HỆ THỐNG MÁY TÍNH

Câu 1: Đặc trưng nào sau đây là một trong những yếu tố cốt lõi của trí tuệ nhân tạo? A. Tự động hóa quy trình làm việc B. Khả năng học tập và thích nghi từ dữ liệu C. Khả năng sử dụng năng lượng hiệu quả D. Thực hiện các phép tính toán học nhanh chóng Đáp án: B. Khả năng học tập và thích nghi từ dữ liệu Câu 2: Trí tuệ nhân tạo (AI) chủ yếu được sử dụng để làm gì? A. Phân tích dữ liệu và đưa ra quyết định dựa trên dữ liệu B. Thiết kế hệ thống mạng C. Giảm lượng tiêu thụ điện năng D. Thực hiện các công việc thể chất Đáp án: A. Phân tích dữ liệu và đưa ra quyết định dựa trên dữ liệu Câu 3: Hệ thống AI được gọi là “học máy” (machine learning) khi nó có khả năng: A. Tự động sửa chữa lỗi trong phần mềm B. Tạo ra các hệ thống mạng bảo mật C. Học hỏi và cải thiện hiệu suất mà không cần lập trình rõ ràng D. Tăng tốc độ xử lý của phần cứng Đáp án: C. Học hỏi và cải thiện hiệu suất Câu 4: Khả năng học của AI liên quan đến yếu tố nào sau đây? A. Học từ kinh nghiệm và dữ liệu mới để cải thiện hiệu suất B. Ghi nhớ tất cả các lệnh do con người cung cấp C. Chạy các chương trình mà không cần cập nhật D. Sửa lỗi phần mềm một cách tự động Đáp án: A. Học từ kinh nghiệm và dữ liệu mới để cải thiện hiệu suất Câu 5: Khả năng suy luận trong AI giúp hệ thống thực hiện điều gì? A. Phát triển khả năng thể hiện cảm xúc B. Sử dụng thông tin để đưa ra các quyết định có căn cứ C. Tăng tốc độ xử lý dữ liệu D. Sao chép chính xác các hành vi của con người Đáp án: B. Sử dụng thông tin để đưa ra các quyết định có căn cứ Câu 6: Khả năng nhận thức của AI là gì? A. Khả năng tự nhận biết và điều chỉnh hành vi của nó dựa trên môi trường B. Khả năng xử lý dữ liệu với tốc độ nhanh hơn C. Khả năng làm việc liên tục không cần nghỉ D. Khả năng thu thập dữ liệu từ các cảm biến và hệ thống khác Đáp án: A. Khả năng tự nhận biết và điều chỉnh hành vi của nó dựa trên môi trường Câu 7: Khả năng hiểu ngôn ngữ tự nhiên (NLP) của AI cho phép hệ thống: A. Xử lý văn bản và ngôn ngữ giống như con người B. Dịch thuật chính xác từ ngôn ngữ này sang ngôn ngữ khác C. Thay thế hoàn toàn con người trong việc viết và giao tiếp D. Tăng cường khả năng suy nghĩ trừu tượng Đáp án: A. Xử lý văn bản và ngôn ngữ giống như con người Câu 8: AI có khả năng giải quyết vấn đề khi nào? A. Khi nó sử dụng các thuật toán để tìm ra giải pháp tối ưu cho các vấn đề phức tạp B. Khi nó thay thế toàn bộ con người trong mọi công việc C. Khi nó tự động sửa chữa các lỗi phần mềm D. Khi nó cung cấp thông tin chi tiết về dữ liệu mà không cần bất kỳ sự can thiệp nào Đáp án: A. Khi nó sử dụng các thuật toán để tìm ra giải pháp tối ưu cho các vấn đề phức tạp Câu 9: Khả năng học của AI là gì? A. AI có thể học từ dữ liệu và kinh nghiệm mới. B. AI có thể tự sửa lỗi mà không cần dữ liệu đầu vào. C. AI có thể cải thiện hiệu suất thông qua học tập. D. AI không cần cập nhật khi học tập từ dữ liệu. Đáp án: • Đúng: A, C • Sai: B, D Câu 10: Khả năng suy luận của AI giúp hệ thống thực hiện điều gì? A. AI có thể đưa ra quyết định dựa trên dữ liệu. B. AI có thể suy nghĩ giống con người mà không cần dữ liệu. C. AI sử dụng thông tin để phân tích và đưa ra lựa chọn hợp lý. D. AI tự động đưa ra quyết định mà không cần học tập trước đó. Đáp án: • Đúng: A, C • Sai: B, D Câu 11: AI có khả năng nhận thức và điều chỉnh hành vi dựa trên môi trường xung quanh không? A. AI có thể nhận biết thay đổi trong môi trường và điều chỉnh hành vi. B. AI luôn cần con người giám sát để đưa ra quyết định. C. AI tự động thay đổi mà không cần lập trình lại khi môi trường thay đổi. D. AI không có khả năng điều chỉnh theo môi trường. Đáp án: • Đúng: A, C • Sai: B, D Câu 12: Khả năng giải quyết vấn đề của AI được biểu hiện như thế nào? A. AI có thể áp dụng các thuật toán để tìm ra giải pháp tối ưu. B. AI giải quyết vấn đề mà không cần dữ liệu đầu vào. C. AI tự động phân tích và đưa ra các phương án giải quyết dựa trên dữ liệu. D. AI chỉ có thể giải quyết vấn đề khi được lập trình trước. Đáp án: • Đúng: A, C • Sai: B, D

“There’s No Such Thing as Sound Science” by By Christie Aschwanden was a lead science writer for FiveThirtyEight. FiveThirtyEight, Science, Dec. 6, 2017 Science is being turned against itself. For decades, its twin ideals of transparency and rigor have been weaponized by those who disagree with results produced by the scientific method. Under the Trump administration, that fight has ramped up again. In a move ostensibly meant to reduce conflicts of interest, Environmental Protection Agency Administrator Scott Pruitt has removed a number of scientists from advisory panels and replaced some of them with representatives from industries that the agency regulates. Like many in the Trump administration, Pruitt has also cast doubt on the reliability of climate science. For instance, in an interview with CNBC, Pruitt said that “measuring with precision human activity on the climate is something very challenging to do.” Similarly, Trump’s pick to head NASA, an agency that oversees a large portion the nation’s climate research, has insisted that research into human influence on climate lacks certainty, and he falsely claimed that “global temperatures stopped rising 10 years ago.” Kathleen Hartnett White, Trump’s nominee to head the White House Council on Environmental Quality, said in a Senate hearing last month that she thinks we “need to have more precise explanations of the human role and the natural role” in climate change. The same entreaties crop up again and again: We need to root out conflicts. We need more precise evidence. What makes these arguments so powerful is that they sound quite similar to the points raised by proponents of a very different call for change that’s coming from within science. This other movement strives to produce more robust, reproducible findings. Despite having dissimilar goals, the two forces espouse principles that look surprisingly alike: Science needs to be transparent. Results and methods should be openly shared so that outside researchers can independently reproduce and validate them. The methods used to collect and analyze data should be rigorous and clear, and conclusions must be supported by evidence. These are the arguments underlying an “open science” reform movement that was created, in part, as a response to a “reproducibility crisis” that has struck some fields of science.1 But they’re also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on “sound science.” Science’s virtues are being wielded against it. What distinguishes the two calls for transparency is intent: Whereas the “open science” movement aims to make science more reliable, reproducible and robust, proponents of “sound science” have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests. “Our criticisms are founded in a confidence in science,” said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. “That’s a fundamental difference — we’re critiquing science to make it better. Others are critiquing it to devalue the approach itself.” Calls to base public policy on “sound science” seem unassailable if you don’t know the term’s history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer. A 1992 Environmental Protection Agency report identified secondhand smoke as a human carcinogen, and Philip Morris responded by launching an initiative to promote what it called “sound science.” In an internal memo, Philip Morris vice president of corporate affairs Ellen Merlo wrote that the program was designed to “discredit the EPA report,” “prevent states and cities, as well as businesses from passing smoking bans” and “proactively” pass legislation to help their cause. The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how it’s sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, it’s a process of uncertainty reduction, much like a game of 20 Questions. Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. “Science is a process rather than an answer,” said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. It’s not entirely correct to say that “this study proves this fact,” Ledgerwood said. “We should be talking instead about how science increases or decreases our confidence in something.” The tobacco industry’s brilliant tactic was to turn this baked-in uncertainty against the scientific enterprise itself. While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve. “Doubt is our product,” wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt “is the best means of competing with the ‘body of fact’” and “establishing a controversy.” These strategies for undermining inconvenient science were so effective that they’ve served as a sort of playbook for industry interests ever since, said Stanford University science historian Robert Proctor. The sound science push is no longer just Philip Morris sowing doubt about the links between cigarettes and cancer. It’s also a 1998 action plan by the American Petroleum Institute, Chevron and Exxon Mobil to “install uncertainty” about the link between greenhouse gas emissions and climate change. It’s industry-funded groups’ late-1990s effort to question the science the EPA was using to set fine-particle-pollution air-quality standards that the industry didn’t want. And then there was the more recent effort by Dow Chemical to insist on more scientific certainty before banning a pesticide that the EPA’s scientists had deemed risky to children. Now comes a move by the Trump administration’s EPA to repeal a 2015 rule on wetlands protection by disregarding particular studies. (To name just a few examples.) Doubt merchants aren’t pushing for knowledge, they’re practicing what Proctor has dubbed “agnogenesis” — the intentional manufacture of ignorance. This ignorance isn’t simply the absence of knowing something; it’s a lack of comprehension deliberately created by agents who don’t want you to know, Proctor said.2 In the hands of doubt-makers, transparency becomes a rhetorical move. “It’s really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?” said Karen Levy, researcher on information science at Cornell University. But at the same time, “you can couch everything in the language of transparency and it becomes a powerful weapon.” For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money. Delay is a time-tested strategy. “Gridlock is the greatest friend a global warming skeptic has,” said Marc Morano, a prominent critic of global warming research and the executive director of ClimateDepot.com, in the documentary “Merchants of Doubt” (based on the book by the same name). Morano’s site is a project of the Committee for a Constructive Tomorrow, which has received funding from the oil and gas industry. “We’re the negative force. We’re just trying to stop stuff.” Some of these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the “quality, objectivity, utility, and integrity of information” that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. “It was passed in this very quiet way with no explicit debate about it — that should tell you a lot about the real goals,” Levy said. But what’s most telling about the Data Quality Act is how it’s been used, Levy said. A 2004 Washington Post analysis found that in the 20 months following its implementation, the act was repeatedly used by industry groups to push back against proposed regulations and bog down the decision-making process. Instead of deploying transparency as a fundamental principle that applies to all science, these interests have used transparency as a weapon to attack very particular findings that they would like to eradicate. Now Congress is considering another way to legislate how science is used. The Honest Act, a bill sponsored by Rep. Lamar Smith of Texas,3 is another example of what Levy calls a “Trojan horse” law that uses the language of transparency as a cover to achieve other political goals. Smith’s legislation would severely limit the kind of evidence the EPA could use for decision-making. Only studies whose raw data and computer codes were publicly available would be allowed for consideration. That might sound perfectly reasonable, and in many cases it is, Goodman said. But sometimes there are good reasons why researchers can’t conform to these rules, like when the data contains confidential or sensitive medical information.4 Critics, which include more than a dozen scientific organizations, argue that, in practice, the rules would prevent many studies from being considered in EPA reviews.5 It might seem like an easy task to sort good science from bad, but in reality it’s not so simple. “There’s a misplaced idea that we can definitively distinguish the good from the not-good science, but it’s all a matter of degree,” said Brian Nosek, executive director of the Center for Open Science. “There is no perfect study.” Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially “a way of saying, ‘We don’t want to use evidence for our decision-making,’” Nosek said. Most scientific controversies aren’t about science at all, and once the sides are drawn, more data is unlikely to bring opponents into agreement. Michael Carolan, who researches the sociology of technology and scientific knowledge at Colorado State University, wrote in a 2008 paper about why objective knowledge is not enough to resolve environmental controversies. “While these controversies may appear on the surface to rest on disputed questions of fact, beneath often reside differing positions of value; values that can give shape to differing understandings of what ‘the facts’ are.” What’s needed in these cases isn’t more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. “As long as we continue down this unabashedly naive road about what science is, and what it is capable of doing, we will continue to fail to reach any sort of meaningful consensus on these matters,” Carolan writes. The dispute over tobacco was never about the science of cigarettes’ link to cancer. It was about whether companies have the right to sell dangerous products and, if so, what obligations they have to the consumers who purchased them. Similarly, the debate over climate change isn’t about whether our planet is heating, but about how much responsibility each country and person bears for stopping it. While researching her book “Merchants of Doubt,” science historian Naomi Oreskes found that some of the same people who were defending the tobacco industry as scientific experts were also receiving industry money to deny the role of human activity in global warming. What these issues had in common, she realized, was that they all involved the need for government action. “None of this is about the science. All of this is a political debate about the role of government,” she said in the documentary. These controversies are really about values, not scientific facts, and acknowledging that would allow us to have more truthful and productive debates. What would that look like in practice? Instead of cherry-picking evidence to support a particular view (and insisting that the science points to a desired action), the various sides could lay out the values they are using to assess the evidence. For instance, in Europe, many decisions are guided by the precautionary principle — a system that values caution in the face of uncertainty and says that when the risks are unclear, it should be up to industries to show that their products and processes are not harmful, rather than requiring the government to prove that they are harmful before they can be regulated. By contrast, U.S. agencies tend to wait for strong evidence of harm before issuing regulations. Both approaches have critics, but the difference between them comes down to priorities: Is it better to exercise caution at the risk of burdening companies and perhaps the economy, or is it more important to avoid potential economic downsides even if it means that sometimes a harmful product or industrial process goes unregulated? In other words, under what circumstances do we agree to act on a risk? How certain do we need to be that the risk is real, and how many people would need to be at risk, and how costly is it to reduce that risk? Those are moral questions, not scientific ones, and openly discussing and identifying these kinds of judgment calls would lead to a more honest debate. Science matters, and we need to do it as rigorously as possible. But science can’t tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold — those are value judgements that only humans can make.

