM1SYumafDw8JDuUBdPLBaLbC9ktrNTE51V3kdGDFjm6uoma6MsdhZFtCzM+sHEPfCs9laRS0tPx6pVqyXMxcmTqVbZSWyZuKkwJ02L1Sr2hihyJRVb+KA87eJkblG2apomBImTMMvYb2KimUyNXiCWweaH9XnJNnlsnkjMXFxcVV+t0m+SNzs7s2DYmvtL12ex2MGqcDUpG+0VFrSjsrJKcCD+mqYpzO1UMqO1P/b29mKTbnt9fZ0iXMWCAe2kh2rEiOHo06cP7JTXzVavRdnCe0DTNEVKS8STRBxZr3PnTkK0OW6Uc3RylHY4NkOHDBFvp60unlOWR+p0UZ45kiwdH9rJMo4Jj2xD0zRQH9vk3xz/DhvKHKQtEk6SQNahl5Iki3+DvF8op1iuHPQPTdNk2yziquddq6PpyjZkaDMQMBAwEGg/COgT0IUsrqurl3ANSQb/qTeX5QTAieDsZFGl/sfXNxe76tfHT5xQHqrjuPnmm3HXXXeDHqNt27YJgeAkN2jQIPG63Dx3LqYo71V4eISayBzFY8DJh2SGa5lIKDmxk2DQ81FfXw96PnhNj8D5OsIJkWVZmZnSfy6Gr6qqZlarU11dnXhwWIHenXHKO0RiyGvqd3JyBj0etLW6qgpca8Q1WixvKXHCJplgnQpFWtiXxMRENeE6CPFsqU7zPOpgXnV1DQ+S2L6cqA96uDIyTitiVSHr4dhWZWUliFVr7i+l4ry/TorA2Ns7CP60vbq66rK8MZpmEq+Xk5MT5ihvF71w9EIx9GiniNX5DCGB4T00YcJEuYduvfU2jBw5UjyI1So0SLJJTEpKSrFs+XJZf9ZcFzFhHr+I8OlJ4kqdzGMiVjpJIobsL0Of9GQyHK6X0YMYlGDSAAAQAElEQVTMtuid5fpCeuSOHDmqQprDhfxFiMfPjiqbJOpj2/w7ZVtNCq/yhUG0rjLAhnoDAQOBtosAJ/bLtY7/wPmPm8fL1XU59elZWLhwEf797xfx9ddfIS4uTrxW9FZ07twZL774EriA+F+q/A9//KM0xXUxK1aswBtvvKHKX8Sbb74lBIGhO4bM+CqC119/HX/9699w//33qzJvqdfSB4ldVFQUXvjXC+DC8n/969/KE9IQYm1JvqU84hiiQodcJ8YF3C+99B9ZDF9XVwuGx7h+iQvDucD7f//xf+CaMhIwhjsLCwvAvnDi1XW7ubqif//+snD9lVdeFrvefPNNzJt3u3hodLkLHf39A6S4oCBfjiQH9IRx4fm+/ftBMlhSUoI//emPCr838e6774F9IBaapkmdS/1g36ZMmSw6iSlfMbFv3z4hdLY6iRs9Rdu2bZdQJomzbbl+bjJpuOvOu7Bp0yZwfIjjH/7wBzCUSvKiyzU/0nNE7+Zf/vIXeciCr47gQnoPDw/0V/jyvnn33XfllRJ8bQU9Vs118OEJLnxnP5KTk2Q9Ge9ZXU7TNERFRko4mbp43/3qV78C1/QxpMwjSdK/1P1FPXxilWNBAlarQorvv/8+/t//+yc+//xz9eWhAOr7ka5ajvxbZyia95GD8vRJ5jX6MIjWNQLaaMZAwECg7SHACeqHrDKbTUJY+K2eE19zea6LofeCHi/+M3d0dICmXd4E27yN1lxzYv9//+//FCHxVRNNIbjm6Pbbb5dQ4rPPPou7774LJCHBwUH4xS9+AX9/P1mb9Pjjj4t6TtRvvPE6SMqo65lnnpHJkCTil7/8Be68804VJrRDz549ZU2M2WSC2WTC1KlTxHvGCe/ee+8Fw5JmFYZ65JGHVZt3w2Q2i379g5Ml1+OEh4dLlqsiQ+PHj4eHh6fgNkSFnn7zm+dBHbSVEyoXkHNSnT1rFh599FHpX0CAv7yHKiwsDN26xYiHxtHREfSwdOvWDSNGjJC2SQR++tNnQc9WrQpB/uc//wHbJxkgoeTCdk3TQLvuuON2ZYcHbH+IU0BAIOLj40EyzXrsI0kq2/Jwd1ek5V+yuJ9YzZ17Ex566CHlLXSyVQP2k4u1ScJYwP6PHz8OZpMJXLPENUlWRQBMZrOsUeNidZMqmzp1Kp555mkhV2PGjMETTzwhRI469MSx4+syBg4cIKFGhm+57slVheiog30cMmSw2NCjZw95mpBruojHHXfcgTGjR4vnU9fn6uqCUaNGqXskQLJ4f5NkjRkzWh6uIOF9WPWR+XxFxa233iIL72NiovG73/0ODGPzPiHJt1rtRQft498PHxp46qmnwDJecz0W8yjkprB84IEH5B4iluz7XxW5oweOnkPeq/TMVilvJu9pvm6DNjz//POCP++JZ9R9O3bsWChOKR43rmtj2LikuFg8g8TVqsLObO9aJdO1ashox0DAQKBdIHBDGUli9EMd5uTds0cPMMVER8PH2wecvFiPEwUX5DIskpOdI6TGSU32LLvWSdM0mYA5EZNIcfE37dM0TdZhcRHyr3/9azz44IMysWuaBovVioEDB6qJ/Bn8+Mc/bszXtAZdJE7UNXz4cJmI6dXgOcmQxWqV+pThU3ua1rD+ieSOuujpYVskTLZYcNIkCezatasQKxIgkjhOkpSjPD0YbJf1x4wZIySKRMhitUqIiGWPPPIIWEfTGvrBhdaPPfaY9IF9YhvURYJGbwhx+dnPfiZEkfkkhrSRhIDXtOsZNUnrkz5tYWK7kyZNlNcy0CNCWdrOtnQcvL29QRxoF3GnLta1Tewnx4D3C/Opg1hZrFaQCDGMx3uN+mkXMdA0TRbs85q26+E+kjRNO0vmNU0D84gJZYkL7XP38BCMu3fvLmE12kD9tIFjxP6yHYvVSpMaE79UzFUh5rCwUMnTNE2+bHCceA/RVl038SH27DsxIBYWa8M48V5xsG/QTUJ03333yX3Gp1I5LrSHOnXyqWmaEGLiRH1sx1mRRU3TpB8kpJQnFtRNHXp/2F/2n/jr9dhPYmwym5Fw5Iiso+ODERarVfp1rT4MonWtkDbaMRAwEGhzCOiE6UKGaVrDRG6xWsFv3OER4fDy9BKyZTaZVHisBHyMnTro+bjQWhfKGKn9IUDvC71qq1atEs9S++vB9bWYJJAhu9b8vV0NS/mkLZ9apAeTZO1qtHEhnQbRuhA6rSkzZAwEDATaLQKt8WjZdk7TNNATEhEZIUe+jPF0+mnx9pCAubg4yzdv2zrGeftHwMHBAQxb0hvS/ntzbXtgsVrBMCa9jJqmXdvGz7TGUCGJcr9+/SVEfCb7mh0MonXNoDYaMhAwEGhrCFzKN2xN02StCwkXwyahKrzC0A/DIJp2fSaStoZrR7SHISyG2Riqauv9a2v2MTTIkOL1sot/mwxvc+3Z9bDBIFrXA3WjTQMBA4E2gcDFerR0ozVNAydcEi0PD4/r8i0Zxo+BgIFAu0DAIFrtYpgMIw0EDASuBgINHq3L06xphhfr8hA0ahsIdGwEDKLVscfX6J2BgIHABRC4VI/WBVQaRQYCBgIGAk0QMIhWEziMi9YgYMgYCHQUBK6ER6ujYMF+8L1KpSUlV+XJOr7JnW/mZhtsyzbx/VTM59E23/ac5XxXGfXY5p/vnLpYh8fzyVzLfNrB/vNVINey3SvVFndA4L3Rkr6LxZnyTC3p6oh5BtHqiKNq9MlAwECgVQgYHq2mMGVn5+Drb74BH4dvWnJ5VyQZqSdPgm8Np25Osty2hW8wZ1lmZhb27NkDEpHztVRWVo41a9aAW+6w/vnk9Pyy0lJ59xVf0qrnXcyRtpHY8Xgx9c4nW15eDu7Jx7fen0+GbXGzZm4CrhNK4sO39LMedZyvLvNZp7j40ogySdS2bduwfv16rFu3TrDmkdfcR5D7Z363ZAmbaZI4FqzHbZqaFJzngjYePHAQycnJV5LQn6e1tpFtEK22MQ6GFQYCBgLXAQHDo9UUdG4zw+1YSIKallzeFQltdna2EB/uY0ey9eWXXyIrK0sUFxcXybvI6DWRjBY+KirKpX5rJ/SKykqQIPAN4y2ou2AWyQ3fjbZ8+XKkp5++oGxrC0mS9u7di6SkpPNWobeLbb7wwgvg3pW0g9gdO3ZMtpYh4TpvZVWQnJKCb7/9BnwLurq8qN8yRQT59vtdu3bhq6++Are52bhxE3jN/Qa5t+DWrVvP0VlXW4sU1S7H9ZzCFjJqlHz66XTZpaCF4g6ZZRCtDjmsRqcMBAwEWoMAJ7HWyLUXGU7UJErffvstOKnTe8DJmt4QekrolWDZoUOHGr0J9NrQ08L8803kGRmZsh/e0aNH1UT+LfbF7wPJGD0ZrEfdbIdeEZalp6fLdjW8XrZsGWiXjiHboGfqq6++Fl0kTvb2DuDTm3zTN9tg2rlzp5TTu0PdsPlJS0sXz4veP5IX9pFkRhfjPnp8rJ9PhtJ+llMv7SVGOqmjFykhIUHaWqc8OdRBL9iKFSvw9ddfY/nyZSBJpA35+flgf2i/nsf26EViHnVTF2WZT28Pr79SxIXt19TUMvv8qb5ethc6cOAQFi9eDNpCYdpKvKmP12xv5cqVYjP7znySStq2aNEiLPn+exkf5nMsKMu+FRYUsLq0wbErKyuTa37ob4O/6667MXToUHh5eeOmm+bIG++5pRHHhlsO6RiyP8TfZDbL29y5CwH10Gb9PtNlmK8nfrnhWOvytJFjTIxoE+9HXbajHA2i1VFG0uiHgYCBwEUjwH/6F12pjVbgRPyvf/0L36jQHye4+fPnY5nyyJDkkEj97W9/w/ffLxWv0KuvvgpuTkzi8MYbb4CT8+HDhzF//gcqbNiwebJtN5OTk/DnP/8ZH330kdR/6T8vgVuxrFy5Clu3bsNvf/s7HDx4ELl5+VizVoX3lAeGJJbXr732OppPnpxcq6oqwT3reJ6enqaI3BZFAIrAyfavf/0rli1bLptBv/jiS9i4caMihnWNJtXW1oAbLDMcyf7xje07duwA29SF6MliPXpjjh9PxL///W9wE2W9n+xzdVUVWPftt98GMfviiy/wz3++0EhSqqqqG3WePHlK9fO3qv+7VJ3VYJ3U1FSQxP3ud7+VcFtcXLzkc8PpmpoakHxxA2a2+b0iPySPun3nO/K1IWPGjFJ93421a9cKYbWVJaGiTvaNNnOT5vUq3EcSVKu8RbSZbdfX1eHEiROykfbmzVuwdOlSvPb66yDZ4lZCHDt6FnXdJFLcfojb93h5ecm+ljwyT99SiP3Q7wH2f4ciw2yXdtIDyLEghh9++CGIBTeGXq3CvbRHb4cyxIGEjd4w4kIPHnUvWLBA3YPzxUZdviMcDaLVEUbR6MPVRsDQ30ERsJ2Y23sXOYHR8/Dssz/Fk08+KV4JTsTFxcXiGQkNDcNTTz2JJ554EtwqiBPb/v37JWTHPeieeuop3H33XXBycjwHCupmJusy8Q3pfAEl6/38589JHRK3WkWA6G2pUgSG8rzm+qva2rMkiZM33xIeHByMsWPHgkfKl5QUK1JRJ7Zyy5bHH38Mzz7zNPr37yekq7KygiolBQYGiheFYS16n0h2/P39ZU9HEVAfHFuST+quVGFEs9kO99xzj+y1N378OJCYFRQWCkFkfx599FE899xzqiZkf8H+/fvLHoTctoUvp/34449kP8Gf/vRZPPTQg6hR3iliWKzCnmPGjMHTTz8N2hwVFSXrzRgWXa6I7rRp086UPY5u3WJE/4U+SLTYf+41+N5774EeK12+RpE3etp4zb0Kn3rqxxgxYgToraIHr1+/fggNDcGYMWPh4OgIerL4stCnn/6JGvcnkJiYiBMqdNlJ2fjEEz8CcaSu1iZ//wDB7/HHH0dERAQYTiS+JOy0jeSW9wFt4j6KU6ZMkXV3JH16GzynHL10rMt1e8T66aefxn333QcXFxeU2nja9Hrt+WgQrfY8eobtBgIGApeFQEfyaDH0Q9Lyn//8R7xNX6nQXEFBAehxIEiBgQGybZCbm6sK07mjWBEwejZIUDgZ02vB/egcHBwofk6yWu3h7eWpCI4bfHx8hCC5u7vJW/JZhyHBcyq1kKFpmmxZxCJ6UTTt3PeQeSmPCsmNi6srSILKykrFXtZhIqmYNGmS8i7tBD0jzOPb+S80nrTZx8dXSBS9NMSF7ffo0UPp2aU8ZK8IEeHGxMSEZXZ2ZljsLBL6ZAiQHqonnngC//M//6Pq7JR9LklaGQajl+mPf/yjeLEYPqO3iASE+okt+8OQGW39oUSyNXnyZHTq1Anvvfd+Y9+pl2HTmJho2eSZWz517dJV7ONYsx6xod011dXiVVqyZIlsGv773/8eJG20yWK1gkSZ8j9ki225v78fiJ27m5vcS8SwVnnRdBmSJG5gzRDqO++8Dd5PEyZMwPn2/7QqO8aMGSOYvfDCv1CoiO/UqVPhr0izrrMjHK8OKbImLAAAEABJREFU0eoIyBh9MBAwEOjwCNDr0VE6SW/FK6+8ojxZQ8SjNXHiBHB90oX6x4m2RnlmbGWqq2tsLy/r/Ergq+toTqIGDRoEkoYNGzbCw8MdJIuapl20vfSmPKU8gP379wNJyf/+79/Bpy9tFWmaCSRe48aNE88QyRbDhSNGjFQhvl149933MGvWLPzoRz9S+A8Ff2gvvWh1Nt485rc2kbzSy5aWdkqe1iSpoU4hUcqzRc8QdVXXVKuwai1PmyaFBb2TtJl20WaSwT59+jSVu4JXJtXmhAkTlef0KSFi77zzLr766isJEbfUTF19PYYMGQoS1B49uossQ5IM97Yk317zDKLVXkfOsNtAwEDgshHgxHXZStqIAnoDqqqqERQUJBYxpEYSpRMVyWz2ERoaqrwIBYiLixNvB586q7QJ0TUT/8FLelMoxPU6x48fB/Xxunki7jWKLHChdllZefNieVqQT9pRBxf108Ph4uLaRC4gIEB5PgIkTMcwFr1KTQSaXbR0ybVj9FKdSDoBemLuuusunDiRhIKCfDTYWIvMrEyp2qtXL9Bed3d30OPGTLPZJE/PuSrPG/MqVYgyNzePRYr8echYbNq8SbClR4zrq1hIzxQ9cQxt8vp8KUqF+G666SZZT8dQG4kz9+xLTDyOI0ePigeOr8Wgd4oYkQwST3oqVRxWhSq7qb4USjiO9hFzjhHDu1yATjvO1/al5DMU+91336o2CzB69GiFaTekpaW1TARVAxXl5Vi0aKHg07dvX4wfP17q/hAuqmq7+jWIVrsaLsNYAwEDgSuJwIVIyJVs51ro4qQ8YEB/LFy4SJ6WYyjP1dVFmmZYUQ9baZqmwn/uQgRiYmLA9VJr164DFzGfOHECJDAWi1Xq6R8MfYWGhkAzmaBpmtSlPpPJLNcBAYESiuKEHxvbRxGA48qOhbKGJyoqEmazSbxrDDtZVbjIQ5GVHipkt27dOjURn5JwHsNMZrNZmuQTfVyk/tlnnysiWIjp06YrGQcJW9EWClEP+xugCBfJh16XZUx2KuRH8uHo4AiSMG9vL7GDZdTh6+sn+ZThWquFCxeCC/CnT58mBIm2sg6JXmFhAebOvVn10Ufh9KU8EUiCQ0JAgsAF5F9+uRBcP1VVVSnEhuG1mTNnKNKYBi7y5pOOLi4uUlZYWAQuICdxoz16Ir76WJnOYE3CwrVOPipcS6LF65CQYGXDV/jyyy/FqzdBhedIpAIDg9T4+YsHjK9rYD7vgcWLv1Lyi4WUkgxmKfLIxfG0Q2/b9kh8AtSYkpTp+Qx9env7yCXt5HXDPWASwss67B/HcfPmLfI6ChK6wYMHg2MlFdWHyWwnRNVVkVMHR0fwvuUDFbz/4uLiwXVmgWpMlWiH+TV1mJ4YHTEQMBC4ggjcGKo4mXWUnnIivv/+++WRfE7MDBXdcsstMqlNUOGc4cOHK6JhlkmP4aSRI0dKeGfG9Om48847xANx111346GHHlKEpmFCxZmfrl26SFhM0zRw8h0yZAioz9HRQTw/t99+G0aNGqXIkCPGjBkr+iaoyZ/6nnvuZyCx4oQ6Y8YMWbfjpojWnXfeiemqbRIa6p8zZ46sO2KTJGEkFJMmTcQDDzyAHj17iA4uLCc55LjxiTUS5ejorghVnjnWs02enh5g/yMiI9C1a1dQP+2gTHR0NObNu13Wl/FVBrfddpv0f9q0qcr2uyQ/MDBQ6k+ZPEURUw/VRogKG/4IU6ZMFs/L7NlzQE8aE0N8U6dOwcyZMyVsy/Vj9g4OYJjukUcelkX/DC1Srn///oqouoNjoHsfaRMTidSEM2OlkxMSmnvvvQ9cKM4xZqLnbcaM6aKDOJLskWgGBweJHD1DJD207YEHHgT7xbx58+bJ/RDg74+pU6eKHWy3eSLGHFMPNU562RAV4mMer2nnsGHDwHvISZGle++9ByS7DqrP1HvbbbeKbcSYcnZ2dqwmifcM78+BAwfJvThehWMfeOB+wf+mm+aIXbw/RLiDfBhEq4MMpNENAwEDgYtHgBP1xddqmzU0TVMeF2/xUHHiDQ8Pl8mPnoawsFBZw0TLOSFzPRMneU3T4Ky8LD179gQ9D5TrqkiJo5o8Kasndw8PUIZ1mViXOjiBapomRIbXlHd1dRFZesqoj8TCYrUqsuIuT/FRt6ZpYg/b9Pb2BvVz4TcncOogyWAoj+WRkZFCEC1WqywOp3xZWRneePNNbNq0SfrLPrKebaIuTv4kKp6enlLXYrWCP7wmmaD9lGPbbIu20n5N06RNYti7T29FvFzEc8e22S/K0YtFLJjYd9YnRrSXibqZeD5EEVO2x3ZILElIdNtg80NdxIz6eM4iHtkW8WA9TdMES44x26Qs29Fl2QbtI856XV4zsW3mOasx1/WxXvPEfvI+sFitjUW0gXnMoA7eA0wWqxXsG+tomrqfnJ1VyLC73E/sI21mHT3RVuJKfZqmiLuqTzn2hfhxvDRN08U7xNEgWldoGA01BgIGAu0PAXpG2p/VHddiTdMQGxsr5ImT+fl6qmkNEzo9NJygNa1jTczn67eR3z4RMIhW+xw3w2oDAQOBK4BAR/JoXQE4rrsKkisSJ4Yl6fk4n0H0YD344IOgp4geqfPJ3eD5RvfbCAIG0WojA2GYYSBgIHDtETA8Wtcec6NFA4EbDQGDaN1oI27010DAQKARgSYercZc48RAwEDAQODKIWAQrSuHpaHJQMBAoJ0hYHi02tmAGeYaCLRDBAyi1Q4HrY2YbJhhINDuETA8Wu1+CI0OGAi0eQQMotXmh8gw0EDAQOBqIdCRPFp8yzffpl59ZkPnq4VZW9bLF4jybfK2++/p9hIXvqyzvr5ez2rxyLe3c5PqFgtVJnXzLe08qsvL+uWb2vmG+NKSksvSw8rsF23ny155zrxrnYgJ78Pr1T4AcGx4D9COa93/87VnEK3zIWPkGwgYCHR4BDqSR4uT7IsvvojcvPwOP27n6+D+/fvxr3/9C9wXkCSGpIPv3CIBWL1mDT744APUVFefr7rk823rK1YsP++2Mdze5t1335W33kuFy/goLCzEX//6VyQcOXJJWkgmSArZV/brk08+wcaNG3+wj5fUWCsqcWeB1157DcSoFeJXRYRb/rz11luyXdJVaeASlBpE6xJAM6oYCBgIdAwEOpJHi2QiT5GsurpaIQkteRUow6SX6aPI69bmU5bJtm7z65Z0UZ5yTDxvnpivJ9v6zLO9Zj3m8agn/ZoeqxLlHeJ1VlYW/vnPf2Lbtm3y9nq+DX7woMEwmc1guZ6a6yZ5YaJuyvDIxHMmd3cPeRknt+7htZ6a69Hr6Pm6HPP1RKLP/RZJDHU5vYzy+jmPvGbiORPP9+3bhz//+X/AvjKPfadHh+fN9TGPdVrKZxkTy22TntdSHV2OZZRj8vP1lR0D3N3dL4ixXlc/si4TdTGP57aJeS2V6fm2ZcQ0P79AyLatjut5flWJFgc8Pz9f9mIyjgYOxj1g3APX6h4oKCiAPlle6B8s/ylfqLw9lnHypVfhww8/BEMonIQYNjtw4ADefvttvPnmm9i+fbuEWFiWmnoSn376KegN+/rrr8E9EplPbxCvX375Zbz33nugx4z5Bw8exPLly8F97IjP4sWLsWXLFiF39K7wmnW4dyCvKcP298Xvk/bpbeD+gcxjGRMnzCPKq8O6TKxPm2i/bgPbpAeI4/r666+Lx4L1kpKS8N1338k1dTGRcHz++ec4fDgBq1atFu9TZmYmUlJTWIxdu3aB+LAtYrVhwwbQ8yWF6oP9jIuLw/fffy/zF9uhp4g6KyrKkZKSArZBm9lP7ltIm6lT37+Q+KxatQrMZz32Q8dJNdH4W1VVDYYPOTbEmZtPsy6veU5BjgX7yPZoG+3hOCxatEjGeNmyZchUxJKyJF2fLlgg40m7SD5ZRx9n2kMsGWalvJ4oRzvZZ7a9f99+2WeSfSBG7BvvAbbNuZ17PXIseT/p41laVgZ6tVhOW9ln2s02WZ/9YDvUyfFlf9kO83bu3Am2w7Z3794t9ydt45jTXupgHWLP/nC8eB8zn3U4ptTDOm0tXVWiRRceB9pIa2UDUQOH9o6DYX97uYc3b97cqvBFR/JocXKhd2TDho2gRyExMVGRiY+QlpaOuPh4ITnsL/cqXKAmYk76qampKv+/Qhy4lcvWrVvx2WefIS8vD0uXLsX+/Qdkb7zExOPiHeJERmLDiZWEg21Sz6FDhxRRKcfXX3+FDYq0cBsVbo/Da8qw/Q8+/EC8DFVVVZg/fz6OHD0qXg+Wk/CSoHzxxZdCilifJOK3v/0dkpOTZU+8b7/9FrSPE+w333wjNrIeCRQnaZJr6mLiFj7cFsbT0wPh4WHw8PAUMkM5EoXDhw/jyy8XIiMjQwgiQ4F6Gesz0cu0efMWIQ5lpaWgPcSX7XCCJ6GhzcSScl5eXiD5IBkgGVy+fBm++uorODs7C3n96KOPQLJL3c0T9XHLHPb1gw8+VHadxsmTJ7FkyRKQkJJwEk+OH1/qyvo+Pr7o3LkzuKch95FkfeZv375DvmQw/7//fVvapF5izpAe7Vy0aLHq/5fSd9ZhYvhx9eo1Qqp5XVlVKe2vXbuu8X6ih7C4uBgkoSROHEvKvvLKKzh+4oSMybp161FaWibEl0SWfWab7CMJEb1N/DKwSJFEfvEymU0yrtTB7XpI0qibZIs4sg6JJHUcP35C7OaY8x6kHPMpx/v2SMIRmtPm0lUlWtxzae7cuTCSgYFxDxj3wLW8B7hZMSefH/qPy4n6h2TaUzkndW7wy02HuVEyJ8ITJ44rr84q8E3r3Hw5ICAAfJs6JztOgjU1teDmz5R/+OGHZdPn2to69OrVC0OGDEZYWJia0DuB8iQa58OjrrYGbM/b2wfch2/evHkg2aH8BkW+OBmGh4eDNnCCpReHZbaJ+wLefPPNsjHy5MmTpeiBBx7A7bffrghTuITIqqtrJP9CHyRavXv3RoDqK0OGvr4+TcSJRdeuXcC3yz/yyCPgJtacuPX7gWQmIiJSNskmsUxKTkZmZha4ibLJ1HTaZAjxgQfuVxjehTFjxghBIgmjN40bbd97772yUXfPnr2a2GB7MWfOHKl/9913K/JTo8hxmrRFzE9nZAoR9vDwkP0hWU/TNNU3f7CPbD8mphvcXF3BnzFjRoNt3n3XXWrsQkH7uXYtI+M0uFE2U2RkhAqpbhdyzDp6sljsZL5+QGFOAkPi6OHhLvVI6uhhI+mLV8Sd43j//Q/gEXXPTJ06FVWVVbqaxmNwcAh4X91zzz3gvcX6p0+nSzk3DSf25AlfKULKzafZ7oOqbeaxDZLN9es34I477gB1cGNt7rfIe9ZXhSm5iXe4uqf4JYH318lTJ0V3W/toesdcYesMdQYCBgIGAm0ZgeaTZlu2tbW20RtEouDm5i5EgR4IhgM5EXGi40Tp7e0NTmYkPK6uLkrOAZqmITIyElOnTDyGQdgAABAASURBVIGTk6NM0CQfDAVRrrS0XJGAuvOawW1xRo8aDW9vL6xcuVK8+CR09CCReDDUxqci6V3p3LkLSBCaKyNBslgsaLDfDa6KPDg5OsLObBbRmpoacA2aXFzGB/VbrfZgWw4ODiAhKygobKLR28tTkbswITn0pAUHByFCTepNhNQFPUlM6lS8VzySkFZXV0kfSeqYiCnLmier1QI3N7czfXYXEkyvTq9evRVxrVZhzp3iVevZs6eUNa/f/JqYES+T2Szy9AAyTEj8GXZjyJH979+/H0wtbBHppTxzLOf9wnHnvcM6DPsNHz5CMGM4z9PTEw72Vtip8Zo2bRqiY6LR/MfOzqzkrXJvkQxVqTAp7aEcvxTw/qiqrBQSS8LEdu3VeHir+5NtsM0q5Vnz8/MTHRyD8ePHIzDAX0K69KaSsPP+IgHXiTL1t6VkakvGGLYYCBgIGAhcSwTa6j/my8Gg+sxTdWVlpRJC4oRGEsSJjN6FefPuUB6P+zBq5EhwsuSEqtfh5MYwH0OKBw8eQrdu3TB79mxZ4Ozs7NjELHq9SKJIflhQXlGB4pJi8erQQ8MJm2E1TdNAbwzbnzv3ZrD9hx56ENw8WtM0Vr2WSdriGh+e6PYzVOqqCCfz9GQym8WrR6/KmjVrMWKEIhlWq158wSMJhMlkRkFBAepqa0VWb1MubD5IPhiSpS3l5WXguVW14+PjjWHDhoLhVIbK6L0yK5tsqrb6lONPMjlFkWjif++994nnykGR2JaUaJomJI33R79+/WTM6PXkuIWGhEi4kmSytq6BeNNjxvVbLeliHvtGLEgqaQvz9GS1t1fhaU/xVjKP9xNlGfpk+8xjWzySMDLsy/Voa9askZDmnDlzMG7cOPj4+FCkTSZTm7TKMMpAwEDAQOAaIGBqFga6Bk1e1Sby8/NkQTHX9nCCZmP0HtELsHdvnIQQ4+L2YsGCT7Fj5050795dJnYugqYX6qWXXpJ1RvTQlJeXY/fuPeKZevfd90CPFvWRQHFS/f77JeAaGYa3mE+yxif8Pv/8C/HAcI2uk5Mzi4SopaSkgOuWdu7cgXfeeVc8ZpyAReAiPkhi6I1j21y4/c033yJDhdeaqzCZzNI3ric6ffp0k2JO5nv27Mbnn38ua9LouWO409TsfujapYvy7jmrvpeiX7/+TXRc6MLDw0OR1Bjx7H373XfSxvr1689b5aOPPpYF/SSmJGQkpfSCcdwyMzOUl9AHQYGB59QnIcvLywfHtKCw8JxyZlCPPs4c4/3798n4c82bTgIp1zzR4xgVFSXrp7Zs2Yw1a1bjlVdeRY0ijn369AG9o8SPiePJ8W+u49ixRFm3x8XvfNgiMjIKgYFBTcTYh5tVuHjp0mXggwXURw8a26CHlSFGrtPiPT1//nysW7dOeTXrlRfWUXn7dqsQ6Dboa8GIXRPlbeTCIFptZCAMMwwE2iQCHdyojuTRIqnhN3t6XkhAOHRcr8Vwy/Dhw/H00z8REsUJlqGYwYMHIyIiAo8++qh4vjjJ85rrhHi888471IRWCy7CnjRpIkaOHI6ammr07t0HY8eOVSRstyI4GeB6uKCgIPFazZ07Vx3dsWjRYvF6PP744zQDQ4cMkXVKiYmJWL16tSItfSVMqWlnPVpcwB8VxXVRTlKHE3337t3knGSB5IPtODk54Ze//JUKY9aKrsDAAFlLRs8dPSBcb0XC5OnpgYkTJypPSbaseWKfO3fuLCEo6qN+EkYu0r7pppvklQ2a9v/ZOw84K6rrj/9ml327sCwsvfciiPQiCKhgQbG3WLAn0cSoMZroXxONmkRjYhJTbYkdGwpiQbEBCooI0qX33pe2lKX8z/c+Bh7LLizwdvexe/ez983MLeeee2bm3d/7nTN3AnMXNhD90HG59HTTs6GxWd1VvXo1stwEj5wMc2tWMvdZMwNjyKNPQCgxRADVc885R8RoffTRUOd+xPXnBMR8ADI6dOgg7ItdALfE1zFWqjWoX19Nzc1KrFxKJELWfokyWC/ALmxPUxsfzFVggDEIAmvb1LlF0elnP/uZAc/tBrJedzL69j3Huf3cgX2gf4sWLRzLaYfObUtsXJcuXZydp0yZqisuv9zOb6Y6deokwBH9fmuAHaaLvjkHnLOyZdMQoRo1qrunMwH9uA5/9rNbjIWqsNfGSaZjsrF0PY0tvPnmmxyoB2TBvNJvWWPcbr31Nrvm2hhge9edc64xrmlithg78V3UO+usPs51m5qaZj8gWjqA7JRIgI9jBmixmO/mbdKyddL0BdIn46QBn0ovDJGeecsnbwN/DSTyNcB9yv3Kfcv9y33M/cx9XZzfg0wuxdl/PPuuX7+e7r77bhEg/O9//1v33/8bMXEykQEEuhrYgVWg7KqrrtobF9SkSRPde++9xjL9zwWHAx5oAzB4+OGHRZtLL73UPXXIZJlhLjaOkUN/d911lwNbtIGBuOOOO/TMM087XdCJMaZEIg50PPbYY0Ie4IxJmTISbTt27GguzWsNGNQgS6eeeqruMFkpkYjSy5d3AfFnmeuLSRW5PAGHrNtuu83pDTiBlUInWC8S/TzyyB8ciKLttdde62Kh6I9AbXRnHBdeeKGbpOkY22BD2B6YMNgy5BLPRTkgjCBubEv+zTffbOChogNwjOGWW25xYIyFY2FlHn30EeF2A0TRNvaaA1w++OBvhT0ZC/ZGJueL1eInT5ligKGsuTDb0PUBiXPB+Bkz55HxAbZpn5aW5uwZHgMIuSb+97//ObvWrFnD6RwKxa7IAoCTFwSBMWlVhD2wEXZs07aNsx+2RS7ngEQb+gzPP4HqyCD2jLFzPXCNkU8/jJfzkRKJgseUSMSdb/rhGoHFQn9kMEYeWkAG54s+OH/EcaFvOB7sDrDm2uC6YUv7REgJD7R2mHt79aZdmrFQGvKl9OaH0ksfSJ99JY2bZqBrjjTXWGGfvB38NVD010BBbT7d7lPuV+5b7l/uY+7nSdMl7m/u8+L4QixJjFZx2O9Y7RNWrEqVyvmqv9t+ASxctMitL5aaGhGxakzu+TbIo2Dp0iUuvuo//3lSTz31lGrWrKXOnbvsB27yaLY3a+jHHzvXLKxYtVxPTe6tlMA7qS72qrIIiE9gNYtEtYQFWnada8NmaepM6f0vkvT6R1FgtWyNtMvAV5FYx3fiLeAtEHcLcP9yHwO8BtqPJ+5v7nPud+77uHd4EIGx7MJBqvmiEmYBWCOWJDjY+SfO6lRj1a699jrVyiM+6mAmCYLAQFVn3XDD9ere/SSdf/55uvMXdxjYqnGwZvuVwZjB5Jx37rmORdqv8Bg4aN68uWCtYEiPAXULVcWkQpV+hMK359gv8yXS0K+lwZb4Nbz1wCU6jlB6cTbzfXsLeAvEWmDbtigrzX3O/T7X7vuiZLc8oxV7NkrPPi5QAsSDIMhz0EEQdZvhCsTFdrhsFkJpQz+42Lqa2xb3J/kFTehH/ymRqHutoO0SpV61atUEWMRVmCg6FZceCQe0AFnTZhvIGi2NNzYr21it4jKO79dbwFugaCzAfc79PtTu+9mLpaJitg7GaBTNyH0v3gLFbAHffaFbIKGAFr9k5y41kDVGWrxS3kVY6Kffd+AtkDgWwKXIff/ucLmYzKIAW57RSpzz7zXxFiipFkgooMU7MQcNk9Zu8CCrpF5wflzeAgezAGCL+//Nz6Jg62B141F2BIxWPLr1MrwFvAVKkQUSAmjxy5VA2AEGstZvLEXW90P1FvAWyNMCuBKHjoou55JnhThllnZGiwUeSfEwJ0/qsRAo23jI8zL2twB2Je2fe/RHnH/S0UvyEvKzQEIALd4RSiAsTyLlp6jPP0Yt4NX2FjhCC6zIkkaOk1hv6whFHLJZaWa0mFxnzJghFp3ktS+HNFYeFXK2b3eLSFK0YsVKjRo1Srynj2Ofjs4CnB/sixS2rLS/evVqxRNsIYt3X06YMMGfNwxdSCkhgBbB71PnFNIIvVhvAW+BY9YC85ZIs+dKxG8WxiBKM6PFJDt27FjxzritW7YctnmZ/D/7/HMtWbLUTf7z589zr7Th5cWHLcw3OMACvMwb+2Lnrdu2i9cE8QJlANgBlY8wg+ufa4BV6cP3CR6hqGOqWVErW+xAC5fh+HmSX76hqE+9789bILEtQLxW1mZppoGt7K2Fo2tJY7SYlJmMx40b5177gisvtBwrnPO6lClTpig7OzvM3rul7aSJk7RmzRoHnNatWyfqkrdx46a99diBtZo2bbp4Bx3vL2QFdfJJK1ascKBg3rx5CvsH1CEPWbwjL3f/lK9atcq9/5DyhQsXOaZs27Zt4ph2lKMjctmnL0DH0qVLRUIGq69///337vVA1CFv/fr1Ti7MDbJog1zsBHihLXnII3GM/ahPPfJiEzKxETohA31ogwz0pl/qA1xmzZqlUAa6I5M+ORfUpx5bZNAn74OkHvJ4tx/2nTR5snsVEktFVKlSxS14ig7U4XyiA+cDWfSJLHSgH2xBGfXJ45VD9Efd2ETeksVLnN2oQ33KyacfZGE7dAvzyKce55JxUsYx/WAH9pFBQgeuJcaNLOxAO3Rl3LH1kY8O5Id9Imt9VpY7j5QhA1tRl/NL/6Gd6R+54bVH/8Wdih1ozVsoLVxe3Gbw/R+OBZKSpcoVpPq1oqlWFWnPu2MPR0yR162YEdW7yDv2HR6xBQBbsFp8TxQGq8Uv+iNWLsEaMnENeOstvfLKKxoy5EM9//wL4j1+TICAgmeffVa8d+/VV19T//79xStewiFsz8nRa6+/rg+GfKCcnB1atGixWxX9rbfe1utvvKF//eufAijtrW8uwwULF2jt2rU2+c3X6lWrXRHtBg16R4MGDdK///1vfT/1e5e/cOFCPffccxpo+S+99LLeeecdxYK3HdY/7qu///3vonzy5EmCZXvjjTf06quvunboPGv2bH399dd67733HBDLssn3o48+Eu/HQ5fXXntNb7890I3/qaeeFqzQbGvz7LP/1TPPPKMRI0Y4Fxn9v/DCi07P//3vOU2dMtWBQib3p556yrV/8cUX3bv3wgmcgTDh48LjtS+vm25vv/22ezXRl19+aXbL0YcfDnFghboAkddff8PsluV0/WjoUL388ivunX2ci2nTpolz88knnwj93nvvfSH3y5EjjSVcIgAFY0L/jRs3ivrz5893enJe//Wvf+89nwMHDhSAA92QBUB7//0PxBiGDBnigDX2zY+9nDRpsrPx4MGD9eijjyrs57vvvnMyBg9+152Xl+3ays7eIuyN3bMNsE+aNMmd62XLV4jzSB9ff/0VJtibcHn+4Q+PmIwX3fiffPJJkQYMGGDHg/XXv/7FjQ974H5++eWX3TlgHIPffdfJnW5ubq4Pyri+/va3v7nzi43693/VrsN5zs4ffvihOB+AsL0KFPNOsQItvjj5tbp1azFbwXdfYAtkVpN6nShdfab0g7N2RdPZtn933h09AAAQAElEQVSa1KKJlBazth7gCxBGis0vcGdxqJiaGgWDp51kOp4undRWAijGQbQXUUQWgNVaYvP4th3x77AkMVqwGaSLLrpIV111pXjx7ujRo7XBJunPh32u1NSIrr32GrdKORPfCh7zNpNuN9AEcBlhIOSss85SZmZFzZgxXcuXL9fZZ5/lXiQMKGISt+run/cU8jqZGjVqqlu3rmrarOnefF6AzPvxIpFUfTPmG8eOMSlToV+/q9Snz5maOHGiMW7zXRn5JIBCjgEuXrDMC4XH2SQPoGA8P/jBZUJPwAILYaIrx7AXgAJe5vzVV18ZQFmqC84/342f8TLpI5fxduvWzb2TEXDw2Wefq0uXzrr66qvdy6IBjdT7xz/+oXbt2ll+P/ciY5gTAA8ACx0BErjaVprtLrnkYveOQoApDBegfeXKVQ58UheAtmjRIqc3QBMb9Op1qq677lqVK1fWAUbehwjYaNq0ia655mq1atXKAaw6deq4/uvVq6eePXvauUvVSusTUEEs3OsGitu2bWOyrtMZZ5xuzONUB/C2btlqNljsXhnEue7cubO++OILB2pbt27jZEVyLYAK81O5ciXxUubrrrvOvQT6awOzq1ev0bBhw4Rt0e2CC853QHXcuLGmfzkHxtCJczl37jx9//1UB+hgOnmHYxAEmMElbEGdrl27unNTvXp1B5J4vdA111zj6gwfPlxbDAxwfli5/+qr+6lHjx4OOGMnrm0AJ+eR64tGACrep8i1AGMG8J4+fYZ7MTbvXqROIqRiBVqrNkirsvxSDolwIRREB4DT2QZUerWTatWUKqQmqWxKkqoZu3VcfemiTlLDenJABjDTrMM2/egS6bJeUm1jvQrSR7zqALAAflf2ka4+28Ch6dzAGLiM1Hj1kL8cXxJfC8BqLV4nbciOr1ykMTmyLQmJCZFXxow0RgSWhu2aNWud6wq3EyzEu8YOlCtbTjfddJMaNGjg2JFx5mZ8+uln1a9fFFykpKQoMzPTuRA//vgTZW/J1u233+5W+Q7tlJycrAoVMmzCLSsm1XD1bybsdu3aqWnTpqpbt45Wr17tWAZA0Nix4/T00087FonJOdbdiFxALzoBNgBTsCmwODBZsGFjxowxcLbAyWbSxf0EkElJiRiorGtgY4oBuAl67vnnHFsyfvwEYznmO6DD6u7IxQ6AxEqVMgWThMvp7LP76vTTT1d0kp4p4pVg4xj79OnT9wIndNyxc6cDGI0bN9YJJ5wgtoAhyg6WAAGMBSYG2dgCpmqXXdwNGzZyAGbs2LHq0KGDLrroYtWoUcPsW0GABc4Ftgnl8w5F2EVWnK9fv55OMHBWvXo1p1fOjhyVL19erVu3Vv369dWkSRMBXrdt22oyq6thw4ZKiURCUW5LH9i9WbNmrrxRo8bi3Kw0F3BW1nq1bdvWyenQvr0o43qpWbOmkpKSNcNYppUGLk855WR9++1YLTNwvmnTRh133HFOduxHenpZBwCxGf2R0I9jxrvYXJecmzZt2gjQ++KLL7lztGLFcm2xaxBZAHvOI9cXYyE+kDYnnNBKnEvszLsVGUtSUrHCG9Tdm4pNE5Z0WG9Aa9Pmvbr4nQS3QP2aUp16u1QmWeJVKS8Mlv77tjRsgrTRJsEK1aT2jaRIspRSJjqYcnZPp9txpFwUgEVzo592nyo2RXP3fcaW5d7fVyvvvbIVpJ5tpKZ15Vi25CSJlHdtn5voFjC8oGz7ruB7I566JiXQl/HRjmvx4sX6/e9/r2QDQeec01edOnWyiTpZSUnJOvfcc3XLLbe4skf/+Ef96U9/ckCKPgler1evjoaaa2vbtm1WP0ntbHK97bbbDIzVd6DlnnvudgwX9Quakk0P6u7etYuNeKUMDAVg8Gc/+5ljb4IgcGXhR9iGY1gKQMxJJ53kmA3Yp3P6niMm+VNOOcVcS0MEEGrevJkxGJkGGnc6oEAfJFg9WKeIAQtskLTnXKfar7Bf/vKXxgSd4Ribe+65x7FLW/Y8EHDiiSe6/vr2PVswPEzo6BMmXFLomWS6hzLDsvy2gB2AMGwMul1++Q908cUXm96VdMcddxiDdrW5zqbrgQd+a27Rdx04zk8W54gyABLbpOQy7rwSBxX+cAj1Sk6yL1+rRH4QBC6+yw4P+p9s540xAtp27tzhZNMgKTnZAetscx1mZmY6JhBwBTsH6ONhCAA0L+yuXbs2TfJN9EHKXSErK8s9UDFx4iSdfHJP9erVS5y/3PWCINibxQ8DXvoN6wpI5voAuAXBvjp7KxfTTlIx9auddu+ttl+pW3cWlwa+38OxQJLdr9Uz5BgsJrsZ86T5KyWW5Ph6ovTNdNtfLqUaoEJuj45Sl6qpdmNLZSrKAbD2zSXkUA471ryhnBuyr7n1cEc2riUHiii370JRTlmP1ta+ucQ+iWNixEJZ1I9NYf4yA/KjJ0ufjpYDgrF1/P6xZQEelrEfyu57I56aMwHFU15xyoKF2L49x0DVecZANFV6erpTZ7u5Bt9//30DIjvU76qr9Otf3+cmcoKoqcAkSVzOwoWL9NZbb5nraLNw28EQnHlmH/3ud7+nmmBc3M6ejyAI3B7unHDydxm5PpKSkw2wNXCTdPfu3YUrDNaiUqVKuWrufwjTQQ7sTK9TT3XAsY6xZEy8Z5xxhkaOHOWAFuWAjjp1alsf5cT7AZmgcT/B6lCGnDCtMKYGVyntAFmdOnV0MUfYC9YFtxZArmvXbuJdfRUqVLDvsehYy9hYatWqZe65JVq6bJlj7Navz3KigyBwwBawAOO00lx924xJohD2BvkwMYylQ4eOjg0D5L7wwvMCUN52260677xzNWfOXMeiJVtfuPVg72KvU/pnTAS6r1+/XosWLRQuVGSQT395JYAIAeU7jZXLqzw2j74BhuXLZzgWEdfowoULBYPVqtXxjjXDTgTjcx6bGHMG2/TOO4MdgAbMxsor6D72yMpab+e6o2PSYEsL0hamkusC1hM7ZGTYZFWQhkVUJ6mI+smzmw0bJXPJ5lnmMxPPAivtfOG+se8TtWsaBT+1qkT1HDVWevo96fWP7JxulxrXkOpZorRcRGraWGpeR47tAmT17ipddpp0irFOXVoZ4GonXWEuvi7Hy4Ex+5Gmpg2lrq2l063uBadI1AuP+3SRamQi/cBkbLw2rDWA9aU05Ctp0hJp+25D9gdW9TnHiAVydhhY3ibtIUfipnX4yz9uAotRUO3adcxdVM8FL7/++msuZgd1kpICAwBl9MEHQ9T/1VcdE8Qv/nDyL2+upurVqumXv7zLgZepU6c4FmPChInq3/8VDRz4tmNeWpmLCnlhAnQ0bNhIo0Z9ZWzMNNcGWdg0CALBNOBSZNI+55xzXIzR888/r5dfflm4MJm8Q1lsw/rskwA7uKqoj94ExcNg7TKg0MRcd/Xq1VW1atXVwFxk9EF93IivvNJfxDBRf+rUqU4vWBf0Qi6AB7D16quvuXq4VwFUNc0ddvPNN4tYqldeecWN/dNPP9WGDfaLjYaWyphbtUOHDgZad7ogfeKrZs6c5dyj6I87kT5fsfbEHG034Iv9YfMAfgTqMxbsOmHCBHdeAD6v2nkh8B9ZTZo0NndspmPuaE9w95YtW4UtARN16tRxsWbYsH///i6YHFcrABMdOAfJfIGavknJSQ4U2a659sboExsPzBfHYUImspOSonAAW3EMkOrcuZO5ZKe6sb5idqVvQCxt6tWrZwCxrho2bOhAfffuJwlQmPs6oR9klzfQxpZjgBh9hMfl7RrkGFBbv3499xAH5x37RyKpZu8dzlbUCduwn5pqk4sJzDBg1bhxI3Mh11GjRo3E9WDZCfMftWwxqBN+YTIpFkP3vsvDtADniadDp8yVWJKDGK2+PeXir3p3kIjNIuAd5gHR3xnDNWYWe3Js0pTxxnpNNcCzU2rWYZu6NJNSkswFuVQaMUlasEwqlyb1QFb1aLvYT9Zao97sxQbErF3Lpiannu0nx9bat4++6MJ2X67fO1YtwHncYtdOvPWPZQriLbuo5dUxRofYq5YtWxij1UTXX3+9+vbt6ybtPn366IILzjd3T3UXJ3PFFVcYKKsvJv8e3XsorWxZEVtFADIxXAAG3G5NjKmAFfrJT37iGJjYMQE6rrrqSsc+AF7q1auv888/30261OvatasAP+wT34Mbrnnz5k439ALYUEZKSk4WfaILky55VatWFf3iOmTSZ4Jv17atizFKiUR044036tJLL3G6U79hw4aijw4d2qtKlSqub9yATLynnXaay6Mekzn1ABGwQ9jlpG7dlJaWpgsvvFBXXnmlyId1I3YLZod2pCAI1MRAHoHmLVu2FLFAjW2CZ2KHTTq5Z09dcsklbsLH5j/+8Y9UKTPTgSSCvk8//TR3DggCJ+A/08puuOEGnXrqqS7/1FNPEe3Kl0939rjxxhtcfnp6OXU3NpB4KfQ8++yzneuRceIivuyyHwjwjN6cA1imIAjcODhmDLA+nM+IgUXGQgK0IPOUk09xbCDHp5ounAf64fzBstUxcIe9bjN3cigbdu76668XzCDjZzx33PFzB3SQHZvQE1ukG8saBEHUjWzXHcf0iTuVYHzOTV9zD2N3rrt+V/UT7dAfhpMHJcI22IPzSvsgCJz+7dq1c2MOgiC2+2LfTypODQpzxefiHFdJ7ZsYmbHmimMV/xkL5YBS7VpyrBOB8L1b7Fs+YfxMadH2bcLNuHuzNNEA0lwDU9imi7kUieFavVr64lsJNuxLA1uslZRhrse2dam1L21ZZ3UMpFHvc6u/yn5gRlKkOlUl6u+r6feKyQJF0m1Odvy74Us6/lKLRyKTHRPppZdeai6o89S5c2cBdjIyyruJHtARlgE+qA/wadO2jXuqjWMAAMewBbAwAA9iiWB8KI8dWRAEoj/KkUPAOZMfEzR1aQ+Qo01KJOImV+Sddx6uzSaOoaCMRH10CvsmLwgCIfOss84yQHWpG0+6MR+UkWBwAGe05ZgtbAjsGeNkvIyjdu3aoi6TOPWCIBB5oVzqITcIAmcHjmmPe5J6yKVdmFIiEWEPxgIgqFLFvoj2FFbMzBSuWGyCLdhHNsWADY6RTRlusSAIDAhXdG3IP9VADvWCIHDnDB3QkzzGCrBDH8aFnpdffrmLNcNO5FMP2ZzzsE+O6YtzxPlIiUQocikIAgcWsXtqaqpzkWIrjpFHPxwzHvSAOXMN7YO+uMbCPLaMDyBkxfv9Y3vOe5qBWeRy3dAHx0EQOMCPLMoYC+OmT+rQjr4Aiow5bIM90I3Yuo8//ti94QD7AF736zwBDpKKU4f01OLs3fd9JBYg6B0Q9e5w6YUPpU/GSQAfFwjfUTqhsZzrLz/Zdp+pZjXZDS1VrCyd21265hypTzc5RsvuOaVV1AF/PDQBQ7XaQBYPUVCBeLDkgD2fSoMFUgyEx3ucJYnRirdtvLyCWaClMYhM8AWr7WvF2wI8wuY+VgAAEABJREFUaMBSJLh0AWKAtXj3cbTyig1o7XEHH3RSPtrBJWz7Y1Ax+7Gjji2ly3tJF5h7D/Zp7gJp2DfSe1+aC3CJBEtF7BZPHRZkiLgOy1eQqlWS0u1HFjJxS25dn3/rnTvyL/MlJdcCScmFM7aSxGgVjoW81INZIAgCxx6eesopB6vmywrRArBl0SdS+wq3ZiF2dcSik464ZRwaVsiQC46OgygvopAtQGxlrdpSG3MPntBeql1Fe0HyWnPp5OyUY6lYykH5/DFZApQIqMeliOtw4Ajpqbei6RVjyEhDv89bAO3LGjCraIka26zfnbvZ86mkWwDwXr2cXXNx/sbyjFZJv3L2jY9FR0lhDvsEorMlhfmHu8XllhKxX4qH2zDB6h+r6gRB4NysKZHEPQdx/toq+KlKtp5ZPLJcWsHb+JrFZwGeDl22VFqzeZd4ivDyk+WWW2CpBRYxrVdTYqX/+Wv215FlPMoaY3ViK7nlGnh6bPiCbWJbtarU1fJxN5J6d5a62zFMV6yU9CrmWuwisTzEheZiZIHU7TnSktVygfaxdf1+ybQAjGr5DInvjXiOMCmk1uMp1MtKKAsAolgGgeUqWAR1wYIFYtkElitg0VJWn2fpCl6ZQ92EUt4rUyIsYHCneMZhIFTVa0rl04unf9/r4VmAp76mLZTGz0jS8iwJ8NS9rYGtnlGWC2k8OfjN1OiThdTfuDDVxW/hUmxrbkcWEIWZmD4mVTyRSMwVC4ry9OLZPSTAWnmbTAFyyAsTT6iyPMSlp0ktGsg94s9TiLMW2b4xaWE9vy25FqhSXipn3xV8b8RzlEfOaMVTCy+rMC3AcgYsZMkaUCy9wDvyiOlhpXaWZ2AZgX/9619i6YjC1MPLLr0WKDaghcn58qyWqb0uKPJ8SlwL8NRhGJPFUgujJkojzc3HdsQY6f0vJBYxBWQxiiXLJZ5QpHzkBIlFTrcbMNq2Tfp8dLSMBUVzy2ARVNqHiacOv5oihXJYgHT4eLnFUsM6B9tuNxcjAJH2vFvzYHV9WeJZAJdx3RpSBXMdxls7z2jF26KJJ491twiY5qk1nhLknXuso3X88a3cCvl33nmneyXRiV26KAiCxBuA1+iYt0CxAi0e0W9eR+JJtGPekqVkAICoMAj+02+kT7+0ZNuRk6PAh/LQFACqmfPlFg2lLnXCckAbTy+yoGhuGWH72O14A1rIICEnNxiLrZt7H7cnAJG29BnqkLueP05MC2Qak8VSHqll4q+fZ7Tib9O8JG6zL4Ply1eooCuTEzuVs3274uHKSytbVqzN1LJlS82bN0+se1WnTl3VqVPb2PFdbuVzlnGgXl66H20eY2CleFZmP1pZx1p7xs6Cr7huD0d3rhcWtOU6OJx2iVq3WIEWRmlUX6pZgT2fjiULAFZw/YWJ47z0J59EPbaxdTgmUUZiP7Y89z51SIeql7sd9UlH0ja3LH9c9BaoXk0K37EZ7949o3WgRYlfYm2ieE1yyGHV89/97mF9MGSIe8nzgb3un0M81cuvvKLszZv3LziCo+TkZLEAKC+4Jj7rRz/6kapUriTyidPi9TUVKlRwx0cgvkBNXrGxfPbZp24F+QI1KCGV+CHDyvZvv/32YY3Inf+XX3avIjqshodXuchqFzvQyjB3AIHSSclFNmbfkbeAt8AxYoGKGVL7RlJm2cL5qmIiOEZMUSRqwkDMnDlTTzzxhHuvXTw6Xbt2rT788CO3YjqLibLg5KHkliuXrszMTCWXKXOoqgUqB2QxLhYEpcHCRYtcQDzAi9fGpPG0BQWFlBYvXizclYUkPqHFrly58rDHzjsP58+fL1y+CT24AipXON9eBeycarjEeZ1K84Yc+eQtELUArsX3P5MeeFp67C1p7YZovv8sPRZISpZ4WIIHIcrYfmGMvCQxWrineIoO9xgMEvuhywYABaggnxdHU4c8ykeMGOHei8j79mASYCDGjRsn3tWHuw8X3vjx4/XSSy/po48+Em1oG3s+OIYZeueddzRw4EDnooPJwm3E+/hWrFiuOXPmOIYiCPbFQdFu4cJFQq/33ntP4ZN/SUmBMjIynOuQIPWXrO8woSd90Rb9aEe/gBnyYvViHyBF23vv/bUuuugS/fKXv3Sr0jOJZ2VlRSfzGJ1oEybGwFOJU6ZMcWOnb/RBzw8++MCNNdSFvtknn/FQD3YwlMWWOtgY24auMQAgcjlf2Is61A0T9vn888/FeSB9++23og379IVujJ9zg8zc7TnGbcl5ph/OJXqRj+xRo0YJmejMPmOmb+p8//337tzQPzLIDxPXAbbBFuRxfocPH+4A7OZNm9w1tXDhQsfi7dixU6NHj3bvTKR/dKfNjh07xDHnB/1ph16UxSb6Rgd0zMuusXUTcb/YgRZGIVaLlcFrVeHIJ2+BfRbA5Ufal+P3SosFamRGl/tITy28EZckRmvFihX65z//pb///e+aNm26Bgx4S08//bSY/Fm+4E9/+pPLZ1J9/PHHHWMF0/Pcc8/p8cf/4l4evH379r0utGRzue2ym2/goEGO4VqwYKEDG//4xz8dYIo9K7Nnz9aDDz6okSNHauzYcU4H+mHSRg512eYGtjwJeOedvxBPA3722Wd66qmnBJPBpI27LTs7272oePny5aL/d999V6+//oZ4yTL1/vjHR/X116Ndv//85z/dmHJP1DBovBdx0KC3ReIpwzp16oh8Xu9ywQUXun10zJ0IpAfM/OEPjxgYGSuWh7jjjjtcED0g46OPhupvf3tCWQbYVqxYaXZ8XF988YUmTpxk5+Kftp3o4sCQiy0mT56s//73v47h4WXJQ8yV+oc//MFA6FzRD+PnnFA/TLNnzxKut63btmt7To540TLgJMdACmPmKcoJEyba+R6gZ555Rrnbo9czzzxtYx9kAG2WnnjiCQFseBpzxozpeuyxPzkwhc7sA4gAQsOGDXPyODfYHBm4lEO9uFYAP04Xu27efPNN/fWvfxPnat78+Roy5EPBZlF/1KiRdjzE2ePJJ5/S1wa66B89OObcMq7H7BpdsmQJTfYm4vrQmXOPjoz5q6++coBub6UE30kIoIWNalWS+nTf96488nzyFjiGLeBVPwoLVK4gndpeqlXzKIQUoGnuib8ATRK6SsR+tRKDdP/9v9EPf3ijm+jmzp2r1EiqLrzwQl1xxeXG6lyklJQUA1ZTHAgoX768rrvuWj304G9FwHjvXr3dOwy7de2malWrusmZd/tde+01+slPfqLmzZsph4Xw9lgCAPGRMV0VK2aajAf161/fZ3WaOwajTJkUnX/++apRo6ZOO+00NWjQYE+r6AZAlZISESt7I7tNmzbRgj2fZQzs8T67u+66y/S+0OQepxtvvMGuixp6//33Xa1LLrnYyi4S7ibYIvRxBXs+tm7ZIoAQzBaJfRg9wCH7GzduEDZCl92spLynXeymZ88euvvuX9nYfu1sw7v67r33Xt18801asmSxkw8o7dGjh/pd1U8XXHC+W0STPmBtkLVgwQIDQ285G5x55pkOQL5jDOApp5xibtWLnX1gh9AlPz2QE5sidl4vu+wy/eY3v9Ytt9ziABztQxuwnTlzhrsOwuvi1ltv1TvvDDbgusCJ4uGAm266SQ88cL97n+QoY7iy1q/XsGHD1bBhQ/3gBz/QWWf1ce8SRD/XyD64bmrUqOH6XLZ8hbGY81WpUqaB+WmCWStjNHStWrUdcOf6ue+++8yGd6tp0ybCLvMNjMGccu2hP09/7jDma8yYMQLEWRfuf4wxeDBrvPvwsssuVbVq1d21C9h2FY6Bj4QBWtiqcW2pTxf7cvXMFubwyVugVFoAkMX3QKvmUj4eHcXrryQxWoBGQEvlypXd5MYkB/jBHVW2XFkHJnBPwVjgZgwnM0AXE2YZA1/IiLUteb179zL2YKdjRGASGjdu7CbUsB6gAHdOixbHiRcolytXTvXq1bPJfZVNmNvCanlu27Zt6142/Y4Bji+//FJVDdhVr1bNzvs+9yINV61araFDh6qWIe/u3bsrJRJx617B1vBCYVgkxkHazcJ7NNqTNm7aLFxYAKmDJQBKftdDZmams2nEbMREX6VKFUVMh/T0dBtjjtlnh1ghHrt+PuxzY9m+dkzitm3bnPsTwAPDB8DDfgTfr127xuqsNtAxR4MHDzZX23civ8xhxqVVqlTJuULr16/vdOB87xm6YORguMqXzzCwW8ONgZdLUw7zxLZcuXQ7n5Uc+M7MrGigcb0DregKGMI1O3Xq965OrH0YP2OBSR079lvxMug+ffoIhgvZFStWdG3og+srLS3N9cGLqnHbAto4X/Xq1Xfnu2KFCqpbt47ZZJWzp/b8cV7WrVsrACCAftOmjY6BNO/ynhqJv0kcoGW2iqRIxGudar9k69eSX1/LbOL/vQVKiwWSkiXu+xBk2Q/iQh96bmBR6B0WYgfhJBhut23baszTdje5MkERlM5ECJvC8gYFUWWHuaqYMC+66EJ17drV5OUY4HrHAZewfRAEKm+sGDE7AAr6x+XHRAwjFdbLvQWg4Yo699xz1KtXLwcSiA+bOWuWAydhfWSNGDFcxOmcccYZAkhSRp+NGjVy7xq84IIL3FpYnTt3VhkDQ5SHCQAAa3TWWWeJhA3oD1kch4njZGPQwnaHu8XFNmLECPXs2dP1E2tj5MIWdurU0bkglyxZ6kAHQK1Ll87GgF2gH/zgMl1zzTWOtQuCYL/uYRB3794lM4yBkJ37le3ew8JtM1CH/QF8sRU4Jp9y8mH12AJ42OaVkpPLuBg5GEZsC2sI48haZGF9xtS4cRN3XnD7dujQQSSYu5kzZ6mxAfK01EhY/YBtOQPkAK5tdp1SuGPnTnMJb3F2QTZ5JPSsVKmyuG7R5cYbb3T7aWXLUnxMpKRE0zKyB2z16Sr3ypW0/M9Toqnu9fEW8BY4Qgtwn/OKJe77VsZkFQXIQlVAAduSkphEYXgmTZzkgtlxxbBGFBMtbjLAEG4Y2Ir8xpyUnKRtNmkvWLhAuJCInYExAthUM7Zp/fosIS9sn5SU5IDS5MlTBNCAeSCWpmXLFko1FiOsl3uL7WHCCJZHBswM/ZLCuky+xDV99tnngs3avm27i8Nab64t3HQrViwXQfCMe8KECY4NQW7YPvd2x44dgpVjPMQX0TYEKrnrcnw4CdnZ2VuEbowLG5MXymjVqpUuvPBCd/jpp58IkNWsWVPHfjFmmKeJEycacNng6oQfPBSwzcAIen85cqQxYLPc+QnLGQssEiAVgFKrVi1hT8rLGOgEjMJeMl7qvfbaa8Y41hVAiDp5pYoVMoxpbGl9zREMGXF+uPR2mGsvtn6VKpUNkJXXokWLxfi41rhOFi1a5FysgV0bsfVj9xs2bKQqxgzyI4CAfsZBu9atWyuW1QO8RSIp7rxvs+uS65fztmnjRhdcj36xchNxP+GAFkYym6pxHXMjdpMuOjnqSkxKpicVH0kAABAASURBVMQnbwFvgZJkAe5rWKzTe0bvd+77ogJZ2DGckNgvCYkJiYnnX//+twswJ7aGiZag77Jly4lXzUyaNEnHHXeckpOT3YRWpUpVxyYx/iAIhJunYcOGLsCcCZbV1NesWas///nPLtAbWbipqE8KgkA9e/QwluEMF7TNk2HE4ZxyyqlOLu6hOnVqu/6oHyb672osGRP+f/7zHzHhdunSxekG21GzZk1XFfcVrqjhw0fo7//4u5544u8uDujUU3tZn2cK19azz/5XBFczcR/snCIH9yGTN8zYzJkzXZya6yifD8AlYCcIAgEcqjhwkeFqM7YaNao7NyJu0J49e+jFF1/UmDHfugVRcZcB5KpXr+5ARX1zqZ5xxukurmnFihW67rrrXD7nhac1ASkwiE74ng9cfSeddJIASF988aXQB1AaBIGrkZW13vUJowZbx7kJgmhZEAQOUJ1zTl9Nnz7DnX/A4G233eaYQexcvXq1vcCMvjkmH/aolrlqn3vueWMxB4kxpOViqBjfCSecoG7duqpGjRqi3YknnujisOrUqRN1CZoLEVujLOecPjIzM1WlciUXm0dsHdcWrBhAFHnIQV5SUrKOa97c2YkHEbATjBk22LhpkwvqB3whO5FTQgItDGbXhzLKSW1aSD+6ROp7atStYHan2CdvAW+BhLNAwRXiPq5VJXpfX3221L2lVCFd9sWsIv07GPtRpIrEqbOUlIguvfRSPfnkf/SXv/xFPc2NlZqa6tgFAuSfe+45/fa3vxX7BDk3NEB13333qmXLlmb76OTMJMZE/Mgjj7h8Jj7q0BaZTOZMhLEqE5t1ySWX6B//+IdLN9xwg3DZBUEgWI7HHntMsW6nsC19/fSnP3VPt9H2yiuvdHE9nTp1Ev1XMcYDPQcNGqhXXnnZ1WNsTOYZGeVFGe3Io0/kBUF0HGEfsdtdu3a7Nb1GmIsPFizpIIwL7VIiERdkfu655zqgyLgJOg+PAYnYpEGDBkJXxoKdfve7h8WYGQ+urzvuuMPpmhKJCN3vvvtutWvXzp0XAv15WhA52DY93W4EOt+TACYEq8fKpf/QLXv++ee5c037XntcsHuauk2asYoANXSiH84lwenJBrTJ51yjO8e4LjlOiUQEQGes2BbZ6JYS2d/FRBt0YTwVKlRwwP2iiy4SY8JWlCOTQHyUYWwcc95SIhFzkzZ3AfKMjT5w8WIvbINMrqGUSESMC3uiP7bE7gBmwBz9IjuRU8ICLYzG/UJKT5V6HC/ddJF0q6Vz7ddvx5ZR4EXgLIsa+iR5G3gbJOo1wH3auJbEfcv9y318+5XR+7pCumySV7H8HWqiLRaljrBTxlKuXFnHTjDBkYJgH+jgODYFQWB2DxyACIJAsX9hvSCI5ofHbIMgmhdbn/0gCJysvOqQp3z+giA4oF0QRPNkf0EQ7C1HDikIojoEwb6yIIjm6SB/tWrWEIwSzAjMGwAJux2kies7CPbJzqv/sH0QBK4+dUhBEG0Xux8E0TpBsK+MclIQRPOU6y8Igjzlphsoo12YgqBg7bXnLwgCJ1d7/oIg2O84lMs2CA4uW3v+giDYT0YQHHgcBPtkITtMQRDND4ID24R12Mr+GtqPhIceesixiXaY0P8JDbRyWw6XQu1aUve20qWnRYHXnVdLd/U7NpPX25+30nINcJ/eaD+SuG+5f7mP7bs09y1e5Me7cj2hVuQKxLFDWAkegefprTiKLVGiZpirkAGxvhggi3g2XI7kHWspKTlZV111pbko6xxrqh+1vkEQiPMHSxoEUXB21EILUcAxBbRCO2BXEsCLFEmRfPI28NdA4l4D3Kck7ltSeC8X9/ZQbEZx63c4/QO0zjnnHLfEwuG0K011ly1b5mKTcGeeccYZyszMPGSMVqLaB2aHeDnGEkcdvahCsMAxCbQKwQ5epLeAt0AptEBJYrRK4ek77CETi0YjnnLbuHGje1KOGCbyjjSxinp2drZ7EpDAd+Ts2LHDLVVAoHaYR75PpdMCHmiVzvPuR+0t4C1gFjhqRstk+P9jxwIET7PgKQuqArp4og1m6EhHsG7dOn00dKhbpJNAbZ6QXJ+V5ZaQ4HVEL730klso9kjl+3YlwwIeaJWM8+hH4S3gLXAEFvCM1hEY7RhuEgSBWx4BdxtPKKZE9n+K7nCGBlO1ZMkSTZgw0T1RybIDvFJm9Zo17hUxPO3JwqRjx449HLG+bgm0wDEJtFgzbcNmaekyac5in44hG/jzVYqv12XrJO5b7t9E+S71jFainIljT48gCNwaT7xTkqUiWOWeZRNYK+uyyy5zsWC7du1UyxYtj73BeY3jaoFjAmjxhoHN26LA6pNx0itDpafekp5+T/rfu9Kzg3zyNvDXQCJfA9ynT78pd99y/3If80OJ+5r7O67faochrLQxWsQMTZ8+XcQUHYaZiq0qrBGLpsIWsV9QRYibYgXxgj5RyEr3vAgZ+xS0D+qVSUlxL49mTaeaNWu54PqUSMQt1ErgPQuQppdPp6pPCWuBwlcsoYEWX8D8Ap40XRrwmfTfD6XPvpKmz5HWbpC2GfiyHwyFbyXfg7eAt8BRWYD7dOv26H3L/ct9zA8l7mvub+7z4mC6ShujBWh59NFHRSzRUZ3QImrMuxZ5dczzz78g9gvaLa8OeuCBB4RrryBtsrO3uNe5zJo1qyDVXR2AH6/NYSX+s88+W6xh9uqrrwrARuratZt7B+Tbb7/t6vuP0muBhAVa/NKdsVAa+rX0xrAouMo2d2HpPVV+5N4CJcsC/FCaOV8a+GX0Pp9tbtXtOUU7xpLEaBGYzaSPBUOGJmR0yCdIe9eu3RS7J+J4XxzAC/bHZdoH7i/yly9fYT9k7Zes5WVnZ4tjwANbZPNUHW0XLlykjRs3Wa0D/6lHHdgothzH1uIYebBIgBbcb+hIPseUZW/Z4prggluzdp3C/iingLq0IZ8+0Iv83Il85FEPfcP2YT1eXdSsWTPn7iOP+sijPu8upB/yY9OuXbs0evRo93qa5cuXi/cJElg/e/ZsDRgwQPPmznV5sW38fum0QMIBLVis1Zt26asp9uU7Sho/U+LXcOk8PX7U3gIl2wLc2wCucdOi9/uISdE4rqIadUlhtAAOBF2zACf7a9eu1csvv+zedwho+PTTTzXm22+1e/cuAWiGDx/uGJznn39eEyZOFGALQAFAgJV56aUXNWzYMG3etMm9V/A///m3q//xx0PdS4a/+eYbvf766+rf/xXr5yUtXbp0v1OGPEBI//79xQrsPH03YcIExQIWgMmAAW+6wHHYKmS+PXCg0D1782ahA4wUbQBrAwe+7d7p9+qr/Q3cbXSyYKD6G4vU3/Tob30hg75jlQE8jho1yvR9ba++yI2tg42QBSClPXKQ13+PXBjA3UxOMY24dng9EXFZyOOJxvPPP18NGjQUrxDKWp+lWrVqiff3xTTzu6XQAgkFtLiON2ZLY8Yn6euJ0rI1HmSVwmuyhA3ZD6egFuB+574f+V3RgS1YiYLql8j1giBw6rGkACzWXGNTPv98mCYaiAJAARyoEARJxrLkuNeWsMwBIAYQsmHjRg0ePFiwMV27dhXvkhs9+hvNNFcabM2YMWMcaGjXtp1zO37xxRfu+OSTT9bixUv03nvvOeBDHyTkff/99+I1KbynLhKJCBC4yYAb5STe1QcI+vLLL0X98ePHi3cQLlu6TIsWL9b48RNcrBMgaLtRnejUrl1bt3QCMVGMc9CgQY6dQ4/KlSvrgw+GaOGiRYjfm4hJ++