Make a multiple choice quiz for my year 8 science students based on the science in this transcript from a video: 3°C 0:04 It can be the difference between snow and sleet 0:08 Wearing a jacket or not 0:11 In your day-to-day life, it may not seem significant 0:15 But 3°C of global warming would be catastrophic 0:20 Heatwaves, droughts, extreme precipitation, even fire 0:25 3°C of warming is really disastrous 0:28 The scary thing is, the world is well on its way there 0:32 Since the industrial revolution, the Earth has warmed between 1.1°C and 1.3°C 0:40 This is a problem that babies you pass in the street will have to live with 0:46 Children born today... 0:47 ...are up to seven times more likely to face extreme weather than their grandparents 0:52 If global temperatures do rise by 3°C... 0:55 ...what would their world look like? Climate change is already having devastating effects 1:03 Rising sea levels 1:05 Desertification 1:07 Hollywood has always enjoyed imagining the end of the world 1:11 While blockbusters like this are clearly fiction... 1:14 ...this film will show the scenario we all face... 1:17 ...unless more drastic measures are taken to stop burning fossil fuels 1:30 In some parts of the world the effects of inaction are already clear 1:35 The slums of Bangladesh’s capital are filling up with climate migrants 1:41 Minara comes from Bhola District, an area in southern Bangladesh 1:46 There, like many other parts of the country... 1:49 ...rivers swollen by heavier rain and melting Himalayan glaciers... 1:53 ...are washing away people’s homes 1:56 Many, like her, have lost everything 2:00 Our home in Bhola had endless amounts of land 2:03 There was lots of space for farming, we had a spacious house 2:08 There were different types of fruits, vegetation and trees growing at home 2:12 We used to eat the fruit from our own trees 2:18 I can’t eat them now because they don't exist anymore 2:21 Since the river flooded for the third time, I had to flee to Dhaka 2:26 Life was much better back home 2:29 It was unbearable to live through, truly intolerable 2:33 We didn’t have the time to save anything at all 2:38 1.1°C to 1.3°C of global warming has already transformed Minara’s life 2:45 It’s one of the reasons why so many migrants like her... 2:47 ...are moving to the city each year... 2:50 ...nearly 400,000 according to the last estimate 2:53 And climate models show there could be much worse to come How climate modelling works 3:02 Climate scientist Joeri Rogelj... 3:04 ...has spent the last ten years modelling future climate scenarios... 3:08 ...for the United Nations 3:10 The models we use to carry out this exercise... 3:13 ...really represent the state of the art... 3:15 ...of our current knowledge of climate change and where we are heading 3:19 Joeri’s projections use data collected by hundreds of scientists around the world 3:26 Here this is the 3°C level... 3:28 ...and so there is at least a one-in-four chance that under current policies... 3:32 ...we would hit 3°C by the end of the century 3:36 This is just one of the scenarios Joeri looks at 3:40 Another one imagines that all policy promises are kept 3:44 The most optimistic assumes that all promises have been kept... 3:47 ...and net-zero targets are met 3:50 Where our best estimate ends up around 2°C at the end of the century... 3:54 ...there is still a one-in-20 chance that we end up with 3°C instead 3:59 One would not be entering a plane if there is a one-in-20 chance... 4:03 ...that the plane will crash Nowhere is safe from global warming 4:07 A rise of 3°C would affect everyone 4:10 Even wealthy cities in rich countries wouldn’t be immune to the consequences 4:15 European capitals like Paris and Berlin... 4:18 ...would bake under more extreme heatwaves 4:22 Frequent storm-surges in New York could turn parts of the city desolate 4:27 In many ways, cities magnify, intensify climate events 4:33 Cities are hotter than the places around them... 4:36 ...they tend to be more vulnerable to flooding 4:39 And you can get a really bad event in a city in a way that you can’t in the countryside 4:46 And because of their denser populations... 4:49 ...disasters in a city affect far more people 4:52 Some cities might be badly prepared for the changes coming 4:56 But they have the means to adapt 4:59 Cities tend to be wealthier than surrounding places 5:03 They have a lot of amenities 5:05 A city that has taken seriously the risks of a 3°C world... 5:08 …wouldn’t necessarily be a worse place to be in a 3°C world 5:12 But a city that hasn’t prepared for these sort of eventualities... 5:16 ...that might be a really nasty place The impact of prolonged droughts 5:20 So far, many developed cities have got off lightly... 5:24 ...but some rural parts of the world are suffering disproportionately 5:29 Smallholders—small-scale farmers—are particularly vulnerable to climate change 5:35 And there are over 600 million around the world 5:38 Smallholders with farms under two hectares... 5:40 ...produce around a third of the global food supply 5:46 Central America’s “Dry Corridor”... 5:48 ...supports a mix of smallholdings and medium-sized farms 5:53 Sandwiched between the Pacific Ocean and the Caribbean Sea... 5:56 ...the area is prone to droughts 6:08 Israel Ramírez Rivera is a smallholder in Guatemala 6:12 Here, climate change is making the dry seasons longer, and more severe 6:18 This is the biggest ear of maize that this plot could deliver 6:23 He depends on his crops of corn and beans 6:26 But they’re getting harder to grow 6:30 The surrounding mountains... 6:32 ...used to provide us with native food... 6:38 ...and now that isn’t an option anymore... 6:41 ...due to climate change and its effects 6:46 Nearly two-thirds of the smallholders in the Dry Corridor now live in poverty 6:52 The impact of all of this for us... 6:59 ...malnutrition among children 7:03 We’ve lost a few 7:07 For my crops especially, the midsummer heat is harder than before 7:16 The plant dries up and can’t provide us... 7:19 ...with the necessary food provision 7:24 Severe droughts in Central America... 7:26 ...are now four times more likely than they were last century 7:30 Many families from here have gone to the States 7:37 The economic despair and debts... 7:44 ...have pushed many people from this community to do this journey 7:53 Migration from Guatemala to the United States has quadrupled since 1990 7:59 Not all of this has been due to climate change 8:02 But longer droughts would force even more to move 8:05 In a 3°C world, annual rainfall in this region... 8:09 ...could drop by up to 14% 8:12 At 3°C, over a quarter of the world’s population... 8:16 ...could endure extreme droughts for at least a month of the year 8:19 Northern Africa could see droughts that last for years at a time Rising sea levels, storm surges and flooding 8:24 But for some, too much water will be the problem 8:29 10% of the world’s population lives on a coastline... 8:32 ...that’s less than 10 metres above sea level 8:35 For these coastal inhabitants, a 3°C world would spell disaster 8:40 By 2100, global sea levels could have climbed by half a metre from 2005 levels 8:46 Low-lying cities like Lagos would be especially vulnerable... 