KLL50u1EPfDz74YD996QMgCGuHLkOHDnWxV9RfuXKV6TJ+v/oID4JA9evXV/fuPZy9AFToWK1aVfc+w1atWumss85y7zOkvk+l1wIJBbSyt0t8yY75XvJuwtJ7UfqRl14LcN9z/xMyQPhAYVsCVqKw+ygq+c2bN1d29hYDPosdk9W8eTPhTgQ8oQOvLGHL+/F69OghXigMI4MrbfPmbPeyZYAGi3kC1ObNm+tkAUZr1Kgh4pBatmyhefPmadKkyW59KOquN+YGIIYLEPmkChkZOv3009nVd999p2XLljtZsGku0z5SIhF1NVAHwKJfdK9UqZJWrFzhWC5ealy9eg33omL2AT0n9+zpXjq9YsUKrVy50gHD3r17u7GgX7ZdQOhu4t0/Ok2bNs3qzdLMmTOdXPQdN+47AdRcpVwfXBM7duzUggULHSC97rprxcuOcQvGVkU2wBBWDqD51ltvOcbtxRdfdCwewJX4LI5DoBvb3u+XHgskDNCy69q5C0dOlgiaLT2nwI/UW8BbINYC3P+EDIwYI/G9EFsW731ARLxlFpc8wFDNmjUcsIFN6tOnjwAHX3/9tWOfADHoRjwSazwFQaCUlBTH1OTkbDdQtlYVK2ZSxQVxA8SaNGkigEeZMmUUoe6uXQ6gIAPZMGIwN4CcFKvjGttH1vr1evbZ/2rChIlizarq1atZrg543U3Lli0dwzZp0iQXTN6hQwctMkZq9OjR6tKls9JSI24MMGLIT0ou44BXTk6OAG07duxQhQoVFASB0xk9cT26zuyD8wugSk1Nc6Ap1Pess/o4OVblgH/k/eQnP1HTpk3cGB588EHBoCErtjI69TTAeuWVV+pQqUP79rFN/X4ps0BCAC1chgTCjhprN+LOUnYG/HC9BbwFDrAAsVtjZ0lTZ0p8PxxQIU4ZgIg4iSp2MYAngMqAAQMEAGnduo1gr3An8vJdlhpISoq6GHMrS1uAGuDihz/8oX78ox/pmmuuUbOmTR3QCesnJyWpYsWKqlOnrohHuummm3T99deLdyymRCJhNS1cuFAwR9dcc7VjwgBjgLq9FfbsZJqsRo0aGZv2odCR2KbZs+eImKjWrVvvqZX3BlchwArXJuOF4cIVSVxU2IJygBNg74ILLlCoLy49xhzWi91mZWVpxozp6tv3HP3lL39RmzZtXLzarp07Y6s5cJcSiTgXY9myZd2W1/lQLzs7W+yH+SmRqG0AesSAsd1PmD8o0RZISoTRLc+KBsLySzYR9PE6eAt4CxS/BcwLpFFTJb4fCkub3CxFYfVTFHKDIBCABkaHbZXKlRyblJIScYxWZM9kD/iIBZgwU2XKpOjqq692MVL9+/fXAHODvfDCC5ozd65TPdmYJHbKGKtF8DeyiI9655139K9//csBpVjwULlyZceW4VLDfUa9bHNr7trz1COySMjr1KmjVq1aLVyf9erVN6YpWYC+qlWrUkXoR3IH9sE++lezcuLMiMuij1dffVWsZQVLZtWs/4ilFAeUtm/froEDB+rdd9/Vk08+qSFDhjgmj3phSrYxInuXsXbEjfXv/4qGDv3IuShxuwYGMsO6+W2zDWB98umnzo6x9qA+wfSLFy/WB9b3kiX7PzxAuU8l1wLFDrRwDYyfIq3IKrlG9iPzFihVFojjYFeukabYXL89J45CY0QxYcccHvO7PPkGYDqlwkibAAAQAElEQVT11FMFiIHVuuqqKwVrBIiA4TrttNOUmVnJjZVg7s6dOznmi6D1G2+80VyI69xaUG3bthUAgzqnnnqKkpKTHYvTsGFD9et3lQBCPKlHndwxTLxL8MYbbnR98MRg3759ddppvY31SXN54UcQBOYi7KJLL73EBY2zFhWxXZdcconTKSk5WeiOjknJyQacyqhbt25Or5RIRLBUuBjpg7Ffe+01bomGcsYwnXHG6crMzHRyb7jheudinDFjhmPOGCv2CPUAODJGAB4gERviamV8nTt31hlnnKHY+mG72C3ACj2ICYsN+o+tEwRJh5QTW9/vlwwLFDvQWrlSmrVIfgmHknE9+VF4C8TVArDcs+ZJq1erUFyIsBdxVbiYhZUrV06AJdaECoJA9evX03nnneeYLVQDPFx11VXG/NTgUMcff7xwo2VklFeZMmVc0Pddd92l2267TbBFuL6oQ5sQaLBFPv3ce++9uvzyy1WlShUnL/xAVpu2bXTHHXfo7rvvdq5F6lWrVi2ssneLy/Daa691QAjZBL0T4I4Mjjt27Oh0ZD8tLc0tl0AQPwLo98ILL3R9IAPQR7308uWdHSjnGH1//OMfKz99GSdjBNRRH3YtHN+ll17q3o8YBAFd5ptYGgI3JjrkVSkIgr3ng/OSVx2fVzItUKxAi9iLqcagrttYMo1bwFEdU9WSkqX6taST20nn9oym006SWjSRyqUn1lBSU6N6oV+oK3pXriAxjsTS1muTnwVWb5DmrpByduRX48jzSxqjdeSW8C2PxgLEXbGURvXq1ZWRkeFEwXC5Hf9R6i1QrECL5RyW2Bcov1pL/Zk4BgwAOGnfXLqwu3RKF6lr62g6pY108SlSn+MlQAxDoW7jBtK5p0kAnVr7/+ClSqEmQNaJLU2nbhL67dXV9O5jqUZmoXbvhcfRAsRqLTNGqzC+J0oaoxVHs3tRh2EB1t6aPHmyWOaChw+mTp3qHgg4dsHWYQzeVz2kBYoVaC1fJa33sVmHPEmJUqFudalHR6lWTSklSeJJ0dEzpDWbjM1Kk9pb2QmN97FFGfW3qetxUpd6UtnoQzdFMhRAXqO61m/7XappgGrLOmn0ZGnBMtPT9GjZVGpmOqXZfpEo5Ds5agssXSlt3n7UYg4Q4BmtA0ziM47AApmZmbrxhht05plnuvgxmC1ivfz1dQTGLIFNbLosnlHhNtxkLkNYreLRwPd6OBYAvFRquk0VykVbjR8nvfCu9P5n0iBLgBgeymlnICZi7sWUMtF6yXuusIi1Q0Y0N/rJMcwTgId9UrQk+skx5WxJ7OdXN9oi+knfTRtKmWWTxJsG3vjC9PxSGjBS7gk2yutUNdCVFq3vPxPfAoQXrN8Q/ziteDFaiW9Br2FhWiA5OVnl0tPdKvUso0GcFk9/+uurMK1+7MjeMw0WvcI7d0krsyXec1b0vfsej8QCZVanumZB4DaqmCEX67RirfTZd9LHX8k9jr99p/STy6Qr26WKuhWNCbu+r3R5LykESrgVrz1H+vUN0m9vkh78cbQ8dDES79X3VOn+H0r3XCrdelF0n7oc48JEVlST/T+Ty0iLtm9zjNs0Y7KWrtlXzmQdHu3cHe75baJbgGtqtTGTfG/EU9ckfh3EU6CXVWotEASBCLq/9tprRQA9+wCwUmsQP/C9Fig2oLXLgFaOAS2+QPdq43cS2gJzVku4e1mSAzfhRQacerSW6lQ296GBLVb15+XADGKOuemW2cTIPo/mL7XjJdae4wqVpfN6Sk3NvUfczXJzH+fY9dCmhXTuyXIAjnphSq8ila8grTJGA4aqQjXpzDZSQ3P/hXVit8T0TPwyVa8NlQYbAKSPJGPZalaQahuTRVA1uniQH2u1xN/fYgCe7414auoZh3ha08vyFvAWyMsCxQa0QmVYATrc99vEtQDnaYOBqS8nRWOzAEbH1ZdO7yqdd5rUs50BH2OuADTU/XJMdP0jXMTESLHwJCt9A6x7GEiqmSllb5V7t+V75tb7aoodb5ca1IoCsFhLhPVwUfIuTNzNgK2WleUYsti6sfsAKXQhj+D3ntZvhrkwF62QFlsCgFHmU+JbgPPID7N4a+oZrXhb1MvzFjhGLVCIahcb0IKx37ytEEfmRcfdAkx2M+dHV/EfYuBo0nRpw7ZdLuCcp/rO7S413AO2YJ5WJ+87weuMtYJpIj6qRX2jr0y73Zvtw/4jZexjz38ZY57ql99zsGdDPRatXGisGGANVs1YelU0UFauAHFWmcaA9THdAHEbVknfmd6x7sQ93fhNAlsAAF8Y6nlGqzCs6mV6C3gLxFqg2IAWLoD01GiMT6xCfj8xLcBEx9INPHmIhlPnSEO+kd78KEmfmntu2w65pxFPbCURDE+dvBLxU2VTklzsVtlKUo8OcktDnGhuw9Q9gCutYl4to3k7rZ8ccyFFjw79Cci6sJucmxJmbNQMCd09m3Vo2yVSDUB+irGR8dbJM1pHbFHf0FvAW6CAFkgqYL24V4PR4ovzYJNy3Dv1Ao/YAmnGHJ3UWfrBWbt0Wa/oE3vrN0qwTONmSYuWR0U3rBLd5vcJUNpifsfQpTjJ2n5jDBNblmAYOUGauSS/1hJALSU5//LYEkDW2W2jIAtgj9txzPeSB1mxVjo29pPsnJe1xPdGPDX2jFY8relleQt4C+RlgWIDWsnWc9myUlJKXmr5vESzwNat0pYtEksmVDf34CnHyS1OytOBBJlXrBDVeHM+bFOlTIm6BKKvXmMnP1pdLET59UTpc2PFZi+VSGFA/Z4qCtKl6ub+4ynD+jWlmrYPUFtvrkRYqrBe7Ja+iAVjzSzyWY6iWEEWSvh0xBbgB1mGMeB8bxyxkDwaJiXtuxbzKPZZ3gLeAt4CR22BYvuWIcamlk3OFdOOegxeQBFZgHfOsV4W3XU5UfrJpdKPL5IuO83AjwEpgtQnzJYIeKfOtqWp7rUpBK73MffdBZaYMD//VlqzeZfIv+CUqAzkXHWGdFEnqXEtWu9LBLDTx03nR/sqF5GItZq2Nm92CvajUzOpfRMpkhKVU7WudMVZ0vUmg3Tl6VK4lES0hv9MZAtUypCq2TXG90Y89fSMVjyt6WV5C3gL5GWBYgNaKFOtklS2PHsHJJ+RYBYgRmbxSmnoaInV4JdnGaDavUspKbuEK3DZcoknByfOkahLWr5BmmbAC1C13eqGQ8Ld+P4XSZqx0ADXJjkZyFm9Wpo+V8odqA6AW2+gKpKxry9ireYvCiXuvyXgnhz0Wr1pl7K27BLXWtUquxQmJu2iXK0efXw6cgtUNJDFEh9HLiHvlp7RytsuPtdbwFsgfhZIip+ow5dUIV2qa2CLFb8Pv7VvUdQWADwBtoYMj64GD1gK04Bh0rBvJOK2Qr1YDmLw11JYZ/h4A2d7XIs8vTjI2rC0Q1iOjEHGduWOodqxXnpn1D457LNmV+56Yb+4J2cZCAvlsh04Yl97jj82XXh1UNjGbxPXAriMm9bWQZfyOFLtPaN1pJYrje38mL0FjswCxQq0UPm4RhJPH7LvU+JbALBFgpWabuxVmJatiTJZsSOgHks65FWHMkDZ3AXGYu2Rg4zY9rH7mzbvq0fftI8tj92nDFlhv/lt6T+2nd9PTAtUryLVqiqFTGU8tfSMVjyt6WV5C3gL5GWBpLwyizKvXg0p9kXERdm378tbwFug8CwQD8mwWQ3tO4IHIOIdn4V+ntHCCj55C3gLFKYFih1oEazcrqmUaW7Ewhyol31sWYBlIGbPN3fkBIl4rPyeLjy2RuW1PVwLEATP90Nhsd6e0TrcM+Lrewt4CxyuBYodaKFwrZpSny5yLyjmuHQmP+pYC/D6HFx+xH19YWArv3is2DZ+v2RZADar4/HmNrTvh8IamWe0Ds+yOdu3a+PGTdqxY4druHXrVq1fv97t+4+Sb4Hdu3dr86ZN4jpgv+SPOD4jTAighUuA9Y7aN/dgKz6nteRIId6q5IzGj6SgFmCJjlZNpPYt5d4ioEL684xWwQ27fPkKvfzKK3r11f7617/+pTlz5mju3Lm6/fbbdeWVV7n0u9/9XuvWrSu4UF8zsS0Qox2g+v3339fQjz/WgLfe0uRJk7Vz556nm2Lq+d0DLZAQQAu1cCGy1pIHW1jDJ2+B0msBQFbzhlKvrrsK/UEZz2gV/DqbOXOGNm/erHPOOUfbjdn6/vvvtWXLFv30pz/Vr399ny677FJ1736SKlSoUHChvuYxY4HVq1dr5syZ6tq1q9q1a6dFixdplwdaBTp/CQO00JaFKXt0lABbuA3I88lbwFug9FgAkMX9z4+uquUL/+spzoxWiT5RLVu2VK9evbRr1243zpSUFDVt0kQdO3RQenq6MjIydOKJJyo5OdmV+4+SZYGM8uWd2/ivf/2rRo0apZo1ayop2Z/rgpzlwv8mK4gWe+rgQqyZKQG2uhwvVczYU+A33gLeAiXeApWNCOnRWo7JqlWpaIa7i5dgFk1Xhd4LcTMwDuPHj1eYpkyZojVr1uibb77RF1984Vw9S5cu1aSJk9z+4ShVrVo1NWvWTIsWLVSDBg3Upk0bVczMVJCUpGHDhqlG9RoOcB2OzOKsS6wZNpk+ffph2yJeeq9atcqBljDmLV5yD0fO4sWL9cknnwhdDtWuceNGql69uiZMmKDly5fvjdU7VLvSXp5QQIuTEQSSA1sdpL4nSo0byFAzJT6VOAv4AXkLmAVgr7nPeSDmlC5SlfSi+1oqSYzWho0b9b///U/9+/fX++9/4NLQoUO1cOFCNzF+++23IoB52bJlGjtu7GG7fYjHmTdvnptcW7c2RGznjrzVq9do3LhxqlqtquXk/Y/L8YMPPhDAL+8a8ctFx3/+858uYDu3VPp/7rnntG3bNmNnNmj06NGaNWuWs0vuukVxDAgG7BUn0OJ6GDXqq0MCrekzZig1NdVcxbfowgsvFABt06ZNRWGmY76PovtGOwxTAbYqpEutmkvn9TTAdZLce+nsHB+GFF/VW8BbIJEtkGReh/q1pNPtBxX3Ofd7eqoKNfhduf5KEqPFWGAZTj/9dP3whze61K/f1WpuLFTssOvXr+/ibGCi1mdliQTLBUDhiTLAWGz9cH/JkqUCwAwZMkSvv/66qE/ZsmVLtXbtOjcJc5w7AcaoC+v13XffacOGDQ7YEN+1YMECkQBiudtxjC4wT9SBcSGFOiIXoBKWAVaQDZgaNGiQ5ptsWD7kkBgn/aM/4HPHjmggN6Br6dJlBkgXOXBGn9SnLf0hH7lhPmUk+qec4P+FCxcpOzvbMWPUpQ1lO/Y8nUl9xks9AAp1yatRo4bOPPNMlSlTxsW/0YaEvXiakz5J6L58+QpjkVYYQNzk+sEO1EMegerII6EXdqGMNhyTjxx0JZ82jI980q4CPHUUiUSUZdfL1q1bBHuJ7pGI3bAIKEGpMIaSVBhC4yWzjH0R40Lo3lb60SXSxQa6OraUcynyfUTfVwAAEABJREFUJU2KV19ejreAt0DhWoD7lURIAPfx5b2k686TuL+5z7nfC1eDA6WXJEZr585dbsKuVKmSateu7VLNmjWUVrbsfgOHfXrmmWdswt6o/q++qjvvuks/+clPdcUVV+m3Dz6o1atX71c/PMjJ2a6TTz5ZHTp0UOfOnZ37EPsx4V544QX5ug1zcnL08ssvC5Dz7rvvOnZtxYqVevzxv+iGG25w6bHHHtNSc2mGfYXbZca+PfTQg64OQfekTz791AGNqVOm6s4773Rlv/zlL517dOzYsXr11dc0Z+Em/fe//9UaA4DIAmyMHDVK9L9o0RKnT9a6dYKRefvtgbr11lt1/fXX6amnn3ayAUUfGRtIf+h47733mst0MaL2JkAHet9yy89cW9y1PIlJXdrQFnAJoAFIMt6bbvqxfvSjHwn7A6h4oOChhx7Wli1b9eWXX+r223/u0g9/+EM3tiVLljj27fU33nB93Hrrz8zN97F72vPue+4xMP1D0T8sHWAMMAVzeeutt7ky6gMsAWLY5p57/s/lX3vttXrNwHIsENw7sHx2TmjVSm3btnUs4Oo1q9W9e3eVL2+MSD71ffY+CyQ00ArVhOFKT5XatpQuO126q59060XStedI5/b0ydvAXwPHwjXA/XrbldH7l/uY+5n7mvs7vNeLegsLVNR9FmZ/TJwwKkzisBqwQUy+sX0COgA/jJ2nB+vVq28ux//aBD7ULc0wcOBABzZi2yAD8Hb++eeLBGtWpUoVbd26VQA78qgDO4T82LZpaWm6++671aNHD1133XVugh448G0DORv1zjvvuFTWwOCbb77pWJ2wLfJwNwJ6BgwYoEceeUSAOsYIm/Pw7x7WRRddpEGm72mnnabPPx+mFi1a6I47fq6WTSvrQQONAE3kJScnu6clr7P+GzdupHsMpODq3GGsVqdOHfX888/pib89oVdeedWA5hoRtzVy5Ej94he/EH0z1gED3kTUfgnd2rdv5+rgTgXktTJAAqN29dVXC/2z1q/XGwaUli9f5gDeM888awzgWk2ePNm5Ybdv3+ZkYrfKlSvp/vt/o/fee889XPD88y9op7FinKcmTZroL3/5i07r3dv0fcEB3aEffaS///0Jc+MtEQB00aLFro/LL/+Bnc9P3DhHjBihmTNmatq0abr44oucvR999FF99tlne1lJp0AeH+jEOWWcO3budECLc9+tWzcDWeUFgKMsZ/v2PFr7rNACxwTQCpUNtywFUdtcDi0aSD3a+eRt4K+BY+Ea4H4l/pL7N7yXi3sLI1PcOsSz/+3bc8y99y/B8MD2sOYVLqj8+gCA1K9fz7FRLMsAYFmwYKGbQGPbMJl+akzSoRJPo61atTq26QH7mzZudMsEALx4UjE9Pd09rQh7hWsrbLDDmLCpU6c6YAbQIRi/Zs1ajrVDx0XGTMEgwfbMnTtP69dnOaAGQAtlHGqbmVlRzZs3V8WKFVXP7ED9tWvXOHcmbj7YobfeesuxSnPnznXAiDph4snLTp06KTMz09xq6zVjxgxz7y13rlUeTGA8AN/Ro79xY6xatarq1Kmta665RoDCIAhCUe5pzWrVqotxYhPOxezZs5S9ZYsi5rbjQYS6detqrTFxuP8At2VSUlSzZk01bdrE6TxjxnQnD504tyeccIJj0OrUraPeBtAofMfALawmLBu6kZdfgrUbPXq0DnXep9h5ApTlJ6e05x+TQKu0nzQ//mPXAqVd85h5JSFMAauTEIrESYlIJEW33XarueUed+mqq/o5EFFQ8UzoedUlCLpz5y7mMjx4wrVUqVJmXiL25sGMcBALcgEF5O3as3QE+ySYt7CM4zDl7MhxuzBhgDVYKpgWgIwryOcjts98qrjsHcYisRPKh6W68MILFQT7gBHlpFDm7t27lGPu1ZSUiGOjAEXnnXeeKleurJ07dziAKPujPuwg4NEO8/0HxOVVuGvPk7LICYKoPsR4UXd7LmYpYgCtnoEzymDZcG9WMtcyfaMn+QdLFTIyBFjL69x37Nhx7/XQuHFjoc/BZJXmMg+0SvPZ92P3FijlFihpkwMTLswUrAgpI6N8nuAgPO07zR1ETFbIbnz33XjVqlVTEWNKwjpsATu44Ug1alRXSkoZrVyxQiz1kJoaMValhktM4KkHeWoJNxTgpV69es49B6MCwwVzRduKFTLozqWk5GS3nMS0adPdEhXouWbNagE0atSoYW7E6mKCBwDB1jRs2FBp5qYMgsAtqLp92zYXdO+E7fmgLbu4vNjmlbgmWMKgho2zXbt25m672D08UKdOHcc65dWGvPLly6uh6VDHGKsLzMXau/dpwt3HeJEzc+YsrV27VsSnffjhh+5pR9qFiXORlbVOsEi4RgFFderUdWxWWIct7Bl9EHNFUP3KlSuNzVromDD6o87s2bMdCwfjN/jdd7Vw4UKrs0DHHXecevfqJVgw6h0qlbHrAJstWbLYztc0V71atarasiXbLSHy/fdTjcWbbmziBlfmP/K2QIIDrbyV9rneAt4C3gLxsACTSDzkHMsyZpi76/HHHxdB3NnZm4XLigk2vzExueNGC1mlr776yhib6BN8+bVJM/AFswPAAED06dNH2dlb9Nvf/la/ffBBrVy5SmeccYbKG4MSygDc8UTepk0b9cADD7jgdp6W45xVq1ZN/fpd5WKZ7rvvPnOX/tO9Emj37t1unafy5TP0l7/+VYCzUB7bRo0aOffif/7zpAM95OVO9MvirLBYL730kv7v//5PL7zwont4IHfd2GPcj3379tWkSZP069/8Rn/721+dixR9zz33XAOIO/W73/1Of/zjo2IcuAdj27NPPkH8tJ83b74uueTiPIHWpZde6h4uYOx/+9vfVK5cWediZXzY8Z133nHxWc888wxiVcOAKeueffTRUKfb0KEfOzscDHDSMDs7W2PGjHFjByQ+++yzrh2uS0A5YI9g+1WrVtr4dtHEpzws4IFWHkbxWd4C3gKlwwKwFyVlpFUqV9KvfvUrARJix8QYeW3OZZf9wLFbvELl5z//udIM/AAqCOK++OKLxZNoBH83b97c1YuVEbvP5Exg9apVq1xs15o1awTAia2Tez+tbFldccWV7uk+5Ldo0UI//OGNBpb6uXTjjTeKp9rQJ7YtDM3NN9+s66+/3gWz446DMaMebrnbbrtNV155pYt5OumkkwR7VNeYJ8AMgfIZMcANucQ5PfLIH3TRRReKZS4uv/xyx1Yhr3x6uv7zn3+pjrWvbO4+wAxPDiL/2muvEXZChvZ84Fb72c9+5gLEsTFsIjqgU79+Ni5z2/bu3dvp1NCYrptuusnpSUA+tqB/XK1/euxPBqZSHFtGPWKv6PNXv/ql2rRubWURMdaLL77EuefQldX46Zt6yGMZD9piG8ApfVGG3QB5AC1YtltNX/J/+MMbhR2OP/54tWjR0j252aBBgz0j27chTo7zix2pS8zaCmMyYfyuvrqfe1MAT6LSN3rta+n3Yi1wTAGtHTulDZul6QukT8ZJAz6VnnlX+s9bPnkb+Gsgka8B7lPuV+5b7l/uYyMfYr+LimUftqFYOi6ETlMiEecaqpDrXYNBEAiAUq9eXTeZ46IDcLCOFmpQnzicLl26iMkWwEB+fgmAQZwPzAtPwbHcw6HaMAnjdmzXrp1zcVGfOCWCtkkE5KdEIgd0yZpYr7/+hnMF4g7LyckRrA3yypUr58aL3q1atXJPPwZBoJRIxIFN+kozV2KsUIAIdUmMG7ADOxYE0XaMBbnIZ4zUQz4uN/JjZaVEImratOnefimjP8AhY2rdprUbaxAEDrhyDpCPXtiCPmDBqMc+7WHiAKL0yTlKiUTcOcNWnL8gCKjmxogdqBcrj0L0BGxThv6ME/kVMzNFX+SjI2WMMcPcyw0bNnSgmfaxCYbxkksucXFaAKyaNWuqZs1azr5cR1u2bFELA80A09h2fn9/CyQ80OLLePM2ac5iadAw6SkDVS99IH32lTTOXMZzDXQtXCb55G3gr4GEvAbcvcl9yv3Kfcv9y3381mfR+5r7m/t8/6+mojmCiSianoqmlyCITsR59RYE+8qCIHDsSK1atQTbwUQcBPvKdZC/rdu2u0n5sssuczFRgwa9c8BTivk1D4L9+wiCwIGQ/OoDNho0qO/WncIlBwNFXhAErkkQBK59EATuOPwIgsDlh8ex2yDYVxYEQWzRAW2CIHB5QRDsVy88CIL884PgwLIgCJy8sD3bIIjmhbFXxMcFQUDRfikI8s4Lgvzzg2D/siAI9vYfBMFe+UGwb39vpu1wXQDcYLWIo7v99tvE2lncN8R9rVy5UgC5IMi7vYnw/2aBhAVafPHyBTxjoTFX9oX8soErvqjXbpAKsIitDc3/ewt4CySiBbh/uY+5n7mvB9j9zX3O/c59X5Q6lyRG63DtlmZsD+4x3IrsF7T9ypUr3Orup5xyqh5++GHBamRlrS9o88OqxySOS/PFF1/UE088IdxUsFKHJeQYqAygwaX74x//WDBPiaIyLmGC94nD4ynDbdu2ubg3XIqsfs/DDGlpZRNF3YTVIyGBFi7CZculEWOkN+1LePocaWtpWQ8tYS8Vr5i3QPwtwH09c36UreZ+X54lcf/Hv6e8JfLLPO8Sn5ufBdLTyyslJUXLli0VcVpt27YxViMjv+o+/xi2AMtFjBz5pXjy8+uvv9bHH3/snkhliQ4AdpqB9eTkhIQRCWX1hLPQ9hxptrkJ3/9W+sZcg9mbE8peXhlvAW+BOFsAhmv9RmnkZGno19KCZVJRMVulmdE60tNYrVpVtW7dxj1ltn79ep1izBbupSOV59slrgVgtJo3a67OnTu5WCwYReK2ANpt27Z1r2Nira7EHUFiaJaUGGpEteCX7Nyl0ucGsuYb2DKWMlrgP70FvAVKvAUAXLBb738h4UosCrCVlJRQX4HHxDlOTk4WgdkEYRP0XaNG9WNCb6/k4VsAxqqNMZZnnXWWSLzfkPPPwwysYUa8HPuHL7l0tUiYbxm+VFeutF+0o6TFtuVLt3SdCj9abwFvAe77ZWui3wNzlxQ+s1U4jFbJP49BELin4Zh0gyCQ/yt9FuDck0rfyA9/xAkDtDZmS+8YyOJLli/bwx+Kb+Et4C1QUizA98DQ0dKazYW7CKJntErKFePH4S2QuBZICKCFy5DYDB7PT1xTec0KywJerrdAXhaA2R42OknEbeZVHo88z2jFw4pehreAt8DBLJAQQIvg96lzDqamL/MW8BYobRaA2Z5n7kPiNgktKIzxe0arMKzqZXoLHPMWiOsAih1osXbO6Kl++Ya4nlUvzFughFgga7M0eZZEaEFhDMkzWoVhVS/TW8BbINYCxQ60Zs+Vlq2MVcnvJ7oFkpKlyhWkWlWk+rWi23Lpiak1esXqWTEjMfX0WuVtgZDVWrpahbLkg2e08rb7Yef6Bt4C3gL5WqBYgRaxWTPNNawzSK0AABAASURBVFBYv1bzHbUvOGILZFaTep0onX+qdFkv6cLu0rknSxd0k1o0kdIi+0QDckIgFpu/r0bh7QEGGzeQeneN6hfq2dd079hyfz0LTwsvOR4WgPWeu1DKLoRFiz2jFY8z5GV4C3gLHMwCxQq0Vm2QVmXJv1LnYGcogcoATj3aSCedIB1XX6paVSpvzFa9GlKr5tKZ7aXaVSRADqlZh2266DSpj4Ex8otqKPTdsK50Wgep63FSPdMPPWtWk9OzeyupYb2onkWlU65+/OFhWID19Bavk7bkxP8JRM9oHcaJ8FW9BbwFjsgCxQa0CG5db0Br0+Yj0ts3KmILAF7q15Ra1N+l9FSJNY5e/UR65UNpxCQpe6u5EK38RAMxEXMthurVzLT8suFR0W0b1ZEDWLtsbv50tPT8YGnIl1E9q1eXWlaWYvUsOs18T0digSwDWuuzkuLuPvSM1pGcDd/GW8BbID8LBEGgSGpkv+Kk/Y6K8GCnTYCr7ctz684CdOqrJIQFqmdIZVOik91306XpcySW5Bg7WZq0QMrZITU0RgtlcS92qZoqu+ZUpqJ0cmcJlx2AjXK2uBVPO0k6t6exT7Yl7osyUmqqnCuSspPb7dvnGDmHckXOmicBsAaPkMZ8L7EuE0+3EutTJllKM53KpdGTT8eCBQDymzZKfG/EU1/PaMXTml6Wt4C3AN8pVapUUdmyZfcao9iAFhpssC/OrcaEsO9T4ltgpZ0v3DeAJ9xvxGQRXI5rZ8hw6YGnpEffiD5BekJjqUGt6JjKGbhvXFtqbiwTLBIgqu+p0o8ukE7vYO691tHtHVcZIDNQBQhLLiM1bRgtO9NA2NV9ovvd20oX9bJ0slxAfrSH/T8JoAYAfjFBGjdN2h3IxY5VLC9VrCD30uKt66Ps1v4t/VGiWmC7/SDbuE2CoYynjp7Riqc1S5csP1pvgfwsUK5cOTVs2FD16tVzqdiAVviFyaSYn7I+P3EswHlauNxYrIVJIji5Vk3pqjOk6wwAde8kNTR3HDFcocYjx0kwSLiIedhh2mxpvLFMTJiAsC7NojVxQY6eIS3PknjtXA8DXsiKlu77XLBMGm3MGfXJbdpYQg6gjOP8Ejqd2FI6/UQDZ6dJ1Qxo8aqniYsldMmvnc9PLAtw/W0xsBVvrfj1GW+ZXp63gLeAt0CqMQowW6RiA1pMqkzY/nQcOxbI3iyNnCSNGBON0SI2mXinXu2ky41h6nO8MUbmXmRE42casFpnFIQd7LZ230w1kGauRjtUhxZSShlp9WrpS5P3pckDmOEeyignta1LrX1pM+++G22uwG8kXsvCQxTEidWpKlF/X80D9yImr/0JUpdWciALgM8DGFu2GztSCBP3gRr4nKgFjv4zJ/voZeSW4Bmt3Bbxx94C3gLxtkBSvAUWVB4THpNlQev7eolhgaxV0jfmjnv/i2hwOWwUwKdCNWOY2htIamLMVHL+uqalSTz9h/uRJwHbN5JYcqF1Mzn3HvnET+WWwEMTWw0crd4g8RAF5anlpOSAvfzTFqvP652I1UJXZDSqL3VtHO0v/5a+JNEskGLnO946eUYr3hb18rwFvAVyW6DYgBaMFsocyvVDndKYEm3MxoK6YHaC0XHFrdsYjX/63JgmgAyuP2Kx2jVVgZ/mI6Ad0EOqbewUIGiDsV/ET+U3/p078ivZl881hb7EjwW7o0wasVqwcfMWRlmweg2kSnvYt30t/V6iWoBzWhi6eUarMKzqZXoLeAvEWqDYgBZKVLCJjuBo9n1KbAsQnF6rdtQFRxxV7SpRfXEnLjfWCJYJNio9OZqf3ydAacMeFxCuw4Ej5JZeYPmF1z+TXv9Q+nx6fq2lshXMPWmJGttMzk4DUuzHJlizHh2j8WMXmUuTOC3Kt1v9jXnUp8ynxLYA3xPVjdEKf6DFS1vPaMXLkl5OKbCAH+IRWqDYgFay9ZyRKsE8HKHuvlkRWoCnQ5ctjT5RWCFdLiYLduvkdtLZbaXGBsIIfJ+/5kClylaSWF+LpxRZAmL4gm1uPSQWPO3ZRmpWL5pYYJRlIHJLSDdQ16eLHKN2YTe5WKvtOdKS1Xm/Aw8whwzix1hIlVXrWRKCVeLbm2uTslVZKpSVxpHtU/wtkJQilbcfZnxvxFN6SWO0du7cqaVLl2rSxEmaOXOmNm/aFE9zlXhZGzdu0ueff67Nm41aj8NoZ82apXvuuUc527cftTTOLbq9+uqrWr9+vebNm6fRo0drx468aX7qT58+XVOmTBH7eSlAW+pwrbCfV52izlu8eLGefvppodduJpUYBch77rnn3Nhzl8VUS7hdgzvFoxPsR/WaEo/cF48GvtfDsQBPfU0zt9s3xjat3rRLgJ8eBrL69pTatIhKWrZcIuidp/mov3FhqtZs3iUC39u2lABVMBPTx6RqhskimL5xHQkZJFZwr1VWqlI+Ki/2s2VT6bLTpRbm8iO+b66BvlmL8g5oZ7kJ1tHiqUfqoh9texwvpSRJ6MkTkDwNGduH309cC1Q1FhNmku+NeGqZFG+KLFa5It7fZhf+W2+9pbvu+qUe/eMf9dvfPqi//u0JMdnnN9EWsYoJ39369VkaOnSoAFzLl68QoAagUtBJfav9Iv3oo4/0wQcfOAC0JXuLpk2zL804jXzVqlUCiGw34DZ79mx98cUXrp+8xO8y0P39999r0qRJYj+vOjk5OaIOY2Q/rzpFnbdlyxYtWLDQzsHGA7reuHGj5s+fHzcgfEAHhZRh004hST6EWIAqE2q1TKmw4i8OoYIvPkwL2HeIhn0jvf9Fkggsn75AmrNYDjSNmSoNGCbNXym7qaOClxjwGjY6yZVTb+6KaL7NB3rzs+jTiwAuypA1fpz0wqfS3GXReuEnTx2y+jx1qEtfQ0cZYMqDPQvbLDQZ73xtfUyK6kc72tMWPWfO36dn2MZvE9MCfD80rCFVKBd//UoSo7Vw4UINGDBAP/3pTwwg9Nff/vY3ZWSU13fffScmZtgtJtRvvvnGsRzrjRXJDSAWLlwkEvnr1q1zIC07O9sY6N0unzJAG2WhLIBcXoxNfv3BFsFMoMe4ceOErNj+mPgpg5Wj79izTt9z5swR7WkL6ABgwu58++23Gj9+vNasWeMYHOoBTGgDaOIYPTlmnzLyGQftkFGlShVdc801KpuWan1M06hRo5z9srKynA1oQ7/0hS2QF+qHXEDA6NHfCP2XLl2mnB05rnje/PkujzGtN1lkUh/9kUVaakwkeZSFCbuEfU6YMEErWZvGCvmB0K5dO1144YXaaYwW4+F8WpE2bNjgzi/7Xbp0UY8ePW2OTTbgssnloxt6ACYjkYio07VrV7EPq8X5pA42wT7ohI2xOTZi/KSwjH7ChA7Yk7rIYAtwohy5lNE3bbHdggULxNhJ2IK+qLvT3BJLlizR2LFjXTnnFFtQFpuwJXrSHhsAdENd6Y98dEU25RzTP9dmrJzC3i82oMUv04i5A4j7IaamsAfq5R+9BWCpSKwI/74BpRfelZ4dJLF9/8so8KE87AlAxTIPlFPvs6+irkfKie36YkK0LWUvvCsN+jYqg/LcafyUfXXDvnLXyX3ME5L0GfbPNmwbq2fudv44sSzAEh4s5ZFaJv56MWHFX2rxSUxPT9eyZctcqlAhQ+ecc45atWrlgNbbAwfqv//9rwba9uWXX3asywYDW7HaDh8+TP37vyImx6+++kp/NGZs2rRprj0uG8pXrVqt9957z8Dca07Wv//9b02YONEBkVAWAOlDY3boJ7Y/AAtyYYrIR+aLL74oJkcmzD//+XG9/vrrTi6sHIxN7AQL60L9Rx99VG+++aYDDjA2r7zSX7B5lCF7k7lM33nnHX344Ydi8n3vvXf117/+VatWr9ZWY0yefPJJAVxGjBiuP/zhEdGOCRmw8+CDD2q2gbnJkydr0aLFjhEC7KxYsVLPP/+86/eNN95wbWYZqxTqB2v0vTFIM2bMMIA6W3PnznFs06ZNG529GO/TzzytTz791I2XetgHvUN5Cw0sh/KwJfbinGGnwYMHO+CRbSwZPxBwI/7nP//REgNor776msaMGePOAfZlfJvM/QmzNnjwO8IeQ4d+JPoL9Rg0aKDLpw4JuQAbzieAnfPw+uuvGcBeKMb/5z//Wdh5sOmBPpShH3qGiWvlvvt+bYD/Lb322mv65z//qa+//tq5ThkHtn7r7bfMrT1DXDPPP/+CGDs2YB8wxPjRd+TIkRo06B09++x/nd65r1UA5Ut2HaMnMjiHnFPOE7r27/+qa//008/oiSeecOeNfv7y17+4c7DTGL9Q78LeFhvQCgfWxlxBNc0tEB77bcmygAc0Jet8FvVoYLNqVZfq1NslXp0U7/6ZsOIts7jk1a1bVxdccIFjAJ555lkHWJiMGjdubIBhkUaMGKErrrhCv/71r3X++ecbSJmqadOnK3bCAZTBHsAmADpgKBYtWuRYEoBBu7bt3CQ5depUnXxyT91www3KzKzkJrQd5oYKxz5//nwxUQL0Hrj/fl166aWOaVq7dq1YyLF3796u7XnnnSdcbVlZ613TlJQy6tOnj+679161b99Ow4YN208/V8k+6tSpq1/84k61adPGsU7lypV1TBT9ffXV1268jGXu3HkuZm21AawVK1Y4ALrctgDJpk2bmiSpRo3quu6663T22WcrBN7VqlXXGWecoXbt2qpv375q1LCh2W+4GDc2vOyyyxwYBYwBEhFUJiVFvXr1Us+ePXTSSd0cUwRLRNkZp5+hu+++W927d3euRIALIHDHjp2u78svv1xZWVkC7MWeD8AnrNBPf/pT3XbbbWaT9kpOTkbk3lSpUiXVqVNb2BwwAvDs2LGjyhvoDivBIn733Xgdd9xx+tnPbtVVV12lMmXKOCAY1tm4cYO7Zjp06OCukR/96EeOBQPAodMOY86aNGmsu+68U+hLf9g0bB9u063fc889x8ngHAwfPtwBdcobNWqkm266SeR/aoCzevVq+uUvf2Xpl+IcDhkyxNVNMVvCsv3qV7/UrT/7mWMqp9g1h4wwYSuu6YsvvljXXnOtypcv7659gC26cu7+7//uUb9+V2nJkqU64YQT3Dk48cQThU6A9lBW/tv4lBQ70OLX6vHHy62hFJ8heSklxQL2w1Pbdkibd0p5PV1YUsbpx5G/Bfh+aN9IyixbOF9V4cSavwbHTkmauQbOOussMUF27txJgAtYhdGjR4vJmvJWrU5QhQoV1KRJU2VmVnTxPjAx4Sjr16/vJvKJxlAxETFhM6HOnTvXValXv54DK8QdvWes1lNPPaV58+Zq/fosc5PZzepqScuXL3d7zZsfp3SbAAFEl1xyiWrWqOFcVLAcAwa8pa+MNcOtuWVLtquP66527dqqmJmpBg0amFvRXHYEWrrSfR8tWhznABJAGRfR2LHjHFv3jrFYgIr169eroYEjJl3AEZPw8TbRABZhnSpWzFR1npa2IBJcAAAQAElEQVQxkTVMJ0AqAMEO3X9SUuAAYVJSsgMkZE6cOEkAixdffNGxNfPmzXOxQoAQyoMgUMQAQrIBIVKKAZnkpGQDABk6zvStWLGiqlWrRlUHXLEpujzzzDPGIvZ3Nss2N20oj4rYnjbHNW+uypUrq1atWqZXhKK9ide9NGnSxGy1ToARgHKnjp32lrPD2Lp06ezisdAf5qhTp05Ki3kaDRA814DpKaecIsAbNgHA4a7cYl/GqalpAqhxbrAdgDkEmfRBCoLA3NUZoi16A27QZ6u5N5KTy6hRo4ZuDMgDWLZo0cJsUlVVq1Z1IJJzSVm5cuni9TWZmZnOdugDU0sfYeKaRmeu8eeef86BYNqiE7py/XCtcz3VMDDNFhuie7axgrF2DmUW1japsAQXVK6dF7VvIjWsV9AWvl5psADxYF9PlP77tvTKx3k/XVga7FCax2hzlGCzWGetMNgsbMtEzbYkJAAFMUXNmjVzrNDVV18tJhsYjmybwGEJwnHuMqqZiSYpKUmBpTAfQEIbmKRkAwwwTytXrjI2Z4RNhO0UviiXCfT66693LMsDDzwgWDIm3lAObEm4z5bjajaZbty0Wcimj6uv7qdLL7nUAS/qkJKSktkcVkLns88+y+lyp7Etf//7E6ZrewHaAFQwa+yffvrpmjJlqrmyRqtDh/aK1TcpxgYH67xDh46uH9ilRx75g2MQAbAHa0NZUhCw2S9xPs444/S98h40lyUMX8iChZVhZ8L9vLbJdp4aNWrsij7/fJgB6EwBiF3Gng9kAqB+ZuwQfQKoXnjhRXE+9lTZCyiDIMll4cIDbHMQ2if3lrK8UlgvrzLy8irneqQsTGGdvGxHHeq3bNnSGLqfORtyHcKwAqYoT06KXkvI4fpjSz5p5859Pwo4LuwUtWhh93II+emp0kWdpMoVDlHRF5caC9g8oOzN0rI10toNPnC91Jz4mIFmpktnttchX7MU0+Swd2O/fA+7cYI14Nc8j8WPHTtWyTb5MpET68J+B3MHrVixUpMmTXTuItgY2JlG5sqhPBwKbQBBxNqw37p1aweucO/h9iIPtmK9MVj0R122yAtlsK1Tp46YpKdPn8ahiy367YMPObdjVlaWYz1qGJM019gwGC1X6Qg+Mowtg6HgKTXYD1gUWCtYDVgcXFNTpkxxbFBHswEs3+jRXzuXYxAcCH5yqwAgBYwnJSebK7CzvvtunFJSIuaqq+NcfTAqudtwvHPnTu3iiS8O8kjly2c4xgYQjM7YC91IsdWxP4HcMIgwdexv23bgUhE1jLGB9Rk27HPhKo51GyKP80O8He5g7NC7dy9zpy02Rm4TxS4BRps3b6aBA992MWS4j+cak4lu5cqVc3UO9QE427hxo2M9CTgn+JzrJTcYBXTTH65RrtHszZuFKxHmk/PG9QW7xXmcNHmyY16bGGsX2z/XNNcp11n9evWczsuWLhPnK7ZeIuwnBNDCEBWMUT3/VKliBkc+eQuUBgv4MeZnAfMciLXTatWUCjAf6kj/EvFL+UjH0q5tW8FiESBNDBFxPTxZdtppp4lf/tddd61wU11xxRUimPnUU0/VCa1amX2DvV0CugBPTGK4iWCwcEPWqFFTuHkoZ/IHdP3vf/9zMV883YiAWNCKjEvMVUjw9ZVXXuX6JaYLVySyCd6+4oor9cknnzjXGmAN2cTpJJuLCXkwTgT0sx+byhu4Cif+8hkZLraK9jfffLNuvvknBiYnObaK9rB7bc0uDc2NWC49XR07dlDTps0cUEImdRgj+yT6ZqJnLDAjuPsIpga8nmGM2Fnmmr3zzl/ohhtudPFMAAHahSkSiTi32YgRI/T2229ry9YtQl5YDlBljNS7/PLLnRv3xhtvdPJwxYb1wi3n9IwzztDDv3vYsTZjzUWamhoR+qWa26+c3ShBEDhWkPMFUGnZoqXKmAsTGfRHX/Xq1Ve3bt3cebj2uuv15JNPCfaspoFdxo8s9ITx+v77aerXr58eeOC3jhHt2bOnypRJcTFUyJP9ca7KG1gMWSPL2vu/YsVy/eMf/9R111+vGTNmCpsBtMJ+qJgSiYjrY/369frJT37q6pYtW07EW6ELTOTw4SOcXR566GEXJ8e1WsbcseXt/LPt0rmzu94fMEaVMRHEv3HTRgPCKWbXDCUlJ9GVkpKSTPdyLp8M5GfYdcN+UaWoJkXV20H6sWvFLXrJe+882DqIoXyRt0AJtwD3f+8OEovN8r1QmMPlS7gw5Rel7JRIxE2ejz/+uB5++GHxZN4999ztQBYTIxM2eZQ99NBDOvfcc5USieynYhAEApzggmvfvr0DYUy0f/zjo44VojJxL0ySv/vd710/MCUnnXSSq0s5iYkQV9Xvfvc7cyveJ7b0z2R+8UUXCXl/+tNjeuSRR4SrD2DWoUNHN3HWqlkDEaL97bf/XCFoIJOJHjBJ0DnHjAsQSdA0sn7/+985QFLOGBjKCHz+xS/uVJPGjZ1+P/jBDwxA3O8mXs49fQD4AFTIgxnChQfjwjivN7Dw8MMP6fjjW7lYs5/dcosee+wx/fa3D7jAavqmH9qSUiIRFxDPU2+MF3CAToyBeh07djIQc7WqVK7kwN4999yj3//+907eXXfdZSCwqdMTWaSUSETXXXed6xNA8Ze/PG7g4wahL7rfcstPha2DIBAxV//3f/e6mKYgCJSUnOyuB8BL+fLp7nz/4Q9/0P33/0bY/8ILL1Ra2bIOqPIQAQAEQPrnP//J6YRr9HobP4wb+t55511qsodVgqW64Ybr1bRZU+X+A8gCRhkX1xrgD1v/8Ic3uqdg2acNshgztqTu3Xf/ysVqIfv222/XH/7wez300IP629/+qmvMDZ4SiQgwyflHz5RI1DZ//vOf3Zjuv/8Bde3aVTWqV9ftdt0gn36IzSIAn+MgCNSjRw8xFsAf5UWREgZoMdiUMlJLO289u0i1qsguFHL3Jb/nLeAtUHItkJQcve/5sdW1tQrlKcPc1itJjBZjS7bJlYnx+OOPd4CJCTkIAopEGZMOZUxmTNCuINcHEy71ACsUAY4AQkEQlUMederXr2cA5HjRXxDsK6OcFPZHPBfyOCY/JRJxTAkMGfo1MvclfWRklBf1UiJR8IcrjD6CIKCZS8igDm6nIIjmB0HggrebN2/ugADMiatsH8itacAtJbJPJmMPgsABGvqgPLQF40KflEjEldMPwBPdTJwDpkzY6E4Z+pAfm7AbMrBLurEv1A+CaH/Iob+USFQ++iGLhC2CIIgV5fYBBMggMXbkoi+6M5ZQB/pFNmOgIfnUJQVB4AAZ9Tn/nE9khHXCsQRB4EAc+jAGZCIrJRIR5yK0LX0gKyynDikIovrTJzLQhz6CIHDnln6CIFqH+oyZeiRkBUHg2EjaISM8pymRCNUdQMYG2IQMZKMnY6INxymRvHUNdcdujIW6yCiKlFQUnRS0D7OxIilSl2ZSn+5S84YSLx4uaHtfz1vAW+DYtAD3Ofc79z1MVmEFv+e2TvjrOne+P/YWKKAFfLUYCxDPdd5557q4vpjsUr+bUEArPBswW8fVN7DVTTr9RHl2KzSM33oLlDALJCVL9WtF7/M+dr9z3xcVyMKUJY3RYkw+eQsUlwUAWqw7BjtVXDokYr8JCbRgtkg1M43daiX94Gyp70lS4wZSuXR5l2IiXkleJ2+BgljA6gCuuI8bG8Divr7otOh9zv3OfW9ViuzfM1oHNzVPkfEEHSmsmVdeWHY0W/pgKQPkI4dXtHDMfjwT/ZDCfpDNMSk2j/x4JGQyjsKSHw8d4yUjCALnopb/288CCQm0Qg3tnDlXYq1KEjEb/fpIP9oDujq2jDJdBM6mpsr8uj55O/hrIFGvAe5TmCvuW8AV93G/86L3Nfc3IQPc7+G9X1Rbz2jlb2mAwdixY8Vq3bw+ZeHCRW5pCJZP4DUs/fv3F8sGUC9/KYcuAYiwUvqgQYPEq2NYxBSQ9d348WJ9LgL4n3jiCbeWV+6n/A4tff8aLDlAP+hP4mlFFtT8/PPPRT6v9aHv/Vsd+RFjY4mEV199Vbz+hX3yjlyib3ksWiChgVasQXEnpBugqm2/gnu0ky47Xfr5VdK910sP3VRikx+bP7cl4hrgPr3l0uh928PuX+5j7mfu69j7vKj3PaOVv8VXrFgh3jXYoH4D92j8P/7xd/E4PksXZGRkONDFa2R4l2D+Ug5dAnhioVUe2+eJMADP/AULtHLlSrESOgHTACLW20pOTj60wIPUGD5ihHsFDk9Ujhnzrb755hv32pb58+eLJyd5lyGrqx9ExGEVsVAsII6lHFgSg3WjGMthCfGVj3kLHDNA65i3tB+At4C3QMJZwDNa+Z8SljjgvYMZFTIE6OLJrgoGsHr37u0AEO9RZLFQnl7LX8qhS5KTktyTi4A3llTAzbYle4tbt4vH8s8++2z3jkCAytH21aVLF5155hnKyspSGUP56N+uXXsnnzzAHk+7HVrrgteYN2++e3EybBZP6x0tWCx4z4VV08s9XAt4oHW4FvP1vQW8BUqMBTyjlf+pTIlE3BIRABBYGIBWmZQU8T7EXTt3CYaJR/yPFjikRCJu/SNYpkWLFrl1v2oZ5cmyCrt37RIruxNkHT6en7/Ghy4BRLFkAO/6q1y5sgN4rJ1F/vfff6+2bduJ1eYPLalgNSJmL94x+Nlnn+nFF190zGB+r5QpmERf61i0gAdax+JZ8zp7C3gLxMUCRcFoxUXRYhBCPBOvbAFMde7cWazyDovFa2Cq16jhXvWCy49XrhytesQtLVu2TLghYZ1YXwqZSy2P16zgQgyCgKyjSsSZARwZD0Bx9OjR4lUzW7ZsdQukLl++TF9b3tHGnYVKZq1fL17Tc++99zr5U6dO1QpziYblfls6LOCBVuk4z36U3gLeAnlYwDNaeRjFsgA+8+bP18cffyxACAtELlq0WLyLb+jQoQYe1pjrrYzWrFnrYrWsSZ7/ABbA2Lp16/IsJ5O+YLKIZSIGDGAFGKIM5ikra717xQzHR5uGDv1IY8aMES5C3hlIED76TZw4QWlpZcV79wBGR9tP2B5gyjsKWdH8zDP7OJcrNgnL/bZ0WOCYBFo7dkqrN+3S0mXSnMXS9AU+lRwb+HNZEs8l9yn364bNEvdvony9liRGiwmcYOv77vu1eGcdT+rB4ABkADrPPvusbrrpZv3yl790Qe48XQe4eemll7Q+K2u/UxIEgWoYa8VK3oCQWbNm6bbbblXVKlVUr1494WYjbuucc/oqs2LF/drGHhBvNWDAAC1auCg2e7/9HTk5mj17tohlmjZtuguCT0qKBr2npaWpQYP6bpX2/RrtOWDMsG4E7TOWMJG3p8p+m3bt2rn4LJgsVhI//fQz1LRpU8HKDR8+TK1atVLv3qcdsEQBNsS2AwcOFH3C9tEXbk2O9+sk5qBmzZpq2LChhho4nTBhvFu5HrvGVPG7pcACxwzQiuPMlQAAEABJREFU2p4jB6w+GSe9MlTq/26SXmT7sfT6Rz55G/hrIJGvgf52n3K/Pj9Y7v7lPgZ4cV8X5/dsUtIx8xV4SDMBfF5//XV16NBeV111lYGHTfrwwyG23eiWLgDI3HjjDVbewQVn82QfweAAgZRI5AD5VatWde+m42m8K6+80r3Dr0LFiuIdfryo+orLLxfvEkyJHNg2FEbwOu+Va9a8WZh1wJa4r5NPPlm413j33Y9//GNVq1bV1UM+fScf5GlDXH8ffTRU7777rkssRwFD5gTk+ujQoYN7ETbvxLvKxlSvXl3x0mne+8g4f3bLLQYwq+dqFT3kPYsDBrzllmn48KOP3LIXOQYSo6V5f+ICPfPMM4WrslvXrurQvr0xZ2l5V/a5iWuBo9Qs6SjbF3pzvoj5NfzqJ9J/P5Q++8oYjznSsjXS+o1Stv1C3rpd8snbwF8DiXsNcJ9yv3LfTrf7l/v4mXcl7msYPO7z3bsL/evkgA5KEqNVqVIlY6xucsCBJRFgbAAhuMNwXxFMDkMFUILxAmTxHkJATu6VvGFwcBMCWFhnChcbT83BbC1cuFAcE2tEHjFbuQ3LsgkwZzfddJMeeuhB3XrrrY5le+eddxwjFFsfRmjBggVatmypS+iMy3DmzJmi/+XLl4t91uxiuYTYtgAwwNNDD/5Wf/7Tn1x69JFH1KlTp9hqbh83HvoCSBnTkqVLxXjIo48wj2PYPtdoz0cQBC5I/9Zbf6ann35aANrTTz9dJxgDhg57qrkNbbEJOpMYG7Kx17z5891YyF9oLB+Mn2vkP0q0BRIWaPHFyy/ewSOk/9kXMl/OfFmX6LPhB+ctUIosADDmvn7zM4n7fO4Sifu+KE1Qkhgtgrvfe+89/fnPj7vA9ZEjR4o1qpKSknXRRRc5s/7xj3/UP//5TwFkYGhcZj4fgANAx6ESwCWXCNWqVVsAEZZmgNFhC8Djib/cdQEbh+qDckAXTz/GtgekTZ0yVX974gn94ZFHXfrjY3/SpEmTYqu5fYDWfAM6yDpYAhjl7Njh2sR+7Nq507kUy5fPEExVxJi8XXn8OthuLNeyZct0sD4oW7p0yQGgM7Y/v19yLJBwQIvrljiOMVOlAcOk8TOlXTtLjsH9SLwFvAX2twA/oLjP3/9CGjNL2rxt//LCPCpJjNb06dP1zTdj9MAD9xuL9JD69u0r1m3asSPHMVDXXnuNnnji786NBbPEE3CwL4Cx3Xzxxhg6CAK1aNFCZ5111n7ptN69XXu2YVnHjh1jWkZ369ev59pdeOGFgi3r0aOn2GeJiORcbkDisEJZbE855RQhs1279ortB+YNRi7aw77PquZm5EnF7t1PUpjyioPi6UnAHn2EqU+fPsKl17NHD7FPfm8bIzrv60HCPnPmztVzzz1vrsfLnW0//fQzzZg+Q4C92LqAsHZt2zo7wRgiG7nof/zxrdSmTRsxtpYtW7oHCmLb+v2SaYGEA1obs6WR30mfW8LN4EFWybzw/KhiLOB33Y8p7vcvx0hfTZH4sVUUZkkqQTFaLPhZrlxZffjhh+L1Ml9//bVjtAACPGnHa2A+++xTB7qIv8KVyCroPHWX2yWXl+2RM2v2bH3wwQfasHFjXlUOyIOtmjBhontK8YDCPDIAfgBGGLfvv58q9APk5FHVZQHaateurVNPPdXFjgGkAErkuQqH+Niwfr0++fRTzZw1S4cC3du3bdd5552ryy69VDB0p59+msqklDmgB+wEKJs4caJ4hdHbAweKccGmvfjii3rttdf0/PPPady4cXbdexbhAAOWwIyEAlr8kgVkjbVftfzKLYH29kPyFvAWOIgFiOMaNVbuxxbfBwepGpeiQ02ucemkiIQ0atRI/fr1E/FYWVlZ6tatmwtWL1++vAtqb9y4sXgajwDuc845xz0Bh2oAA6Ns2D1oYo0rgMOCBQsPCUpCQTBqt9zyUzVr2jTMOugWADd58mSxQnzNmjXFfmGdI8DP3Hnz9N1344Vb8WCKBUGgVie00lnGgKVEIgLUwlCxbANgTzF/MIQ8jYhMXKUffviRFi5a5EBvq1bHuycbiaFDRlJy9OnKmOZ+twRaIGGAFo9880t2zPdyAe4HsbUv8hbwFijBFiB265tpUWaL74XCHGpJYrRgqJj8b7j+enNvXaELLrjAucMyMzOF2+z8888XT/BdccUV7r1+1D/++OPVw9xm5dLTD2pmwBigB9ddamr+TxnmFhIEgWiTEilYm0gk1TFuMD9ffvmlACqFcY5gydasXSeWvahevVq+y0fEjgdAlRKJjiMIAvFEJXmxddiPWB1cnx06dBS2z8nZLsbAWHAhsrI+TyHiVsyrPTJ8KlkWSBigNXux9PXE6FNTJcvEfjTeAt4Ch2uBbduksZOlqTMPt+Xh1S8stuTwtIhfbSb/igasYEyIfSJeKJzMAVY8mUgZ9eg1NTVV5AfBwVddJ7ibtaZ4LU4oj/bxTpFIigNX6PXGG2+Ip/cK4xzBOi1Zslg8eQl7dvTj2CcB27JkRq2aNfTVV1+5eC7AFeeCYH6enoTN4vzsa+X3SrIFEgJoEY8xdJRnskryhebH5i1wuBZwbsSp0rJ1h9uy4PVhGgpeu3TWxMVGXBZg69NPP3WLlcJuARriaRFYJpZbQOYvfvEL/fnPfxZPTsZzpXZkk3hScvjw4eY2/M49ofjtt98ak7aaorgkwOGEiRMFqO3b9xzhyoUVXLhwoQOPgLsgODi4jYsiXkhCWKDYgRaugW+mSyuyEsIeXglvAW+BIrBAQbtYuUaaMrfwln1gQiyoLqW1XpmUFF188cXq3r27iJtKS0sTzFiZQowv4vU4derUFU/mRax/xfmPcVx22Q9EjFW5culuPGXTUuPSC4CK5SUAb7CAgwe/42LAAJKsTca6ZodaWiMuinghCWOBYgdaqzZI38+Q/NOFCXNNeEW8BRLGAsRrzVsirdlUOCp5RuvQdg2CQNWqVRNP8uXk5LiXSfOU4o6d8X1iLggCJxsX24wZ0zVhwnixbEP5jIxDK3mYNXBN1q5dS2XTyqpWrZqu9Zat5q92e0f3wXpbxH7xHsgJEyZo2bLlYrmJIAjE055NmjRRubJlj64T3/qYskCxAi2WbpmzQFpXsCeFjynDxlfZxJGWlCzVqiJ1bCmd3C6a2G/cQLIfhomjaC5NUu3HKnqiM9tE1jWX6qX+cLl5dOYsKxxWyzNaBb+8iOW6/PLLxWtyYLc4LnjrgtUsV66cWEerffv2IrC/Xbt2bpHQgrU+vFrEUrVp20a33XabbrzxRrGS/uFJyLt2SiQilpi4//7f6OGHH9aDD/5WjCvZGMDWrVvrnL59daiHD/KW7HOPVQsUK9DK3i7NXuoD4I+ViyfJQFbzhlKf7lLfntLZPaLbi3pJl3e1/OOlyhX2jQbwddpJcoAsNn9fjaLba1Q3qit6d28l1YzRs+i08D0diQVY6mVZIX1PeEbrSM5I4bZJNkBCDBPgJAhKVhwT4C4lEinQU46Fa+U4SPciCmyBYgVay1dJ631sVoFPVnFXrFtd6tlGOq5+VJMZC6WR30u4f9OrSCe0t9RYSjJARsqov0292kndj5My06NtiuMzs5qBwG5SurFaxdG/7/PoLbB0pbTZfpgdvaT9JXhGa397+CNvAW+B+Fug2IAWbsNN5jKE1Yr/sLzEeFsA4FQt05igalHJU8ZLvKPu0y+l9ywtMNdOuYjUrqkUSZbS0qSqO1OVvOcKq2Rt0yLRtuEnMnHhVcyQUelRgBaWsaU+ZWxx/YV1OaYtdQ6VqNfDwGE1Y7C45g5V35cnpgXWb7UfZRtUkHU1D2sASUW3Mvxh6eUrewt4C5QcC+yZBot+QDt3SSuzJdbLKfrefY9HYoEdVfcPFsWlQ7DykuXSZ99JH46URk2Vtu+UfnyRdHoHGUUuVawuXXqadNHJBsD2gC1YpmvPke7qJ/3fddHtBVYfECX7A1Sdbu7JX10j/cJk3Xye1bN9jm86X2rf3Cod4h+Q1dxcne2bSLvseuP1Todo4osT1AK7cqTV6yS+N+Kpome04mlNL8tbwFsgLwsUG9Bi4ssxoMWknJdiPi+xLMBToetmpwp3L5p17Cxdb4CHwHJcckuN0Ro5WRo3zUCNAS1AWMhWsoQHIGfrelpKgKwfnbvLuSBT7AqkXmoZ6cSu0jUGvhzYilZ1nwC1qlWlHANLXDc8JHRmG6mFAShXIZ+PCpUlXJ3InjZbmrQgn4o+O+EtwPfEFruuOP/xVNYzWvG0ppflLeAtkJcFbJrLK7vo8pjAi64339PRWGDxSunLSdLcJcZE7pADSgTC33y2dHZbiRguWCT66P+x9O60bc7Vs3mNNHCE9OFEObYLV16V9CQBvkaYvP5DpdEzrMxYi3o1pFa5ABTvvPt0tPTiexL1AWYVqkktDUjlBmX0TUKPjs2irs6Vpvdwc3WS79OxaQG+J/hhFm/tPaMVb4t6ed4CJdcCRzqyYgVaTKBHqrhvV/QWYLKbOV8aaqDnqykSwfBZW3aJQPiOxnD1MUaqobkJATlbt+6v33ZjL3Ezphhz1aK+UVNWvGmDlGXuINvVBgNjMFaRFKl+eXL2pR3GhLFo5UJjzXgtC6waDyOlVZTKpe2rF+7Rf8O60gmNozm4M4nxiR7t+6TeviO/Vxot4Bmt0njW/Zi9BYrWAsUGtIhBxeXkJ7uiPeFH2hvnicD0GplSznZp1FhjrIZL73+R5NiobcZwNahl7r9WcsHw+fWTbECrrPkLAUq4A3t13aXzekpd2u8SLj7aAaDY5pUAazk7oyWp5aLb3J8E4h/fVCIA3rpS8zpSbwOBTUw/6lY0JuxE0zMEheT5lPgWSCkXfx09oxV/m+6T6Pe8BbwFsECxAS0654uTJ9TY9ymxLQB46dRauqyXxDpaPAW41hip6XOkcROkRculMslSwyoHH8dOA2RbjLriCcAtxmYtWZQkFq2dPjtJoydLI03WTHNN5icFoJZi/eRXTn7EJuSq6VF9YMjatpR6HC/VqkSp3DIPLQ2I1a0RPfafiW8BgH5ZO+/8QIuntp7Riqc1vSxvAW+BvCyQlFdmUeQlW8/uizOlKHrzfRytBQBIyKheXWpc2xiiFgZcDFTBclXMlCpWUDQeaw/bRN3YVMnq8CRhjgGt1Wvs5O8pXLJaGvd9NC2zfdJUA297it0mMNBUvZpE+5b1pWqVon2tN1didi4XJQ02rDX35ijpmXf3pReGSNP3BMOvXykR8zXR+sEdSptESF6H/C0A0M9I1d7lQvKveXglntE6PHv52t4C3gKHb4F9M97htz2qFriOalWVKuYRY3NUgn3jQrEAy3DMmie3OClxVsRk3XCBdL2ly06TahqQAkRNmC0X8I4SZVanusfxCVzv0026wBIM5uffSmFA+yldpB+cHU0XnGJsmdWpbQCO9mHKKCfRx4+sHiu7VzDgtWGVtHCThCsxrJkHjCsAABAASURBVBduAU/L1khzDViFidiy1ZujNTYbGFy8Qlq/MXrsPxPfAmnGZlWza4zvjXhqmxRviiyeynlZ3gLeAiXCAsUGtHAdwUyULX+kdvTtitoCBKMP+kwuCB4mCTdelT3nD+AzfpwUskSAnTnGUM1eHAVV1A31Rc4Ak7N8z1sBkEECNE0z9+FSA0lhXbaAMtyNxFYRcwUjNWqGlJv5ou6h0vYciWUCjFg7VFVfnkAWgNEsb6xpvFXyjFa8LerleQt4C+S2QLEBLX6ZwlTUNTcQ8Re5FfPHiWkBQNJLH0ivfCgBll79JLp94VNp8Hf7s0S48AYNi5ZTl6f/WA+JkcEwvTA4WoYM0vN2PMjYLgAXdcLEU4cDP0/a21//LyTW7MpdL6yf1xbgN8lclINHSCyuunpDXrV8XiJagCU86tSQ2MZbP89oxduipVyeH763QB4WKDaghS6AreMaScX5Hjz08OnwLABoAXABlgiGJ+GqIz9WEse45ygn0YY86rANy0I5yKAsr8QyEMggxcrJq25+ebRjQVXciSyoml89n59YFqiUITU2oIXLOt6aeUYratGdO3dq1apVLrEfzS15n7vNlbJmzRpt3rwnjiDXEHO2b9ehxr9t2zatW7fukPViRYf9btmyJTb7oPthG3Q6aMVDFDKeHTvix+Fju/VZWUI/5CI/VGHr1q1avnyF1q9fH2Yl5DY7O1tcB7G6F6aixQq0GFg9+wJtVEfuRcQc+3TsWACwFA9t4yUnHrp4GUVqgUN2BtvdrJ5Us5rc65wU579DMVp8EW/cuElMLNu37v8KKlRh0tmwYYObdJgQmWCYhGMTkw91CzsxiX/++ed644039NZbb+mdd97RpImTRP7B+maM3377rZ566mnXZtPGkhu8CLDGPhMmTHDnjAl386ZNDjQBGga/+67mz5+fr7kAF/PmzdOgQYOUZWAj34q5Cuh38ODB+v57o9VzlcUecq1wPXFOduTkuHO5ghWXYysdxj7X5KRJkzR+/HixfxhN8606btw4fTR0qLINrLI/dcpUJ5vrbODAgXr++edEPmPIV8ieAuzPePccFtlm6tSpzrac86LotNiBFo/fd2jhWa2iONnHUh885Tjbvu9Y8oF4LGLCjiX9va7xsUCNTAnWu9yed2TGR+o+KUyA+44O3Fu2bJkG/newBjw5UPNnLXSTc1iLieuzQSM0/N2R2m5MyOK5SzXgP2/rtb+/sV+aMOb7/dqF7eO93WSA4e2339a0adPdr/U5c+bodQNdgKiDTSiARYBZlSqV1alTJ6WVLRtv1RJKHiBg8eLFDlyNGjVKQz/+WAAclOQ8HuyaoAwmBPACs0WbgiQAGm2WL1+eb3XqAADef/99rV27Vjt37dKECRMPCZTzFbinAJ0BPbuMzduTdVSb+fPnCz137Za4rnbu+aUMAH3vvffVsmVLNWrUSIf6EYMS2P+dd95ht0jTkiVLHBhE/6LouNiBFoNsbIzWSW09q4UtDppKUaGx85o5X/r0G8nmqTyfLixF5iiVQyUmq+PxEqw3YQaFYYSDTQb8Qh8zZLwmj5mkad9N1dp1+zM9q1av1oRR3ykttYySk5O1YuVaTZ80Q1lrswpD1UPK3LlzlwMMJ5/cU1dccYUuu+wHAjxNmTLFJuutDuwtXLjI/ZL/6KOPnPsLNmfEiBGizpo1a93EWaZMGcHiffHFF3r11VcdK8ZEDRAAoMCaUQaAA6AAPJgsAWsLFizYT0/aIPubb75xwAbGj3bLzb1EGfogj30AHxMvfdKGPmOFoStyYIXoi4QcJnj2kROyI+RxjAwAEe0AnrvMRYpM8idOnOgYPJgmygFZnEeuiVBPdIWlwV6wL7QNE8CWPrAJ+tMPdqGfsE5+W/pnjLBryOZamzt3rtAFsPLhhx/aOdioFPOXp6amCX0++eQTd+4Yf14Agf5Hjx7tzhl68EOA/lPKpLjrkz7JR7/33nvPsZ7YiXPA+fvggw+0PiuLJsKu1GX86JgfI8a1kpyUrMUGXNB9xYrl4hxs3LBRX331lZYuXequO3RDDtcKHWAvAC/9vmssIlvGRD3yqcu1wPVF/diEvuhFvZdeeknDhw8X9uEc0g67hmNnS12uKcbDdR0ri3104h7ALtiIOlxPJOyDrtQ7mpQQQIsv0S6tpPbNj2Yovm1JswA/lAh4J5W0sfnxHNwC9t2thuYybN9SgvU+eO0jL+XXfn6tZ06cpSnjJ2rHtpwDqvDlO29yFFQ0a91cu4192LJhs02MKep2Znddc9fVuuGe61zqdFKbA9oXZkZ6eroqVKig3bt3uQkoMzPT9CrjJr477/yFZs6cJSb3v/3tb1q5apWVpTh1MjMrKjWSKtiUZ555Wq+80t/VffSPf3SuMmw1e/Zs/f73v9eLL76oRYsWCXBw7733acyYb/Xdd+P1pz/9yYG23THsCZPga6+95lxt06ZN07/+9S9jasYL19jgwe84txZuuFdeecWBhDlz5urBBx/UCAOAsXLWZWUJOb/73e81a9YsARZuuukmPf7444ItevbZ/7pyQMuMGTMEuwewYrL++ONPnNsOlsgN1j5SU1Pd2AELJPoaMGCAAIvY4IUXXnC6Tpo02cb7ko37Dw6IWtO9/6NGfSUmcMYCqGCi37wp7/ivsBGTOa7HJ5980tl34MBBYkyUp6REFImkCN3KGbP46KOPKj29nP7xj386UDjRXMGPPfaYO5fIoQ2JMfbv318vv/yysN+TTz6lvz3xhGNaJ0ycYOfmOxeXNtBce/fcc4/Zf6KGDRumn/70p/rrX//iyt9880395a9/tetmt8mYrUceeUTYYKL1+Yc//EGfmVs6ts/t27c5Vmja9Gni2ohE0D2icuXKGRu309kF4AeABfz07/8qqu5NjDElJcXOQcTGmO5+DHDO/vGPfzjG7JlnnjF39lPOLbm3ke3Mnj3LdP6bnnvuOTtXC/VHuz5vv/12ce6+++47/eEPj+i7Pa7S555/3p1DbMI1O2DAm84OJsadS65NztkXX3zp7hkY7Lvuukvf2bU8yVyuXFtjx46l+lGlhABajMCuLbHWUosmntnCHj55C5RWCziQVVc69+RdbhX/wrQD7EVu+Uy4q5av0bfDxqpc2TTVbVg7dxUHEmZ/P1dVa1RVzQY1tNv8KBuzNiqSliq2s8bN0Xwr37Fjp2MTgiA4QEZhZGRnb9G9996rCy64UDfffLNzIbZr185NhC+++JJjuu644w796Ec/ct3zi71du/aqVKmyTjvtNLU6oZW5HqeJCeeOO36u++//jX784x/p9ddfdwCMCRXX0H333afzzz9fH3/8sZo2baJf/eqXuvXWn6lZs2aCiQB40EEQBGrRooWIWVuyeIlgf2CuADNr1q7T5MlT1KZNGwfYAE/XX3+9fv7z29W3b1/BdACakEPaZTYGEF133bXW36/0wAMPkK3zzjtPv/3tb3XJJRe7iTc7O9uxZzks7OdqyB3v2XWbZGMgj2veXB06dFDr1q3Vtm1bA/QpBkxyXPkuA84VK2bqyiuvdDa49//+zwFIdHQV7CMtraxatTre8qdqw8aNDshZtho1bswm37Rw4UI3kaP37bffZmP5pQGuGcrJyVHXrieaPZvZtqvSy5d3kz8M0fLly/SDH/xA99xzt53bCxxIiO1go/W/ZMlSnXzyybrzF3fo7rt/5Yp37AmCDwESfVxhbOd9992rO++8U/XrN1CXLl10/29+I0ArbBmsEo2bNGni6jz88EPq06ePPv30U4VllJOQS6pdu7bTObyOTmjVSjVq1BDXF/p/9tln6ty5sypkZNBMQRDohBNOcOe+WbOmOuOMM9w1wrVzww03uPP5oIHtzz8fplkG7l2jPR/0V6dObf3yl7/Ub37za1111VXiurj99p/rgfvvF2WwU9vNnnXr1jWb3eOuqbPPPlsLjdHlWkTU9u05gkmbOXOmybhSmRUrClavZs0a1uZu3XJL9HqGEcs9btofTkoYoMUPIJZ7AGw1byglJR/OMHxdbwFvgZJgAe577v/zekpVyxf+1xMTam67bd++XVPGfq+Vy1aqY+8TlVmt8n5VAGIEKK9atExNWzU2BiKinJ07tGVTtjZv3KRxX4zT4Fff1Ut/f00v/+UVrV6xNqZ94e5G7BfrLbfcYszSY3rooYdUs2YtB3yISVm+fLlwSQGeYFNwmTBp7YI63qMWDNDKlSsdK1HHJs9kAyRNmzZzpcuWLnOgsfweALDbwMj8+fONzRrj+oLNmjx5sgCvscxRpjFqDRo00NhxY91k2q1bN8e0zZw5w7nHWtmkDIME6wErBYBiwqVT3KFswxQxxi3DJusgCBwIqVatqoHESk4vGJLs7M0OVIb1j2ZbpkyyswM2aNCgvvWT6QBoKJPy9u3bC3fZQgNPuK46duyo8uXTwyoHbLneVpvLecmSxY59AyD++9//dowOAPSABpZRpUoVB0hg8AC8VatWFf2ilxW7fxjM1q1P0Ndff61n//tfB2ivuOJKlTHGyFWI+ahogIK26enl7fqoIY6pl5aWJtyhIUCFbSprrFoZcyUfd9xx2rBho7FOW1SQv5RIRMcff7wB/bUC9IwfP0HnnntOnvqE8rLWrXP9N2rUyJ3PunXqOJtj27BOuOU6KFu2nANstWrVsnqVlJFR3t2LlMHwMcaaNWu6ax5mimt/1aqVdn3sdmLmzp3nwHxzA9z169VTjoHSBQsWOsDMefnjHx+1HwKTnS7cJ67REX4U/jdZARWz+8aMJtXMlM5sL+dG5JUrBWzuq3kLeAsc4xbgfid8gB9b4XspC3tIgILYPvhCXTpvmcZ//b2aHN9Ux7c/LrbY7TNZLpy+RNvtixm3IV/oKcll1KJdc518zinq84MzdfGNF6he47qaPnGGxn857gAGwgkqhA8mxXo2acAidWjfXi1bttDy5Su0xZguQNgpp5yiG2+4UTffdLNzG3UwRocJNVQlSEpybqsdxsTBCJC/bdtWNjZJlnHb8IO69Ae4uO6665zcnxurAHMQKxP7wFoRU7Nhwwb16NHDMUyAKdiHagYcqAO7cvHFFzk5t956q37yk5+orDGKYX+5t7nPXe7yvcf8it97cGQ72GK7MSCAuVgJgIE6BghwxcLSde3a1eaxILbKAfvYrFKlSo4lCu32q1/9ypispgfUJSM5KUndu3fX5ZdfbvYo6+K0cKtyrVJO4ppsbcwc8mCiRo4cae7Gv7uYPcqPNm3bts1cfGVUxoB3QWU1bNjI6fvJJ58aAEpxwCsI8rdNUnKSsA19yf4APtica8MOD/sflu/pp59xIOyaa64R137Fipl75aSnl1Xv3r2NTZypKVOnih9QkT0AkXuExPV8zjnnuHtib8Mj2EkYoBXqznmoVVPiy7Z3B6l+LSnJs1uheUrd1g+45FuAoHfuc+537vtalYpuzExQsb1t3bJF47+YrFWLFmllxALCAAAQAElEQVTjug36ZthYx2zt3LlbM8ZN0/wZC1yMx6LZi1S9VnVl1qjomuMybNu1jc7rd7a6ndZFbU5srXY92ivJvtAWzl5sLqntrl5hf+ww8LfIdJ8+fbqIU+EJxMzMiqpeo4ab6KZPn+HiZ3J25Dh2JmQvQr2CIFADcydx/OWXXwqWiSBsXDAACvLDFASBc73hDsRdx0S5es1qYz4OXA2YyX/RosWuKSAQWV9/Pdq5m2BTYB4qVMgQbJqTY6xPVlbWIUGLE5jHByzQ2rVrNO6771yaN2+uc83lUdX6XOVsEcvCUQ9QyPhJ2IC8xrncgujes2dPUV6tWjU1aNDAsUksqxECBtqFKclAU61atZWZWcn6XemyORfEvgFikpOTje3LcjJyjFmlwuo1azRkyBBhD8AUYAEGEPaRchJMFOAL9qiRMUKwhPONbcx9fVO3oGnFipUuBotAeGLRGHuaMVwFbV+lciWzR31jVEfqxBNPzBOsAKxgVnHJVq1aTVwXjAP7AV7LlSur445rsV+X2Gi/jHwOdu7c5RhT+sB2S5YsUbYxnmF1fpDgdmzZsqXoi2vvBHOd88Mke0u24Y4krVi5wtk9bHOk26QjbViY7ez+VYV0iQD5C7tLvU6UA1x8IRdmv162t4C3QNFZIMl+QAGwuneSuM+537nvi04D+xFnE19sfwCVnF3blJFZ3gGsKWMmae2qda7KknmLtHTBMq1ZulZLFq1R/aZ1lW7uCwp5UmnY+19q+AcjnauQCW63fdFTVlQpJaWMACwEIA8Y8JaLN8Gd0qtXL1WtWkXX2K/6KlUqu8D2IUM+dDFXyclJSjIbMDnD1iTbRN+kaRP16nWqCCh/6623nTsHpgSXIYHOuGqYvKhLbE27du00dOhQk/uOC1JPMXcVMmPHDVDr1q2rAFnIATA0b97MucCCIFDDhg0dw4Prhj6Z3IMgiBVhrEhE1atXc+48CgAm9erVd243jjPMpUisEH3j6oJpe/fd90QwMyAoMzPTATfa4C5LSk4WbiPaAqa2G7Bp3LjRXnnkL168xAXdT5kyVVdf3c/ZFxswSTPOIAjUunUbcxdmOKYOG06ZMkWfD/t8v3imIAiEbuhYzdyd5513rgPfgwe/ayDqQ1c3sPOA3CrmKvzOAOKmzZtRQZUrVxEgZ/Tob0T9KnYOYc4Aea6CfSAXMAtgwX64xYh1QtdKxp5VMZmcM84DbkZrYi6xJDce2nJc1kAUMpKS9tmdsdAn5xqmEsYHeTVr1nTsFnKdLZOS3HnhOqIu8lIiEQFiKlWqrG7mLiYvd+I6oF+AKkD7vPPOc+7lgYMGaerU79WvXz+zW639mjGmWsbGpNj1TgH61zL3YdhvLSvjXFesWMFYwB+YnKkGpIYaq7xTVapUtes9cG5nQDFjOf300x3zBtg96aST7Dx2N5fie+56njt3rtVPopvYdNj7Ry/hsLsseINIimQ20yltpItOs3Sy1LGl5VWRcDMkJRdclq/pLeAtUHwW4F4lcd/WsvuX+/jyXnZP233N/c19zv1e1BoCiGL7TC9fXr0v7KV+d13p0pW3XKHGxzWySSlQp54d1KJTcy1bvEJBzjY1bNFIKakR13zXzh1aOGuhhr87XF9/+o2+HTVRE7+e6MoAZEzA7qAQPypWrKif/exWEQR/xRWXC3DERAW4YZJlsr7xxhtdPqCBibOque1od8stPxWTMOqlp6cLlgZgds01V4sJG9dfsgET4m6uuOJKMblRl/ZXXXmlq3PVVVfq0ksvFf0Ewb7JmnqVK1cWAfgnn3yK2TLZTcB33HGHiI2hnMnz5JNP1g9/eKNNrlcZqLlauD7pk3JSFWNI6BsQRX55A1Y33fRjAQ4o79ixk6699joxHiZagruRB2tBX507d3FgjTZM/Mho166dc1H26NFT6HDnnXfphFatEOcm424GDq+44gpXhwkZO9J/v35XO5cUFbOy1gnwxBpk27ZuFcxIZRtv7DkH/F199dVq376DGz/B99gV+3IuABgAjobGiN1grl0eZihv5wH5xHzxcADnk/rXXnutA4hBsM/GaWlpOsnADHX69btKnOczzzhD5J9sjBu6c84oJwgduYCMyy67zOkUBIEASXfffbdrQ3mNGtV1Tt9zDKBfbeO/eW+fyKMd9idIvoe5gkO7cB1x/dAe1ybuO+zVuFEjsg5I2Jog9nPPPc8xXu3atnXnkHFy7nruka2Yv9YnnOAe6uA8y/445nzQbxkD+Sxr0st+XDD2s846S8QsYuMf//jH7vqqUb26uBa4PqgD4OpngA43eg1jfrmG6Zvr+eKLLzZG7Th3zqyrI/5PaKDFqOz8K5Ii1cyUWjWXLjhFuuECqd+ZEl/U59oX9bk9JZ+8Dfw1kLjXQN9To/cr9y33L/cx93OtShI/TLnPud+LOjEBxvbJhFGtZhXx5Uuq3aiWInvAVIUaVRWJpGr53JXKqFRelapVdgwJ7Zl0upzcThnly+qLD0borSff0NwZ83RC5xN04hldjvqLmj4OldC9fv167sm/Zs2aOQBSzdxZ5NMWYFHJ2A2ACZMqzEYQBC4uBpCVmppKNZeYgMijLjJoSwGTGU9lhTKDIHBPxyGPujAcYV3qu2Qf5CEnI6O8HclN5shPiUSBKpn0D+uD7mxTIvvKKE+JRETfACKOkUk9AArHyKYc3YIgMPaiirMB/ZAoD4LAGJLaDozRJi0tTdgsbMd+uoFtykhM5oyNfPQjj/6pz8MAuJz+/Oc/uyf3HMtjE303AzyA2IjpS31SEET7RQeO0RF7YDPkIzMIAqVEomOkv5RIdPxBEDgQSB71aUd75MSmlEjEjQ37UTclEnHXXcXMTGcL2mAvziHtOEZWqBN25JrHrpSTqhr7lrtP5NGOepxvbMQ+Y8DO7MPwDh48WK+//obatWvr9Ede7pQSiTj7oy/tUiLR8dMnuqZEojaIbcf5oX/0J59jzgftgyAQ+1znQRC464wxYWPyQ5mMOdQVOchjLMhgHPRPIp88+jmalHQ0jYuyrdnMqEo50FUhXWpSV2pr7FaP46Ue7XzyNvDXQEJfA3afcr9y33L/8uOpTHL0G4R7O7pX9J+5Ga3cGvAl3LlXJ5173YXmKqzp4meWL11i+3VVvmK5vdX5Mm7R4Xj98P4f6tKfXq5z+p2ra37eTzfcbQyLTXR7K/qdY8ICMFKwQA0b5s3EMAhcfZl2bmF3YJm4VgBjAB0m6CDYxzhR/1hKgBOW76hYocIRqZ2cnGTu6qrGTPbTmWee6QDkEQkqIY2OGaBVQuzth+EtcCgL+PIitEBS0sG/ApPNXUaQey+jS2vVqqXUMmVFkHuLE1sau7X/r+0gCJw7qevJHUR92tG+CIfju4qTBWBETjZXJkxLfiIBVsRK4Z6CDcqv3rGYD9vTu3dvx1Yeif7lypUT9iOxfyQySlKbg3/LlKSR+rF4C3gLeAvkssChGK3Y6kEQCLfiSaef6NwdHkTFWsfvewt4C+RngWMfaOU3Mp/vLeAt4C1wCAscitE6RHNf7C3gLeAtcEgLeKB1SBP5Ct4C3gIl1QKHw2iVVBv4ccXfAl6it0CsBY4poLVjp7R60y5NXyCNnCAN+VJ6YYhP3gb+GjgWrgHuV+5b7l/u4zgs2B37XXZE+57ROiKz+UbeAt4Ch2GBYwJobc+R5iyWBg2T+r+bpDc/kz79xsDWZGnmfGn6HJ+8Dfw1kMjXAPfpSLtfuW+5f7mP37L7mPt6e85hfGPFuWpJZrQ2b9qkefPmiVXb42y2oxbHGkvoxircRy2sCAWgN+8k5HUtRdit7+oYt0BCAy0YLL6IX/1EesmYq3HTpGVrJFbR37pd4l2opGP8HHj1vQVKvAW4T0nct9y/3Mfczy9/IHF/c59zvxe1IUoSowUIALjwShOAwMxZs8RLmlnduqjteqj+du3c6XQbMsQugENVTqByVmx/7LHHtGlTdNX2BFLNq5LAFkhIoMUXLq6FYeYe7P9xlKnYti2BrVjEqvnuvAVKigUAXjBxb34qcb9z3xelS/FIGS1ADWnLli0C3LAF3BTXeaHvTRs36vHH/6wXXnhhPxYrJydH69evFwwX9UIded0Q7/MjsR/mh1vetce4SOuzsva2R8bWrVvda2PYJ7FAJfVDm7g21if5lFMfGbBr1An7YB+90I/2YT5tqBu24ZiEXFJYnzzeKcgxcpAXyojdMj50oV5sP9SnHf2gY9gmP7kNGzbUaaedprQ9i9giF/shl33as4X1ChOyyPep9Fog4YAWIGvBMun9L5I0zNyD/PotvafHj9xboHRYYP1GA1p2v3PfL1suFRXYOhJGi8mZyZUX+/J+vCVLFmvWzFnu3YGUFccZA2yMHDVKM02PSZMm6ZtvvhEgkpfofv3113rppZf03PPPC3aLiR9w8dVXX+mVV17Riy++qJEjRyoWgFCHF1IPGjRI7777rp438EZ7XgwNABo+fLh4H+EOA3EAlBdeeF6zZs92L2emDYk+n3nmacECDRkyxMl4/fXXtXDhQu2yE7xz5w7xAuw33nxTz5tun33+udZnZdm53+30fOutt/Tf//1PbNE7e/NmffjhhxowYICrP2PmTK1evdrl0f5FGyN9xY6DcwHgGTt2rF59tb9r9/EnnzjQiN7Uf/W111w/AwcO3Nt/brkTJkwQAIqXE8+0fncYIwdwC21I/1988YUDuAsWLLC+XnW2ff/990U/6FHCkx/eQSyQUEArBFmfjY7GXuFqOIjuvshbwFugBFmA+51YrndGSXOXFA3YAowcjgl32gTLZMvEv2nTJpUrW1YtjjtOaWXTHIAAgAFSDkdmPOqyeCavDOE1MHXq1HXvrQNErlu3TrAt9erV05w5c/SmgRrA4YSJE/XRR0PFyua8QuXll1/WfAMIsbosXbZUQ4cOFa5ImJzp06dr8OB3HJhgHxsAmGDMRowYoVWrVinLgNLw4SME2KhTp44DXg899LArYxFMQOCwYcO0ncBb62zWrNnunYK8DujTTz/VmG+/1YoVKx34Q+/mzZsbY7hcb7/9ttasXaexY8cZKByl6tWri0VCR48erU8MOCF7+/btbkxZ69eb5Og/4Gjy5Mkun/rUwwZfGfgETH1r/bEeGiuhf/bZZxpmABI5owy0Drd96nM8ZMiHDpxhC/oEbI4e/bU+/3yYe70Ni9n279/fgU8AOPkrV64SK8RzHqLa+M/SaoGEAVr2A0crV0qArPm25Uu3tJ4UP25vgdJqAe77hcZoD7UfW0UBtgoyCQKuYEVggZhE58+fL16WyzliEs429yETMhP5ihUrBMtD2UFTnAsd0Grc2L32pG7dOgIY0QUTPa+SueCCC9SjRw/NNtYJMAjAWLFiuWNpACOAGgBJbpAIaOO9fbTHZQZY27lzF6LzTVWrVlWvXr1Em759+2rTpo26+OKLdc4556hVq1aOhdq6dYtrf+KJXXTRRRfpH67OogAAEABJREFUEitvbPrPmjVLEyaM1/fff+/e04edsT/AbdWqlW41/lNPPUWXXHKJAEeUIQjbn3LKKTrzzDP2e6/eNnNxTjRQSVvGyfmi/lhjuDLKl1fbtm3F63bII02YMFGAbxLH5a1O7169dcYZpyuSmkqWS5s3ZztQlZW1zrlQ0SM7e4voiwqsKH/uuecInXgtD3k+lV4LJAzQ2pht7sJvJQ+ySu/F6EfuLRBaYLH92PrsO2nN5oNP6mH9I92GE+rB2uOWY+L/fto0xwoBSsJ2W7dtE8CLSZyX0hI/lJ1tX2YHE1iEZZFIqmN+giBwW/SEgcLtlZxcRujLMSAM1iu3agAYgEIQRF9sTN1doOHcFWOOy5RJVkpKigCxsGWRSETI4Bj2CFACWKN/mCzyADGAGoDQSvvFnZISEfUAWsjo3r270tPTRV1e6cKW1LVrNxczBcMGozRjxowYTeSAJMwjmbjwkNe+fXu1adNGMF+wU7gvKU9LSzOmbbvKJCera9eu7hUyU6dO1Usvv2Qu2ZkKgoBqLuXkbDcAucntIx+5J53UTS1atHB5jBfboaPL8B+l2gIJAbRwGY60L9X5i+WeJCzVZ8QPPi8L+LxSZgHmcr4PxoxP0h4vU6FYgMn/UIIBBUykpLxAFHmwREyuyUnJ2rJ1m4szOpTc4ioHBGVklBfACqbpqqv66brrrnPgIwj2gYmC6AcDtnvXkYHhnTt3CKaQfgBYANiIgTLcgpFIivr06aOr+/XT1VdfrfPOO9+54agbJsDunDmzHbN14403Wp3zXGxaCJyoB9MHgIP9Ovfc85y8G66/Xqca+wVLBqjjXYV9+pwlWEna7DD3MHFkjRo10vVW97zzznPuyiVLzJ9NBUspKREhF3ftxRdf4uRee+216tatm/yft0BuCyTlziiO49kGsL6ZJg+yisP4vk9vgQS1AGBrylxp7lIZcCkcJZmsj1YyYAPAxnYnSh+twCNsHyQlOdYK99eECRPylQIg7Ny5s7kRZ4ngdJZYuOee/3NsXb6NYgpganC3EcdEAPk//vkvLVq0JKZGwXfDoHnYKHTGtXjSSSc5EPP3v/9dnw8b5uK1nnzyP3sZpFA69p4zZ47+85//iPgq3IGUAYDYktLKlnXuQZiugQPfdvLu+/Wv9cmnnzqGjDgtgv1feOF5F+sF+OOaIOD9ySefEvFkodz09PKIdAmg2qlTJ1FG3Bry7rvvPvHggauw5wMGkWD+jz76yDF0e7L9pkRYoOCDKHagxa/V0VNlfu6CK+1regt4C5QOC2RtlibPkggtKIwRA5AOJTcpKVBGRoZLuK1y18e1lZmZaW64rS6+p2xa6n5uptz1C+s42VxeV1xxuYvTAijglmvbto0qVKjouqxdu7ZOPPFERYw1AiT89Kc/VVbWek2cOEm0a9a0qasXftSoUUOtWh3v3H7k1a5VWx07dlR5c+ERt8U+T+01adJYV155uWOc6KtVq1YuyJ422IU4JVg09CMOq2XLlsJGHTp00O233+4C5RcvXqJ+xl6hX4UKFfTggw86ho0g+53GMF122WWqWqWK04cg+yAIBFt1wfnnu9gvYs5gxW6+6WbVrFmTrl2iz47Wz6233mrnZ4uQd8YZZ4iEntdcc417WIC2sFfoBxBFLvFeodzbb7/NxlfVBb536dJFaeZmxJ2JDZctW26M10jHqMFoAUKRzTicEvaRk5Njn/6/tFogqbgHzq/VZSuLWwvf/+FYIClZqpghVa6wL6VFDkdC0dQtl75Pv1hd2Ud/xlE0mvhejtQCEERL7fth6erCYbVgLw6lG5Nq69atdcIJJ6hZs2aqVKmSiz+iHexOc8vbuXOXVq9e5ViSvMAYdQs7BUHg9HvkkT/o8ssvV5MmTdyWwGz6JjbplltucSABMEEc0v33/0bU7927t1Ii+27iIAhE/YsvvtiBC9q3MdCGiy4lEjHQUU3sP/7447rqqqt0xx136Pjjjxd9hX0HQeB0uPfee4WdAEannnqqLrzwQlXMzHS6sX/XXXft1QFb0xdB/DfffLOQj2zceOnly7ugeti4ZAOV1EMOOrKIKP2gI/1QFqaUSMSNhXLk0SfxXvSFPg8//LDQAdcffdIeuZdeeqlCuZx7+uT8U4fxhDZ88MHfOj1xQZIf2h1giyzk4H6kfaiT35YuCxQr0CI2a+7Cwvu1WrpOZdGMFoDSvrnU90TpktOi6fxTpe6dpMa1pCQDYaEmAJ1aVSRSUQMx9GhZX0K3UM/YbdsmUiQ51NRvE9kCK7KkRQa0cnbEX8uCMFrJNqkzKTOJZmZmGpior4oVK4q2KWXKiID4BQvmC9aCx/zLpKTEX1Ev0VvAW+CYtUCxAq2sLbs0f4V8bNYxcvkAnHp2MZDVU2rTQqpZTapWSWpaV+rVTjq3u9SwehRsJRmIqV/T8k6WTm0vVTIGrKiHaZ4Op1uDWlLFzF17EzpXSfi5sKitlbj9wWotse+JDdt2xV3JgjBasZ0mG+jKzMxUw4YNXRzRlq1btcTcXrK/+vXrm5uuQrG4Da17/+8t4C2QoBYoNqDFulmr1yTJvzIqQa+MPNQCOLWov0vpqXILSg75Uho4Qho2QcreKlU3kHViK+1lilJrb1PjOlJDY7XK7vNK5CE5/lkpZaSMQEq2K3yluZ5YcTxM6Dx6rrR9Z/z79RILxwIrV0nrs5LiHhSflGQXyGGqHIItABfxTrVq13IuMmJzgiA4TGm+ureAt0BJt8Dhf8vEySI77cfp6nXS1jhNdnFSy4vJxwJJyRLAqWxKdLKbMU8aPzO6gv+4WdKkBRIMZfk9zFUvcy12qZpqv+6lMhUlAFjHlhJy6IK1/xo3kE47STrXGDK2uBhjy1uYe4+yk9tJtKUOx+zjwkROfqlsBdO3nFz/q7Kies6cv2+7bI1nUnUM/QHkN22U+N6Ip9qHy2iFfQdBoGRjt4jTYYFO3IpBEMj/eQt4C3gL5LZAUu6MojzeYiDLmPei7NL3dYQWwH2zbWmqtuTscuClXVNjqozBIj9rlTRkuPTXl5L0v3clXhR8QmM5NovuykWirsbmdeTYrqRkqUdHqV8f6fQOUve20e0NF0jEf9Em2Rippg2lrq2trKt0US/b7ql7wSnmvjQgdyiwlWL9IIsE8CP1MHmZ6eT4dCxZAPZx47b4a3wkjFasFkEQ2P0QxGb5fW+B0AJ+6y3gLFBsQIs17nKyPavgzsIx8rF8gzR9YZJbQNK8JbrxIun2SyUYpxqZ0UEAvNgbOU6asZC96MMOk6YbA2YsGBNmcwNQvYylSjUwtWx5tB4rgGcYA9Wnm1zwfLRl9BM3IO4/ZCw3dorjlk0lAtoBbdFa+39WNlnElJFLPNkpbeTiyM7uIV19poHAWtrLrlHHp8S2ANcVP8z43oinpkfKaMVTBy/LW8BboGRboNiAFmbdXAi/UJHrU+FYAObqyzHSiEnSMnP7btshF5d1prn/rj/dWCpji0Jwg1tx/LptLqZm92bpm6nS9DlRvbq2kpLtygM8fTxeevMzadjoJGVvlwBbzepF64WfG4wxGzBMesPSIKsLKIukSHWqRuuH9WK3aw3Ez1kmLbUEQEPn0TPk+ghjyegrto3fL2YLHKJ7fpgdosphFycdQYzWYXfiG3gLeAuUagvYdFd84yeouvh69z0frgVgj1g4ErYKwDPCQNfUmdHYrPQqBrTMtceSCtTLTzZsVG0DSOZxUbq59prWlrqZ6xC3Im3IB0CxH5u25cg9nbraWDUeoqAs1Vir5IC9A9OGtdLnoyUA2uCvpc++kgCJ4w3sJdtVT4A+Ls0DW/qcRLVAip3veOvmGa14W9TL8xbwFshtAZtycmcV7fHBJuWi1eSY661IFSZ4HZcfMU7EX61cI30xQRryjRwbtcoAEAxRd2OrDrY+FbFXJJQvW0lq00w6sYXUqL600xiyDcZ+bV1Pad6JOnmX7J+bliZVtERuGAdI7NiWLdbPLilIl/87hixQWN8TSZ7ROoauAq+qt8CxaYFiA1p8v1XIkAuOPjZNV/q0btpQOqWLdGYbqbYxWFhg/UZpzmppvQEt2ChYKvLzSwClDebWo3yLuR+HGtv0urkDSSy7wDFLL1CeV+JpwooVoiXb9siJHu37ZFJmKYo+3aVzT5ZY24tSAF7ZsnJuS9yZ5Pl07FigujFafG/EU2PPaMXTml6Wt4C3QF4WKDaglWw9Z6RKMCV5KebzEssCrMq9bKmxQcY6VahmAAYQ01MuEP5sc/3VqykXjzXfmK7cmsNcsbwDyzUgZ8rcaN0yFaXWxmjVNWaLROwWLkRitWJl0L6PATyWdaCvaga0eEfmEgN4vAsvti77BE6zBZCxjhcLqZ7cLuqiZB0wytAzdz/k+5SYFoAtda5i+96Ip4ZJ8UZu8VTOy/IW8BYoERaI89dWwW0C+1HdJmcfJ1NwmxV3zWkLpW+mRwPKa9m5Y+kFAuF5qo/zSNA6Qe88WQjY2bgw1b0MmMD1Vs0lgBRuxa8nyj2RyFOHx5nLEBkk9vOKnWIupD3LOtBXsl21i1ZIsxbJxW3lZZd5iyUAHWAKXZHPk45V0pPEk47j58nplldbn5d4FqhYXgI4870RT+2Km9GK51i8LG8Bb4HEtIBNWcWnWBW+PDOLr3/fc8EtAHDK3iwRCN9/qMSTfMRlkQAuoww89f9Cmr9yH/hZstzqfxd98o9665dF+0MOTxp+/FV0hXnKeAJxzDfSC59KLCYarRn93GwsGU8MrtkkLc+K9v2+9ZW7XrR29HPbNut7nDTA3JIsM0EfJPR+f5Q0c/4+PaMt/GciW6BhDamCuQ7jrWMSKD7eQr08bwFvAW+BGAsUK9CC6eCps3LpMRr53YS2AABm7gLpNQNEf39FIv3jLen9L6WFBqQAZOEAqPvFBIly6g36NrqYKeWALcqeHbRPxmADZfmBp6+s7d9fidal7/zqITtM9M+SEi+8G22HDrSdm0vPsL7fJqYF+H7gSVQY0Hhr6BmteFvUy/MW8BbIbYFiBVoo06LpLlWtwJ5Ppd0CsSCttNvCjz9qgfDBBsIMyiRH8+L56RmteFrTy/IWKIUWKMCQix1oETPTpqmUFimAtr5KqbIASzHw/sTV26Wdu0vV0P1g91iAIHhYbx6A2JMV141ntOJqTi/MW8BbIA8LFDvQIriVtZQa5loNPA9dfVYpsgBrX30/w1ySXyTps9E+cL0Unfq9Q4XNqlVdbq21wmCz6MgzWlihSJPvzFug1Fmg2IEWFudX65ntpcrehYg5fDIL4EYkDosYKx9TZQYphf+Z6VLPNnKvZSqs4XtGq7As6+V6C3gLhBZICKAFq8Uj+KyV5F2I4anxW28BSaXUCHwP8H3QoJbE94MK6c8zWoVkWC/WW8BbYK8FEgJooQ1fpqyVdHpPiaeMyPPJW8BboPRZAJB1+okS3weF5TIMreoZrdASfust4C1QWBZIGKDFAED2bl0AABAASURBVPlS7dJM6t0h6kYkRoP8w0i+qreAt8AxagHu94oZEiCLxXD5PijsoXhGK28L79y5U6S8S4/d3N27d7txsT12R3H4mnMuCzLmgtbLT4OjbZ+f3GM9P6GAFsZkba0urSTcBg3r+qcRsYlP3gIl3QKwWNzvfY3J4v4vCpCFTUsqo7Vu3TqtWrXKgQrGeThpx44dmjNnjmbMmHFE7Q+nr6Kuu3HjRn3++efatGlzkXW9e/duLV68WLNmzdLy5SuEfcPOt27dqnnz5jl7r8/KUkHAUNj2/9k7D/iqirT/P5Ob3HRIKAkQCF1BqoCCIr2KBXvB3tZ11XVft/zX3fV9XXdX17L2igUQxYI0C2BfkV6U3mtCSagJhARCQv7zfS4n3MQgxXQnn8w950x55pnfzDnzu88z98yJHg8ePCgrVqyQjRs3/mR/5uTkyHfffXfK2NAWyu/evftEVfvF5Kt0RAvkIVtstXLhWSJnnyFSv7YI33ZJc8Eh4BCoPghwX3N/c59f1EOE+577v7xaWB0tWkzkH3zwgbzzzjuyd+/eQigzMzPl448/Fib0wsgjJ/uzsuT999+X/fv3y6FDh+Tbb7+Vzz//XHJzc4/kOLlDSkqqTJs2TZi8T65k2eaGfD7//AuyfXt62VZ0RPohi98333wjo0ePlgkTJsh7770rc+bMEeLRZfz48TbuPRk3bpy8Z/Ffu3ZtqZOt7Oxs+fLLL2Xu3LlFSB7WJwj1jBkzBDKWZcfACy+8YMngtiPan9whIyNTXn11uGzZvOWkCjL2Jk6cKLt27dJykFF04suCRlSDj0pJtMCVNVsN6ls3QjeRC3uK9LHfdJs1Dqzf4uFMHhccAg6BqocA9y/rMJvZ+5v7mvu719n2C1W8lOHCdynxrzpatJigPv10sixfvkK8iZvJbOHChfLiiy/Kgu+/F649QCBXCxctkqeeekaWLFliLRpZmsREnJaWppYYZGqk/SAekuBZaLi20YX/kLtZs2bK22+/I4sXL1YrCpYaiB5lIGFYPyhAWaw9TLJYdoLTSCdAHKmP8shBX8pwTnnKevpBGDZt2iSrV68W8lO+pAABhGRQH2XIgzxkoyNp+/Zlqe5p1gqFfNKpj3P04Zx2oDdlKIuc4LDNlh01apS0bt1a+vTpI5GRkdai9o2kb9+uxAfy07NnT+nevbslfzvkv//9ryAzWAb10hbqoG3oTjpkjWuIM/pu3bpVCRxplKEfKLNly5YSCTOWJwjYmDFj1Krm4UC7kEe7IGnII3j1IZM6qYP44mFf1j610NFHnkzy0I/gTXn6jHqQv2TpUnnllVfkezsuwXr27FkyduxYmT9/vhJA6vHaT3kPH8qjI+1EX7BAHrKpg/rJQ90VHSot0fKA4dttsySRXu1F+MZ7Vb8A6ercWoQHNd+GeS2EC6Kvx3A4OBwq4xjgPuV+5b6FXHEfX2TvZe5r7u/ocO+OL99jdbNoMSlhDahXr560a9dWiRMT03brRpw5c6bs2ZMpM2bMlLT0oxad7XbSnz17tqTtyhesL5AICCgk6bXXXpdnnnlGnn32OSUuTJYQtldeeVVJ25NPPqETIvXScxyZ4Jg0U1I2qWWMMhs3bpSXXnpJyzz11H9k0qRJApHBYvb8889b+c9q2mOP/VumTp0qTJjII+TkHLDk5Gu1kOVZaxvtePTRR9VaxiSLrB9++EHlYRlCHnUR0AUZwSHLEgEsfuRDFyxvEIJt27ZZsvm06kEa1ifIyPTp36klkLqx9k2ZMkXbRRpyIK9eALvguiIjI+SKK66Q888/Xzp26CCNGzdW8oYczq+99lrp1q2btG/fQRIS6irJAvtgGevXr5fnnnte9Xr66afl008/VaIMWXv44YflpZdfFvR96qmn5HuLA+SCtjz55JPadyNHjpQfflio9Xpy6Sf6ZMGC7yU1dbMsskTbI3Bjx34oL1uZlMcCSl+QNt5a5KiHtlIn5ZHjyeQI2YQkkY/yjCfGHzrRN+Ct5V96WZYtXSbpdhwyXr1xuWTJYmHsrF+/QWbPnqMW2ZSUlML2P/fcszp2IHrZ2Tny6KP/VlzQ9/HHH5fhw4fLG2+8oXGMkenTp5e6hZB2nmyo9ESLBmHdgnDVjxc5PTlAuoZYN8N1F4ncMlTk11e4UNoYOHluTJXmGOA+5X7lvoVccR9zP3Nfc39zn1dEKD6pVYQOpVlnVtZ+JQUDBw6QNm3aSIp14UGkGiYlyQVDLpD4+Jpy4YUXSHKjo2+I1rQLLpB6tX1y6aWXSsOGDVWlmJgYuebqq+Wuu+7S9VoQLKw5uBSbN28mf/jDHyxBaK/Wh2zrnqKQMUZatmghWGlatWoll19+uYSGhgousry8fLnvvvvkmmuukVmzZllr1yI5nJ+vOiZZ/X772/ukX79+8sUXXwhWGOQRIsL94vP51Eqya/cenYBZc7TeEpCMjAwtHx0dbQnkdFm5cqXcfPPNqhv1oSuWGOQEB3RDfzDCcrJnT4bVZ7HExdXUstddd51s2LBRli1bZglQgk7+GZmZcvDAAbVE1apVy+oxW/Wkvvvv/71gUWL9VzD5IN/gQYOsbjPkX488qn3Tvn07adCggVq50GOUtXhBCmhTr569JCIiQoL/li9fLvXqJapegwcP1nq3WlIIWVu6dLm0bdtW/ud//kf1XLBggWTt26euSCw7f/rTnwQyl5iYECzSWo6NnHHGGRbvvnLaaS3VohYbW0PzQPh+97vfCXUtWrRY15fRX/PmzZNbb71V64q0ljmwhaBqoSMfubkHdUyA7TnnnKPEnb7EwjRixAi58sortXzt2rVk6mdTJSwsTC6wY49xecEFQ1SP3r17W2xayZAh50uNGjXUHYl4MIa0ohNW2QMHcqzFdo0wdtAXq+CcOXNte05TrMAWIlwZ7vEqQbQA2Qv2PhYeztHhIoQa0SIuOAzcGKj8Y4D7lcD9y33s3dMVeaxuFq3Vq1dZgrBBevXqpdYTLEa40UJ8PomOiRa/P1wnrzC/X7y/ML9fIFVi/5jYmPzApWXLltLSTsLNmzeXWrXilVRggWAyX2qtEazpwjW51Lp+IGC2uP6H+f0SbYkPBAt5WDTmz18gAwb0l6ZNm0qXLl2kdu061rW5XA4XiNUpTMlCcnIj6dGjhxw6lGfdaNsLLRFhfr/Ur19fLVbr1q21rs19SgKwlqAPldav38BabX5QHSdPnqzrzdLSttmJeJ0cOJhLlsIQExMrXbt2FQhlkyZNBEIGTgMGDLA6DpCPPvpIpk79zMraLBA5yBiF161bJ1use44F9Y0bNxaIEWSM+saO/cDqt89ahhZL8MQOQQy1ZCI2Nta2oR5iLDFMkYMHDyp5DA8Pl7p161qSVNdaG/dI6ubUwnZrZvsx2BI1MEOvadO+EyxJWPKoB4Jy1llna1vQCcvTzl27BFIMUSKuWbNmQjvRxYor/KfuqKgoi3+4xFpS7fMF6EDfvn2VvNBXZMZth8UQax3WvA8//FB12LQpRbBgkccL8fG1pEvnLqoPOhOfZt3PEFAI4dlnnSXJycmKf0ZGpuzetVvHHuMSjNCHsYNuHCHAuBL1y0FyI+lgrYIQQfoCool86oFs6Xht2UJaWKJP33JNPvqWfBUZAshWpAauboeAQ8AhUEEIMFlVUNWlXi2TN1YGvyUmuHw+++wz65pJU0tNVlZg3dXPrfRw/mEVgUUjxk7OTHA33nij1KwZp/ElfQRcbrlqRSHdGCNRUZECAeOagGuJY0hIiLVyhBZxc4n9wxUabi1b06ZN00l8yJAh6rLE2sPEi4UEwuTzherEjW4dO3YULHsRtpwV8ZP/+fl5AmH629/+JnFxcdLcWuyQQSGu27dvr67L2dbF2rlzZyWr+dYaFxZ2tL5u1gU4ePAgihQG+mTnzp1yliUYt99+u4AVbj0IAGQJUnnRRRep1ZDjvHnz1UXrCcA6hsuOReq1a9e2JKK5klgv/aeOYZbgkV4aYxyyAnEGEwLks3//frYfo6iiSMhnWw8bQ1/SH/bUkuMsJXScE8ItweR4KO8Qh2MG6mU8e21BJteQrNJo1zErLuWEkFKW58Q5BBwCDoEqgwAP7iqj7HEUZT3S4sVLBGsWE5HPWrEgQqmpqcLk7hXH6gFJ8K6Dj6ThzguOCz6PtlYxrAWdOp2pLqnLLrtMcBFBnILzGWOspShPWF+FlaKJtRzxugisI+iJPo2s+zLEBEpBRiAeGzdu1Ii4YsQNqw8TPNY0ZGGlYeLnGstFhHW34V7DJXfhhRfJ9ddfr+uiWrVqLViUVOhPfOTl5QnrlSBRF1hXVts2bXXhOpO5z+KIlYZ1TqwnOq/7eUowEhMTBSy8+vr37y8seie/VxWE6l//+pe6FbOzc9QCBPmAOHzyyScyevRbug4p27peCeGWFAaPSerHfdmxY0fBQtXcWhfDwyM88SUewy2Jod8XL16spC3DuldZT1a8z40JgJ9vSWbOgYOW3AZIdElCkVenTh1184EtGLWyrmFIT3B+LFy4UFl/x+J0XIk1a9ZUdyIL1/lxAP2MlZWycZbU0l7yUZZ+QF6edTMzFnHlgjMYIJOxs8tawSDeoaFhZK0SwRGtKtFNTkmHgEOgLBBgIisLueUtM99aV3DvJCYmyG/vvVfuvPNODbfffodaXyAwWKHi4+PUcpOSklJERdw0jRol6doe3GOQBYIxgckYYsB1PUsuzj77bGFB/ZtvvilvvfWWrlkqTs7i4+KtC/CQjB8/Tg4XFAgWqJUrVwnrdPiVW0JCgpx55plizVySm3tIX3nw9ttv2/rHC8SpfoP6NilQt9g/9GNy5dg4ubGSIPTAUgfpQjfcjjarvPPO28K6p4CLa4P8VB9TjjKhoaHSsWMH63bdKK+//rpMsu5DXGWUxarU1LrfwJa8Lax7CmJH/RAC6gML1qEVxzXR4oWbFH1GjhyhuLVqdbq65mjn5s1bhLKk44rDDRZj3a7UQ4CEYD1auXKl6vXVV1/J7t27lMSS7reuYI4E2kKAaEGEIDq0ZeLEidYNuoUsPwqQINxz06d/Z0lglrUm+oU6vYyhoT69Zv1TZGSU7b+Rii0L23Ebg42X1+cL0VNeX0FbcTPSRkgaZLypdRuDFWMA12bnzp10rRrjMtn2KdZYdEanfEv+cDfyhYE1ZiyQf+ON14U1V5D6du3aSbglpX5rvdVK7UeIWkOPusR9liD7g/CxWSrsP4BMGVWP3371kjXigsOgCowBN06r0b26Ztmmwvfy/NTjjYfzT6VXpbTTWp4mN9xwg0Rbl56nd/16iTJ06FBpYi1KuJ5Y2H7aaafZSSrcy6JH1lKxgLmZJRRYoLpZNxivI4CAQLJYxNypUyeJsiSAX9DhIsOaAwmA4BS3GjVv0VyuvvpqrTfEkjUm2ksvvUQtQLjhkEd5Kvf7w6xLrIVOut27nyuXXXa5sIicNC8waUJs0B/SY4yxFqshctuZnrMYAAAQAElEQVRtt2k58jGp33DD9brei7birmtjLVOUJZ2AZew3v7lL10VxDRYsuk6oW1f69esv11xzterYrVtXXfiNruSLsZa8m266SX71q18J+CDzdIsj+bFiQRy7d++uFi3ye4F23HbbraoT68y62/aBX1xcnHTs0EGGDbtW6wML9OhuZYT5/V5xJZsDBw6USy65RFhv1bt3byXQWANpy513/soS6VglQxDXvn36CmudOp15puqPXProBjsuwIP+lCN/tIG0K6+8QtCNMXDrrbcIlitjjMZB2JKTk4Xxc9NNNwpklLayVooQLA+L47333iODBg3Ssowf3KHIhTzdc8/datlCJ/JgeYVkkU47Tj/9dB2X1HfZZZfponbGXr++ffWXm5SjP0hrakkbhPTuu+/WuowxuvaLcUlbaOLpp7cS5CKD64oMIWVZ+aolG+TD18a54DBwY8CNgXIdA1Pe/lT4xn285xsWi+PlqQrpTJrtO7SXzp07F1E3zO/XONw84dalBIFi0sbFFpyR8qTxqy4mNH6RxuJlJlICBAAiY4yR+Ph4/VUheXFnIcuYo9Yn5GJ54peH1BXm96sFiomeMkzeTJTUSV4C9ZGXtOTkRhKcRjoBvdAxNjaGSzuxNlI9mKyJoAyuNSZ3SB46e3lJJzCpozNHrpEJZtGWnJK3r53UKcvCeIgARMwYo4QHIsMiesoRwvx+tb6hN2XQDRJGmheMMUoE0Ym2Ix+CZIyRML9fCRjxBPQoXh454I0+5KE852BOG8CLMsYYoe2MAaxtYf5Av6MX7YWg0X9ghEwvQEiRB1boxTmkiHTSaC/xlKPPvHbQt14+8hLoB8ojC12pFz0pSzrn6EsaedCfeNJpOwSK/qA91Etd5Anz+3WNG+Uojx6MyTC/X8gDPshBT8YYenPNOCI/ebmuyBByypWfQMGcvfslLTXdBYeBGwNuDJTrGNi2ZYvk7Mw97lOqOlm0jtvYSpgB/CGBsTGxlVA7p5JDoHQQKFOiVToqOikOAYeAQ6BsEKguFq2yQafspWIF4V1P7dq3K5XKnBCHQGVEwBGtytgrTieHgEOgXBDAolIuFblKjokAriNjzDHTXYJDoKoj4IhWVe9Bp79D4JQRcAWdRcuNAYeAQ6CsEXBEq6wRdvIdAg6BSouAs2hV2q5xijkEqg0CjmidRFe6rA4Bh0D1QsBZtKpXf7rWOAQqIwKOaFXGXnE6OQQcAuWCgLNo/RhmXkKZn58vhB+nupjKgAB9dCg3l30RVR2uCXpRwgdphBKStJ9Ppq/Jm5eXV5KoE45DF+QQTrhQFc7oiFYV7jynukPAIfDzEHAWrR/jx5YtvKmcN3P/OLVsYtgTkDfb8zb3adOmCduxUNOaNWvk/fffLxLIs2vXLpJ/sSEra7/cfc+9sn79en0xL/tacl4SIJCZJYuXyDfffCNsYxOch/0mJ0yYIAS2vAlOO9Y5W/v885//KuyjY+X7qXi2XHr++edl4cKFSvR+Km91SAupDo1wbXAIOAQcAieEQLFMzqJVDBB7ibUiPT1d98mzl2X+D8mCTD3++BMyb948efnlV+SVV14R9v5jj74VK1aKFyBhb701Wk6UFJS58hVUweHD+ZKSsklx4MsCWLFdzbHUOZR3SPMWFBTdz5CykFZ2cSkoKDhW8SLx1MV+hocPn1h+CiObrZf+85//CJY4+nz79h3HJWvsjXnTTTcJJBw5VTU4olVVe87p7RBwCPxsBA4fLjrx/GyBFSSAiQzrD5sYowKWisWLFgv79ZFGPOlYN5goly5dKlisOHJNmeKBCZh967799lvdFJl0yiOTeMojk4mTODZ45pw87FnHxsFcI5808i9fvlwnfGR5gU2G2cvurrt+LWzAfP/9/yPz5y+QnTt3CW8If+ih/xPCX//ygF4PGNBfvLd/ezIgh9QJEfP0LbDEAV0gERA46mfPQHTyynHEegZWTOpcQyLAhXwQOs7BAllpaemCfDaXJh9xlPECdWZmZEhweyEVpO/PyhLqQQ+OXBOPHPKDDWkcvTKkewEc0eW///2vgG2udR2SxpvUeelrXFy8UDYlJVWtROhG/7DPZd26CfrmeHYHIJ481DV//nzJsnp594GXRh2zZ88W2ksc9QSHgwcP2LqWCfmo8+DBg5pM3s2bNwv94GEEjitWrJBFixbJqlWrlTRDCvPz82wf7xTqQQ51gZ8Ksh/gM3fuXFm5crUSLXCin9Ed+QTK5Fs3N3XQVvBhbHppwfKsyAr7r/JEi320/BF+iY6Nlvi6taROvdoulB4GDkuH5SmPAe5H7kvuT+7TCnvK/UTF1cmiBZkYPfptnWSZXB/997/lu+++E0jXmDHvCmSGCe7jjz+W119/XT766CNrPXpZJ0VvovSggmDMnDlTJk36SN5880159tlnlSBhYXrnnXfk3Xff1fJPPPGkrFq9WrCAvfrqcElJTdX6kD19+nTJ2r9f3njjDRk9erTmHz58uBDPxOjVFRsbK7fffrt07tRJt95hyxTiQkN9XhY9bt6yxbrKNgh7Lvr9R/cDZDKFQFH/+PHj5YMPPrDE7O+ybds2SzR3qq4jR46UyZMny1NPPS1TP/tMmLBVqP2AwLxn3ZMQAWRNnDhRnn76aaG+DRs2qDxkQVaffPIJdbONHTtWcK+mpKQUrpOyoiQjI0M+sGlgBgbPPPOsQDiob5LF+80RbyoOL7z4onxtXXngAJn461//Ku+9956MGzdOKANhgEAgk0AffvXVV/Lcc88L+mEB3L8/hyTZvn27ll25coUSn0mTJgr9eSAnR0aMGKkkZdasmVrvnj0ZluiskL///SGtCx3nW1JLXQX2S8eypcvkscf+LZ988onKfOutUYqjVnTkg7yptp/BGl2wUs23hI14CNWTTz4ppIHR8OGvyZq1awWc0tLSZPfuXZK6OVXxh+BNnfqZ6sX4ePrpp3SMHalGsq3+kCeuGc+MPfoIayfyCf/4x8NCWkZmptX3fXniiSe07lGjRgl9tXPnTopXeKiSRIsHN4SqVYfT5cwenWXgZf3kohsvkstuHSpX3n6pXPObq11wGLgxUIFjQO/DOy/T+3KgvT+5T7lfuW/DQivPY8f7Jl/hT+KfqYAxRtq2aauWJyYkSAEit1hygiUgMzNDN25mgpw4cZKcd955Sm7Y/2727DmCVYn8XggJ8an16G9/+6v88Y9/tJPzSp3Q8/MPCxsMs0kx5Ij8ELimTZronn5LlizRfBkZmcImwanWusL6nwsuuEBuveVWzcOkzMRIWQJ787GvIhtWMzFiaWFTZzZkJp0AIWGSjY2NsZaZFkrIiCfQh96+ltddd51AWtq1a2sn9d3WGrJCNm3aJHfddZclEI/JZZddqgQJckJZAvvpNWyYZK0tq5QkLlu2zMoP1b0yIQjs6RcXFyfvv/+BEgHaffHFFyu5xJoDwUAOJA09KE99Tzz+uAwderHQF5AYLE/s58fG1C1aNJeFCxcpEaVsYEPmey1BfEgxguAdtpYa0gjbrZttwYLvpV+/vvLoo4/KnXfeSXSREBISIuwZiEWJMZBm3b/p6WnCHo0+31HSCtFOTKwnjz/2mPy///f/pH37dra9PiU274x5R+rVqy8333yz0GeMHcgTbfMqQxZ98+tfByyQHTt2FCxI2dk5EpCdKP/65z+1H8g721rGevfuLeeee66wp2X//v1170s2e6Y9Dz/8sPzlL39RnNKtzl497F143bBhEh9fU/c0ZCNtrFUJCXXl//7v/+SRRx5RyybklC8QEPOABfQhm/6QbNmyVUmuJ68ij5XniXcCKPDtuMkZraTnBb1k6E0Xy+V3XCbD7r5SBl45UM7t31U6dGsvrTu3kdPatXTBYeDGQAWOAe5DAvcl9+e1d12h9yv3ba+h/YT7mC9MJ3Dbl2kWJqcyraAchTdKbiRRUZHWpbNcWLDcu3cvwb3E+paYmFhJTExU60S6nXxZ84SFhwmcybC4muHhfklISLDyoiTOkgy/P0xwsUVGhKs1AmsXlpp9+/bpWq6IyEjp2LGDLFmyVAkK5Rs2bChr161V0ZCrqZ9NFQgY2+5A2DThyAcTOSRrypQpapEbOHCgREREHEkVSbdWG9xlp512mtSuFV8Yzwl9yARev349YcE3kz2uNCbmdDtxx1n969evr2SiY8czBUsK8ZQlYB0j/6pVq3SyJ+6887oL1hQWmFM2PDxc1q5dI4cO5alljAmffGAHieIcwoeLkUk/OTlZwvx+6dOnjxKWEJ9PoqOj1X2GlRECk5W1T7GkbK1a1hNTp45EWRwhk/RbvrUwkQY22dn7tS+bNGmiuNA3EBDSgwP4+Hyh6lqk3xs1Shb09/IcPpxv27FWunTpLNExMapTrVq1BAyzs7O1/ejF2KDPsC7SRq+8d6yl+tZVXSDrtJvxgWUR0ozsWlZu48bJSng8MuqV5xgVFa26UQd5w8L8OsZIKykw1nbt2i1gEGutoFFRUdKjRw8lyFjw/BZvXMocGzSoL02bNhW+WJQkq7zjQsq7wlOpj2/ATVs2lYFXDZIr7hwiAy7vI+27tpPEpAQdzKci05VxCDgEyg8Bv52guV+5bwde0Vfv40tvvkS4r/3W9V9+mhSticmxaEzVvcIyw0SLiwki0b17d7Uc4KpLTm4kpDMJQbq6dz9XhgwZItdcba3/11wtcTVrHrfhYLV23Tp1/bVp00b69u0rSUkNtBwTNXUzSTNB16tXT+rUri1YLagTwuHVN3ToUGuliNNy3geTKJYs3EsXXnihTsBeGpM0JOvgwVy1iISGhXlJekSvGjVqKqnp1auXxMXFydtvv62khvrz8vKFPGTOycnmoHrpif0wxgi67927Ty0yWIVat24t6LJ58xa1MEG0IARNmzaRwYMGq4UFyxZ5g/WhrVakJWSHBIKUl5dnyVS+ZFlCOnbsh9oucEM+Msl7IgGyg8UGedqWggIlXsXL1qhRQ1q1Ot1acmbq2qeePXtIWGhokWwQWMgm+hFIRKYxIRIW5ldLpNfGm2++WTp06CDGGAn+y8/Ps+07rFG4NdHP5wuR8PAIgbCRgEUux7r/wi1p5/rnhtDQMAEDSFWBJaHonpmZqWQPcon8/CNWQNJzcw+K35Iv4is6hFS0AserHyvWIEuwht13jXTvf7Y0atRQHx7GmOMVdekOAYdAJUPAGKMPRib+s/t0lit/e5laqFnPVRHruEKsu6WSQXTK6vis1YT1S5999oXUrl1HGjduoqRj/foNas3CAoClJT4+Tte11KlTV/ZZqwruxUOWEJxIxVhrIEXIYrLGPeNNbljMIHGLFy+Rxo0bS4S1zrRv314JARYcrBYZ1oWJlYGJ3avvUG6uriXDBdmlSxepZa0luL68CTsjI0NwxzW21pEGDRr8aNJnQp85c4Z8+eWXgpuvXbt2ahlBz8ZWD8gfi83RYdKkSdb12NzOI4286vWIJaSObxwxoAAAEABJREFUtSh98cUXcvbZZ1sCmaTrnDKtvvUsaaS9xNO2iMgItQRt3rzZWugytDwfjCX0w2KHuyw1dbOuD5syZbLkWQKAPqFHSM+mTSk/ctcio6RgjNF+pG3IZU3S3HnzbBsDa7SCyzAGwHDRooVqScJtaILGeEiIT3CvQcZxCa5bu866hVeoiOjoKOtm7KgL+WNrxOo8W7yNZKS/GTP0F27RWbNmSbNmzQQrU7duXYVriPFS64LFKgiJ9VtyHGL1oE/37t1rie+J/2KROrGYQdiSkpJ0LLDuCzct1kvaE2n7JNu6LtetW6/rwcAHnCCJlK/oUKmJVr1GiXLjfddK74t6qfXKb78VG+MIVkUPmupdv2tdeSEQ5vfrhDboyn66vjKhYUJ5VV1YT/CEXxhZhU+aN29uSVWCMOHhRmQCbNasqTRq2MhaA0IFN9JvfvMb/eXc0KGXyPDhw60VI0yKWz18lrQFw4Clg4kS+U2aNNU1NfxCkDy8m4nJFyLQrl1b26cNpGXLloIM3IcPPfSQjBkzRq6//npdH4WVgUBZQrZ1WbGA/b//nSYPPPBXQa8LL7xYWHSP1YIJk3VWkEisMZQJDqF2EocEoQdtu+eee6wVpqPgVsKl2LNnT1vvW3LppZerO/D+++9X616wDPTBnVbLuruaWpdTnLWKgR1Erb4lWhCka6+91pKUs4W1SbfddptO+LGxNQqJnzFGmlvCgeVuxIgRcvPNN2l9gwcPFuSdf/5gee655+Tee++1JGizVg9x1ZOgD3ALutRT9Bo0aJCsX79e7rjjDl0QHx0dqWnFP9C/iXUx0h7qDU73+ULkkksuEVylt9xymzz8j4etBSpHQiwJAlvaBenkePfdd2t9WMmKyvBZS1G47dN3FQssTLQx3LpXsVZSNxg98MADOg7oB/qo69ldhUX+vD9r795M4c9XbJwRFxxirIsQK+Xjjz+ultSBAwcpmaYPWacGkbz88stVf8qxZu6++34nDz74oIAXP7AgvqJDSEUrUFL9YaEhwsLZ635/rbTqdIZAsErK5+IcAg6Bqo2AMUZ4QLfv2k6431m7xf0v5fTHBFNOVZVLNSwg/uijSTJgwAAlOt26dZNnnnlG2ndor/UbYyxZ6CqjRo2SOXNm6bG7dTGG+f2azgcy/vSnP8kVV1zBpUCW3n13jLrtSHvwwb8Jbj5eHEo81xARApM4vzrDskNhJlKIDnkpwy8Q0Yl40gk14+JUj9mzZ6pO6EWAUBhjBPccMln7Y4yhSJFgjFEd0YM6CJxDECKtVY1F3eiJzBdffFEgi8YUlYM+LFRHz+joaF2bxkQODuhHhcj73e9+p22njt///vdSr14iSYUhzO9XlypyyIPekDXk33jjjVp26tSp2l76BZzAbPjwV5WwsbaJOoYNGyYRQWvUKE/70R+53pE4iBULysEZRWgz9aKfMUYJNn1JW+g/2gEJAg/0pG6wpt2QLGRRB3pCXCmDXC8wXhhjlCMf7aCNxhhrSa0t6E885cEQmcYYHYPEIR+9H3nkX4Is2hYfH2+tf2OEeK8ejqShK/IuuugiAW/ahRziqAu9ycsXi0suGSoTJoxXnGlTmP/ouCZPRYWQn1txaZf3R/ildac2cuGtFwhmbmNMaVfh5DkEHAKVDAFjjN7v19x9kTRv09JaWMrn0VTdLFqVrFtPSh1j3LP+pABzmYsggFUSYlYkspJclM/T7AQbyxqNZqc3lQHD+qn52Rh3450gdC6bQ6DKI2CMUdcWX7IgWzwPyrpR1c2iVdZ4VRH5Ts1fGAKsocO1jEu0Mt7TlYposUajz0U91AxcWZnpL2z8uuY6BMoVAWOMNGrUUPpf3k8aNmlQ5nU7i1aZQ+wqcAiUOQK4S3FD4no0pvIZaCoN0cJl2PviPnJax1a6tqDMe8ZV4BBwCAQQqGSfxhhpfkYzOe+SvhIdG12m2lXGb79l2mAn3CHgECh3BCoN0Tqr11nS6bwOjmSV+xBwFToEyg4B3vvD3m/8THzDyo2yeskaDZzzc3t+6k2e4hpg0T6jYws567yuUpYuRGfRKo68u3YIOARKG4FKQbTYluOcIV2L/MqitBtaivKcKIeAQ+A4CECedqTtkjWLVsmKxeslZeUW2bY5XXam79bA+cblqbJ84VrNQ15eERAslvfytD2nlSSU4WsfnEUrGHF37hBwCJQFAhVOtPi22rF7J0k68obhsmikk+kQcAiUDwK894itONav2CBrlq6VPXuy5HDuoWNWThp5yJuyJlX3kvMyG2MkqVkDaXt2e2FpgRdfmkdn0SpNNJ2sikPA1VyZEahwolUrsZa063JG4QvHKjNYTjeHgEPg2AhAsvZmZsraJevUakXOgvzDHORYR0088hGwcq2X/VlZgiyieUdOy9aNpVbdeC5LPTiLVlFIefkkbl7e1h6cAnnmpaFevwSnVZZzLKK4oxk/P1cnZPE2csLJtJmXr+IO/7n1V5XyYEN7eUN8Skqq7lNZUbqjC/jv2bNHnyH0YUXpUrzeCidap3doJXWS6ujL2oor564dAg6BqoEADzkeuFvXbbEPuaNbgxhf4BFT0rEk8oV1K2XVJuGB6bW8nrVqJTVtVKrv1vJkO4uWh0TguGHDBnn00UclJTU1EHHkk/0LeVFk3qFjWyePZC1ygKj88MMPOgEzRiBC1FGcyBUpdIoXjD/eID5n7txTksCefWxxA9kk8DLP999/X7fiORGBTOy0la2AOD+RMlU9T/b+/QJGjzzyiLz33ru63dLJtol+mzdvnvycMQHevDV/4sSJus/l+x98IIsXL9Zxd7L6lEX+wFOwLCSfgEzcAY1aNBLe6HoC2V0Wh4BDoJIicOhgrqSnbFdXISqWRKKKxx+LfEG2tqzfKqzzogxrtZJbJos/suQtR8hzqiEkpEIfgaeq9jHLMeFkWqvijh07LOHN0okGgoNFig1+2aZG0+wESTyCtExGhhDvYU588ZBrXcDZOTkCeUIe5bw8TJLEEyApyIYsz5w5U5555hnZtm2bYO2EhIwdO1a2paUX6ubpxNGTiTwmYGSgF+foRh6uiffqLn5EBnoQkMM15SBS5EU3rsGDawL5mKj/8pe/SDARDJTdp232ypMfGWCALljQuCaeN5yz5yPXxJMHPcCE9OCAPNIItM1LQxesMsj2yiEPfZHp9S9p6EdeZFAOGRzJg3xkcI58ynKNTsgjL0fkUp58yCOeIxiBc/E00gnk2ZSSoptX8/b9W265RddZU7+nEzpQB/kJwXWhE+lLliyRf/zjn0ruiSM/8dRLoB7KcqQNjAV+YEM9xBMy7PidPHmysNdhUlKSfQ7tkddff10380YmbeFI3ooIFfqUwR1Qv2FipfmlIR1M5+XlV0RXFK0TXQhFYwNXDLjcAwf1m9ax8gRyHvuTQUdbC05ob8+AHMoQTqZMoKT7rM4IMB737MqU3Xv2FTazJBJFYvH44oTMS0fWrvTdFNEtRJIa15PI6Ai9Ls2P6mTR4t7EIvPcc8/L008/I2+OGKF71dE/X3zxhbz77rvCtimkvf3227Jz5061ImiZ51/QMkxWWdZ1WxLGWVn75K233pL//Ocp3UImxU6yPH+YuMdPmCDPPvusPG/lfPrppyp72bJluqfiypWr5fPPP5e51moxffoM+eGHhTJr1kxrtcyRVatWycsvv6R1v/HG67Js6TIl2GvWrhW2mRk5cqSmvfLKK/LRRx/JyJEj9Jo9GiEGxfVk78AZM2aqHugz9bPPZPfu3TJ58qcyZ84cbS+T+Jgx7+i+e175zVu2yJQpU2RdSpag/7a0NCWCK1euFPYtpM2jR4/WNYTgudbqN2rUKNXlxZdeEq6RBaa4XiEon1gc0Juy7MFHuhcgPOPHj1fM0JO6eR5DJL76+mt54YUXVTb7PUI2cnNzLWaz5JVXX5VXbWCLHdLoV/Ii43Pbx/TFxk2b5CWrE/tL0tecg90o23dcv/baa9o/9N0W227GBeUZN9OnT1e3PZiBNfjTp6QVtxBBbhg7yJg/f4Gkp6cL2KKHpxNtRBZ10WZv/KDT/PnzZfWq1fKZ7aP09O163Llzl5WzXSiHTgTGJHKRg6Xq2Wefk1eHD1ey7uHJkT0WL7/8MmG/xd69e1s56bLPjuU025dY2yDQ5KuIUKFEK6F+gkTFRpVpuzO2rpcF81eK/TJ23Hpydm8TBknqjqMTxo8LFcjmZQtkybodhUkMIurBT81NWJhwiifISFu/Vr5fsEr2HywqhIfptpULZcSokfLxxwskK2t/0QwndFUgG76fL5O+XSVHltActxRtpMw3X8+TXfsD626OW8hl+EUgwJjcnbZDF70XJ04eAMXjvWuPWHH04jiySB6ZTD7IiK9bS2Jja5T6qx6qk0Vr+/bt8vXX30inTmfKxRdfJEzOX9tJm8l73bp11vIwR8466yzp06e3bna8YMECWbd+vRKYpKQGcumll0hMTAxwlxj278+RJk2ayMCBA2T79h3yzTffyL59+3SC/Oqrr4XJrXv3c63LZonMmDFDkqxloX379rrJNZs+t27dWs44o7WwN1+bNm1s2b2WED2vmwQPHXqxsB7vU0uImLh3WhL47bffSqNGjWTw4EGSkZGpBKhJkyYyaNBAS5rmKvHguRSs7KFDeXL4cL5ccMEQi0Mn+eqrrwSSAwGBaGVZSx7uSyxtvOTSK5tQt65069ZN6tX26f577M9HGvLYuLhnzx6KLbIyMjKEvfZ4BQk4s/XLe++9ryQDkgXBxNrEMdW6YMG7YcOGiNPA/QKxwvrSv39/ATfkfW9drPMs+Zg27Tvp2LGD9iFEFNdcrp3A1qxZo8S5S5cuwr6GbMRNO/r27SMtWrSwmM+UTZZkQUjALi4uTnE4aK3NkyZNknr16uk1FiTScftBgLds2Sro0abNGUqkN27caAnlAZk5c5aOIfBHcUjd4fyjVgjGCpt2JyYmyjnndNP+pv3ff/+DxbKrnHvuubJo0SJhI2nmNEjWtm1pqgNj44svvpRDeYd0TLJBdteuXSUsLNTi/JVapsCFgAt3prWMZlnSBNk7dChX+yg+/ui6Tdrau3cf2/eHhfzjxo2XXr16SZ06dSTWjunTTz9dyEM7KiJUGNHi14ax8TUkqkYZEq2C/TJv8scyecqHsirlKDEqGegCyT14QFlw1v4DltWXlMuafwqyZeanM2X8e2NkQ1qAkBnJlpSFK2TW9PVy6CTXMJRUiy/kQEnRNs7qmLldpi1aJc2atpd+/VqfgtvVtsFK2r9zrWzbvN2endg/bZTc3ZK+LevECrhcvxgEmFRw99FgCFPwMT4+RgiR4YH7PDi94AjL947BacjItN8ymBg5j4qNkFr1a1vrt+Gy1EJ1smglJCTILbfcLBAIJlwsPpCW/dnZile7dm3lHEsmunU7R3ffgARgsQkPD7fkaaBOeD179pTw8AjNX/wjMTHBPnP6yXnnnbhtGokAABAASURBVGfzdpGNdkLGijF16mc2vq9ObL3t5HbaaS1l9erVdtIM0y2VIFDNmjWTRKtf/fr1pXbtWhqPFSg1dbNcddVVAhHrba0QuHjQnX6Jj69lJ+xuOmF36NBeEhPr2XrP1rgkSwzRnXzBekZFRWp+yAgTLUQNktmuXbtCEoIlpa4lVpATr2y0nYwbN26sl02aNFXSB5GCGEIYetg248LGKoIbFBm4wSAWFGKN0a5dAQss14SwML+cc8450qNHD6E+4gi41Wh7R0um6A8wHzZsmP4gDGLVuHGyoDvE44ILLrCkco61yu1SPFu2bCldzz5b+vTpY/FIlDaWsHazfcr2M/n5eeoyow5IEPWebYl1586dLAlqKF26nKXYJFkCvNRaDtOsBYr6IMfdu3eXQQMHKjGBQBcUHJZateIt3mcJekDeIai51rKGfALjhnZRF+QZt2lycrJcc83VJFudd6vljDGIhQ9L4fnnD9b+u+iiiwSCmJTUUMciBZo0aWIJXo6SrHZ2rII52HSxxPLLL79SS2dcXLzqQ7tiY49+KaCv6Hv6hP6hnzj3hYRIjZo1td2QLuqpiBBSEZVSp89nJL52DQkPC+OyTELGtnSZvyNb4uJqyqr1aRLsEsT1xo26eNFiJUx5+aaYDgWClYoO4xtIIDGQJy9vp+zZsUE+mTK30OJ0WPbInsMBOLN3bVU/fx7k35I9bkbMv8jBGsY7g6ibwMOQ/EuXLhWu7dwiBRIl/jj7MGpg8fHlBarm05K8jUvX2m+T2yVzb4HkHTxs8/qEb/2URUZaWnphO9E/JSVVtq1bE2SBC7QBcYQdG9cIGJBP9bWRBdY3iE7Er7YPTHTKPxxhU47+IxurHrKplzZ55Y/mcme/BARYM+G10yNN3tHn90tEdLTE1I5SwhUdE+lllWBi5eUPPmLVYuJlPPrtcyI2uoaY0NDC8qVxUp0sWjxLnnnmGRk3bpw+I5jc8o7elOK3fRHi81myGmKDT7/9Q5KZKCFn4Blq8cWqwHlJIcymM6nFxsZqck52jp1QdymRID7U9lNNO7FhRUG2ZjrGB1YrSFiMHR/GGMFiGRrqs5aufaqb3x8m9LsxRpjU0dHnC1Grps+2I3jSD66CdhpjtCxt48tvM0v0wqxuWKSmTZumEy8yg8uVdE49hBCfzxKdUHUn0i4I5vLlKwSCxcSOpTAysugzEnnU4QsJ4bQw0C/IoO0hPp+6xiE66JhlrTaRkZHaXmOMQExzrTULyyEC0MVYefQDfaXyrYwQG0d6fpDFCexCfD6rt8XR9j3YGmMsoaPv83XpCXrQl8gNj4iQ2rVrCxYuCCx4FWJpy4OjHOcvzbrpnrFj8MsvvzwyBnO0RLYdJ/utRZSxQV2QMtpcr16i+EJ8mocPyBGhRo0aEmr7izZCDBkr1O+z7UGnEN/RMpQjgAH9cN9998mDD/5N5s6dK6vs/GWMEeQYY8hWIaHoCChHFXhghtkB5Qsr3QdnoAkFekPsWL9SQmLayeCuZ8n2DYskI+ewJmNK//btV6yJ8muZNXuWfDJ2pMxdkqpp3sfuDYvljXcnyLbM0KBfRAasQeSp37y/SNZymTFnrRw46COqMGxZsVCmfDFDsq1hKnt3pjXpzpAFy/bIwQMHZNqkj+S9sWPku+++U1M45tT3Jk1VM/iECRNk/AcBc+3uFXPk6y+WScaBQBcx2VBBZvpu+yDKku2710uadeHlZmyV/771smDWxVw/adJEmTNrhdh7UzYunClvvvmmTPjsCyWalA8OGZtnyZRvv5PpM6Zbn/g4xYAbde28OTL6w49lztw5wg0z4b0vrIuyqCUL2eNGv6Tl+QY09qMpsmLjjkKSF1yPO6/eCGTvCTxMaWVJ5IkHJGkQrsjoyELCFeI/+iUruBx5vesDmQe4lBCfT0Kjit5nmvAzP5hQfqaISlMc1xKT5IMP/q/cfvvtajkItcTlpxRk4suwbrkM6w7j3sfFhruspDK5uQcl21rHmJyZ+EJCfBJbI1YtEhutdeuQtXaQDgnBugBhQM4h6+rJP2K95Jp6wJ0JlPp27NwpeXl51vphnx+WGMbFxUlISOC5R/6TCYcOHZK9e/eqvOycHDvZ71ALH6QGq9nEiRPVa9G5c+eg53rRGvKsO8t73hZNCVzRLjYvvummG+Wf//iHPPTQQ3LPPXdLnCWYgRw//QmJiIyMEjBHX/DEjcsaJggIhBnCBSZ80QXLGjVq/rTQU0gFk6ioaIvRdv2yTr1YrbBInqi44v0UcO3lyZ/+9Ce57rrrpGXLFiqKurCIQsQYJxge+IUmx3zr6iUTY4J8sdZShfuTdVlgg9WtQYMGShjJV1LAmMFaOowDyIGAku+wHXeMN2RxJK4iwqmN5lLUtHhHlY5oIwcz0uWHmevkzA6tJKl5skSE5srqtVvEGmvk0N7tMnvbPuneY4iarfu17yAF9psEddMZKSvnysgJX0q7s4ZKlzaNxGcf8qSJGPH+IpKTZPCZzWXtytmyZkvAheilHe9Yv1Vva+K/Ra4e3Fty7cOpVacBcuutt8oVPTrI+pS5sjs7/EcijDHWehUlrc9rL42tabnj2b2kbbM6smXFQvl+S4Jce8vdcustt0hfq++mlB9ky66ATpG1O8tVN/5aLunb7kcy/Yeby8VX3Sw333yznF23lmxdm6q4fbd0uf1m08760i+QAV06yc49y2TZhr0/Ko/sK66+VW4bdrmcFhUhq35YY92vATfFjzJXtQin7wkjkG/HMJmDrVFcQ5ZY1J5jv8kSDuzfL+T12W/HEK5a8bGChSskiHB5MigfHHhORISHBkeVyjlyS0VQJRBSw1oBYq2liYXfn376qbCwGeKTZ8lLSerRdtau+G1/fPzxx7ruiDVNBw8GyG3xMnv2ZMqkjz6SSZMmyfz5C4QJGXflxRdfLBAFFsSTBulibVYNq0ucJU2Qhtn2C22O/aIZFRWlEzvrhBo3biJt27bVn+N/8sknutYrIaGu4IZCt+L1n+g17WaB9URLqjIzM6Rjh45qIcIFtmXLFmnevLk0sC7M4vKYnFkrhMWruBswOG9iYqLKYI3Rx1ZvviCz5irXkrzgfMc6p5/at2+na9loN9izID33YK7gCqRu+o80vkD369dPals33rHknWp8ndq1BZcsa9dox/jx4wXi16tXbzvnhZ6QWEhNcEZcifnWhYn+tGv58uUCycE6ecklQ+Xzz78Q6mLdma4f3J+tblrGIMYHrGiMiaXWtckCfqyzuFnPty5HrFLBdQWf03cQ7KmfTZXJkydraGJdkY2SG1mL624d21geg8uU53mFE62yaWyB7E7bJuvysySmRrhsy8iRenlhSiT2WR4QViNB8AGvXD7HPjDmy37r1z+jTT3hj0Exb958yToQKp06NbPmZ2K9cNSiRUxC23MFgrFm0Xeyal8YUScUaoRHqikzMjJUImMTrck8wg5sn9RqkCQFhzLkwMF9UtKf5VpFoo1ky8aVaySiYyupExMiYXbCQkae/XbIOjOxf1ExkZp29Ivt0TZEJSdIXGSIhFl3QFR8iDARbtm9X78RYjHjFyWLUjYLDwY5xl+NaJGoWjUloVakls8u5mI8RjEXXQ0RgFjRLO/IOe6/nNw8yT9QILmH8jVAtkgj+MN8EukP5VQDZT2y5R01oYw+ik8UZVRNuYiFQFx33TB1/fCqAiw4rN+JtC4tiA8TGASG+71du3bCQmbWMF111ZX6/GERc+PGjYWJvfg9j0Xh+uuH6XNr9eo1liC1kb59++kkyVqayy+/XBdqM5n17t1bzj3nHPs88ssZrVvL4MGDNY1JvIMlPZA7rDfR1mWIJQgrzpIlS62lM15YuwORwWWGHv7wcMWuWdNm9nl8pkRZL0iIz6drn1ikrolHPphs+/Tpo5Y8FqKzFurSSy+V1q1biTFGEhISdV3ToEGDVLcjxQoPcTVryp133ilYR7Kz99tyrQXcfCEhEmrr7N69uy46j7PkEbnNmjWVZcuW66sfWCMVYV1vLVu2FNxX6HnWWV0EvUN8Pgn+44v7gAEDpXPnTvqjBPrqyiuvlDZt20iHDh0sXoOUHIAJGAy1RNZvyTD9Rb/Rf7gPWceFfGSjE+vBwC0hIUGC28i6KXSJtiSXvJyfddZZEmGxZBF8x44d9defzH13/upOwZ0XHR2lGCOLMklJScJ6qdCwMC4LA+OE+Fq1amlcO0uc6cNNm1KUtKEHa+Fo89VXXWXb114x45r1Z0lJDYQfCgwbNkxSUlIEyyfyunXrqmvq6Is77rhDOp15ps5DrBVjzDKOtcIjH9Q/dOhQXWO2cOEiHc933XWXjinG3cGDB1WfI9nL/VBaROuUFS+TB11BtqQsXCa5h6MkddVMJVMb8/YJ5GFTWmBRPDcpgW9YK1askFkz1ktODouqRB8itWqEyH9nLStcgxVo4FGLFtcssmt1ZlO90bhZiAsOuQUBV2V+kN88OJ3zmIhAHs5PJURHxkvI7t1aFGtdTk7Qmi6NLf5RtA3FUxnA3AQtmzS3ZLSdvTE66MLLNk1rFM/qrh0CioDPTgKceMTIOxIXHx8jWK5iakcJViwC+bFwZe3KFhbR78/KKfLmeMgWZb0j52XynLCCGe/2UC3+IRo9e/aUv/zlAeHloldffbVACOrUqSN9+/ZVAmKMUZLBQulu3bopcWptydBvfvMbLcfC9Ousy4cywaAwWZIHmcjnyIRMnjC/X58RuIt+97vf6Xl0TAxJ1mIZI/fee6+6MpkMGzVqGLDeX3GFxMRECwQOaz4yb7rpJrUU8fyhPvSItGSA63bWAgRhQy7XTOa0iXOtyH7wLKe9kD7aT2Ahe4jPp8/oGTOm68QLmbHZf/Qf5vfLFVYvykEGIVYs/A/z+xUz2gwpoU7IAfqhN7iQn3gI15AhQyTKksgBAwYIehNfvLLY2BghH5hRH6SYfBGWrGF5AzNkX3jhhYphmN+vBI5+C/P7td+oH/nIhmCBCbg1sZYcMAUPZNK/YMd8RV7OqZs01mRBUNCDdnjy6CuwgKRRBhlcQ/i49gLjhHjqJy7a9jvy0B33NXqAY6j9Mk8aeb00DzP0pC20OTExQX+FCkEDFwJ4hPn9gk7oTjljis5jtIV2M4aQD2Fu1qwZKgm6US/pGlEBHxVGtAqs1eWQ9aEf/gkScmp4FAiL4BdmZkn/XgMtKz9XfwrKAwhSs21LphzYvk74eetBX7zwDa5BSJTsPvKLEQZ6gxZd5dK+58qmxZ/LohWpctTyftQahG7G2G9JzdtKV8vKWbSbbScM4sVfS3Kzd8q29F1qWcMPrfGl/MGi+eSObWT31qW62J1vk6nLUiWkoL7UT6x9jNqKtqF4Jr4ZNQ+P018Xsjg12j4wWHORWwKBO7B3nf0Wkirb1m+VhTt3SUSDehITmquL7/lFJgQzLS1d84AhC+xZQA8hLF6vu666CETUjFDlPWLkHQvMAptBAAAQAElEQVTyDwukKizoWzAEa/eefQK5OpB31EXlleFIORVoP8Jr+O2nWJd/gbX0Hu9LhGY9qY+yInAnpUQpZjbG6Ld5Jh4vGHM0To78eWlcGmMKyxgTODem6ERmTCDeK8dRgv6MMUVkSNAfeQnGGLUscU4wxmguzr2gEfbDGKPy5MifMabIdfH8cuSPeGOM5vX5fFrfYTvHsGidtaRYUXjGyTH+KE8wxhTKkCN/xBOOXBamE2dM0bYYYzTdmEC8lPBHOS8YczSfMUbLkmbM0XiuCXLkj3NjAunGGC1jjNE2kyZH/owxhWli/0gj2FP959wLxhiNM8YUKWNM0Ws58meMKZJP7J8xRuM8mRzlyB/nXjAmUBdJxeOMMYUyjAnkMyYQZ0zgWor9GWMKyyDPmEA+YwLxxgSupQL+Koxo0dasPQetK+EQp6UWmMRZBM/N1KxNa0m2Plq+fbRt01Q61qkte7dvl8OxDfR8yrgRwkvoVmcfkA7ndZTISJ/68mNjI6Te6R3k4q6tZeHcb+Xoe7UCHRUaWkeSokKFP3+EX1p0PVP6NEuQqJhIonRNWJsYIxPHvCoffTvHmkMDljJNtB8x1p1pD/oP09eTIx9R1o3J6aH8GImpWfI7svjmSh4RIwmW6A3r1VI+n/iWrnXYkJetbcElKPYvLjTKfgb/B9oQXSNg6vVSQiReIiypioipLede2F0Om20yYsSb+pLDfXsLbFq4ZiWPnhz5+Mz6xEd+8KGSu87tmgiT6tJvJsuCJRsl/1CebP9+vixZslgsxLqe7L/TFp/wu7uOVOEOlRwBvp17KhZYcsU5R+ML4VRN9sEEC3ciCeQp6eiVC/GHSVR4wDKC+X/Pjj3CFzQpxb8Q6xYqRXFOVCVEINQSfSxbf/jDH6R3r146GVdCNZ1K1RiBwJOwAhp4KO+wtSLtkOx9R7/VloYaxhhp0X2IXHvttVI//qhErD/tzh8il19+jrBgj3PMkphM77rjOmnXvK7ENWgqN9xwg7RtVldNsy26ny933natNK0Xe0RQgYiJkiv/eI9c3r+tBP6MRNZqIH1vuUfuubmvYBGLqt1A+t/2WzXFY8LEJDqwZ3NrAo6Wax94SM7p0EiL1m7WXvWkPiK4Rifqa92zh2CCZe0VaYFgBB0x7yPDNlX8EeG2vecLJnvK0m7awpqsDudfJ9df3y1QtPCzwFoHRMugL/lY2wUeYBNt+RR13HjjDfrLEeT2H3COMJmCB3nqxATIWkSN5uoGAMPrbuwv6M03CdoOPuiGXMzUNaKlSJ2F6riTSoPAqSqCe4dF7ZT3SBJHiBTWq53puyUrc7/k5xwkixCvJ8U+KEOUlx7pD5WacTFijBHWj+zamWW/tNh7kEylFKqbRauUYKlWYowxur6H536Y31+t2uYaUzUQCKlINTN22AdwRskLv3+OXva+0odzsAxjjMYZYzTaGKPfbCAGxgTiRIwYQxD9M8ZoHin8M/bMHMlj7Hng32bTfMYExxmNQz5BhDQjxhDkyB/nhCOXYrSM2D9jiDf2rPi/EWMIR+ONMVqOeowx4v0ZYzSvdx04BuKMCRyLx3nXIiZIpuifMV4Zo9dY8KiTYEwgjgRjjBhjONWjMT8+10T3US0QwIpZN7lOYVs8ogRx8sgV5wQycSRP8SNpXjzntRvWkrDwwMSYkW5d/vv2yGFM1iSWUnAWrVIC0olxCDgEjolAhRKttG07ZG/GXvsttahr7ZjaVqqEX7IyBVKncWvp1LLBLxkE1/YjCEC0cdWz8J0oCBRHjzRx9K69I3mI50icF7xrZGGBMMbo82Hrpm2yLyPLy1ZqR2fRKjUonSCHgEPgGAhUKNHKPZAr6xZvUrfAMfRz0ZUUgYZtOkn381pVUu2cWuWNAOsG6yTVs+7xyMKqPdLkHQsTjpwQD9k6cqkHrnFDNmiepOslieSllps3bJHcnKMvRiW+NIKzaJUGik5GpUHAKVIpEahQogUi61euEt53wrkLVQUBXIFeqCo6Oz3LEgGsWrXqxkm9RkXJFsSJejl6xMo7El88xNSMloYtk6RGzZqFSWmb0iV19UZhXWdhZCmdOItWKQHpxDgEHALHRKDCida21G2yZuEGdQ8cU0uX4BBwCFR6BCBbderVVqKE6w+FPVIVfCTeC8HxdRJrSZNWyRIXF6dr+8jDIviNKzcIywy4LuVwylu9lLYepSWP7U14GzcvG163bp1w7cnmNTO8BZxXHfDCUC/+VI7IZcsf6lm5cmWRek5FHlveZGZkCFvA8HLJYBm8JgZ9eVUM58Fpxc9J37Bhg257xnYsvBmfOOTS9hkzZmgaR3BAJnUXl3O8a8qgE2/ER05mZqYQd7xyx0pnWzhksS0NhoefI+tYdbj4ikMgpOKqDtTMt9QFX8+R3TsyAhHu0yHgEKiyCEC2eLFgkzOaScPTGqgrETJFgzhi2eI8OMRYK1ZyqyRp1KKhWrKQ4aVv375Dls1bKXkHD3lRpXqsThYtSMXIUaPkmWeelQ8//FCef/55+XTyZF2aASl6/PHH9XUt77zzjjz99DMCQTqVCZ162EblxRdf1HqeeuppGf3226dMtiA7L7/8stz/+9/rK2r27Dk6FyxdulTQ+89//rOwtVBxEhY8GNgRY7Jt75NPPikTJkyQV4e/Km+88Ya+ZZ1tXKZMmSps60IYO3asvPDCC7Jq1cpgESd0DnHjJdcvvviSvh5o5MiR8sgjj0h6+vYTKl88E+9gfOLJ/+i+tK+//rq89tprkpq6uXg2d12FEahwogV2mzdulVlf/vh9U6S5UIkQcKo4BE4AAWOM8MoH3gLe6szTpWXbFlK/YaJg5YJUsQarVp0aGnf6mS2EPElJSVrGGFzSgUqwZq2cs0I2rd1Y6r82DNQg1cqitWrVKt3f8A9/+L38/e9/16105s6dJ7zImL3neAv4ww8/LH/961+t1bCmsLccpMHDwjtiXZk4caKwF11J6WyLsnDhQhk8eLAg7/rrr7MkaLKkb98up/KXmpqixXjjd3Z2juTlHSXVbKWTmJgoTZo01a3BfooYbt26TaZOnarb+Pzzn/8UtmCBTEKKeI/WX//ygPzzH//QwJY38fHxwpY5xhit3/uAsGHxYj++7OxsL7rwyLjEkscrb3i1DRikpaUJ+zkWZjrBE9ozY8Z02bBhvTz00ENy//33S0ZGpixatPCUiesJVu2ylSMCIeVY1zGr4ifbsz6fKeuWr/9Z5tdjVuASHAIOgXJHwBijC9rrWndi01ZNpHXnNtK+azsb2us5cUz+LKQ3puhkxwSUsiZVZnwxp8xIFoBUJ4tWw4YN5be//a1whCyw0J8tU3y+UBk4cKBcc821grWQl78SXxLuYGL9tvri4dDQwEuZNS7oA+JzzTXXSOfOnfV5jcywMP+PSCuutf/85z/yv//7vxoeeujvagGDyAWJE/bd+9WvfqV7CyIrOI1tb4YNGyaNGycHR5d4Hh0dJeRlzz/eZ4hltWbNOKGPkRvm90uY3y/sE4i7jw2c2Z6lJGG0HXxKSvOHhQn7DF5yySVSs0YNlR8eHqHYBuennWPGjLEE6u/afnB49dVX1T3q5UM3yGCLFi11ixn6rmnTJtailSpswu3lc8djI1AVUkIqi5L79+2XT0dP0W9fPGQri15OD4eAQ6D0EDDGMI8fV+D2rTvky3FfyZ4dgX08j1vgFDNARk6xaKUrxuswOnbsaC0rs+Wll16SSZM+ko4dO0j9eolyxhlnCETkbevie/bZZ2Xjxo26NVlw+1l3hatu9erVwh6EsbGxsnjxYsGCFWzZqlmzpmB9Yg0Ybq4XXnhRzj9/sCQkJBTBJCoyUthPFiJF6Ny5k+5lGGqJSpGMpXQBaWdfPfSjLax3Cg31yWmnnWbHnCmsBWKDK5W9Eo05Gs+8Q9uXLFkifkvIGjdubF2Lq4S8wS7LML9f2wERGzd+vCVSDwk7emA1K6zEntDO5s2bW0LaSckkGLBnYHR0tE0N/IM/ZC81NVXnPtyPO3fulNzcXCWxgVzus6ojEFKZGoCL4Iv3vxHeJM2gr0y6OV0cAg6B8kFgR9oumfrBF7J68eoyrxCLQplXUs4V1KldR11ijRo1UstIRmamahARHi7NmjVTkoTFBgIR3P7snBxhvRHrhILDjBkz5HB+vsoI/oiLi1PCAYnDxcci7uB0y24EMgKx8ALXIUHkpkj+UrqAZM2cNUu8vQ2xwHmiIUwTJkyUVq1aSbLFx4vnCJnEZRrcds5xR+7du5csRQLu8eTkZEukOsu+ffuUkAVnoJ2REZGW4EYXBsqEhPgKsxljpFev3lKjRqyMGDFSxo8fJxBBMhhjOLhQDRCoVEQLF+KSuYvlu49mOrJVDQaXa4JD4GQQ4MsVJOvrid8IzwGeBydT/lTyhlSjvQ7T0tKFtVNt2raRSy+9VPr27aPWqPT0dOEXeJmWLAwYMEC3/YIcYfHBxejhFhMTI3/4wx/lgQce0PVNbB3Geq7BgwcL1hkvH79eZN0TVq+LLrrIuuuulRUrVsq2rdu8LHpkLRMWMurxwoYNGyT30NE1WJqxFD9oz6zZs3UxPFt/dTrzzCIuPcglv8rs16+fuhGDq/b5fHLLLbdo+2k7a7zAAnck67m8vBA55Ozfny09evSQG66/XurUqaOWRMawl492rl23Vry2cwyU2+9l0WNiYoJ1+d5nrV5dlCAnJTUUrFxY1TSD+6jyCFQqogWa/Lpo3vQ5wsMW90HwwCXdBYdAeSLg6iofBLjPud+57+d9O094mXF51Bxs0SmP+sqyjm3btuqv4DZatyCup4yMDEsyQgXr1fQZ0+Xjjz8WXv6alZUluKcgVlhdPJ0gGvWsmxGX4ffffy+4BhMTEwVXnDFHrSu7d+9WWZA6yFRaWpqKiI456hIjAovXFVdcITfeeGNh6Nmzl7B+ivSfE7CeYfmBWHlysEjNnz9ff1kIOezWrZsmEc/44sivEtu3b6eWOE0M+jDGCO7XROsCxZU3d+5c2/Y4wSUJhl5WCBRrvKZMmay/aNxrrVngyZowY47iRDv79+9f2HZwuGDIEEvKanui9GiMkaSkBuK5HvPz86RFixa6Tk4zuI8qj0ClI1p8i2W9Fg/bca+Nl5SUFPeOrSo/zFwDHALHRiDfuqU2rtok3O/c9+VFstCoOlm0WA/EGqC//e1BufXW2/SXgD179hDWGvXs2VPWr18vt99+h1pPsrNzBItPsKUKPAisrerdu491iXX50QJ30uvVq6+Wl1GjRlkL0K0yfPhwSyZu+JErDuIGSYG8eCE2NsaSPx9iflbAKjVixAjBFegJggCOHj1avvtuhuDyu+222+X2O+4Q9MzK2q/tx8U5dOhQdWl65YofQ3w+6dixo/TvP0AiIyOKJytRbNumrWzalKJY3nPPvdKkSVMZOHBQkby0v0aNGkrevPbXjItT4lsko73gV4x33vlrmTZtmgwalo5PLwAABhNJREFUNEjX1FHeJrn/aoBASOm2ofSkYdlijcaof4+WOd/Mdz91LT1onSSHQKVBIDs7W2Z/OVfefek9XZNVniQLEKqTRYtJ/aabbpInnnhc/v3vR+Whhx6Sfn37WrIQqb/o+4t1CT722GNC+J//+Z00adJEjDlqgQEPQpjfL8nJjQTrljE/To+xlqsLL7xQ/vWvR7Sexx57XIZefPGPXHHIOtEAqejbp4/85jd32XrrFSnGui5+4UfbIiIi9Iv3okWLJC4uTvgFoJcZ996DD/6vvPfeGOHXjmDwj3/8UyBWLFbnF33oyuJ4r0xJR3SBGIFBsCXLy0s67tn/96c/Kpbgeb/FM9G6AL08J3vs2KGDyvrzn/8skOLIyMiTFeHyV2IEKi3RwrJF2Jm2S8a9+oGM+s/bsnrJGuHBzDfgSoypU80h4BD4CQS4f3E5cT+PefY9mTByoqSlpgv3+08UK5Ok6mTRAiCICIQCKxZkIczvJ1qtSFhTIA8E3IEQBk08yQ9jjFp1IGLUwzHMH6jnJEUVZjfGSHRMzI/cdGQwxggkEiKFzrgB+YUjxCvYIgcpQpemTZuqFQ/daGvt2rW1/ZAX0smH3J8T0CMYT3Q35sek9ETroDy60sbS0O9E63X5ygeBSku0gpvP2+MXz10iI54YJWNfnSBL5y2T9C3bhfeU8NDmxgvO784dAg6ByoMA9yf3Kffr1q1bZdF3S+X9l8fp/cx9Xd5WrGBkqpNFK7hd1fkcIsLaLxbjG3Pq5KY6Y+TaVrkQqBJEy4OMtVsLps2X0c++I3wT/uTtqep2WPn9ctmwcqOkpKTqy+AgYS5sVzLqcHA4nOQYKJVxA6HifuS+5P7EPcj9+v4zH8qYV8cI9zH3s3dvl9URi5UxRSdjXljp1Ue6d+6ODgGHgEOgLBCoUkTLA4BvwBvWbJAZn82Q91/5QN569l0ZN/xDGffCBJk4/CNhUa0L4x0OrzkMKuo+0PvQ3o/cl9yfY18dq/cr9y33r3cvV/TRWbQqugdc/Q6B6o9AlSRaxbuFb8YpG7YID/GVi1ZJuQZXn8PbjYESxwD3I/cl92dFrL8q/pwo6dpZtEpCxcU5BBwCpYlAtSBapQmIk+UQcAg4BBwCDoGqjIDTvXIh4IhW5eoPp41DwCHgEHAIOAQcAtUIAUe0qlFnuqY4BBwCx0Yg+C3oRXO5K4eAQ8AhUHYIOKJVdtg6yQ4Bh0AlQMCYor86rAQqORUcAg6BXxACjmj9gjq7tJrq5DgEqhoCxjiyVdX6zOnrEKguCDiiVV160rXDIeAQKBEBYxzJKhEYF+kQqD4IVOqWlBnRKigQOb1Tc7n611e54DBwY8CNgXIdA9fedZ1cfuMlktSggYSFhQlvEw/x+STE59P9/XitA4GnszFG44wxXFaKgM61a8WL/2dubVMpGuOUcAj8ghAwxgj7c0ZGRIgXQsqq/bYuYYuE7oPOERccBm4MuDFQnmOgz4U9pFu3blIzLk73uWNvuuBgjKl05Cr4WQwxZP87jsHxpXbuBDkEHAJlhgD3bZjfL2H+QCgzolVmLXCCHQIOAYeAQ8Ah4BBwCFQRBBzRqiId5dSsUARc5Q4Bh4BDwCHgEDglBBzROiXYXCGHgEPAIeAQcAg4BBwCx0egbIjW8et1ORwCDgGHgEPAIeAQcAhUewQc0ar2Xewa6BBwCDgEHAIOAYdARSHgiFZFIe/qdQg4BBwCDgGHgEOg2iPgiFa172LXQIfAqSDgyjgEHAIOAYdAaSDgiFZpoOhkOAQcAg4Bh4BDwCHgECgBAUe0SgDlVKJcGYeAQ8Ah4BBwCDgEHALFEXBEqzgi7toh4BBwCDgEHAJVHwHXgkqCgCNalaQjnBoOAYeAQ8Ah4BBwCFQ/BBzRqn596lrkEHAInAoCroxDwCHgECgDBBzRKgNQnUiHgEPAIeAQcAg4BBwCIOCIFii4cCoIuDIOAYeAQ8Ah4BBwCBwHAUe0jgOQS3YIOAQcAg4Bh4BDoCogUDl1dESrcvaL08oh4BBwCDgEHAIOgWqAgCNa1aATXRMcAg4Bh8CpIODKOAQcAmWPwP8HAAD//2w2eEUAAAAGSURBVAMAgAioSTz2QzgAAAAASUVORK5CYII=\">Here Numi, the AI tutor, encourages a student to pick a step to review in more detail. The original problem was 8 \u003csup>1\u003c/sup>/\u003csub>4\u003c/sub> ÷ 3 \u003csup>3\u003c/sup>/\u003csub>4\u003c/sub>.\u003cbr>\u003cem>Source: Appendix of Oreopoulos et al., “Making AI Tutoring Productive: Evidence from a Mastery-Based Math Practice Experiment.”\u003c/em>\u003c/p>\n\n\n\n\u003cp>The AI tutor, by contrast, could respond directly to a student’s work and guide the student through the mistake.\u003c/p>\n\n\n\n\u003cp>The students who used AI combined with mastery learning spent more time per question than students in any of the other groups — a sign that they were engaging more with the material. These students were also more likely to get the next question right after making a mistake. \u003c/p>\n\n\n\n\u003cp>That’s important because requiring students to answer three questions correctly in a row is common in educational software. But hitting a short mastery threshold doesn’t necessarily mean a student has developed a deep understanding. Students can guess their way to three correct answers or succeed from repeated exposure without really learning the skill.\u003c/p>\n\n\n\n\u003cp>There was a limit to the benefits for students in this study. Students in the AI-plus-mastery group performed better primarily on the easiest fraction questions — the ones most similar to what they had practiced. The advantage did not extend to more challenging problems.\u003c/p>\n\n\n\n\u003cp>In this study, AI didn’t produce a deeper or more transferable understanding of fractions. Then again, it was only a 50-minute intervention and it’s unknown how this combination of AI plus mastery learning might improve student learning over the course of many months. \u003c/p>\n\n\n\n\u003cp>Oreopoulos cautions against concluding that mastery learning is the best way to use AI in learning math. The researchers tested only the four combinations in their study; there could be better ways to enhance computer-assisted learning and make practice work more effective. His larger ambition is to keep testing different features against one another, continually improving the software.\u003c/p>\n\n\n\n\u003cp>For now, he said, the goal was more modest: to show that AI “has a little bit of benefit, and talk about its potential.”\u003c/p>\n\n\n\n\u003cp>Part of that potential may lie not in helping kids learn math faster, but in helping them slow down.\u003c/p>\n\n\n\n\u003cp>\u003cem>Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story with The Hechinger Report’s Jill Barshay.\u003c/em>\u003c/p>\n\n\n\n\u003cp>\u003c/p>\n\u003cp>\u003cem>This story about AI and \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-mastery-learning/\">\u003cem>mastery learning\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"slug": "adults-have-struggled-to-set-rules-for-ai-in-school-these-teens-figured-it-out",
"title": "Adults Have Struggled to Set Rules for AI In School. These Teens Figured It Out",
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"headTitle": "Adults Have Struggled to Set Rules for AI In School. These Teens Figured It Out | KQED",
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"content": "\u003cp>BOSTON — Over the course of one frantic, late-July weekend, 98 teens representing all 50 states put their busy lives on hold to try to do something remarkable.\u003c/p>\n\u003cp>The students, most of them high school juniors and seniors, gathered in a precise replica of the U.S. Senate chamber and attempted what the real, adult Congress has largely failed to do: draft and pass “legislation” to help the nation’s K-12 schools navigate \u003ca href=\"https://www.npr.org/2026/01/14/nx-s1-5674741/ai-schools-education\" target=\"_blank\" rel=\"noopener\">the questions and chaos\u003c/a> created by artificial intelligence.\u003c/p>\n\u003cp>Should students be allowed to use AI on assignments? What about on tests? Is it schools’ job to teach the nation’s children what AI is and how to use it? There is \u003ca href=\"https://www.npr.org/2026/06/05/nx-s1-5779757/school-ai-education-students-teachers-poll-critical-thinking\" target=\"_blank\" rel=\"noopener\">no national policy for AI use in schools\u003c/a>, meaning states and school districts have had to scramble to craft their own.\u003c/p>\n\u003cp>“This is a once-in-a-lifetime opportunity for us to actually help and try to change the country for the better,” said student Gabriel Sutphin, representing South Carolina, speaking from the chamber floor at the Edward M. Kennedy Institute for the United States Senate.\u003c/p>\n\u003cp>To these teens, the stakes for getting ahead of AI are clear. They pointed out how adult leaders were slow to protect students from the risks of other tech developments.\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>“We missed the mark with social media and phones,” said Hunter Wurzel, a high school senior representing Ohio. “That’s been a huge talking point already [this weekend], is how we failed to implement those things into education and teach the youth how to use them.\u003cem>“\u003c/em>\u003c/p>\n\u003cp>Wurzel and his 97 colleagues were handpicked by their school leaders and hosted by a handful of education- and tech-focused groups, including the Edward M. Kennedy Institute, AASA (The School Superintendents Association), and Day of AI, a nonprofit launched out of MIT’s RAISE AI literacy initiative.\u003c/p>\n\u003cp>At times during the weekend, where NPR was able to watch the events unfold, the bill seemed doomed, only to be revived by a flurry of student-led negotiation, old-fashioned compromises and some spirited speeches.\u003c/p>\n\u003cp>“[This bill] is about who gets a seat at the table. Today, students have that seat,” Bena Mejia Romero of Connecticut told her fellow senators before the final vote.\u003c/p>\n\u003cp>Ultimately, their Students First Act passed overwhelmingly, 82-16.\u003c/p>\n\u003cp>Among the bill’s requirements: States should provide AI literacy as soon as students get access to classroom devices; AI use should be banned on all graded tests; and teachers can require an oral defense of any project from a \u003ca href=\"https://www.npr.org/2025/12/16/nx-s1-5492397/ai-schools-teachers-students?unified=true&renderPlatform=nprone_ios\" target=\"_blank\" rel=\"noopener\">student suspected of using AI inappropriately\u003c/a>. (You can read the full bill \u003ca href=\"https://www.npr.org/2026/07/30/nx-s1-5853571/students-set-ai-policy#bill\">at the end of this article\u003c/a>.)\u003c/p>\n\u003cp>“The adults themselves haven’t been able to come to consensus on this, right? And so now it falls to the kids. Let them lead the way,” said Jeffrey Riley, the executive director of Day of AI and former education commissioner of Massachusetts.\u003c/p>\n\u003cfigure class=\"wp-block-embed npr-promo-card insettwocolumn\">\n\u003cdiv class=\"wp-block-embed__wrapper\">\u003c/div>\n\u003c/figure>\n\u003cp>While the Students First Act isn’t actually law, any more than the teens are actually senators, AASA plans to send the text to its members: 10,000 school leaders across the country, many of whom are right now crafting their own AI rules in the absence of regulation.\u003c/p>\n\u003ch2>\u003cstrong>Rules for students\u003c/strong>\u003c/h2>\n\u003cp>When students arrived at the start of the weekend, they were presented with a stew of policies that they had suggested in the run-up to the event. Then they were divided into subcommittees — focused on students, educators, administrators and families — to debate the dozens of proposals and create a coherent bill they could all support.\u003c/p>\n\u003cp>The student-focused section of the final bill includes 15 provisions, several focused on a concern many of the senators shared: that teens are using AI to do their thinking for them.\u003c/p>\n\u003cp>Without guidance and guardrails, “[AI use] is just gonna go unhinged,” said Campbell McHenry, a high school junior from Mississippi. “Everyone’s gonna stop learning and start relying on AI. Instead of using it as a tool, they’re gonna use it as a brain.”\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/7008x4672+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F31%2Fbe%2F614f0b1b4243a1938739d8d2e2cb%2Fkesner-npr-studentai-005.JPG\" alt=\"Student senators representing (from left to right) Colorado, Arkansas, North Carolina, New Mexico and Connecticut meet in their assigned subcommittee to debate the AI bill's student-focused provisions.\">\u003cfigcaption>Student senators representing (from left to right) Colorado, Arkansas, North Carolina, New Mexico and Connecticut meet in their assigned subcommittee to debate the AI bill’s student-focused provisions. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>Among the bill’s student-focused proposals:\u003c/p>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Approved uses\u003c/strong>: Students should not be allowed to use AI for writing, “though editing, brainstorming and studying” with AI should be allowed after eighth grade.\u003c/li>\n\u003c/ul>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Prove mastery\u003c/strong>: Students permitted to use AI should have to cite how they used it and demonstrate their grasp of a subject through discussions, handwritten tests or oral defenses.\u003c/li>\n\u003c/ul>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Plagiarism review\u003c/strong>: Any student suspected of using AI inappropriately should have their work reviewed not just by AI checker software, \u003ca href=\"https://www.npr.org/2025/12/16/nx-s1-5492397/ai-schools-teachers-students?renderPlatform=nprone_ios&unified=true\" target=\"_blank\" rel=\"noopener\">which can be unreliable\u003c/a>, but also two school officials.\u003c/li>\n\u003c/ul>\n\u003cp>One of the most contentious issues was deciding when students should first be exposed to AI in the classroom: High school? Middle school? Earlier?\u003c/p>\n\u003cp>Lucia Herrera, a Missouri high schooler, took issue with an early draft of the bill.\u003c/p>\n\u003cp>“There’s nothing that says students need to be proficient before using it,” Herrera told her subcommittee colleagues. “It’s basically saying they can use it whenever. Which I think is a misuse of it.\u003cem>“\u003c/em>\u003c/p>\n\u003cp>Her subcommittee’s proposed solution: require schools to teach AI literacy as soon as devices are introduced in the classroom, including misinformation, plagiarism, bias in AI design, student privacy, appropriate academic use and AI’s environmental impact.\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/3738x4672+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F63%2F01%2Fa6777694447680086165b146e2f9%2Fkesner-npr-studentai-017.jpg\" alt=\"Sophia Fenn of Washington state took the work seriously, going line by line through the proposals and making detailed notes about what she would like to amend or strike altogether.\">\u003cfigcaption>Sophia Fenn of Washington state took the work seriously, going line by line through the proposals and making detailed notes about what she would like to amend or strike altogether. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>When the provision came up later that day, before the full Senate, Connecticut’s Bena Mejia Romero told her fellow student lawmakers they should support the new requirement. \u003cstrong>“\u003c/strong>If we’re going to be using devices, we should know the dangers and the benefits that they have.”\u003c/p>\n\u003cp>But one of the senators from California, Om Lala, argued that requiring schools to begin teaching AI literacy would be a heavy lift. “Teachers already are pretty under-resourced.”\u003c/p>\n\u003cp>Tristan Tjetjep of Tennessee added that he worried how “underprivileged schools” would pay for this new instruction.\u003c/p>\n\u003cp>Suddenly, the students had run headlong into \u003ca href=\"https://www.npr.org/series/473636949/schoolmoney\" target=\"_blank\" rel=\"noopener\">U.S. schools’ funding inequities\u003c/a> — a problem they attempted to resolve with a requirement that the federal government chip in funding.\u003c/p>\n\u003ch3>\u003cstrong>Rules for educators, parents and caregivers\u003c/strong>\u003c/h3>\n\u003cp>The Students First Act not only covers students’ use of AI but also insists on \u003ca href=\"https://www.npr.org/2025/12/16/nx-s1-5492397/ai-schools-teachers-students\" target=\"_blank\" rel=\"noopener\">rules for educators\u003c/a>:\u003c/p>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Approved teacher use of AI\u003c/strong>: Allowed for tasks including lesson planning, making practice materials, providing feedback and improving instruction.\u003c/li>\n\u003c/ul>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Must have a clear AI policy\u003c/strong>: Each semester, teachers need to post “a clear, written AI usage policy,” explaining when AI is allowed and when it’s not.\u003c/li>\n\u003c/ul>\n\u003cp>What’s more, if an AI detector flags potential inappropriate AI use in a student paper, the bill says “teachers must personally investigate the issue before reporting the student to admin.”\u003c/p>\n\u003cp>The student senators struggled with the 10 provisions in the bill’s parents/guardians section because, as Isabella Stringer of New Hampshire said on the Senate floor, “We cannot legislate parenthood. Schools cannot tell parents what or how to teach your children.\u003cem>“\u003c/em>\u003c/p>\n\u003cp>As such, some of the provisions here suggest rather than tell. For instance, one says simply that parents should encourage balanced technology habits and emphasize the importance of ethical academic behavior at home.\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/7008x4672+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F74%2Fdb%2F0e9f08d84ec387cfe9c1ddfa383e%2Fkesner-npr-studentai-040.JPG\" alt=\"The Edward M. Kennedy Institute for the United States Senate sits on the University of Massachusetts, Boston campus and is home to the world's only full-scale replica of the U.S. Senate chamber.\">\u003cfigcaption>The Edward M. Kennedy Institute for the United States Senate sits on the University of Massachusetts, Boston campus and is home to the world’s only full-scale replica of the U.S. Senate chamber. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>The early version of the bill also gave parents a full veto over their students’ AI access, but many of the senators argued that AI is here to stay and students must be taught how to use it.\u003c/p>\n\u003cp>“Giving [parents] the complete say, especially in middle to high school, in what their child can and can’t do with AI is gonna limit [students] because a lot of [adults] don’t even know what AI is themselves,” said junior Tatiyana Reaves of North Carolina.\u003c/p>\n\u003cp>In one of the weekend’s more passionate exchanges, senators debated what should happen if a student attempts to use a school-based AI tool, like a chatbot, “for emotional support.”\u003c/p>\n\u003cp>Several teens worried that if a student confided sensitive information about, say, \u003ca href=\"https://www.npr.org/2025/10/08/nx-s1-5561981/ai-students-schools-teachers\" target=\"_blank\" rel=\"noopener\">their sexuality\u003c/a> or a mental health crisis, they should be able to trust that it would be kept private.\u003c/p>\n\u003cp>But Dylan Dornack of Iowa argued on the Senate floor that, for students in crisis or experiencing suicidal thoughts, the technology must alert a \u003cem>human\u003c/em>.\u003c/p>\n\u003cp>“This could be lifesaving,” Dornack told his colleagues, “whether or not that student is fearful that they might get outed. This is just one of those things that has to be taken to trusted adults.”\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/6439x4293+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F25%2Fd4%2F0578ac934294b32e55308a0b3d41%2Fkesner-npr-studentai-056.jpg\" alt=\"Wehiwaalani Gapero of Hawaii was one of dozens of students who chose to address their colleagues for a minute each before the final votes of the weekend were cast.\">\u003cfigcaption>Wehiwaalani Gapero of Hawaii was one of dozens of students who chose to address their colleagues for a minute each before the final votes of the weekend were cast. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>Ultimately, the students agreed: When a school chatbot detects a student in need of emotional support, it should not fulfill the student’s request but instead alert school officials.\u003c/p>\n\u003ch3>\u003cstrong>The rush to passage\u003c/strong>\u003c/h3>\n\u003cp>At the end of the whirlwind weekend, the student senators gathered in the replica chamber and more than half volunteered to address their colleagues for one minute each.\u003c/p>\n\u003cp>Dornack was the first to speak and called the bill an important, if imperfect, foundation for schools’ AI policies. “You have to lay the blocks before you can have the building. So here I say, let’s lay the blocks and let’s pass this\u003cem>.”\u003c/em>\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/7008x4672+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F5f%2Fc8%2Fca171e364dbab8cdf737b2e58d3a%2Fkesner-npr-studentai-027.JPG\" alt=\"In the final minutes before a key vote, student senators from (left to right) Minnesota and Washington state confer with their colleague.\">\u003cfigcaption>In the final minutes before a key vote, student senators from (left to right) Minnesota and Washington state confer with their colleague. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>But Jadelynn Petitjean of Alabama called the bill an “unstable foundation” and opposed it.\u003c/p>\n\u003cp>Earlier in the day, West Virginia’s Ethan Liu had also opposed it, highlighting several contradictions in the bill, including amendments that both restricted students’ AI access while appearing to give teachers wide discretion over when and how AI is used.\u003c/p>\n\u003cp>“I thought it reflected really badly on us. I had a whole different speech planned out against this bill, actually. It was really good,” Liu told the Senate chamber before the final vote.\u003c/p>\n\u003cp>But at the last minute, the event’s organizers allowed the students to iron out a few of the bill’s inconsistencies, and, as a result, Liu changed his vote, saying “this bill is in much better shape.”\u003c/p>\n\u003cp>Student after student walked to the microphone at the front of the chamber, and most endorsed the bill, including Kendall Terao-Toma of Hawaii:\u003c/p>\n\u003cp>\u003cem>“\u003c/em>This is for our future — not just for education but for the workforce we will join, the economy that we will build and the communities we will lead.”\u003c/p>\n\u003cp>\u003cem>Edited by: \u003c/em>\u003ca href=\"https://www.npr.org/people/g-s1-123933/nirvi-shah\" target=\"_blank\" rel=\"noopener\">\u003cem>Nirvi Shah\u003c/em>\u003c/a>\u003cem> and \u003c/em>\u003ca href=\"https://www.npr.org/people/348780034/nicole-cohen\" target=\"_blank\" rel=\"noopener\">\u003cem>Nicole Cohen\u003c/em>\u003c/a>\u003cem>; audio story produced by: \u003c/em>\u003ca href=\"https://www.npr.org/people/348774853/lauren-migaki\" target=\"_blank\" rel=\"noopener\">\u003cem>Lauren Migaki\u003c/em>\u003c/a>\u003cbr>\n\u003cem>Visual design and development by: \u003c/em>\u003ca href=\"https://www.npr.org/people/348775569/la-johnson\" target=\"_blank\" rel=\"noopener\">\u003cem>LA Johnson\u003c/em>\u003c/a>\u003c/p>\n\u003ch3 id=\"bill\">Read the full text of the Students First Act:\u003c/h3>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003ciframe loading=\"lazy\" style=\"border: 1px solid #d8dee2; border-radius: 0.5rem; width: 100%; height: 100%; aspect-ratio: 612 / 792;\" src=\"https://embed.documentcloud.org/documents/28508881-17-s2026-the-students-first-act-final-bill-passed-84-14/?embed=1&title=1\" width=\"612\" height=\"792\">\u003c/iframe>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>BOSTON — Over the course of one frantic, late-July weekend, 98 teens representing all 50 states put their busy lives on hold to try to do something remarkable.\u003c/p>\n\u003cp>The students, most of them high school juniors and seniors, gathered in a precise replica of the U.S. Senate chamber and attempted what the real, adult Congress has largely failed to do: draft and pass “legislation” to help the nation’s K-12 schools navigate \u003ca href=\"https://www.npr.org/2026/01/14/nx-s1-5674741/ai-schools-education\" target=\"_blank\" rel=\"noopener\">the questions and chaos\u003c/a> created by artificial intelligence.\u003c/p>\n\u003cp>Should students be allowed to use AI on assignments? What about on tests? Is it schools’ job to teach the nation’s children what AI is and how to use it? There is \u003ca href=\"https://www.npr.org/2026/06/05/nx-s1-5779757/school-ai-education-students-teachers-poll-critical-thinking\" target=\"_blank\" rel=\"noopener\">no national policy for AI use in schools\u003c/a>, meaning states and school districts have had to scramble to craft their own.