8:49 ...with up to up to a third of the population displaced 8:54 And in Fiji, rising waters are already upending lives 9:04 You can see the graveyard there, it’s all under water now... 9:08 ...due to this rising sea level and climate change 9:15 The village of Togoru in Fiji is being swallowed by the sea 9:19 Barney Dunn, the village headman, has seen over half the village disappear 9:24 Relatives’ houses have been abandoned, and family graves are now under water 9:29 We have been asked by the government to relocate... 9:32 ...but no one wants to relocate... 9:34 ...because we have our great-great-grandparents down there in the sea 9:39 This is the place we’ve been brought up in 9:41 ...it’s not easy to leave 9:44 Past attempts to build a seawall haven’t worked 9:48 But Barney sees building a new one as the village’s only hope 9:52 If they do that, maybe we can save whatever is left 9:56 But if we don’t have the seawall, then it will be keep eroding and time will come... 10:01 ...maybe in ten,15 years, Togoru will be all eroded 10:05 Rising seas also mean storms cause more floods 10:11 And many more countries could suffer 10:14 The Philippines and Myanmar are just two countries... 10:17 ...that will also see an increase in storm surges in a 3°C world 10:21 To escape, many will move… 10:24 …often, to urban areas Extreme heat and wet-bulb temperatures 10:27 Half the world’s population already lives in cities... 10:31 ...almost a third in slums 10:36 For them, a 3°C world could be deadly 10:40 Minara has moved to Dhaka to escape the impact of climate change 10:44 But life could get even worse for her 10:47 I’m struggling a lot nowadays 10:49 The heat during the day is unbearable 10:52 Even late at night it doesn’t cool down 10:57 The heat is getting more intense every day 10:59 I mean, it’s going to get much worse 11:03 I can barely survive it now, how will I live through it in the future? 11:08 Dhaka is getting hotter 11:11 In the last 20 years the average daytime temperature... 11:13 ...has crept up by nearly half a degree 11:17 Days that approach 40°C are now being reported 11:20 And high so-called wet-bulb temperatures are on the rise 11:26 A wet-bulb temperature is a measure of heat and humidity 11:30 Humans cool themselves by sweating… 11:32 But in these conditions, when relative humidity is near 100%... 11:36 ...sweat doesn’t evaporate well 11:38 So people can’t cool down… 11:41 ...even if given unlimited shade and water 11:45 At a high wet-bulb temperature, the body can’t lose heat... 11:49 ...and so it gets hotter and hotter... 11:51 ...and the body is designed to work at a given temperature 11:53 And if it gets too hot inside, you will die 11:58 The human limit for wet-bulb temperatures is 35°C... 12:02 ...around skin temperature 12:04 Dhaka will have a much higher chance... 12:05 ...of reaching dangerous wet-bulb temperatures... 12:07 ...if global warming reaches 3°C 12:12 You can’t really adapt to that 12:14 You have to get out. If the temperature is so high that you can’t work... 12:20 ...can’t do hard manual labour outside for significant parts of the year... 12:25 ...then many places will become functionally no longer part of the economy 12:33 Jacobabad in Pakistan, and Ras al Khaimah, in the United Arab Emirates... 12:37 ...have already recorded deadly wet-bulb temperatures 12:40 More of the tropics and the Persian Gulf... 12:43 ...as well as parts of Mexico and the south-eastern United States... 12:47 ...could all get to this threshold by the end of the century 12:50 Climate modelling might show us the weather Increased migration and conflict 12:52 But it doesn’t show us its other effects on society 12:56 Established migration patterns could change 12:59 Climate disasters may exacerbate reasons people cross borders 13:03 Within countries, more people will move to cities 13:07 In a 3°C world, tens of millions of people a year... 13:10 ...could be displaced by disasters made worse by climate change 13:15 When people are displaced by climate... 13:18 …they may well go to cities... 13:19 ...because cities are the places that attract people from the countryside already 13:25 A lot of people who can get to the developed world... 13:28 ...not least because the developed world tends to be less hot, will give that a go 13:35 As migration around the world increases... 13:38 ...there could be more competition for fewer resources 13:42 Water—already a highly contested resource—will be a focal point 13:47 Turkey’s new Ilisu dam has reduced the flow of water into Iraq 13:53 China lays claim to rivers vital to India and Pakistan 13:57 The prospect of a water-conflict makes people very uneasy 14:03 How national tensions would exacerbate those sorts of reactions... 14:08 ...in a 3°C world... 14:09 ...is the sort of thing that no one should really want to find out 14:14 I think you’d have to be incredibly sanguine... 14:16 ...not to think that the sort of climate extremes that we talk about... 14:19 ...in a 3°C world wouldn’t lead some places... 14:22 ...to the brink of societal collapse 14:25 Those lucky enough to escape unrest... Adaptation and mitigation are crucial 14:28 ...would still have to adapt to a radically different world 14:32 People can adapt to climate change in all sorts of ways, one of the most obvious ones... 14:37 ...is air conditioning 14:39 But other ways to adapt at a local or regional level... 14:42 ...I mean, one of the most obvious is diversifying agriculture 14:47 There are physical things you can do, like seawalls 14:52 The fact that people can adapt and that adaptation will reduce suffering... 14:57 ...doesn’t mean that it will eliminate suffering 15:00 Suffering is built into this whole process of heating up the planet 15:06 Adaptation will only get the world so far 15:09 The best way to deal with a 3°C world... 15:12 ...is not to go to a 3°C world 15:14 And that’s why increasing efforts on mitigation are important 15:17 It’s why working towards negative emissions... 15:20 ...that could bring down the temperature after it peaks are important 15:25 Once you get to a 3°C world, you are in real bad global trouble 15:33 The scale of change needed... 15:35 ...and the slow progress of governments so far... 15:38 ...means 3°C of warming is uncomfortably likely unless more is done 15:44 Despite existing pledges, greenhouse-gas emissions... 15:48 ...are still set to rise by 16% from 2010 levels by 2030 15:54 The need to act has never been clearer 15:57 There’s still time to reduce emissions, so that a 3°C world remains fiction... 16:02 ...rather than becoming fact