\u003c/p>\n\u003cp>“This is a once-in-a-lifetime opportunity for us to actually help and try to change the country for the better,” said student Gabriel Sutphin, representing South Carolina, speaking from the chamber floor at the Edward M. Kennedy Institute for the United States Senate.\u003c/p>\n\u003cp>To these teens, the stakes for getting ahead of AI are clear. They pointed out how adult leaders were slow to protect students from the risks of other tech developments.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>“We missed the mark with social media and phones,” said Hunter Wurzel, a high school senior representing Ohio. “That’s been a huge talking point already [this weekend], is how we failed to implement those things into education and teach the youth how to use them.\u003cem>“\u003c/em>\u003c/p>\n\u003cp>Wurzel and his 97 colleagues were handpicked by their school leaders and hosted by a handful of education- and tech-focused groups, including the Edward M. Kennedy Institute, AASA (The School Superintendents Association), and Day of AI, a nonprofit launched out of MIT’s RAISE AI literacy initiative.\u003c/p>\n\u003cp>At times during the weekend, where NPR was able to watch the events unfold, the bill seemed doomed, only to be revived by a flurry of student-led negotiation, old-fashioned compromises and some spirited speeches.\u003c/p>\n\u003cp>“[This bill] is about who gets a seat at the table. Today, students have that seat,” Bena Mejia Romero of Connecticut told her fellow senators before the final vote.\u003c/p>\n\u003cp>Ultimately, their Students First Act passed overwhelmingly, 82-16.\u003c/p>\n\u003cp>Among the bill’s requirements: States should provide AI literacy as soon as students get access to classroom devices; AI use should be banned on all graded tests; and teachers can require an oral defense of any project from a \u003ca href=\"https://www.npr.org/2025/12/16/nx-s1-5492397/ai-schools-teachers-students?unified=true&renderPlatform=nprone_ios\" target=\"_blank\" rel=\"noopener\">student suspected of using AI inappropriately\u003c/a>. (You can read the full bill \u003ca href=\"https://www.npr.org/2026/07/30/nx-s1-5853571/students-set-ai-policy#bill\">at the end of this article\u003c/a>.)\u003c/p>\n\u003cp>“The adults themselves haven’t been able to come to consensus on this, right? And so now it falls to the kids. Let them lead the way,” said Jeffrey Riley, the executive director of Day of AI and former education commissioner of Massachusetts.\u003c/p>\n\u003cfigure class=\"wp-block-embed npr-promo-card insettwocolumn\">\n\u003cdiv class=\"wp-block-embed__wrapper\">\u003c/div>\n\u003c/figure>\n\u003cp>While the Students First Act isn’t actually law, any more than the teens are actually senators, AASA plans to send the text to its members: 10,000 school leaders across the country, many of whom are right now crafting their own AI rules in the absence of regulation.\u003c/p>\n\u003ch2>\u003cstrong>Rules for students\u003c/strong>\u003c/h2>\n\u003cp>When students arrived at the start of the weekend, they were presented with a stew of policies that they had suggested in the run-up to the event. Then they were divided into subcommittees — focused on students, educators, administrators and families — to debate the dozens of proposals and create a coherent bill they could all support.\u003c/p>\n\u003cp>The student-focused section of the final bill includes 15 provisions, several focused on a concern many of the senators shared: that teens are using AI to do their thinking for them.\u003c/p>\n\u003cp>Without guidance and guardrails, “[AI use] is just gonna go unhinged,” said Campbell McHenry, a high school junior from Mississippi. “Everyone’s gonna stop learning and start relying on AI. Instead of using it as a tool, they’re gonna use it as a brain.”\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/7008x4672+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F31%2Fbe%2F614f0b1b4243a1938739d8d2e2cb%2Fkesner-npr-studentai-005.JPG\" alt=\"Student senators representing (from left to right) Colorado, Arkansas, North Carolina, New Mexico and Connecticut meet in their assigned subcommittee to debate the AI bill's student-focused provisions.\">\u003cfigcaption>Student senators representing (from left to right) Colorado, Arkansas, North Carolina, New Mexico and Connecticut meet in their assigned subcommittee to debate the AI bill’s student-focused provisions. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>Among the bill’s student-focused proposals:\u003c/p>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Approved uses\u003c/strong>: Students should not be allowed to use AI for writing, “though editing, brainstorming and studying” with AI should be allowed after eighth grade.\u003c/li>\n\u003c/ul>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Prove mastery\u003c/strong>: Students permitted to use AI should have to cite how they used it and demonstrate their grasp of a subject through discussions, handwritten tests or oral defenses.\u003c/li>\n\u003c/ul>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Plagiarism review\u003c/strong>: Any student suspected of using AI inappropriately should have their work reviewed not just by AI checker software, \u003ca href=\"https://www.npr.org/2025/12/16/nx-s1-5492397/ai-schools-teachers-students?renderPlatform=nprone_ios&unified=true\" target=\"_blank\" rel=\"noopener\">which can be unreliable\u003c/a>, but also two school officials.\u003c/li>\n\u003c/ul>\n\u003cp>One of the most contentious issues was deciding when students should first be exposed to AI in the classroom: High school? Middle school? Earlier?\u003c/p>\n\u003cp>Lucia Herrera, a Missouri high schooler, took issue with an early draft of the bill.\u003c/p>\n\u003cp>“There’s nothing that says students need to be proficient before using it,” Herrera told her subcommittee colleagues. “It’s basically saying they can use it whenever. Which I think is a misuse of it.\u003cem>“\u003c/em>\u003c/p>\n\u003cp>Her subcommittee’s proposed solution: require schools to teach AI literacy as soon as devices are introduced in the classroom, including misinformation, plagiarism, bias in AI design, student privacy, appropriate academic use and AI’s environmental impact.\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/3738x4672+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F63%2F01%2Fa6777694447680086165b146e2f9%2Fkesner-npr-studentai-017.jpg\" alt=\"Sophia Fenn of Washington state took the work seriously, going line by line through the proposals and making detailed notes about what she would like to amend or strike altogether.\">\u003cfigcaption>Sophia Fenn of Washington state took the work seriously, going line by line through the proposals and making detailed notes about what she would like to amend or strike altogether. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>When the provision came up later that day, before the full Senate, Connecticut’s Bena Mejia Romero told her fellow student lawmakers they should support the new requirement. \u003cstrong>“\u003c/strong>If we’re going to be using devices, we should know the dangers and the benefits that they have.”\u003c/p>\n\u003cp>But one of the senators from California, Om Lala, argued that requiring schools to begin teaching AI literacy would be a heavy lift. “Teachers already are pretty under-resourced.”\u003c/p>\n\u003cp>Tristan Tjetjep of Tennessee added that he worried how “underprivileged schools” would pay for this new instruction.\u003c/p>\n\u003cp>Suddenly, the students had run headlong into \u003ca href=\"https://www.npr.org/series/473636949/schoolmoney\" target=\"_blank\" rel=\"noopener\">U.S. schools’ funding inequities\u003c/a> — a problem they attempted to resolve with a requirement that the federal government chip in funding.\u003c/p>\n\u003ch3>\u003cstrong>Rules for educators, parents and caregivers\u003c/strong>\u003c/h3>\n\u003cp>The Students First Act not only covers students’ use of AI but also insists on \u003ca href=\"https://www.npr.org/2025/12/16/nx-s1-5492397/ai-schools-teachers-students\" target=\"_blank\" rel=\"noopener\">rules for educators\u003c/a>:\u003c/p>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Approved teacher use of AI\u003c/strong>: Allowed for tasks including lesson planning, making practice materials, providing feedback and improving instruction.\u003c/li>\n\u003c/ul>\n\u003cul class=\"rte2-style-ul\" style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\">\n\u003cli>\u003cstrong>Must have a clear AI policy\u003c/strong>: Each semester, teachers need to post “a clear, written AI usage policy,” explaining when AI is allowed and when it’s not.\u003c/li>\n\u003c/ul>\n\u003cp>What’s more, if an AI detector flags potential inappropriate AI use in a student paper, the bill says “teachers must personally investigate the issue before reporting the student to admin.”\u003c/p>\n\u003cp>The student senators struggled with the 10 provisions in the bill’s parents/guardians section because, as Isabella Stringer of New Hampshire said on the Senate floor, “We cannot legislate parenthood. Schools cannot tell parents what or how to teach your children.\u003cem>“\u003c/em>\u003c/p>\n\u003cp>As such, some of the provisions here suggest rather than tell. For instance, one says simply that parents should encourage balanced technology habits and emphasize the importance of ethical academic behavior at home.\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/7008x4672+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F74%2Fdb%2F0e9f08d84ec387cfe9c1ddfa383e%2Fkesner-npr-studentai-040.JPG\" alt=\"The Edward M. Kennedy Institute for the United States Senate sits on the University of Massachusetts, Boston campus and is home to the world's only full-scale replica of the U.S. Senate chamber.\">\u003cfigcaption>The Edward M. Kennedy Institute for the United States Senate sits on the University of Massachusetts, Boston campus and is home to the world’s only full-scale replica of the U.S. Senate chamber. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>The early version of the bill also gave parents a full veto over their students’ AI access, but many of the senators argued that AI is here to stay and students must be taught how to use it.\u003c/p>\n\u003cp>“Giving [parents] the complete say, especially in middle to high school, in what their child can and can’t do with AI is gonna limit [students] because a lot of [adults] don’t even know what AI is themselves,” said junior Tatiyana Reaves of North Carolina.\u003c/p>\n\u003cp>In one of the weekend’s more passionate exchanges, senators debated what should happen if a student attempts to use a school-based AI tool, like a chatbot, “for emotional support.”\u003c/p>\n\u003cp>Several teens worried that if a student confided sensitive information about, say, \u003ca href=\"https://www.npr.org/2025/10/08/nx-s1-5561981/ai-students-schools-teachers\" target=\"_blank\" rel=\"noopener\">their sexuality\u003c/a> or a mental health crisis, they should be able to trust that it would be kept private.\u003c/p>\n\u003cp>But Dylan Dornack of Iowa argued on the Senate floor that, for students in crisis or experiencing suicidal thoughts, the technology must alert a \u003cem>human\u003c/em>.\u003c/p>\n\u003cp>“This could be lifesaving,” Dornack told his colleagues, “whether or not that student is fearful that they might get outed. This is just one of those things that has to be taken to trusted adults.”\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/6439x4293+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F25%2Fd4%2F0578ac934294b32e55308a0b3d41%2Fkesner-npr-studentai-056.jpg\" alt=\"Wehiwaalani Gapero of Hawaii was one of dozens of students who chose to address their colleagues for a minute each before the final votes of the weekend were cast.\">\u003cfigcaption>Wehiwaalani Gapero of Hawaii was one of dozens of students who chose to address their colleagues for a minute each before the final votes of the weekend were cast. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>Ultimately, the students agreed: When a school chatbot detects a student in need of emotional support, it should not fulfill the student’s request but instead alert school officials.\u003c/p>\n\u003ch3>\u003cstrong>The rush to passage\u003c/strong>\u003c/h3>\n\u003cp>At the end of the whirlwind weekend, the student senators gathered in the replica chamber and more than half volunteered to address their colleagues for one minute each.\u003c/p>\n\u003cp>Dornack was the first to speak and called the bill an important, if imperfect, foundation for schools’ AI policies. “You have to lay the blocks before you can have the building. So here I say, let’s lay the blocks and let’s pass this\u003cem>.”\u003c/em>\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/7008x4672+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F5f%2Fc8%2Fca171e364dbab8cdf737b2e58d3a%2Fkesner-npr-studentai-027.JPG\" alt=\"In the final minutes before a key vote, student senators from (left to right) Minnesota and Washington state confer with their colleague.\">\u003cfigcaption>In the final minutes before a key vote, student senators from (left to right) Minnesota and Washington state confer with their colleague. \u003ccite> (Kieran Kesner for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>But Jadelynn Petitjean of Alabama called the bill an “unstable foundation” and opposed it.\u003c/p>\n\u003cp>Earlier in the day, West Virginia’s Ethan Liu had also opposed it, highlighting several contradictions in the bill, including amendments that both restricted students’ AI access while appearing to give teachers wide discretion over when and how AI is used.\u003c/p>\n\u003cp>“I thought it reflected really badly on us. I had a whole different speech planned out against this bill, actually. It was really good,” Liu told the Senate chamber before the final vote.\u003c/p>\n\u003cp>But at the last minute, the event’s organizers allowed the students to iron out a few of the bill’s inconsistencies, and, as a result, Liu changed his vote, saying “this bill is in much better shape.”\u003c/p>\n\u003cp>Student after student walked to the microphone at the front of the chamber, and most endorsed the bill, including Kendall Terao-Toma of Hawaii:\u003c/p>\n\u003cp>\u003cem>“\u003c/em>This is for our future — not just for education but for the workforce we will join, the economy that we will build and the communities we will lead.”\u003c/p>\n\u003cp>\u003cem>Edited by: \u003c/em>\u003ca href=\"https://www.npr.org/people/g-s1-123933/nirvi-shah\" target=\"_blank\" rel=\"noopener\">\u003cem>Nirvi Shah\u003c/em>\u003c/a>\u003cem> and \u003c/em>\u003ca href=\"https://www.npr.org/people/348780034/nicole-cohen\" target=\"_blank\" rel=\"noopener\">\u003cem>Nicole Cohen\u003c/em>\u003c/a>\u003cem>; audio story produced by: \u003c/em>\u003ca href=\"https://www.npr.org/people/348774853/lauren-migaki\" target=\"_blank\" rel=\"noopener\">\u003cem>Lauren Migaki\u003c/em>\u003c/a>\u003cbr>\n\u003cem>Visual design and development by: \u003c/em>\u003ca href=\"https://www.npr.org/people/348775569/la-johnson\" target=\"_blank\" rel=\"noopener\">\u003cem>LA Johnson\u003c/em>\u003c/a>\u003c/p>\n\u003ch3 id=\"bill\">Read the full text of the Students First Act:\u003c/h3>\n\u003cp>\u003c/p>\u003c/div>",
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"slug": "the-trojan-teddy-bear-the-promise-and-peril-of-childhood-in-the-age-of-ai",
"title": "'The Trojan Teddy Bear': The Promise and Peril of Childhood in the Age of AI",
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"headTitle": "‘The Trojan Teddy Bear’: The Promise and Peril of Childhood in the Age of AI | KQED",
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"content": "\u003cp>Back in 2001, Steven Spielberg released an underrated scifi movie named \u003cem>A.I. Artificial Intelligence\u003c/em> (yes, the title is a bit redundant). The movie, which loosely borrows from \u003cem>Pinocchio\u003c/em>, tells the story of a family who adopts a robotic boy programmed for love, and that robot’s heartbreaking quest to become a real boy.\u003c/p>\n\u003cp>Much of the technology in \u003cem>A.I.\u003c/em> remains elusive. We’re probably not anywhere close to building androids that can convincingly pass as Haley Joel Osment — or Jude Law, for that matter. But some of the AI products imagined in the movie are starting to look surprisingly plausible. Take Teddy, an animatronic teddy bear. Teddy can walk, talk, make decisions, and respond to the needs and emotions of people around him. He’s more than just a toy. He’s an intelligent companion and protector for children.\u003c/p>\n\u003cp>Today, a slew of technology companies are developing AI companions that sort of resemble Teddy. The most intelligent AI chatbots still live on digital screens, but a wave of startups is giving them bodies — creating dolls, action figures, and robots that can serve as companions for kids.\u003c/p>\n\u003ch2>What happens when kids grow up with AI?\u003c/h2>\n\u003cp>AI is already a part of childhood. Recommendation algorithms curate what many kids watch and listen to. Chatbots stand ready to answer questions like, “Are monsters real?” or “Why is the sky blue?” They can help with homework, tell bedtime stories, or even feel like a friend. And companies are racing to embed AI into toys, nurseries, classrooms, and eventually robots that live alongside families.\u003c/p>\n\u003cp>In a new book, \u003ca href=\"https://humanraised.org/\" target=\"_blank\" rel=\"noopener\">\u003cem>Human Raised: Nurturing Connection, Curiosity & Lifelong Learning in the Age of AI\u003c/em>\u003c/a>, author Dana Suskind grapples with what the rising tide of artificial intelligence means for raising kids. On the one hand, she acknowledges that the technology offers promise as, for example, a productivity enhancer and time saver for parents, a monitoring and research tool that can give parents and scientists valuable data on child development, and an interactive tutor that might help some kids learn.\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>But Suskind worries about what happens if AI begins replacing the kinds of human interactions that young brains evolved to learn from.\u003c/p>\n\u003cp>In fact, Suskind says, her original, working title for the book was, “The Trojan Teddy Bear,” a warning that AI companions may seem cute and cuddly — but they carry hidden risks for child development. She ultimately went with \u003cem>Human Raised\u003c/em> because she wanted to emphasize the positive — and irreplaceable — role that parents, teachers, and caregivers play in molding young ones.\u003c/p>\n\u003cp>“If we want children to be able to continue to connect with each other and with other human beings, to be able to think critically, to be able to navigate the human world, we’re gonna need to make sure that kids have a distinctly human-raised early childhood,” Suskind says.\u003c/p>\n\u003cp>Suskind is a professor of surgery and pediatrics at the University of Chicago Medical Center, where she directs a program aimed at giving kids hearing with cochlear implants. After she began doing this incredible work — literally helping children hear — she noticed that some kids who had the procedure went on to understand spoken language and talk with relative ease, while others had a much harder time. Hearing alone wasn’t enough. And that led her to dive into neuroscience and social science to understand why.\u003c/p>\n\u003cp>The brain development of young kids, Suskind learned, is heavily influenced by the back-and-forth interactions they have with their parents and caregivers during the first several years of their life. And she grew concerned that there is a big population of kids who aren’t getting the enriching communication their brains need. And so she founded \u003ca href=\"https://cri.uchicago.edu/portfolio/thirty-million-words/\" target=\"_blank\" rel=\"noopener\">the TMW Initiative,\u003c/a> a research center that helps parents create the kinds of brain-enriching environments that children need to reach their full potential. (You can read more about Suskind’s biography and previous work in \u003ca href=\"https://www.npr.org/sections/money/2022/05/17/1098524454/the-case-for-revolutionizing-child-care-in-america\" target=\"_blank\" rel=\"noopener\">a\u003cem> Planet Money\u003c/em> newsletter from 2022)\u003c/a>.\u003c/p>\n\u003ch2>Why Dana Suskind is sounding the alarm\u003c/h2>\n\u003cp>With the explosion of AI, Suskind has grown alarmed by a rush to introduce an unprecedented technology into kids’ lives without careful reflection and rigorous scientific study about its effects on young minds. She is especially concerned about AI companions and other systems that interact socially with children, which she fears many people will use to substitute for the human interactions that children need most.\u003c/p>\n\u003cp>Since the dawn of civilization, humans have used technology to make raising children a little easier. In \u003cem>Human Raised\u003c/em>, Suskind traces that history back to prehistoric times, when mothers used woven slings to carry infants while they worked. Over the centuries, new technologies — like television and tablets — have eased the burdens of caregiving or helped keep children occupied. Many of these technologies have also been greeted with fears that they would rot kids’ brains.\u003c/p>\n\u003cp>But Suskind argues AI may mark a fundamental shift. Interacting with a chatbot or intelligent teddy bear is more than just a kid glued to a television or an iPad watching Sesame Street or Paw Patrol. AI systems carry on conversations that can feel strikingly human. They respond to kids’ questions, emotions, and fears. They create a kind of synthetic social relationship — one that, Suskind argues, may shape developing minds in ways that, until recently, only humans could.\u003c/p>\n\u003cp>Suskind cites the research of renowned University of Washington developmental psychologist Patricia K. Kuhl. Kuhl proposed what’s known as the “social gate” hypothesis — the idea that children’s brains are biologically primed to learn through social interaction. Studies have shown, for example, that babies learn language much better from a live person than from a screen. Neuroscientists and psychologists suggest that’s because social interactions engage the brain in ways passive media does not. The sing-song way adults naturally speak to babies, smiles and other facial expressions, gentle touch, eye contact, and back-and-forth exchanges all appear to help open that social gate and facilitate learning and healthy brain development.\u003c/p>\n\u003cp>While artificial intelligence is no match for human educators and caregivers, Suskind argues, it is capable of opening the social gate in young children in ways that previous technologies could not. That makes AI a potentially extraordinary educational tool — but also a potentially dangerous one.\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/2400x1700+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2Fdd%2F5d%2Fdb82bca1461ab00fc032e5d5a054%2Fgettyimages-2006327337.jpg\">\u003cfigcaption>\u003ccite> (Getty Images)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>Companies design AI systems with their own goals, which could include maximizing your kids’ engagement, keeping their attention, collecting data, and making money. They don’t have the same priorities as parents. And while those systems may imitate human interaction, Suskind argues they cannot recreate everything that makes human relationships developmentally valuable.\u003c/p>\n\u003cp>“Eye contact, shared laughter, patient answers to ‘why’ questions activate ancient neural circuits designed for connection,” Suskind writes. “These exchanges provide a form of nourishment no algorithm, however sophisticated, can match.”\u003c/p>\n\u003cp>Human relationships are also messy and filled with emotions. Parents misunderstand their children. Kids get frustrated. Families argue, reconnect, and then smooth things over. Suskind argues that those imperfect interactions — and “the productive struggle” they create — are how children learn resilience, emotional regulation, flexibility, and how to navigate real relationships.\u003c/p>\n\u003cp>Unlike most humans, AI systems can be endlessly engaging, infinitely patient, and relentlessly affirming. Interactions with them often feel frictionless. Suskind worries giving young kids considerable exposure to them may make them less prepared for the messy, unpredictable nature of real human relationships.\u003c/p>\n\u003ch2>AI as junk food for the young mind\u003c/h2>\n\u003cp>Suskind compares AI relationships to ultra-processed food. “ If all you eat is fruit snacks, which is a synthetic version of fruit, when you actually eat the real fruit, you’re gonna be like, “Hmm, it’s not quite as sweet,” she says.\u003c/p>\n\u003cp>AI could eventually be programmed to try and mimic real parents and caregivers even more closely. But Suskind argues that the problem isn’t simply that today’s AI falls short of human relationships. It’s that AI represents a fundamentally new kind of social experience for children — one that already raises concerns based on what we know about child development and whose long-term effects remain deeply uncertain.\u003c/p>\n\u003cp>Suskind uses an analogy from the 19th century, when a German chemist named Justus von Liebig created one of the first infant formulas, hoping to replicate the nourishment of human milk. But when a French physician tested the formula on four newborns, \u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/37435903/\" target=\"_blank\" rel=\"noopener\">all of them died within days\u003c/a>, and the episode sparked a fierce controversy.\u003c/p>\n\u003cp>The lesson, Suskind suggests, is that we should be cautious about engineering substitutes for something as biologically, emotionally, and socially complex as human caregiving before we understand how those substitutes shape children’s development.\u003c/p>\n\u003cp>Given so much uncertainty about this rapidly evolving technology and its potential effects on kids, Suskind spends a lot of the book offering parents a practical guide for safely navigating child-rearing in the age of AI. She emphasizes that it’s especially important to shield kids from AI during their first years of life.\u003c/p>\n\u003cp>“Older children and adults encounter AI with already-built neural scaffolding, but young children are still wiring the very circuits that shape future learning and relationships,” she writes. “Introducing AI during this sensitive period presents a fundamentally different challenge with greater potential for harm.”\u003c/p>\n\u003cp>Suskind is open to the idea of using AI to enhance education for some kids — but only as a tool that enhances, rather than replaces, humans. She argues that human caregivers are the best way to cultivate what she calls “the Human Edge,” a set of social, emotional, and cognitive skills like “critical thinking, interpersonal connection, genuine creativity, empathy, and resilience.”\u003c/p>\n\u003cp>But, like time-crunched parents who rely on screens to buy themselves some time today, there may be growing temptations to outsource parts of child-rearing to AI, especially considering the fact that childcare is incredibly expensive. Suskind worries that, over time, a fully human-raised childhood could become a kind of luxury good — much the way fresh, healthy food often is today. Families with the time and resources would provide rich human interaction to their kids. Everyone else might increasingly rely on cheaper, more convenient AI substitutes.\u003c/p>\n\u003cp>And children raised largely by AI might not only lag socially, emotionally, and cognitively, but, ironically, they could also be less prepared for an AI-driven economy.\u003c/p>\n\u003cp>Suskind points to \u003ca href=\"https://static1.squarespace.com/static/57967bc7cd0f68048126361d/t/69dbbeb4bd54b97b00d8dec3/1776008884067/Technical+Note+Structural+Change.pdf\" target=\"_blank\" rel=\"noopener\">a recent essay\u003c/a> by the University of Chicago economist Alex Imas. Imas argues that as AI automates more cognitive work, human jobs may be increasingly concentrated in what he calls “the relational sector” — occupations where humans are valued for qualities that make them distinctly human, from education to health care to hospitality, the arts, and therapy.\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>If that’s true, then the traits children develop through a human-raised childhood won’t just matter for their social lives. They may also become an economic advantage. In a world increasingly shaped by artificial intelligence, the most valuable skills may be the ones that are the most deeply human.\u003c/p>\n\n",
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"excerpt": "AI is moving beyond chatbots and into toys, dolls, and robots built to befriend children. A leading child-development expert says the technology offers real promise — but also risks crowding out the human relationships children need most.",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>Back in 2001, Steven Spielberg released an underrated scifi movie named \u003cem>A.I. Artificial Intelligence\u003c/em> (yes, the title is a bit redundant). The movie, which loosely borrows from \u003cem>Pinocchio\u003c/em>, tells the story of a family who adopts a robotic boy programmed for love, and that robot’s heartbreaking quest to become a real boy.\u003c/p>\n\u003cp>Much of the technology in \u003cem>A.I.\u003c/em> remains elusive. We’re probably not anywhere close to building androids that can convincingly pass as Haley Joel Osment — or Jude Law, for that matter. But some of the AI products imagined in the movie are starting to look surprisingly plausible. Take Teddy, an animatronic teddy bear. Teddy can walk, talk, make decisions, and respond to the needs and emotions of people around him. He’s more than just a toy. He’s an intelligent companion and protector for children.\u003c/p>\n\u003cp>Today, a slew of technology companies are developing AI companions that sort of resemble Teddy. The most intelligent AI chatbots still live on digital screens, but a wave of startups is giving them bodies — creating dolls, action figures, and robots that can serve as companions for kids.\u003c/p>\n\u003ch2>What happens when kids grow up with AI?\u003c/h2>\n\u003cp>AI is already a part of childhood. Recommendation algorithms curate what many kids watch and listen to. Chatbots stand ready to answer questions like, “Are monsters real?” or “Why is the sky blue?” They can help with homework, tell bedtime stories, or even feel like a friend. And companies are racing to embed AI into toys, nurseries, classrooms, and eventually robots that live alongside families.\u003c/p>\n\u003cp>In a new book, \u003ca href=\"https://humanraised.org/\" target=\"_blank\" rel=\"noopener\">\u003cem>Human Raised: Nurturing Connection, Curiosity & Lifelong Learning in the Age of AI\u003c/em>\u003c/a>, author Dana Suskind grapples with what the rising tide of artificial intelligence means for raising kids. On the one hand, she acknowledges that the technology offers promise as, for example, a productivity enhancer and time saver for parents, a monitoring and research tool that can give parents and scientists valuable data on child development, and an interactive tutor that might help some kids learn.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>But Suskind worries about what happens if AI begins replacing the kinds of human interactions that young brains evolved to learn from.\u003c/p>\n\u003cp>In fact, Suskind says, her original, working title for the book was, “The Trojan Teddy Bear,” a warning that AI companions may seem cute and cuddly — but they carry hidden risks for child development. She ultimately went with \u003cem>Human Raised\u003c/em> because she wanted to emphasize the positive — and irreplaceable — role that parents, teachers, and caregivers play in molding young ones.\u003c/p>\n\u003cp>“If we want children to be able to continue to connect with each other and with other human beings, to be able to think critically, to be able to navigate the human world, we’re gonna need to make sure that kids have a distinctly human-raised early childhood,” Suskind says.\u003c/p>\n\u003cp>Suskind is a professor of surgery and pediatrics at the University of Chicago Medical Center, where she directs a program aimed at giving kids hearing with cochlear implants. After she began doing this incredible work — literally helping children hear — she noticed that some kids who had the procedure went on to understand spoken language and talk with relative ease, while others had a much harder time. Hearing alone wasn’t enough. And that led her to dive into neuroscience and social science to understand why.\u003c/p>\n\u003cp>The brain development of young kids, Suskind learned, is heavily influenced by the back-and-forth interactions they have with their parents and caregivers during the first several years of their life. And she grew concerned that there is a big population of kids who aren’t getting the enriching communication their brains need. And so she founded \u003ca href=\"https://cri.uchicago.edu/portfolio/thirty-million-words/\" target=\"_blank\" rel=\"noopener\">the TMW Initiative,\u003c/a> a research center that helps parents create the kinds of brain-enriching environments that children need to reach their full potential. (You can read more about Suskind’s biography and previous work in \u003ca href=\"https://www.npr.org/sections/money/2022/05/17/1098524454/the-case-for-revolutionizing-child-care-in-america\" target=\"_blank\" rel=\"noopener\">a\u003cem> Planet Money\u003c/em> newsletter from 2022)\u003c/a>.\u003c/p>\n\u003ch2>Why Dana Suskind is sounding the alarm\u003c/h2>\n\u003cp>With the explosion of AI, Suskind has grown alarmed by a rush to introduce an unprecedented technology into kids’ lives without careful reflection and rigorous scientific study about its effects on young minds. She is especially concerned about AI companions and other systems that interact socially with children, which she fears many people will use to substitute for the human interactions that children need most.\u003c/p>\n\u003cp>Since the dawn of civilization, humans have used technology to make raising children a little easier. In \u003cem>Human Raised\u003c/em>, Suskind traces that history back to prehistoric times, when mothers used woven slings to carry infants while they worked. Over the centuries, new technologies — like television and tablets — have eased the burdens of caregiving or helped keep children occupied. Many of these technologies have also been greeted with fears that they would rot kids’ brains.\u003c/p>\n\u003cp>But Suskind argues AI may mark a fundamental shift. Interacting with a chatbot or intelligent teddy bear is more than just a kid glued to a television or an iPad watching Sesame Street or Paw Patrol. AI systems carry on conversations that can feel strikingly human. They respond to kids’ questions, emotions, and fears. They create a kind of synthetic social relationship — one that, Suskind argues, may shape developing minds in ways that, until recently, only humans could.\u003c/p>\n\u003cp>Suskind cites the research of renowned University of Washington developmental psychologist Patricia K. Kuhl. Kuhl proposed what’s known as the “social gate” hypothesis — the idea that children’s brains are biologically primed to learn through social interaction. Studies have shown, for example, that babies learn language much better from a live person than from a screen. Neuroscientists and psychologists suggest that’s because social interactions engage the brain in ways passive media does not. The sing-song way adults naturally speak to babies, smiles and other facial expressions, gentle touch, eye contact, and back-and-forth exchanges all appear to help open that social gate and facilitate learning and healthy brain development.\u003c/p>\n\u003cp>While artificial intelligence is no match for human educators and caregivers, Suskind argues, it is capable of opening the social gate in young children in ways that previous technologies could not. That makes AI a potentially extraordinary educational tool — but also a potentially dangerous one.\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/2400x1700+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2Fdd%2F5d%2Fdb82bca1461ab00fc032e5d5a054%2Fgettyimages-2006327337.jpg\">\u003cfigcaption>\u003ccite> (Getty Images)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>Companies design AI systems with their own goals, which could include maximizing your kids’ engagement, keeping their attention, collecting data, and making money. They don’t have the same priorities as parents. And while those systems may imitate human interaction, Suskind argues they cannot recreate everything that makes human relationships developmentally valuable.\u003c/p>\n\u003cp>“Eye contact, shared laughter, patient answers to ‘why’ questions activate ancient neural circuits designed for connection,” Suskind writes. “These exchanges provide a form of nourishment no algorithm, however sophisticated, can match.”\u003c/p>\n\u003cp>Human relationships are also messy and filled with emotions. Parents misunderstand their children. Kids get frustrated. Families argue, reconnect, and then smooth things over. Suskind argues that those imperfect interactions — and “the productive struggle” they create — are how children learn resilience, emotional regulation, flexibility, and how to navigate real relationships.\u003c/p>\n\u003cp>Unlike most humans, AI systems can be endlessly engaging, infinitely patient, and relentlessly affirming. Interactions with them often feel frictionless. Suskind worries giving young kids considerable exposure to them may make them less prepared for the messy, unpredictable nature of real human relationships.\u003c/p>\n\u003ch2>AI as junk food for the young mind\u003c/h2>\n\u003cp>Suskind compares AI relationships to ultra-processed food. “ If all you eat is fruit snacks, which is a synthetic version of fruit, when you actually eat the real fruit, you’re gonna be like, “Hmm, it’s not quite as sweet,” she says.\u003c/p>\n\u003cp>AI could eventually be programmed to try and mimic real parents and caregivers even more closely. But Suskind argues that the problem isn’t simply that today’s AI falls short of human relationships. It’s that AI represents a fundamentally new kind of social experience for children — one that already raises concerns based on what we know about child development and whose long-term effects remain deeply uncertain.\u003c/p>\n\u003cp>Suskind uses an analogy from the 19th century, when a German chemist named Justus von Liebig created one of the first infant formulas, hoping to replicate the nourishment of human milk. But when a French physician tested the formula on four newborns, \u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/37435903/\" target=\"_blank\" rel=\"noopener\">all of them died within days\u003c/a>, and the episode sparked a fierce controversy.\u003c/p>\n\u003cp>The lesson, Suskind suggests, is that we should be cautious about engineering substitutes for something as biologically, emotionally, and socially complex as human caregiving before we understand how those substitutes shape children’s development.\u003c/p>\n\u003cp>Given so much uncertainty about this rapidly evolving technology and its potential effects on kids, Suskind spends a lot of the book offering parents a practical guide for safely navigating child-rearing in the age of AI. She emphasizes that it’s especially important to shield kids from AI during their first years of life.\u003c/p>\n\u003cp>“Older children and adults encounter AI with already-built neural scaffolding, but young children are still wiring the very circuits that shape future learning and relationships,” she writes. “Introducing AI during this sensitive period presents a fundamentally different challenge with greater potential for harm.”\u003c/p>\n\u003cp>Suskind is open to the idea of using AI to enhance education for some kids — but only as a tool that enhances, rather than replaces, humans. She argues that human caregivers are the best way to cultivate what she calls “the Human Edge,” a set of social, emotional, and cognitive skills like “critical thinking, interpersonal connection, genuine creativity, empathy, and resilience.”\u003c/p>\n\u003cp>But, like time-crunched parents who rely on screens to buy themselves some time today, there may be growing temptations to outsource parts of child-rearing to AI, especially considering the fact that childcare is incredibly expensive. Suskind worries that, over time, a fully human-raised childhood could become a kind of luxury good — much the way fresh, healthy food often is today. Families with the time and resources would provide rich human interaction to their kids. Everyone else might increasingly rely on cheaper, more convenient AI substitutes.\u003c/p>\n\u003cp>And children raised largely by AI might not only lag socially, emotionally, and cognitively, but, ironically, they could also be less prepared for an AI-driven economy.\u003c/p>\n\u003cp>Suskind points to \u003ca href=\"https://static1.squarespace.com/static/57967bc7cd0f68048126361d/t/69dbbeb4bd54b97b00d8dec3/1776008884067/Technical+Note+Structural+Change.pdf\" target=\"_blank\" rel=\"noopener\">a recent essay\u003c/a> by the University of Chicago economist Alex Imas. Imas argues that as AI automates more cognitive work, human jobs may be increasingly concentrated in what he calls “the relational sector” — occupations where humans are valued for qualities that make them distinctly human, from education to health care to hospitality, the arts, and therapy.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>If that’s true, then the traits children develop through a human-raised childhood won’t just matter for their social lives. They may also become an economic advantage. In a world increasingly shaped by artificial intelligence, the most valuable skills may be the ones that are the most deeply human.\u003c/p>\n\n\u003c/div>\u003c/p>",
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"content": "\u003cp>Artificial intelligence is often promoted as a way to make teachers more effective by helping them write lesson plans, generate classroom materials and provide feedback to students in seconds. But one of the first randomized trials testing AI in real classrooms found that it can also undermine learning. Students whose teachers were given access to an AI teaching assistant felt less motivated to learn.\u003c/p>\n\u003cp>The damage was especially pronounced among students whose teachers were already weaker instructors, as measured by their performance before the experiment began. Their students also scored lower on standardized final exams, the researchers found.\u003c/p>\n\u003cp>“Teachers, just like students or coders, might be using AI as a crutch,” said Alp Sungu, lead author of the study and an assistant professor at the Wharton School at the University of Pennsylvania. “Instead of doing the actual work, they’re using AI to delegate the task, and that lowers the quality of their teaching.”\u003c/p>\n\u003cp>A draft of the study, “\u003ca href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7007339\">Generative AI Can Harm Teaching\u003c/a>,” was released online in June and has not yet been published in a peer-reviewed journal. It echoes Sungu’s widely discussed 2024 research on how \u003ca href=\"https://hechingerreport.org/kids-chatgpt-worse-on-tests/\">students’ use of AI is harming learning\u003c/a>.\u003c/p>\n\u003cp>“Students use AI as an answer machine, not as a tool for learning, and therefore it harms learning,” said Sungu. “Here, I think teachers are potentially using AI as a material generating machine for homework, lecture notes, lesson plans, syllabus. Instead of improving their own output, they’re using AI as a replacement with very minimal interaction, and therefore the quality of output is not good enough.”\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>Sungu’s experiment, conducted with fellow University of Pennsylvania researchers, including educational psychologist Angela Duckworth, followed 193 teachers and more than 2,800 middle and high school students in a private school chain in Turkey during the spring of 2025.\u003c/p>\n\u003cp>Teachers were randomly assigned either to receive access to a ChatGPT-based teaching assistant customized to Turkey’s national curriculum or to continue teaching as usual. Over 10 weeks, teachers primarily used the tool to generate lecture notes, assignments and exams.\u003c/p>\n\u003cp>Students whose teachers had access to the AI tool rated their classes as less enjoyable, less interesting and less important than students in the control group. The decline in intrinsic motivation was modest, but larger among students of those teachers who had already been heavier AI users before the experiment began.\u003c/p>\n\u003cp>Average academic achievement did not change overall. But among teachers whose students had lower marks before the experiment — a proxy for lower-performing teachers — student achievement and confidence both declined. Academic achievement was measured through externally administered standardized exams, ruling out the possibility that these teachers had different grading standards.\u003c/p>\n\u003cp>The study cannot explain exactly why teaching quality deteriorated. Researchers did not observe classrooms or analyze the AI-generated materials teachers used. But Sungu suspects that teachers may have been giving up one of their most effective tools.\u003c/p>\n\u003cp>“When you start using AI-generated material, you’re losing your personal voice,” said Sungu. “It might be technically good enough, but it doesn’t really carry your own style. If everything is very uniform, it just becomes a bit more boring.”\u003c/p>\n\u003cp>One possible explanation for the weaker academic performance among students of low-performing teachers, Sungu said, is that stronger teachers treat AI output as a first draft, revising and adapting it to their classrooms. Weaker teachers, he suspects, may be more likely to use AI-generated material as is.\u003c/p>\n\u003cp>This study is not a clean comparison between teaching with and without AI. Teachers in the control group were free to use other AI tools, making this a comparison between access to a customized AI assistant and whatever teachers chose to do on their own. If anything, Sungu said, these findings might be understating the risks of teachers relying heavily on AI-generated materials.\u003c/p>\n\u003cp>Still, Sungu cautions that it would be a mistake to conclude that “AI is terrible and will ruin education.” He sees a different lesson: Access to AI technology alone does not improve teaching.\u003c/p>\n\u003cp>The challenge is to help teachers use AI in ways that preserve human judgment and creativity. That will require teacher training programs, guardrails and better interfaces.\u003c/p>\n\u003cp>“As of right now, how teachers are using it organically, there is something to be worried about,” he said.\u003c/p>\n\u003cp>Sungu says he personally uses AI in his university teaching to create interactive games and polls that would otherwise take too long to build. “When I first get the output, it just looks great,” he said. “And then, if I don’t immerse myself in it, the examples, the numbers don’t make sense. I end up spending an equal amount of time to improve the output or calibrate it to my class.”\u003c/p>\n\u003cp>“It’s not a time saver,” he said.\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-in-teaching/\">\u003cem>AI in teaching\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>Artificial intelligence is often promoted as a way to make teachers more effective by helping them write lesson plans, generate classroom materials and provide feedback to students in seconds. But one of the first randomized trials testing AI in real classrooms found that it can also undermine learning. Students whose teachers were given access to an AI teaching assistant felt less motivated to learn.\u003c/p>\n\u003cp>The damage was especially pronounced among students whose teachers were already weaker instructors, as measured by their performance before the experiment began. Their students also scored lower on standardized final exams, the researchers found.\u003c/p>\n\u003cp>“Teachers, just like students or coders, might be using AI as a crutch,” said Alp Sungu, lead author of the study and an assistant professor at the Wharton School at the University of Pennsylvania. “Instead of doing the actual work, they’re using AI to delegate the task, and that lowers the quality of their teaching.”\u003c/p>\n\u003cp>A draft of the study, “\u003ca href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7007339\">Generative AI Can Harm Teaching\u003c/a>,” was released online in June and has not yet been published in a peer-reviewed journal. It echoes Sungu’s widely discussed 2024 research on how \u003ca href=\"https://hechingerreport.org/kids-chatgpt-worse-on-tests/\">students’ use of AI is harming learning\u003c/a>.\u003c/p>\n\u003cp>“Students use AI as an answer machine, not as a tool for learning, and therefore it harms learning,” said Sungu. “Here, I think teachers are potentially using AI as a material generating machine for homework, lecture notes, lesson plans, syllabus. Instead of improving their own output, they’re using AI as a replacement with very minimal interaction, and therefore the quality of output is not good enough.”\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>Sungu’s experiment, conducted with fellow University of Pennsylvania researchers, including educational psychologist Angela Duckworth, followed 193 teachers and more than 2,800 middle and high school students in a private school chain in Turkey during the spring of 2025.\u003c/p>\n\u003cp>Teachers were randomly assigned either to receive access to a ChatGPT-based teaching assistant customized to Turkey’s national curriculum or to continue teaching as usual. Over 10 weeks, teachers primarily used the tool to generate lecture notes, assignments and exams.\u003c/p>\n\u003cp>Students whose teachers had access to the AI tool rated their classes as less enjoyable, less interesting and less important than students in the control group. The decline in intrinsic motivation was modest, but larger among students of those teachers who had already been heavier AI users before the experiment began.\u003c/p>\n\u003cp>Average academic achievement did not change overall. But among teachers whose students had lower marks before the experiment — a proxy for lower-performing teachers — student achievement and confidence both declined. Academic achievement was measured through externally administered standardized exams, ruling out the possibility that these teachers had different grading standards.\u003c/p>\n\u003cp>The study cannot explain exactly why teaching quality deteriorated. Researchers did not observe classrooms or analyze the AI-generated materials teachers used. But Sungu suspects that teachers may have been giving up one of their most effective tools.\u003c/p>\n\u003cp>“When you start using AI-generated material, you’re losing your personal voice,” said Sungu. “It might be technically good enough, but it doesn’t really carry your own style. If everything is very uniform, it just becomes a bit more boring.”\u003c/p>\n\u003cp>One possible explanation for the weaker academic performance among students of low-performing teachers, Sungu said, is that stronger teachers treat AI output as a first draft, revising and adapting it to their classrooms. Weaker teachers, he suspects, may be more likely to use AI-generated material as is.\u003c/p>\n\u003cp>This study is not a clean comparison between teaching with and without AI. Teachers in the control group were free to use other AI tools, making this a comparison between access to a customized AI assistant and whatever teachers chose to do on their own. If anything, Sungu said, these findings might be understating the risks of teachers relying heavily on AI-generated materials.\u003c/p>\n\u003cp>Still, Sungu cautions that it would be a mistake to conclude that “AI is terrible and will ruin education.” He sees a different lesson: Access to AI technology alone does not improve teaching.\u003c/p>\n\u003cp>The challenge is to help teachers use AI in ways that preserve human judgment and creativity. That will require teacher training programs, guardrails and better interfaces.\u003c/p>\n\u003cp>“As of right now, how teachers are using it organically, there is something to be worried about,” he said.\u003c/p>\n\u003cp>Sungu says he personally uses AI in his university teaching to create interactive games and polls that would otherwise take too long to build. “When I first get the output, it just looks great,” he said. “And then, if I don’t immerse myself in it, the examples, the numbers don’t make sense. I end up spending an equal amount of time to improve the output or calibrate it to my class.”\u003c/p>\n\u003cp>“It’s not a time saver,” he said.\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-in-teaching/\">\u003cem>AI in teaching\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"content": "\u003cp>When ChatGPT arrived in late 2022, educators quickly asked whether students would use artificial intelligence to cheat, learn or simply get through homework more efficiently. Evidence is beginning to point toward a troubling answer: Many students appear to be completing assignments faster while learning less from them.\u003c/p>\n\u003cp>This conclusion comes from one of the largest studies of how generative AI is changing student behavior and academic skills. Sina Rismanchian, a doctoral student at the University of California, Irvine, partnered with researchers at McGraw Hill to \u003ca href=\"https://arxiv.org/pdf/2605.21629\">analyze millions of student interactions with ALEKS\u003c/a>, an online math platform used by more than four million students a year, from fifth grade through college. Because ALEKS includes both low-stakes practice problems and college placement tests, the researchers were able to compare how students behaved and performed before and after ChatGPT’s arrival.\u003c/p>\n\u003cp>To isolate AI’s effects, the researchers compared two kinds of math problems that differ in how easily students can outsource them to AI: word problems and graphing problems.\u003c/p>\n\u003cp>Word problems can be copied and pasted directly into AI chatbots for instant answers. Graphing problems are far more cumbersome. A student would need to upload a screenshot and still recreate the graph inside ALEKS using its tools.\u003c/p>\n\u003cp>After ChatGPT’s launch, student behavior and performance on the two types of problems began to diverge.\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>Beginning in early 2023, students started spending less time on word problems while continuing to spend about the same amount of time on graphing problems. The gap widened every quarter. By the end of the study period, near the end of 2025, average time spent on word problems had fallen 31 percent among high school students and 27 percent among college students — from about four minutes per word problem to less than three. (Middle school students showed only a modest decline of 9 percent, and fifth graders showed essentially none.)\u003c/p>\n\u003cp>The researchers believe those averages are being pulled downward by some students who spend only seconds on word problems because they’re using AI to answer them.\u003c/p>\n\u003cp>The same pattern appeared in college placement tests. When the exams were taken without supervision, students spent much less time on word problems after ChatGPT’s release. During proctored exams, the time spent on word problems returned to historical norms.\u003c/p>\n\u003cp>But time is only half the story. The more troubling finding is what happened to learning.\u003c/p>\n\u003cp>Many colleges allow incoming students to retake placement tests after practicing more math in ALEKS, giving them a chance to qualify for a higher-level course. Before ChatGPT, that practice generally paid off. After ChatGPT, students answered more word problems correctly during unsupervised practice sessions but performed substantially worse on those same kinds of problems when they later took a proctored placement test.\u003c/p>\n\u003cp>Historically, students answered about 80 percent of these word problems correctly on supervised placement tests. After ChatGPT’s introduction, that fell to about 60 percent — a roughly 25 percent reduction in the odds of answering a word problem correctly.\u003c/p>\n\u003cp>Performance on graphing problems, by contrast, did not decline.\u003c/p>\n\u003cp>\u003cstrong>After ChatGPT’s release, students performed worse on word problems (AI-susceptible) during proctored exams, but answer more word problems correctly in nonproctored settings\u003cbr>\n\u003c/strong>\u003c/p>\n\u003cfigure id=\"attachment_66423\" class=\"wp-caption alignnone\" style=\"max-width: 512px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"wp-image-66423 size-full\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/07/Rismanchian-et-al.png\" alt=\"Graph showing score gaps in exams. \" width=\"512\" height=\"186\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/07/Rismanchian-et-al.png 512w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/07/Rismanchian-et-al-160x58.png 160w\" sizes=\"auto, (max-width: 512px) 100vw, 512px\">\u003cfigcaption class=\"wp-caption-text\">The dotted line marks the public release of ChatGPT. Source: Figure 4, Rismanchian et al “Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build,” June 2026 preprint.\u003c/figcaption>\u003c/figure>\n\u003cp>If students’ math skills had generally deteriorated because of pandemic learning loss, weaker high school preparation or digital distraction, graphing performance should have deteriorated too. It didn’t.\u003c/p>\n\u003cp>The study cannot definitively prove that students were using AI. The researchers couldn’t see what else was happening on students’ screens outside of ALEKS. But it’s difficult to think of another explanation. The changes appeared only in problems that are easy to outsource to AI, disappeared under supervision and grew steadily over nearly three years.\u003c/p>\n\u003cp>“What makes me nervous is that it’s not only about the word problems,” Rismanchian told me. “This cognitive surrender might be going on in writing, science, everything.”\u003c/p>\n\u003cp>The paper, “\u003ca href=\"https://arxiv.org/pdf/2605.21629\">Faster Completion, Less Learning\u003c/a>,” was released in June 2026 as a working paper and has not yet been peer reviewed. Like any single study, it doesn’t settle the questions of how much students are using AI in their schoolwork, whether it’s harming learning and by how much. But it joins a growing body of evidence that generative AI is causing students to skip the brain work that leads to learning, and that this “cognitive surrender” is becoming commonplace.\u003c/p>\n\u003cp>A randomized experiment in Turkey found that high school students who used AI to help them study math ultimately \u003ca href=\"https://hechingerreport.org/kids-chatgpt-worse-on-tests/\">learned less\u003c/a> than students who practiced without it. Anthropic, the maker of Claude, has separately reported that many college students appear to use AI to obtain answers and \u003ca href=\"https://hechingerreport.org/proof-points-offload-critical-thinking-ai/\">offload cognitive work\u003c/a>. Rismanchian’s earlier research, released in March 2026, documented \u003ca href=\"https://www.researchgate.net/publication/403013405_Artificial_Integrity_Concerning_Patterns_of_AI_Usage_Among_Undergraduate_Students\">troubling patterns of AI usage\u003c/a> in short response essays among undergraduate students at a large California research university.\u003c/p>\n\u003cp>That doesn’t mean AI always undermines learning. Carefully designed AI tutors have improved student achievement in controlled experiments by asking questions, personalizing instruction and withholding answers until students reason their way through a problem. But using AI this way should increase the time students spend on a problem, Rismanchian said. The ALEKS data show the opposite.\u003c/p>\n\u003cp>Rismanchian doesn’t believe the answer is simply banning AI. Instead, he argues, students need to value learning enough to resist the temptation to outsource it.\u003c/p>\n\u003cp>A recent RAND survey suggests many already recognize the threat to their brains. Students report worrying that AI is \u003ca href=\"https://www.rand.org/pubs/research_reports/RRA4742-1.html\">weakening their critical-thinking skills\u003c/a> while more of them admit using it for schoolwork.\u003c/p>\n\u003cp>Students are not entirely to blame. Even as many professors have warned students not to use AI to complete classwork, universities themselves have embraced the technology, often giving students free access to premium chatbots.\u003c/p>\n\u003cp>“I think we need to communicate to students that you should value your learning,” Rismanchian said. “If ChatGPT does it for you, then you haven’t learned it.”\u003c/p>\n\u003cp>Rismanchian understands the temptation.\u003c/p>\n\u003cp>An international student, Rismanchian began using ChatGPT to help polish the English in his papers. The ideas were still his own. But after several months, he said, he noticed something unsettling.\u003c/p>\n\u003cp>“I realized that I cannot write anymore,” he said. “I was losing my writing abilities.”\u003c/p>\n\u003cp>So he stopped using AI to write.\u003c/p>\n\u003cp>He still uses it to code.\u003c/p>\n\u003cp>[ad floatright]\u003c/p>\n\u003cp>\u003cem>This story about \u003c/em>\u003ca href=\"https://hechingerreport.org/proof-points-ai-eroding-math-skills/\">\u003cem>AI use eroding math skills\u003c/em>\u003c/a>\u003cem> was produced by \u003c/em>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">The Hechinger Report\u003c/a>\u003cem>, a nonprofit, independent news organization that covers education. Sign up for \u003c/em>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003cem>Proof Points\u003c/em>\u003c/a>\u003cem> and other \u003c/em>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003cem>Hechinger newsletters\u003c/em>\u003c/a>\u003cem>.\u003c/em>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>When ChatGPT arrived in late 2022, educators quickly asked whether students would use artificial intelligence to cheat, learn or simply get through homework more efficiently. Evidence is beginning to point toward a troubling answer: Many students appear to be completing assignments faster while learning less from them.\u003c/p>\n\u003cp>This conclusion comes from one of the largest studies of how generative AI is changing student behavior and academic skills. Sina Rismanchian, a doctoral student at the University of California, Irvine, partnered with researchers at McGraw Hill to \u003ca href=\"https://arxiv.org/pdf/2605.21629\">analyze millions of student interactions with ALEKS\u003c/a>, an online math platform used by more than four million students a year, from fifth grade through college. Because ALEKS includes both low-stakes practice problems and college placement tests, the researchers were able to compare how students behaved and performed before and after ChatGPT’s arrival.