TECH FREE! by Sam Winton Have you ever wondered what it would be like to give up technology? I'm a TV journalist and I spend a lot of my working life in front of a computer or a TV. I decided to conduct my own private experiment: I would spend a day trying to manage without technological devices. What a scary thought! The first thing I usually do every day is reach for my smartphone to check the time and read any messages or emails. But I'd locked it away in a drawer the night before. Already I was feeling very cut off from the world, and it was only... actually, I had no idea what time it was! After breakfast, I needed to get some cash. Inevitably, this meant a trip to the bank because cash points are technological devices. I had to queue, but I had a very nice conversation with a woman whilst I was waiting. Not surprisingly, the bank teller thought I was a bit strange withdrawing money this way. I think she thought I was a robber! Then it was on to the supermarket. You may be wondering what's technological about that. Well, I had to make sure I avoided the self-service check-out and joined the queue for a normal one - with a real person. Naturally, it took longer, but I had a great chat with the guy who served me, and he told me about a new club that is opening up nearby. Would I have found out about that if I'd gone to the self- service check-out? No. Afterwards, I came home to have a go at writing a news story by hand. Strangely, I found it easier to concentrate on my writing. But my hand and fingers got really sore! And I have to confess - by this stage, I was having to make a real effort not to get my phone out and check my messages. I was starting to wonder what my friends were doing. Maybe they were making plans to go to that new club, and I would never know! All in all, I wouldn't say I could live without technology. Predictably, I really missed my phone all day. The worst part was not being able to check updates in the news or from my friends. I felt very out of touch. However, I kept to my promise of a tech-free day and I did have more face-to-face interaction. Undoubtedly, it made me realise just how addicted to technology we all are.

Etymology explains the origin of the word itself. Example: Using the example term “arbitration”: Arbitration comes from the Latin judicium which means “judgment”. 2. History discusses the history of the term, its use, and controversies associated with it. Example: The use of arbitration as third-party mediation dates from the 1630s. 3. Cause and Effect discusses how the situation came about and what effects it may have. Example: An arbitration clause is considered to be ambiguous when the parties do not express clearly, that in case of conflict, the method to use to settle the disagreements will be arbitration. Hence, parties are compelled to refrain from signing confusing agreements to arbitrate, because the general rule is that arbitration is prompted out of the contract, and if there is not an explicit arbitration clause within the contract it would not be an agreement to arbitrate. 4. Description lists and defines the term. Example: Arbitration is the process of solving an argument between people by helping them to agree to an acceptable solution. It is the formal process of having an outside person, chosen by both sides to a disagreement to end the disagreement. 5. Principles of Operation discusses how something functions, including any special materials or conditions required. Example: Arbitration is conducted by a trained arbiter who sets down the rules that the parties must abide by. The object of arbitration is to obtain a fair resolution of disputes by an impartial third party without unnecessary expense or delay. Parties should be free to agree on how their disputes are resolved, subject only to such safeguards as are necessary for the public interest. Courts should not interfere. 5 6. Classification shows how the topic fits into a larger category. Example: Arbitration is one of the alternatives to going into a formal court to settle disputes. 7. Contrast shows how the topic differs from others in the same class. Example: In an arbitration proceeding, no lawyers are present. The main difference between arbitration and litigation law is that the court is involved in the case of litigation, as it is a lawsuit, whereas, in arbitration, a settlement between the parties is done outside of court. 8. Comparison shows how the topic is similar to others in the class. Example: As with lawsuits or other court proceedings, the decision in an arbitration proceeding is legally binding on the parties. 9. Analogy explains and compares two dissimilar topics, where the second is familiar to the audience. Example: An arbiter is like a referee–he or she listens to both sides and decides as to who is at fault, without the intervention of outside parties. 10.Examples represent other things because they have all the main qualities or characteristics that the thing they represent also have. Examples: Arbitration was used to settle the dispute between the labor union and management. Two people who are divorcing cannot agree on terms and allow a third party to come in to help them negotiate

Alright, Isti — here’s a longer and more detailed English version of the Isaac Newton text, still written at a level that’s accessible for Grade 4 students, but rich enough in information to meet PISA literacy expectations and EF A2-level vocabulary. I’ve kept sentences short, clear, and with explanations for new concepts so it’s easier for young learners to follow, while still including both famous facts and lesser-known stories. ⸻ Isaac Newton: The Man Who Changed the Way We See the World A Boy from a Small Village Isaac Newton was born on January 4, 1643, in Woolsthorpe, a small village in England. His life was not easy. His father died before he was born. When he was just a few months old, his mother remarried and left him to live with his grandmother. Isaac missed his parents, but he kept himself busy by making things and exploring the world around him. As a child, Isaac liked to build models and machines. He made a small windmill that could turn with the wind. He built a water clock that told the time by dripping water into a container. He even made a sundial — a clock that tells the time by using the shadow of the sun. 💡 Did you know? The sundial marks that Isaac carved as a boy can still be seen today on the wall of his old house. ⸻ School and Curiosity When Newton first went to school, he was not the top student. At first, he did not pay much attention in class. But one day, another boy teased him for not being smart. Newton decided to study hard to prove him wrong. Soon, he became the best in his class. Isaac loved asking questions. He wanted to know how and why things happened. He enjoyed watching the stars at night and thinking about how the world worked. ⸻ The Falling Apple and Gravity One of the most famous stories about Newton is the falling apple. One afternoon, Isaac sat in his mother’s garden and saw an apple drop from a tree. This made him think: “Why does the apple fall straight down? Why doesn’t it fly up into the sky?” From this question, Newton began to think about gravity — an invisible force that pulls objects toward each other. Gravity is what keeps our feet on the ground. It’s also what keeps the Moon moving around the Earth and the planets moving around the Sun. 💡 Fun fact: The apple did not hit Newton’s head. That’s just a story people made up later to make the tale more exciting. ⸻ Newton’s Three Laws of Motion Newton studied movement and wrote three important rules: 1. Objects stay still or keep moving unless something makes them change. • Example: A ball will not roll unless you push it. 2. The bigger the push, the bigger the movement. • Example: If you kick a ball harder, it will go faster and farther. 