\u003c/p>\n\u003cp>To isolate AI’s effects, the researchers compared two kinds of math problems that differ in how easily students can outsource them to AI: word problems and graphing problems.\u003c/p>\n\u003cp>Word problems can be copied and pasted directly into AI chatbots for instant answers. Graphing problems are far more cumbersome. A student would need to upload a screenshot and still recreate the graph inside ALEKS using its tools.\u003c/p>\n\u003cp>After ChatGPT’s launch, student behavior and performance on the two types of problems began to diverge.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>Beginning in early 2023, students started spending less time on word problems while continuing to spend about the same amount of time on graphing problems. The gap widened every quarter. By the end of the study period, near the end of 2025, average time spent on word problems had fallen 31 percent among high school students and 27 percent among college students — from about four minutes per word problem to less than three. (Middle school students showed only a modest decline of 9 percent, and fifth graders showed essentially none.)\u003c/p>\n\u003cp>The researchers believe those averages are being pulled downward by some students who spend only seconds on word problems because they’re using AI to answer them.\u003c/p>\n\u003cp>The same pattern appeared in college placement tests. When the exams were taken without supervision, students spent much less time on word problems after ChatGPT’s release. During proctored exams, the time spent on word problems returned to historical norms.\u003c/p>\n\u003cp>But time is only half the story. The more troubling finding is what happened to learning.\u003c/p>\n\u003cp>Many colleges allow incoming students to retake placement tests after practicing more math in ALEKS, giving them a chance to qualify for a higher-level course. Before ChatGPT, that practice generally paid off. After ChatGPT, students answered more word problems correctly during unsupervised practice sessions but performed substantially worse on those same kinds of problems when they later took a proctored placement test.\u003c/p>\n\u003cp>Historically, students answered about 80 percent of these word problems correctly on supervised placement tests. After ChatGPT’s introduction, that fell to about 60 percent — a roughly 25 percent reduction in the odds of answering a word problem correctly.\u003c/p>\n\u003cp>Performance on graphing problems, by contrast, did not decline.\u003c/p>\n\u003cp>\u003cstrong>After ChatGPT’s release, students performed worse on word problems (AI-susceptible) during proctored exams, but answer more word problems correctly in nonproctored settings\u003cbr>\n\u003c/strong>\u003c/p>\n\u003cfigure id=\"attachment_66423\" class=\"wp-caption alignnone\" style=\"max-width: 512px\">\u003cimg loading=\"lazy\" decoding=\"async\" class=\"wp-image-66423 size-full\" src=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/07/Rismanchian-et-al.png\" alt=\"Graph showing score gaps in exams. \" width=\"512\" height=\"186\" srcset=\"https://cdn.kqed.org/wp-content/uploads/sites/23/2026/07/Rismanchian-et-al.png 512w, https://cdn.kqed.org/wp-content/uploads/sites/23/2026/07/Rismanchian-et-al-160x58.png 160w\" sizes=\"auto, (max-width: 512px) 100vw, 512px\">\u003cfigcaption class=\"wp-caption-text\">The dotted line marks the public release of ChatGPT. Source: Figure 4, Rismanchian et al “Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build,” June 2026 preprint.\u003c/figcaption>\u003c/figure>\n\u003cp>If students’ math skills had generally deteriorated because of pandemic learning loss, weaker high school preparation or digital distraction, graphing performance should have deteriorated too. It didn’t.\u003c/p>\n\u003cp>The study cannot definitively prove that students were using AI. The researchers couldn’t see what else was happening on students’ screens outside of ALEKS. But it’s difficult to think of another explanation. The changes appeared only in problems that are easy to outsource to AI, disappeared under supervision and grew steadily over nearly three years.\u003c/p>\n\u003cp>“What makes me nervous is that it’s not only about the word problems,” Rismanchian told me. “This cognitive surrender might be going on in writing, science, everything.”\u003c/p>\n\u003cp>The paper, “\u003ca href=\"https://arxiv.org/pdf/2605.21629\">Faster Completion, Less Learning\u003c/a>,” was released in June 2026 as a working paper and has not yet been peer reviewed. Like any single study, it doesn’t settle the questions of how much students are using AI in their schoolwork, whether it’s harming learning and by how much. But it joins a growing body of evidence that generative AI is causing students to skip the brain work that leads to learning, and that this “cognitive surrender” is becoming commonplace.\u003c/p>\n\u003cp>A randomized experiment in Turkey found that high school students who used AI to help them study math ultimately \u003ca href=\"https://hechingerreport.org/kids-chatgpt-worse-on-tests/\">learned less\u003c/a> than students who practiced without it. Anthropic, the maker of Claude, has separately reported that many college students appear to use AI to obtain answers and \u003ca href=\"https://hechingerreport.org/proof-points-offload-critical-thinking-ai/\">offload cognitive work\u003c/a>. Rismanchian’s earlier research, released in March 2026, documented \u003ca href=\"https://www.researchgate.net/publication/403013405_Artificial_Integrity_Concerning_Patterns_of_AI_Usage_Among_Undergraduate_Students\">troubling patterns of AI usage\u003c/a> in short response essays among undergraduate students at a large California research university.\u003c/p>\n\u003cp>That doesn’t mean AI always undermines learning. Carefully designed AI tutors have improved student achievement in controlled experiments by asking questions, personalizing instruction and withholding answers until students reason their way through a problem. But using AI this way should increase the time students spend on a problem, Rismanchian said. The ALEKS data show the opposite.\u003c/p>\n\u003cp>Rismanchian doesn’t believe the answer is simply banning AI. Instead, he argues, students need to value learning enough to resist the temptation to outsource it.\u003c/p>\n\u003cp>A recent RAND survey suggests many already recognize the threat to their brains. Students report worrying that AI is \u003ca href=\"https://www.rand.org/pubs/research_reports/RRA4742-1.html\">weakening their critical-thinking skills\u003c/a> while more of them admit using it for schoolwork.\u003c/p>\n\u003cp>Students are not entirely to blame. Even as many professors have warned students not to use AI to complete classwork, universities themselves have embraced the technology, often giving students free access to premium chatbots.\u003c/p>\n\u003cp>“I think we need to communicate to students that you should value your learning,” Rismanchian said. “If ChatGPT does it for you, then you haven’t learned it.”\u003c/p>\n\u003cp>Rismanchian understands the temptation.\u003c/p>\n\u003cp>An international student, Rismanchian began using ChatGPT to help polish the English in his papers. The ideas were still his own. But after several months, he said, he noticed something unsettling.\u003c/p>\n\u003cp>“I realized that I cannot write anymore,” he said. “I was losing my writing abilities.”\u003c/p>\n\u003cp>So he stopped using AI to write.\u003c/p>\n\u003cp>He still uses it to code.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cp>As colleges scramble to write rules for artificial intelligence in the classroom, one basic question remains unknown: How many students are actually using it?\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">An anonymous survey of 338 undergraduates at the University of Chicago shows that the answer may be hard to pin down — not just because AI use is changing quickly, but because students may not be self-reporting it accurately.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">In the survey, 60 percent of students said they personally use AI tools such as ChatGPT. But 90 percent said they believed the average student on campus uses AI. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">That 30-point gap could mean that students are underreporting their own AI use, overestimating their peers’ use, or both. Without reliable information about how many students are using AI and how they are using it, college administrators risk designing policies based on assumptions rather than evidence. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">The University of Chicago researchers behind the survey suspect that college students aren’t being truthful about their actual use of AI because they’re ashamed. \u003c/span>\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">“Students don’t want to be perceived by their peers as not able to do the work,” said Alex Kale, a computer scientist at the University of Chicago and a co-author of the \u003c/span>\u003ca href=\"https://dl.acm.org/doi/10.1145/3772318.3791073\">\u003cspan style=\"font-weight: 400;\">study\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400;\">, which was presented at a conference in Barcelona, Spain, in April. “They don’t want to be perceived by their peers as dishonest … And it feels deeply personal.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">Kale calls this phenomenon “social desirability bias,” the human tendency to answer questions in a way that makes us look good to others (and to ourselves), rather than being completely honest, even in an anonymous survey. In a separate online survey of 98 undergraduates conducted by the researchers, respondents said that admitting to using AI was akin to admitting that you’re “not able to complete coursework independently,” or are “lazy.” Another respondent thought that students were hiding usage for fear of getting caught and possibly expelled.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">The researchers offer an alternate explanation for the gap. Students may be overestimating how many of their peers are using AI because it is such a visible part of campus life. They hear people talking about ChatGPT. They see AI tools open on laptop screens. That can start to feel like the norm. One survey respondent expressed it like this: “I think only a small portion of students actually rely on LLMs to do coursework, while most students do not. That small portion leads some students to assume most are using it.” (The current post-2022 generation of AI tools like ChatGPT are often referred to as large language models or LLMs.)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">In other words, students may be using AI more than they admit, while AI hype may also be creating the impression that everyone is using it. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">This same phenomenon — a big gap between what students admit to doing and what they believe their peers are doing — is commonly found in public health research on \u003c/span>\u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/10368559/\">\u003cspan style=\"font-weight: 400;\">alcohol, drugs\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400;\"> and \u003c/span>\u003ca href=\"https://academic.oup.com/ijpor/article-abstract/20/1/52/738000?redirectedFrom=fulltext&login=false&utm_source=chatgpt.com\">\u003cspan style=\"font-weight: 400;\">sex\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400;\">. Students often overestimate how much their peers drink heavily, use drugs or engage in casual sex. And that has had big implications for curbing unhealthy behaviors. When students believe that “everyone else is doing it,” they are more likely to engage in it too. The false perception becomes partly self-fulfilling.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">More than 25 years ago, colleges began to worry that warning students about binge drinking on campus was backfiring and actually encouraging students to get drunk. Many \u003c/span>\u003ca href=\"https://www.nytimes.com/2000/10/03/us/new-tactic-on-college-drinking-play-it-down.html\">\u003cspan style=\"font-weight: 400;\">shifted strategy\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400;\">, downplaying the problem of binge drinking and publicizing statistics that most students drink in moderation. The number of students who said they drink heavily declined, according to some public health officials. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">There may be some lessons here for how to encourage the responsible use of AI, even though the University of Chicago study doesn’t link the AI use to drugs or booze. But it does raise the point that perceptions matter. If students believe that nearly everyone is relying on AI to complete coursework, they may feel pressure to use it themselves just to keep up.\u003c/span>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400;\">Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story along with The Hechinger Report’s Jill Barshay.\u003c/span>\u003c/i>\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400;\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-ai-use-college-campuses/\">\u003ci>\u003cspan style=\"font-weight: 400;\">AI use on college campuses\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400;\"> was produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003cspan style=\"font-weight: 400;\">The Hechinger Report\u003c/span>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400;\">, a nonprofit, independent news organization that covers education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400;\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400;\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400;\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400;\">.\u003c/span>\u003c/i>\u003c/p>\n\n",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>As colleges scramble to write rules for artificial intelligence in the classroom, one basic question remains unknown: How many students are actually using it?\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">An anonymous survey of 338 undergraduates at the University of Chicago shows that the answer may be hard to pin down — not just because AI use is changing quickly, but because students may not be self-reporting it accurately.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">In the survey, 60 percent of students said they personally use AI tools such as ChatGPT. But 90 percent said they believed the average student on campus uses AI. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">That 30-point gap could mean that students are underreporting their own AI use, overestimating their peers’ use, or both. Without reliable information about how many students are using AI and how they are using it, college administrators risk designing policies based on assumptions rather than evidence. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">The University of Chicago researchers behind the survey suspect that college students aren’t being truthful about their actual use of AI because they’re ashamed. \u003c/span>\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">“Students don’t want to be perceived by their peers as not able to do the work,” said Alex Kale, a computer scientist at the University of Chicago and a co-author of the \u003c/span>\u003ca href=\"https://dl.acm.org/doi/10.1145/3772318.3791073\">\u003cspan style=\"font-weight: 400;\">study\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400;\">, which was presented at a conference in Barcelona, Spain, in April. “They don’t want to be perceived by their peers as dishonest … And it feels deeply personal.”\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">Kale calls this phenomenon “social desirability bias,” the human tendency to answer questions in a way that makes us look good to others (and to ourselves), rather than being completely honest, even in an anonymous survey. In a separate online survey of 98 undergraduates conducted by the researchers, respondents said that admitting to using AI was akin to admitting that you’re “not able to complete coursework independently,” or are “lazy.” Another respondent thought that students were hiding usage for fear of getting caught and possibly expelled.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">The researchers offer an alternate explanation for the gap. Students may be overestimating how many of their peers are using AI because it is such a visible part of campus life. They hear people talking about ChatGPT. They see AI tools open on laptop screens. That can start to feel like the norm. One survey respondent expressed it like this: “I think only a small portion of students actually rely on LLMs to do coursework, while most students do not. That small portion leads some students to assume most are using it.” (The current post-2022 generation of AI tools like ChatGPT are often referred to as large language models or LLMs.)\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">In other words, students may be using AI more than they admit, while AI hype may also be creating the impression that everyone is using it. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">This same phenomenon — a big gap between what students admit to doing and what they believe their peers are doing — is commonly found in public health research on \u003c/span>\u003ca href=\"https://pubmed.ncbi.nlm.nih.gov/10368559/\">\u003cspan style=\"font-weight: 400;\">alcohol, drugs\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400;\"> and \u003c/span>\u003ca href=\"https://academic.oup.com/ijpor/article-abstract/20/1/52/738000?redirectedFrom=fulltext&login=false&utm_source=chatgpt.com\">\u003cspan style=\"font-weight: 400;\">sex\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400;\">. Students often overestimate how much their peers drink heavily, use drugs or engage in casual sex. And that has had big implications for curbing unhealthy behaviors. When students believe that “everyone else is doing it,” they are more likely to engage in it too. The false perception becomes partly self-fulfilling.\u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">More than 25 years ago, colleges began to worry that warning students about binge drinking on campus was backfiring and actually encouraging students to get drunk. Many \u003c/span>\u003ca href=\"https://www.nytimes.com/2000/10/03/us/new-tactic-on-college-drinking-play-it-down.html\">\u003cspan style=\"font-weight: 400;\">shifted strategy\u003c/span>\u003c/a>\u003cspan style=\"font-weight: 400;\">, downplaying the problem of binge drinking and publicizing statistics that most students drink in moderation. The number of students who said they drink heavily declined, according to some public health officials. \u003c/span>\u003c/p>\n\u003cp>\u003cspan style=\"font-weight: 400;\">There may be some lessons here for how to encourage the responsible use of AI, even though the University of Chicago study doesn’t link the AI use to drugs or booze. But it does raise the point that perceptions matter. If students believe that nearly everyone is relying on AI to complete coursework, they may feel pressure to use it themselves just to keep up.\u003c/span>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400;\">Kristin Fasiang is a graduate student in computer science and learning sciences at Northwestern University. Fasiang reported and wrote this story along with The Hechinger Report’s Jill Barshay.\u003c/span>\u003c/i>\u003c/p>\n\u003cp>\u003c/p>\n\u003cp>\u003ci>\u003cspan style=\"font-weight: 400;\">This story about \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proof-points-ai-use-college-campuses/\">\u003ci>\u003cspan style=\"font-weight: 400;\">AI use on college campuses\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400;\"> was produced by \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/special-reports/higher-education/\">\u003cspan style=\"font-weight: 400;\">The Hechinger Report\u003c/span>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400;\">, a nonprofit, independent news organization that covers education. Sign up for \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/proofpoints/\">\u003ci>\u003cspan style=\"font-weight: 400;\">Proof Points\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400;\"> and other \u003c/span>\u003c/i>\u003ca href=\"https://hechingerreport.org/newsletters/\">\u003ci>\u003cspan style=\"font-weight: 400;\">Hechinger newsletters\u003c/span>\u003c/i>\u003c/a>\u003ci>\u003cspan style=\"font-weight: 400;\">.\u003c/span>\u003c/i>\u003c/p>\n\n\u003c/div>\u003c/p>",
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"content": "\u003cp>\u003cem>Editor’s note: NPR uses only the first names of minors in this story because it discusses their learning disabilities and placement in special education.\u003c/em>\u003c/p>\n\u003cp>BAY POINT, Calif. — The sun would just be rising when teacher Mary Acebu began her days. She’d blast music on the way to work to get energized and get to her classroom by 6:30 to prepare for her students’ arrival at 8. Often, it’d be dark by the time she headed home, sometimes with paperwork in tow.\u003c/p>\n\u003cp>Like so many special education teachers around the country, this was Acebu’s life for much of the 10 years she’s been teaching at Riverview Middle School, in this small, unincorporated northern California town.\u003c/p>\n\u003cp>“I don’t do that anymore,” she says with a laugh.\u003c/p>\n\u003cp>That’s because Acebu has been experimenting with artificial intelligence for the last two years to get through paperwork more quickly and says it’s helped her instead use precious time for student interaction. “I have time to talk to the kiddos and really build those relationships,” she says, “instead of sitting here in front of my computer.”\u003c/p>\n\u003cp>[ad fullwidth]\u003c/p>\n\u003cp>For years, schools nationwide have \u003ca href=\"https://www.npr.org/2024/05/15/1247795768/children-disabilities-special-education-teacher-shortage\" target=\"_blank\" rel=\"noopener\">struggled with hiring and retaining\u003c/a> special educators. In the 2024-25 school year, \u003ca href=\"https://learningpolicyinstitute.org/product/teacher-shortages-subjects-across-states-factsheet\" target=\"_blank\" rel=\"noopener\">45 states reported\u003c/a> special education teacher shortages, and staff turnover is worse in schools that largely serve low-income students, like Riverview.\u003c/p>\n\u003cp>Some special educators say part of what makes them feel overworked is legally required paperwork layered on top of regular teaching duties. Acebu is one of a growing number of those teachers around the nation using AI to help speed up that paperwork — including for writing individualized education programs (IEPs). Educators and families maintain these detailed documents that outline goals and services students need to meet those goals at school.\u003c/p>\n\u003cp>According to \u003ca href=\"https://cdt.org/wp-content/uploads/2025/10/2025-10-28-CDT-AI-IEP-Brief-1.pdf\" target=\"_blank\" rel=\"noopener\">a recent survey\u003c/a> by the nonpartisan Center for Democracy and Technology (CDT), 57% of special education teachers polled nationwide said they used AI to help develop individualized plans for their students in the 2024-25 school year. That’s up from 39% the previous school year.\u003c/p>\n\u003cp>Along with the survey results, the CDT warned of privacy, legal and ethical risks around using AI. Other research, however, including from the University of Virginia (UVA) and the University of Central Florida (UCF), has shown that when used appropriately, AI can help special education teachers craft IEPs of equal or higher quality than when teachers produce them alone.\u003c/p>\n\u003cp>And the time saved can benefit students, too. “The more face time a student with a disability has with a teacher, that often yields better outcomes for them, both educationally, functionally — just across the board,” says Olivia Coleman, a researcher and professor at UCF who has been studying the role of AI in special education.\u003c/p>\n\u003cp>Acebu says that rings true in her classroom. She points out King, one of her eighth graders, as an example. “He was a non-reader, beginning of seventh grade. He’s reading now.” That, for Acebu, is the \u003cem>point\u003c/em> of IEPs — to put what’s on paper into practice for her students. She says that is only possible with intentional, hands-on work in the classroom.\u003c/p>\n\u003ch2>\u003cstrong>What IEPs are and why they matter\u003c/strong>\u003c/h2>\n\u003cp>Every seventh and eighth grader in Mary Acebu’s class learns differently — some work independently, some in pairs, others with headphones on and yet others with speech-to-text technology. Those differences are captured in each child’s IEP, a document required by federal law for each of the over 8 million students with disabilities in this country.\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/4000x2668+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F8d%2F57%2F8601fa57482dbd294f690c16221d%2F36a0496-tif.jpg\" alt=\"Mary Acebu has been a special education teacher for a decade at Riverview Middle School. She is part of a task force that is working on an AI policy for her school district.\">\u003cfigcaption>Mary Acebu has been a special education teacher for a decade at Riverview Middle School. She is part of a task force that is working on an AI policy for her school district.\u003cbr>\n\u003ccite> (Talia Herman for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>Every IEP includes annual goals tailored to each student’s present needs, but importantly, “also where you want them to go within the next year,” says Danielle Waterfield, Coleman’s research partner at UVA.\u003c/p>\n\u003cp>Both Coleman and Waterfield say while many teachers report feeling bogged down by the work that goes into developing IEPs, teachers also recognize they are a necessary tool for students with disabilities to get a quality education.\u003c/p>\n\u003cp>Acebu says that to develop those goals, teachers must know each student’s learning style intimately. “The key term is ‘individualized.’ No two kids are the same,” she says. For special educators, the process involves hours of meetings and a deep knowledge of complex education law and policy.\u003c/p>\n\u003cp>It used to take Acebu around 45 minutes to develop three or four IEP goals per student. She points to a big, blue binder at least 5 inches thick on her bookshelf that contains California’s education standards. “It used to be flipping through all those pages,” to find the right standard to match unique student goals, she says.\u003c/p>\n\u003cp>Then came AI.\u003c/p>\n\u003ch2>\u003cstrong>Using AI — with a ‘human touch’ \u003c/strong>\u003c/h2>\n\u003cp>A couple of years ago, Acebu began taking courses on how to safely and effectively use AI. Around the same time, her district, Mt. Diablo Unified, entered agreements with companies that offer education-focused AI tools including MagicSchool AI and Google. They promise to protect sensitive student data, a primary concern for those who warn against the risks of using AI in schools. A growing number of districts are adopting such products, though \u003ca href=\"https://www.edweek.org/technology/which-states-require-schools-to-have-ai-policies/2025/09\" target=\"_blank\" rel=\"noopener\">only a few states\u003c/a> have official AI education policies.\u003c/p>\n\u003cp>Recently, using a district-vetted tool, Acebu customized chatbots for her school and trained them on state standards, assessments and other special education data. She now uses her “little assistants” for a wide range of tasks, from creating personalized worksheets to developing IEP goals.\u003c/p>\n\u003cp>And then, she says, “you’re double-checking everything. Like you have to put that human touch, that’s the final step.”\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/4000x2668+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F5c%2F9b%2F7917c6324542801ed762bdb30d77%2F36a9904-tif.jpg\" alt=\"King, an eighth grader, went from not being able to read to reading confidently since he joined Acebu's class last year. She says that has been possible, in part, because AI has given her more time to work directly with students in the classroom and less on paperwork.\">\u003cfigcaption>King, an eighth grader, went from not being able to read to reading confidently since he joined Acebu’s class last year. She says that has been possible, in part, because AI has given her more time to work directly with students in the classroom and less on paperwork.\u003cbr>\n\u003ccite> (Talia Herman for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/4500x3000+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F46%2F00%2F54e6a456459fa6fb438ca613f8a0%2F36a9793-tif.jpg\" alt=\"For a science project, King made turtle pieces from clay. They are part of a board game he created with Acebu's help called Turtle Catastrophe. It was one of two projects from his school that was accepted at a local science fair.\">\u003cfigcaption>For a science project, King made turtle pieces from clay. They are part of a board game he created with Acebu’s help called Turtle Catastrophe. It was one of two projects from his school that was accepted at a local science fair.\u003cbr>\n\u003ccite> (Talia Herman for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>\u003ca href=\"https://journals.sagepub.com/doi/10.1177/01626434261419099\" target=\"_blank\" rel=\"noopener\">In their research,\u003c/a> Coleman and Waterfield found special education teachers nationwide are using AI to help write IEP goals, track student progress, synthesize data and create differentiated learning materials, among other things.\u003c/p>\n\u003cp>Acebu is uniquely equipped to use tech-tools: She just earned her doctorate in instructional technology and is on her district’s AI task force, which is developing an official AI policy.\u003c/p>\n\u003cp>Some of Acebu’s less tech-savvy colleagues, however, were skeptical, including Paul Stone, who has been a special educator at Riverview for 22 years.\u003c/p>\n\u003cp>Then the number of students he serves shot up.\u003c/p>\n\u003cp>“I don’t want to say it’s killing me, but it has put a huge stressor on my mental health and my life,” Stone says of his work this year. “It would be kind of nice if there were two jobs, like one paperwork job and one working with the kids.”\u003c/p>\n\u003cp>So, a few weeks ago, after a tutorial from Acebu, he gave her chatbot a shot. He was surprised by the results.\u003c/p>\n\u003cp>“It’s an amazing time-saver so far,” he says. Stone has used AI for a number of things including producing simple summaries of complicated data to present to parents at IEP meetings. “I mean, it’s not like ‘that’s it, I’m done.’ I still have to go through and check it all.”\u003c/p>\n\u003cp>He and Acebu both say it could help them, and other educators, avoid burnout. Yet, Ariana Aboulafia, who was the lead author of CDT’s report, calls AI tools “a Band-Aid” for special education teachers who feel overworked.\u003c/p>\n\u003ch2>\u003cstrong>Using AI in special education — with guardrails\u003c/strong>\u003c/h2>\n\u003cp>Band-Aid or not, more teachers \u003cem>are \u003c/em>using AI around the country. There are a litany of concerns about its use, especially in special education, which is highly regulated. “Student privacy is number one,” says Acebu. “Don’t put information there that’s gonna identify your students.” CDT’s Aboulafia adds that while the risks around privacy may be reduced if a school is using a vetted vendor, data breaches could still make that information vulnerable.