3. Every action has an equal and opposite reaction. • Example: When you jump off a boat, the boat moves backward as you move forward. These three laws are still used today to understand how cars, rockets, and even roller coasters work. ⸻ Discoveries in Light and Color Newton also studied light. He found that white light is not just one color — it is made of many colors. He used a glass prism to split sunlight into a rainbow. This helped scientists understand how colors work. ⸻ Inventions and New Ideas Newton made a special telescope that used mirrors instead of lenses. This type of telescope made images of planets and stars much clearer. It is still called the Newtonian telescope today. He also worked in mathematics and helped create a new type of math called calculus, which is used to study changes and movement. ⸻ Strange Experiments Newton was so curious that he sometimes tested ideas on himself. Once, he put a thin needle, called a bodkin, beside his eye to see how it would change his vision. It was very dangerous, but luckily he did not go blind. 💡 Did you know? Newton also studied alchemy — an old kind of science where people tried to turn metal into gold. He never succeeded, but it showed how wide his interests were. ⸻ Later Life and Work At the age of 27, Newton became a professor at Cambridge University. He later worked for the Royal Mint, making sure coins were made safely and stopping people from making fake money. He was very strict, and some criminals were sent to prison because of his work. Newton never married. He spent most of his life reading, writing, and doing experiments. ⸻ The End of His Life Isaac Newton died in 1727 at the age of 84. He was buried in Westminster Abbey, a famous place in London where great people of Britain are honored. His work changed the world forever. Even today, scientists, engineers, and students still use Newton’s laws and ideas. 💬 Newton once said: “If I have seen further, it is by standing on the shoulders of giants.” This means we can make new discoveries by learning from the work of others who came before us. give 10 questions to each passage with PISA literacy standard for kid 10 years, 1. Nikola Tesla: The Man Who Dreamed of Lightning Born: July 10, 1856 Died: January 7, 1943 When Nikola Tesla was a boy in Croatia, he saw a flash of lightning and asked his mother, “Can we catch the light?” That question never left him. As he grew older, Tesla became a brilliant inventor, especially fascinated by electricity. He believed in a future where energy could be sent wirelessly through the air—like music through the radio! Tesla invented the alternating current (AC) system, which became the foundation of modern electricity. At the time, Thomas Edison promoted direct current (DC), and the two men had a fierce competition. Many laughed at Tesla's bold ideas, but he never gave up. He dreamed of wireless communication, flying machines, and even free energy for everyone. Though he died alone and poor, today the world honors his vision. Think About It: Why do you think people didn’t believe Tesla at first? What can we learn from Tesla’s courage to dream big? 2. Charles Darwin: The Man Who Studied the World’s Weirdest Creatures Born: February 12, 1809 Died: April 19, 1882 When young Charles Darwin got on a ship called HMS Beagle, he didn’t know he would change science forever. He sailed around the world for five years, collecting plants, animals, and fossils. On the Galápagos Islands, he noticed something curious: finches had different beaks depending on their island. Why? Darwin’s observations led him to write the theory of evolution by natural selection. It explained how animals adapt and survive. But his ideas shocked many people because they seemed to challenge religious beliefs. Despite the controversy, Darwin continued his work. His book On the Origin of Species changed how we see life on Earth. Think About It: Should scientists share their ideas even if they go against what others believe? How did traveling help Darwin make new discoveries? 3. Marie Curie: The Woman Who Glowed in the Dark Born: November 7, 1867 Died: July 4, 1934 Marie Curie was born in Poland at a time when girls were not allowed to study science. But that didn’t stop her. She moved to France, worked day and night, and discovered radioactivity, a powerful energy hidden inside atoms. She and her husband, Pierre Curie, found two new elements: polonium and radium. She became the first woman to win a Nobel Prize, and the only person to win in two different sciences: physics and chemistry. Even when Pierre died in an accident, Marie continued their work. Her discoveries helped doctors treat cancer—but working with radioactive materials also harmed her health. She died from radiation exposure, but her legacy lives on. Think About It: What challenges did Marie Curie face as a woman in science? Why is it important to balance discovery with safety? 4. Galileo Galilei: The Star Watcher Who Defied the Church Born: February 15, 1564 Died: January 8, 1642 Galileo loved looking at the stars. He built one of the first powerful telescopes and made stunning discoveries: mountains on the Moon, moons around Jupiter, and that the Earth orbits the Sun—not the other way around. This idea, called heliocentrism, went against the teachings of the Church. He was put on trial and forced to say he was wrong. But he wasn’t. He spent his last years under house arrest, quietly writing. Today, Galileo is called the father of modern science for daring to question what others blindly believed. Think About It: Why do you think Galileo was punished for telling the truth? Should science always follow evidence, even if it goes against powerful beliefs? 5. Isaac Newton: The Man Who Asked “Why?” When an Apple Fell Born: January 4, 1643 Died: March 31, 1727 One day, an apple fell from a tree, and Isaac Newton began to wonder: Why did it fall down, not sideways or up? This simple question led to his theory of gravity. Newton also invented calculus, described the laws of motion, and changed physics forever. But Newton wasn’t just a genius—he was curious, quiet, and often worked alone. He believed everything in nature followed rules, and it was our job to discover them. Thanks to him, we understand how planets move, how rockets launch, and why you fall when you trip. Think About It: How did Newton’s curiosity lead to great discoveries? Do you think working alone helped or hurt Newton? 6. Ada Lovelace: The First Computer Programmer Before Computers Existed Born: December 10, 1815 Died: November 27, 1852 Ada Lovelace was the daughter of the famous poet Lord Byron, but she didn’t love poetry—she loved numbers! At a time when girls were expected to sew, Ada studied mathematics. She met Charles Babbage, who designed an early computer called the Analytical Engine. Ada imagined the machine could do more than just math—it could create music, art, and even write! She wrote what is now considered the first computer program, long before real computers were built. Think About It: How did Ada imagine something that didn’t exist yet? Why do we call her a pioneer in technology? 7. Albert Einstein: The Man Who Brought Time and Space Together Born: March 14, 1879 Died: April 18, 1955 Albert Einstein wasn’t always a good student. In fact, his teachers thought he was slow. But Einstein thought deeply. He asked big questions like, “What if you could ride a beam of light?” His theories of relativity changed how we see space, time, and gravity. He also warned the world about the dangers of nuclear weapons, even though his ideas helped create them. Einstein believed science should help people, not harm them. With his messy hair, kind smile, and brilliant mind, he remains a symbol of genius. Think About It: Can someone be bad in school but still be brilliant? Should scientists be responsible for how their inventions are used? 8. Pythagoras: The Musician Who Loved Math Born: Around 570 BC Died: Around 495 BC Long ago in ancient Greece, Pythagoras believed the universe followed numbers. He discovered the Pythagorean Theorem, a rule about triangles that helps us build houses, design computers, and navigate space. He also believed that music had math inside it—that certain notes made perfect harmony because of mathematical ratios. Pythagoras started a secret school and taught his students to search for truth through numbers, shapes, and sound. Think About It: Why do you think Pythagoras saw math in everything? How does music relate to math? 9. Rosalind Franklin: The Woman Behind the DNA Discovery Born: July 25, 1920 Died: April 16, 1958 Rosalind Franklin loved looking closely at things. She used a special machine called X-ray crystallography to photograph molecules. One of her greatest photos, called Photo 51, showed the shape of DNA, the molecule that carries life’s instructions. But her work was taken without credit. Two men, Watson and Crick, used her photo to build their famous model of DNA and won the Nobel Prize. Rosalind died young and never knew how important her work became. Think About It: Why is it important to give credit in science? What can we learn from Rosalind’s quiet strength? 10. Carl Linnaeus: The Man Who Gave Names to Everything Born: May 23, 1707 Died: January 10, 1778 Have you ever wondered why a tiger is called Panthera tigris? That’s thanks to Carl Linnaeus, a Swedish scientist who created a way to name and organize every living thing. His system is still used today in biology. Linnaeus loved nature and spent his life collecting plants, animals, and even rocks. He believed that by organizing life, we could better understand it. Thanks to him, we now have a global “dictionary of nature.” Think About It: Why is it important to name and organize living things? How does order help us understand the world?

Translator: Joseph Geni Reviewer: Morton Bast Before March, 2011, I was a photographic retoucher based in New York City. We're pale, gray creatures. We hide in dark, windowless rooms, and generally avoid sunlight. We make skinny models skinnier, perfect skin more perfect, and the impossible possible, and we get criticized in the press all the time, but some of us are actually talented artists with years of experience and a real appreciation for images and photography. On March 11, 2011, I watched from home, as the rest of the world did, as the tragic events unfolded in Japan. Soon after, an organization I volunteer with, All Hands Volunteers, were on the ground, within days, working as part of the response efforts. I, along with hundreds of other volunteers, knew we couldn't just sit at home, so I decided to join them for three weeks. On May the 13th, I made my way to the town of Ōfunato. It's a small fishing town in Iwate Prefecture, about 50,000 people, one of the first that was hit by the wave. The waters here have been recorded at reaching over 24 meters in height, and traveled over two miles inland. As you can imagine, the town had been devastated. We pulled debris from canals and ditches. We cleaned schools. We de-mudded and gutted homes ready for renovation and rehabilitation. We cleared tons and tons of stinking, rotting fish carcasses from the local fish processing plant. We got dirty, and we loved it. For weeks, all the volunteers and locals alike had been finding similar things. They'd been finding photos and photo albums and cameras and SD cards. And everyone was doing the same. They were collecting them up, and handing them in to various places around the different towns for safekeeping. Now, it wasn't until this point that I realized that these photos were such a huge part of the personal loss these people had felt. As they had run from the wave, and for their lives, absolutely everything they had, everything had to be left behind. At the end of my first week there, I found myself helping out in an evacuation center in the town. I was helping clean the onsen, the communal onsen, the huge giant bathtubs. This happened to also be a place in the town where the evacuation center was collecting the photos. This is where people were handing them in, and I was honored that day that they actually trusted me to help them start hand-cleaning them. Now, it was emotional and it was inspiring, and I've always heard about thinking outside the box, but it wasn't until I had actually gotten outside of my box that something happened. As I looked through the photos, there were some were over a hundred years old, some still in the envelope from the processing lab, I couldn't help but think as a retoucher that I could fix that tear and mend that scratch, and I knew hundreds of people who could do the same. So that evening, I just reached out on Facebook and asked a few of them, and by morning the response had been so overwhelming and so positive, I knew we had to give it a go. So we started retouching photos. This was the very first. Not terribly damaged, but where the water had caused that discoloration on the girl's face had to be repaired with such accuracy and delicacy. Otherwise, that little girl isn't going to look like that little girl anymore, and surely that's as tragic as having the photo damaged. (Applause) Over time, more photos came in, thankfully, and more retouchers were needed, and so I reached out again on Facebook and LinkedIn, and within five days, 80 people wanted to help from 12 different countries. Within two weeks, I had 150 people wanting to join in. Within Japan, by July, we'd branched out to the neighboring town of Rikuzentakata, further north to a town called Yamada. Once a week, we would set up our scanning equipment in the temporary photo libraries that had been set up, where people were reclaiming their photos. The older ladies sometimes hadn't seen a scanner before, but within 10 minutes of them finding their lost photo, they could give it to us, have it scanned, uploaded to a cloud server, it would be downloaded by a gaijin, a stranger, somewhere on the other side of the globe, and it'd start being fixed. The time it took, however, to get it back is a completely different story, and it depended obviously on the damage involved. It could take an hour. It could take weeks. It could take months. The kimono in this shot pretty much had to be hand-drawn, or pieced together, picking out the remaining parts of color and detail that the water hadn't damaged. It was very time-consuming. Now, all these photos had been damaged by water, submerged in salt water, covered in bacteria, in sewage, sometimes even in oil, all of which over time is going to continue to damage them, so hand-cleaning them was a huge part of the project. We couldn't retouch the photo unless it was cleaned, dry and reclaimed. Now, we were