\u003c/p>\n\u003cp>But not all teachers are using district-approved tools. Coleman, Waterfield and CDT’s research all found that educators around the country are using AI both formally and informally — from free consumer platforms like ChatGPT and Claude to district-approved tools like MagicSchool AI, Google Gemini and Playground IEP, among others. To help teachers navigate this complicated landscape, Waterfield and Coleman \u003ca href=\"https://ciddl.org/navigating-ai-in-iep-development-a-framework-for-ethical-practice/\" target=\"_blank\" rel=\"noopener\">developed a “decision tree”\u003c/a> for ethical AI use.\u003c/p>\n\u003cp>Another consideration is the fact that AI models can be biased, including against people with disabilities, says Aboulafia, who leads the Disability Rights in Technology Policy Project at CDT. In addition, she worries AI models built on pattern recognition are, “to a certain extent, inherently incompatible with a process that legally requires individualization.”\u003c/p>\n\u003cp>Aboulafia is most concerned about the 15% of teachers CDT’s survey found have been relying entirely on AI to develop IEPs. There must always be a “human in the loop,” she says.\u003c/p>\n\u003cp>Acebu, who happens to be her district’s teacher of the year, says these days, she comes to class just 30 minutes before her students, and leaves just after the last bell. This has improved her work-life balance and the quality of her teaching.\u003c/p>\n\u003cp>King, the eighth grader in her class who has evolved into a confident reader, also goes to math class now without any additional support.\u003c/p>\n\u003cp>“That’s the dream of every special educator,” she says, beaming. “But guess what? 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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003cp>\u003cem>Editor’s note: NPR uses only the first names of minors in this story because it discusses their learning disabilities and placement in special education.\u003c/em>\u003c/p>\n\u003cp>BAY POINT, Calif. — The sun would just be rising when teacher Mary Acebu began her days. She’d blast music on the way to work to get energized and get to her classroom by 6:30 to prepare for her students’ arrival at 8. Often, it’d be dark by the time she headed home, sometimes with paperwork in tow.\u003c/p>\n\u003cp>Like so many special education teachers around the country, this was Acebu’s life for much of the 10 years she’s been teaching at Riverview Middle School, in this small, unincorporated northern California town.\u003c/p>\n\u003cp>“I don’t do that anymore,” she says with a laugh.\u003c/p>\n\u003cp>That’s because Acebu has been experimenting with artificial intelligence for the last two years to get through paperwork more quickly and says it’s helped her instead use precious time for student interaction. “I have time to talk to the kiddos and really build those relationships,” she says, “instead of sitting here in front of my computer.”\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"content": "\u003cdiv class=\"post-body\">\u003cp>\u003c/p>\n\u003cp>For years, schools nationwide have \u003ca href=\"https://www.npr.org/2024/05/15/1247795768/children-disabilities-special-education-teacher-shortage\" target=\"_blank\" rel=\"noopener\">struggled with hiring and retaining\u003c/a> special educators. In the 2024-25 school year, \u003ca href=\"https://learningpolicyinstitute.org/product/teacher-shortages-subjects-across-states-factsheet\" target=\"_blank\" rel=\"noopener\">45 states reported\u003c/a> special education teacher shortages, and staff turnover is worse in schools that largely serve low-income students, like Riverview.\u003c/p>\n\u003cp>Some special educators say part of what makes them feel overworked is legally required paperwork layered on top of regular teaching duties. Acebu is one of a growing number of those teachers around the nation using AI to help speed up that paperwork — including for writing individualized education programs (IEPs). Educators and families maintain these detailed documents that outline goals and services students need to meet those goals at school.\u003c/p>\n\u003cp>According to \u003ca href=\"https://cdt.org/wp-content/uploads/2025/10/2025-10-28-CDT-AI-IEP-Brief-1.pdf\" target=\"_blank\" rel=\"noopener\">a recent survey\u003c/a> by the nonpartisan Center for Democracy and Technology (CDT), 57% of special education teachers polled nationwide said they used AI to help develop individualized plans for their students in the 2024-25 school year. That’s up from 39% the previous school year.\u003c/p>\n\u003cp>Along with the survey results, the CDT warned of privacy, legal and ethical risks around using AI. Other research, however, including from the University of Virginia (UVA) and the University of Central Florida (UCF), has shown that when used appropriately, AI can help special education teachers craft IEPs of equal or higher quality than when teachers produce them alone.\u003c/p>\n\u003cp>And the time saved can benefit students, too. “The more face time a student with a disability has with a teacher, that often yields better outcomes for them, both educationally, functionally — just across the board,” says Olivia Coleman, a researcher and professor at UCF who has been studying the role of AI in special education.\u003c/p>\n\u003cp>Acebu says that rings true in her classroom. She points out King, one of her eighth graders, as an example. “He was a non-reader, beginning of seventh grade. He’s reading now.” That, for Acebu, is the \u003cem>point\u003c/em> of IEPs — to put what’s on paper into practice for her students. She says that is only possible with intentional, hands-on work in the classroom.\u003c/p>\n\u003ch2>\u003cstrong>What IEPs are and why they matter\u003c/strong>\u003c/h2>\n\u003cp>Every seventh and eighth grader in Mary Acebu’s class learns differently — some work independently, some in pairs, others with headphones on and yet others with speech-to-text technology. Those differences are captured in each child’s IEP, a document required by federal law for each of the over 8 million students with disabilities in this country.\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/4000x2668+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F8d%2F57%2F8601fa57482dbd294f690c16221d%2F36a0496-tif.jpg\" alt=\"Mary Acebu has been a special education teacher for a decade at Riverview Middle School. She is part of a task force that is working on an AI policy for her school district.\">\u003cfigcaption>Mary Acebu has been a special education teacher for a decade at Riverview Middle School. She is part of a task force that is working on an AI policy for her school district.\u003cbr>\n\u003ccite> (Talia Herman for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>Every IEP includes annual goals tailored to each student’s present needs, but importantly, “also where you want them to go within the next year,” says Danielle Waterfield, Coleman’s research partner at UVA.\u003c/p>\n\u003cp>Both Coleman and Waterfield say while many teachers report feeling bogged down by the work that goes into developing IEPs, teachers also recognize they are a necessary tool for students with disabilities to get a quality education.\u003c/p>\n\u003cp>Acebu says that to develop those goals, teachers must know each student’s learning style intimately. “The key term is ‘individualized.’ No two kids are the same,” she says. For special educators, the process involves hours of meetings and a deep knowledge of complex education law and policy.\u003c/p>\n\u003cp>It used to take Acebu around 45 minutes to develop three or four IEP goals per student. She points to a big, blue binder at least 5 inches thick on her bookshelf that contains California’s education standards. “It used to be flipping through all those pages,” to find the right standard to match unique student goals, she says.\u003c/p>\n\u003cp>Then came AI.\u003c/p>\n\u003ch2>\u003cstrong>Using AI — with a ‘human touch’ \u003c/strong>\u003c/h2>\n\u003cp>A couple of years ago, Acebu began taking courses on how to safely and effectively use AI. Around the same time, her district, Mt. Diablo Unified, entered agreements with companies that offer education-focused AI tools including MagicSchool AI and Google. They promise to protect sensitive student data, a primary concern for those who warn against the risks of using AI in schools. A growing number of districts are adopting such products, though \u003ca href=\"https://www.edweek.org/technology/which-states-require-schools-to-have-ai-policies/2025/09\" target=\"_blank\" rel=\"noopener\">only a few states\u003c/a> have official AI education policies.\u003c/p>\n\u003cp>Recently, using a district-vetted tool, Acebu customized chatbots for her school and trained them on state standards, assessments and other special education data. She now uses her “little assistants” for a wide range of tasks, from creating personalized worksheets to developing IEP goals.\u003c/p>\n\u003cp>And then, she says, “you’re double-checking everything. Like you have to put that human touch, that’s the final step.”\u003c/p>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/4000x2668+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F5c%2F9b%2F7917c6324542801ed762bdb30d77%2F36a9904-tif.jpg\" alt=\"King, an eighth grader, went from not being able to read to reading confidently since he joined Acebu's class last year. She says that has been possible, in part, because AI has given her more time to work directly with students in the classroom and less on paperwork.\">\u003cfigcaption>King, an eighth grader, went from not being able to read to reading confidently since he joined Acebu’s class last year. She says that has been possible, in part, because AI has given her more time to work directly with students in the classroom and less on paperwork.\u003cbr>\n\u003ccite> (Talia Herman for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cfigure class=\"wp-block-image size-large\">\u003cimg decoding=\"async\" src=\"https://npr.brightspotcdn.com/dims3/default/strip/false/crop/4500x3000+0+0/resize/1200/quality/75/format/jpeg/?url=http%3A%2F%2Fnpr-brightspot.s3.amazonaws.com%2F46%2F00%2F54e6a456459fa6fb438ca613f8a0%2F36a9793-tif.jpg\" alt=\"For a science project, King made turtle pieces from clay. They are part of a board game he created with Acebu's help called Turtle Catastrophe. It was one of two projects from his school that was accepted at a local science fair.\">\u003cfigcaption>For a science project, King made turtle pieces from clay. They are part of a board game he created with Acebu’s help called Turtle Catastrophe. It was one of two projects from his school that was accepted at a local science fair.\u003cbr>\n\u003ccite> (Talia Herman for NPR)\u003c/cite>\u003c/figcaption>\u003c/figure>\n\u003cp>\u003ca href=\"https://journals.sagepub.com/doi/10.1177/01626434261419099\" target=\"_blank\" rel=\"noopener\">In their research,\u003c/a> Coleman and Waterfield found special education teachers nationwide are using AI to help write IEP goals, track student progress, synthesize data and create differentiated learning materials, among other things.\u003c/p>\n\u003cp>Acebu is uniquely equipped to use tech-tools: She just earned her doctorate in instructional technology and is on her district’s AI task force, which is developing an official AI policy.\u003c/p>\n\u003cp>Some of Acebu’s less tech-savvy colleagues, however, were skeptical, including Paul Stone, who has been a special educator at Riverview for 22 years.\u003c/p>\n\u003cp>Then the number of students he serves shot up.\u003c/p>\n\u003cp>“I don’t want to say it’s killing me, but it has put a huge stressor on my mental health and my life,” Stone says of his work this year. “It would be kind of nice if there were two jobs, like one paperwork job and one working with the kids.”\u003c/p>\n\u003cp>So, a few weeks ago, after a tutorial from Acebu, he gave her chatbot a shot. He was surprised by the results.\u003c/p>\n\u003cp>“It’s an amazing time-saver so far,” he says. Stone has used AI for a number of things including producing simple summaries of complicated data to present to parents at IEP meetings. “I mean, it’s not like ‘that’s it, I’m done.’ I still have to go through and check it all.”\u003c/p>\n\u003cp>He and Acebu both say it could help them, and other educators, avoid burnout. Yet, Ariana Aboulafia, who was the lead author of CDT’s report, calls AI tools “a Band-Aid” for special education teachers who feel overworked.\u003c/p>\n\u003ch2>\u003cstrong>Using AI in special education — with guardrails\u003c/strong>\u003c/h2>\n\u003cp>Band-Aid or not, more teachers \u003cem>are \u003c/em>using AI around the country. There are a litany of concerns about its use, especially in special education, which is highly regulated. “Student privacy is number one,” says Acebu. “Don’t put information there that’s gonna identify your students.” CDT’s Aboulafia adds that while the risks around privacy may be reduced if a school is using a vetted vendor, data breaches could still make that information vulnerable.\u003c/p>\n\u003cp>But not all teachers are using district-approved tools. Coleman, Waterfield and CDT’s research all found that educators around the country are using AI both formally and informally — from free consumer platforms like ChatGPT and Claude to district-approved tools like MagicSchool AI, Google Gemini and Playground IEP, among others. To help teachers navigate this complicated landscape, Waterfield and Coleman \u003ca href=\"https://ciddl.org/navigating-ai-in-iep-development-a-framework-for-ethical-practice/\" target=\"_blank\" rel=\"noopener\">developed a “decision tree”\u003c/a> for ethical AI use.\u003c/p>\n\u003cp>Another consideration is the fact that AI models can be biased, including against people with disabilities, says Aboulafia, who leads the Disability Rights in Technology Policy Project at CDT. In addition, she worries AI models built on pattern recognition are, “to a certain extent, inherently incompatible with a process that legally requires individualization.”\u003c/p>\n\u003cp>Aboulafia is most concerned about the 15% of teachers CDT’s survey found have been relying entirely on AI to develop IEPs. There must always be a “human in the loop,” she says.\u003c/p>\n\u003cp>Acebu, who happens to be her district’s teacher of the year, says these days, she comes to class just 30 minutes before her students, and leaves just after the last bell. This has improved her work-life balance and the quality of her teaching.\u003c/p>\n\u003cp>King, the eighth grader in her class who has evolved into a confident reader, also goes to math class now without any additional support.\u003c/p>\n\u003cp>“That’s the dream of every special educator,” she says, beaming. “But guess what? That takes a lot of hard work.”\u003c/p>\n\u003cp>AI tools, Acebu says, have given her more time for that kind of hard work.\u003c/p>\n\u003cp>\u003c/p>\u003c/div>",
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"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Bay-Curious-Podcast-Tile-703x703-1.jpg",
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"officialWebsiteLink": "/news/series/baycurious",
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"source": "kqed",
"order": 3
},
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"npr": "https://www.npr.org/podcasts/500557090/bay-curious",
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}
},
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"id": "bbc-world-service",
"title": "BBC World Service",
"info": "The day's top stories from BBC News compiled twice daily in the week, once at weekends.",
"airtime": "MON-FRI 9pm-10pm, TUE-FRI 1am-2am",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/BBC-World-Service-Podcast-Tile-360x360-1.jpg",
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"meta": {
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"source": "BBC World Service"
},
"link": "/radio/program/bbc-world-service",
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"rss": "https://podcasts.files.bbci.co.uk/p02nq0gn.rss"
}
},
"californiareport": {
"id": "californiareport",
"title": "The California Report",
"tagline": "California, day by day",
"info": "KQED’s statewide radio news program providing daily coverage of issues, trends and public policy decisions.",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/The-California-Report-Podcast-Tile-703x703-1.jpg",
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"officialWebsiteLink": "/californiareport",
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"source": "kqed",
"order": 8
},
"link": "/californiareport",
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}
},
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"id": "californiareportmagazine",
"title": "The California Report Magazine",
"tagline": "Your state, your stories",
"info": "Every week, The California Report Magazine takes you on a road trip for the ears: to visit the places and meet the people who make California unique. The in-depth storytelling podcast from the California Report.",
"airtime": "FRI 4:30pm-5pm, 6:30pm-7pm, 11pm-11:30pm",
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"officialWebsiteLink": "/californiareportmagazine",
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"order": 10
},
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"google": "https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5tZWdhcGhvbmUuZm0vS1FJTkM3NjkwNjk1OTAz",
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},
"city-arts": {
"id": "city-arts",
"title": "City Arts & Lectures",
"info": "A one-hour radio program to hear celebrated writers, artists and thinkers address contemporary ideas and values, often discussing the creative process. Please note: tapes or transcripts are not available",
"imageSrc": "https://ww2.kqed.org/radio/wp-content/uploads/sites/50/2018/05/cityartsandlecture-300x300.jpg",
"officialWebsiteLink": "https://www.cityarts.net/",
"airtime": "SUN 1pm-2pm, TUE 10pm, WED 1am",
"meta": {
"site": "news",
"source": "City Arts & Lectures"
},
"link": "https://www.cityarts.net",
"subscribe": {
"tuneIn": "https://tunein.com/radio/City-Arts-and-Lectures-p692/",
"rss": "https://www.cityarts.net/feed/"
}
},
"closealltabs": {
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"info": "Close All Tabs breaks down how digital culture shapes our world through thoughtful insights and irreverent humor.",
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"officialWebsiteLink": "/podcasts/closealltabs",
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"source": "kqed",
"order": 1
},
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"id": "code-switch-life-kit",
"title": "Code Switch / Life Kit",
"info": "\u003cem>Code Switch\u003c/em>, which listeners will hear in the first part of the hour, has fearless and much-needed conversations about race. Hosted by journalists of color, the show tackles the subject of race head-on, exploring how it impacts every part of society — from politics and pop culture to history, sports and more.\u003cbr />\u003cbr />\u003cem>Life Kit\u003c/em>, which will be in the second part of the hour, guides you through spaces and feelings no one prepares you for — from finances to mental health, from workplace microaggressions to imposter syndrome, from relationships to parenting. The show features experts with real world experience and shares their knowledge. Because everyone needs a little help being human.\u003cbr />\u003cbr />\u003ca href=\"https://www.npr.org/podcasts/510312/codeswitch\">\u003cem>Code Switch\u003c/em> offical site and podcast\u003c/a>\u003cbr />\u003ca href=\"https://www.npr.org/lifekit\">\u003cem>Life Kit\u003c/em> offical site and podcast\u003c/a>\u003cbr />",
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"meta": {
"site": "radio",
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},
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"id": "commonwealth-club",
"title": "Commonwealth Club of California Podcast",
"info": "The Commonwealth Club of California is the nation's oldest and largest public affairs forum. As a non-partisan forum, The Club brings to the public airwaves diverse viewpoints on important topics. The Club's weekly radio broadcast - the oldest in the U.S., dating back to 1924 - is carried across the nation on public radio stations and is now podcasting. Our website archive features audio of our recent programs, as well as selected speeches from our long and distinguished history. This podcast feed is usually updated twice a week and is always un-edited.",
"airtime": "THU 10pm, FRI 1am",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Commonwealth-Club-Podcast-Tile-360x360-1.jpg",
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"meta": {
"site": "news",
"source": "Commonwealth Club of California"
},
"link": "/radio/program/commonwealth-club",
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"apple": "https://itunes.apple.com/us/podcast/commonwealth-club-of-california-podcast/id976334034?mt=2",
"google": "https://podcasts.google.com/feed/aHR0cDovL3d3dy5jb21tb253ZWFsdGhjbHViLm9yZy9hdWRpby9wb2RjYXN0L3dlZWtseS54bWw",
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"id": "forum",
"title": "Forum",
"tagline": "The conversation starts here",
"info": "KQED’s live call-in program discussing local, state, national and international issues, as well as in-depth interviews.",
"airtime": "MON-FRI 9am-11am, 10pm-11pm",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Forum-Podcast-Tile-703x703-1.jpg",
"imageAlt": "KQED Forum with Mina Kim and Alexis Madrigal",
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"meta": {
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"source": "kqed",
"order": 9
},
"link": "/forum",
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"google": "https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5tZWdhcGhvbmUuZm0vS1FJTkM5NTU3MzgxNjMz",
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"freakonomics-radio": {
"id": "freakonomics-radio",
"title": "Freakonomics Radio",
"info": "Freakonomics Radio is a one-hour award-winning podcast and public-radio project hosted by Stephen Dubner, with co-author Steve Levitt as a regular guest. It is produced in partnership with WNYC.",
"imageSrc": "https://ww2.kqed.org/news/wp-content/uploads/sites/10/2018/05/freakonomicsRadio.png",
"officialWebsiteLink": "http://freakonomics.com/",
"airtime": "SUN 1am-2am, SAT 3pm-4pm",
"meta": {
"site": "radio",
"source": "WNYC"
},
"link": "/radio/program/freakonomics-radio",
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"apple": "https://itunes.apple.com/us/podcast/freakonomics-radio/id354668519",
"tuneIn": "https://tunein.com/podcasts/WNYC-Podcasts/Freakonomics-Radio-p272293/",
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},
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"id": "fresh-air",
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"info": "Hosted by Terry Gross, \u003cem>Fresh Air from WHYY\u003c/em> is the Peabody Award-winning weekday magazine of contemporary arts and issues. One of public radio's most popular programs, Fresh Air features intimate conversations with today's biggest luminaries.",
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"link": "/radio/program/fresh-air",
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"apple": "https://itunes.apple.com/WebObjects/MZStore.woa/wa/viewPodcast?s=143441&mt=2&id=214089682&at=11l79Y&ct=nprdirectory",
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"info": "A live production of NPR and WBUR Boston, in collaboration with stations across the country, Here & Now reflects the fluid world of news as it's happening in the middle of the day, with timely, in-depth news, interviews and conversation. Hosted by Robin Young, Jeremy Hobson and Tonya Mosley.",
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"hidden-brain": {
"id": "hidden-brain",
"title": "Hidden Brain",
"info": "Shankar Vedantam uses science and storytelling to reveal the unconscious patterns that drive human behavior, shape our choices and direct our relationships.",
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"airtime": "SUN 7pm-8pm",
"meta": {
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"source": "NPR"
},
"link": "/radio/program/hidden-brain",
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},
"how-i-built-this": {
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"title": "How I Built This with Guy Raz",
"info": "Guy Raz dives into the stories behind some of the world's best known companies. How I Built This weaves a narrative journey about innovators, entrepreneurs and idealists—and the movements they built.",
"imageSrc": "https://ww2.kqed.org/news/wp-content/uploads/sites/10/2018/05/howIBuiltThis.png",
"officialWebsiteLink": "https://www.npr.org/podcasts/510313/how-i-built-this",
"airtime": "SUN 7:30pm-8pm",
"meta": {
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"source": "npr"
},
"link": "/radio/program/how-i-built-this",
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"apple": "https://itunes.apple.com/us/podcast/how-i-built-this-with-guy-raz/id1150510297?mt=2",
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},
"hyphenacion": {
"id": "hyphenacion",
"title": "Hyphenación",
"tagline": "Where conversation and cultura meet",
"info": "What kind of no sabo word is Hyphenación? For us, it’s about living within a hyphenation. Like being a third-gen Mexican-American from the Texas border now living that Bay Area Chicano life. Like Xorje! Each week we bring together a couple of hyphenated Latinos to talk all about personal life choices: family, careers, relationships, belonging … everything is on the table. ",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2025/03/Hyphenacion_FinalAssets_PodcastTile.png",
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"officialWebsiteLink": "/podcasts/hyphenacion",
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"order": 15
},
"link": "/podcasts/hyphenacion",
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},
"jerrybrown": {
"id": "jerrybrown",
"title": "The Political Mind of Jerry Brown",
"tagline": "Lessons from a lifetime in politics",
"info": "The Political Mind of Jerry Brown brings listeners the wisdom of the former Governor, Mayor, and presidential candidate. Scott Shafer interviewed Brown for more than 40 hours, covering the former governor's life and half-century in the political game – and Brown has some lessons he'd like to share. ",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/The-Political-Mind-of-Jerry-Brown-Podcast-Tile-703x703-1.jpg",
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"officialWebsiteLink": "/podcasts/jerrybrown",
"meta": {
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"order": 18
},
"link": "/podcasts/jerrybrown",
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}
},
"latino-usa": {
"id": "latino-usa",
"title": "Latino USA",
"airtime": "MON 1am-2am, SUN 6pm-7pm",
"info": "Latino USA, the radio journal of news and culture, is the only national, English-language radio program produced from a Latino perspective.",
"imageSrc": "https://ww2.kqed.org/radio/wp-content/uploads/sites/50/2018/04/latinoUsa.jpg",
"officialWebsiteLink": "http://latinousa.org/",
"meta": {
"site": "news",
"source": "npr"
},
"link": "/radio/program/latino-usa",
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"apple": "https://itunes.apple.com/WebObjects/MZStore.woa/wa/viewPodcast?s=143441&mt=2&id=79681317&at=11l79Y&ct=nprdirectory",
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"rss": "https://feeds.npr.org/510016/podcast.xml"
}
},
"marketplace": {
"id": "marketplace",
"title": "Marketplace",
"info": "Our flagship program, helmed by Kai Ryssdal, examines what the day in money delivered, through stories, conversations, newsworthy numbers and more. Updated Monday through Friday at about 3:30 p.m. PT.",
"airtime": "MON-FRI 4pm-4:30pm, MON-WED 6:30pm-7pm",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Marketplace-Podcast-Tile-360x360-1.jpg",
"officialWebsiteLink": "https://www.marketplace.org/",
"meta": {
"site": "news",
"source": "American Public Media"
},
"link": "/radio/program/marketplace",
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"rss": "https://feeds.publicradio.org/public_feeds/marketplace-pm/rss/rss"
}
},
"masters-of-scale": {
"id": "masters-of-scale",
"title": "Masters of Scale",
"info": "Masters of Scale is an original podcast in which LinkedIn co-founder and Greylock Partner Reid Hoffman sets out to describe and prove theories that explain how great entrepreneurs take their companies from zero to a gazillion in ingenious fashion.",
"airtime": "Every other Wednesday June 12 through October 16 at 8pm (repeats Thursdays at 2am)",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Masters-of-Scale-Podcast-Tile-360x360-1.jpg",
"officialWebsiteLink": "https://mastersofscale.com/",
"meta": {
"site": "radio",
"source": "WaitWhat"
},
"link": "/radio/program/masters-of-scale",
"subscribe": {
"apple": "http://mastersofscale.app.link/",
"rss": "https://rss.art19.com/masters-of-scale"
}
},
"mindshift": {
"id": "mindshift",
"title": "MindShift",
"tagline": "A podcast about the future of learning and how we raise our kids",
"info": "The MindShift podcast explores the innovations in education that are shaping how kids learn. Hosts Ki Sung and Katrina Schwartz introduce listeners to educators, researchers, parents and students who are developing effective ways to improve how kids learn. We cover topics like how fed-up administrators are developing surprising tactics to deal with classroom disruptions; how listening to podcasts are helping kids develop reading skills; the consequences of overparenting; and why interdisciplinary learning can engage students on all ends of the traditional achievement spectrum. This podcast is part of the MindShift education site, a division of KQED News. KQED is an NPR/PBS member station based in San Francisco. You can also visit the MindShift website for episodes and supplemental blog posts or tweet us \u003ca href=\"https://twitter.com/MindShiftKQED\">@MindShiftKQED\u003c/a> or visit us at \u003ca href=\"/mindshift\">MindShift.KQED.org\u003c/a>",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Mindshift-Podcast-Tile-703x703-1.jpg",
"imageAlt": "KQED MindShift: How We Will Learn",
"officialWebsiteLink": "/mindshift/",
"meta": {
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"source": "kqed",
"order": 12
},
"link": "/podcasts/mindshift",
"subscribe": {
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"google": "https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5tZWdhcGhvbmUuZm0vS1FJTkM1NzY0NjAwNDI5",
"npr": "https://www.npr.org/podcasts/464615685/mind-shift-podcast",
"stitcher": "https://www.stitcher.com/podcast/kqed/stories-teachers-share",
"spotify": "https://open.spotify.com/show/0MxSpNYZKNprFLCl7eEtyx"
}
},
"morning-edition": {
"id": "morning-edition",
"title": "Morning Edition",
"info": "\u003cem>Morning Edition\u003c/em> takes listeners around the country and the world with multi-faceted stories and commentaries every weekday. Hosts Steve Inskeep, David Greene and Rachel Martin bring you the latest breaking news and features to prepare you for the day.",
"airtime": "MON-FRI 3am-9am",
"imageSrc": "https://cdn.kqed.org/wp-content/uploads/2024/04/Morning-Edition-Podcast-Tile-360x360-1.jpg",
"officialWebsiteLink": "https://www.npr.org/programs/morning-edition/",
"meta": {
"site": "news",
"source": "npr"
},
"link": "/radio/program/morning-edition"
},
"onourwatch": {
"id": "onourwatch",
"title": "On Our Watch",
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