lucky with our hand-cleaning. We had an amazing local woman who guided us. It's very easy to do more damage to those damaged photos. As my team leader Wynne once said, it's like doing a tattoo on someone. You don't get a chance to mess it up. The lady who brought us these photos was lucky, as far as the photos go. She had started hand-cleaning them herself and stopped when she realized she was doing more damage. She also had duplicates. Areas like her husband and her face, which otherwise would have been completely impossible to fix, we could just put them together in one good photo, and remake the whole photo. When she collected the photos from us, she shared a bit of her story with us. Her photos were found by her husband's colleagues at a local fire department in the debris a long way from where the home had once stood, and they'd recognized him. The day of the tsunami, he'd actually been in charge of making sure the tsunami gates were closed. He had to go towards the water as the sirens sounded. Her two little boys, not so little anymore, but her two boys were both at school, separate schools. One of them got caught up in the water. It took her a week to find them all again and find out that they had all survived. The day I gave her the photos also happened to be her youngest son's 14th birthday. For her, despite all of this, those photos were the perfect gift back to him, something he could look at again, something he remembered from before that wasn't still scarred from that day in March when absolutely everything else in his life had changed or been destroyed. After six months in Japan, 1,100 volunteers had passed through All Hands, hundreds of whom had helped us hand-clean over 135,000 photographs, the large majority — (Applause) — a large majority of which did actually find their home again, importantly. Over five hundred volunteers around the globe helped us get 90 families hundreds of photographs back, fully restored and retouched. During this time, we hadn't really spent more than about a thousand dollars in equipment and materials, most of which was printer inks. We take photos constantly. A photo is a reminder of someone or something, a place, a relationship, a loved one. They're our memory-keepers and our histories, the last thing we would grab and the first thing you'd go back to look for. That's all this project was about, about restoring those little bits of humanity, giving someone that connection back. When a photo like this can be returned to someone like this, it makes a huge difference in the lives of the person receiving it. The project's also made a big difference in the lives of the retouchers. For some of them, it's given them a connection to something bigger, giving something back, using their talents on something other than skinny models and perfect skin. I would like to conclude by reading an email I got from one of them, Cindy, the day I finally got back from Japan after six months. "As I worked, I couldn't help but think about the individuals and the stories represented in the images. One in particular, a photo of women of all ages, from grandmother to little girl, gathered around a baby, struck a chord, because a similar photo from my family, my grandmother and mother, myself, and newborn daughter, hangs on our wall. Across the globe, throughout the ages, our basic needs are just the same, aren't they?" Thank you. (Applause) (Applause)

A BAD CASE OF THE STRIPES By David Shannon Parts(18): Camilla Narrator 1 Narrator 2 Narrator 3 Narrator 4 Mr. Harms Mother Father Dr. Bumble Old Woman Environmental Therapist Dr. Grop Dr. Gourd Dr. Sponge Mr. Mellon Dr. Cricket Dr. Young <><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><> Narrator 1: A BAD CASE OF THE STRIPES By David Shannon Narrator 2: Camilla Cream loved lima beans. But she never ate them. Narrator 3: All of her friends hated lima beans, and she wanted to fit in. Camilla always worried about what other people thought of her. Narrator 4: Today she was fretting even more than usual. It was the very first day of school, and she couldn't decide what to wear. There were so many people to impress! Narrator 1: She tried on forty-two outfits, but none seemed quite right. She put on a pretty red dress and looked in the mirror. Then she screamed. Narrator 2: Her mother ran into the room, and she screamed, too. Mother: "Oh my heavens! You're completely covered with stripes!" Narrator 3: she cried. This was certainly true. Camilla was striped from head to toe. She looked like a rainbow. Narrator 4: Mrs. Cream felt Camilla's forehead. Mother: "Do you feel all right?" Narrator 1: she asked. Camilla: "I feel fine, but just look at me!" Narrator 2: Camilla answered. Mother: "You get back in bed this instant. You're not going to school today." Narrator 3: her mother ordered. Camilla was relieved. She didn't want to miss the first day of school, but she was afraid of what the other kids would say. And she had no idea what to wear with those crazy stripes. Narrator 4: That afternoon, Dr. Bumble came to examine Camilla. Dr. Bumble: "Most extraordinary! I've never seen anything like it! Are you having any coughing, sneezing, runny nose, aches, pains, chills, hot flashes, dizziness, drowsiness, shortness of breath, or uncontrollable twitching?" Narrator 1: he asked. Camilla: "No, I feel fine." Narrator 2: Camilla told him. Dr. Bumble: "Well then, I don't see any reason why she shouldn't go to school tomorrow. Here's some ointment that should help clear up those stripes in a few days. If it doesn't, you know where to reach me." Narrator 3: Dr. Bumble said, turning to Mrs. Cream. And off he went. Narrator 4: The next day was a disaster. Everyone at school laughed at Camilla. They called her "Camilla Crayon" and "Night of the Living Lollipop." Narrator 1: She tried her best to act as if everything were normal, but when the class said the Pledge of Allegiance, her stripes turned red, white, and blue, and she broke out in stars! Narrator 2: The other kids thought this was great. One yelled out, Narrator 3: "Let's see some purple polka dots!" Narrator 4: Sure enough, Camilla turned all purple polka-dotty. Someone else shouted, Narrator 1: "Checkerboard!" Narrator 4: and a pattern of squares covered her skin. Soon everyone was calling out different shapes and colors, and poor Camilla was changing faster than you can change channels on a T.V. Narrator 2: That night, Mr. Harms, the school principal, called. Mr. Harms: "I'm sorry, Mrs. Cream, I'm going to have to ask you to keep Camilla home from school. She's just too much of a distraction, and I've been getting phone calls from the other parents. They're afraid those stripes may be contagious." Narrator 3: he said. Camilla was so embarrassed. She couldn't believe that two days ago everyone liked her. Now, nobody wanted to be in the same room with her. Narrator 1: Her father tried to make her feel better. Father: "Is there anything I can get you, sweetheart?" Narrator 2: he asked. Camilla: "No, thank you," Narrator 3: sighed Camilla. What she really wanted was a nice plate of lima beans, but she had been laughed at enough for one day. Dr. Bumble: "Hmm, well, yes, I see. I think I'd better bring in the Specialists. We'll be right over.” Narrator 4: said Dr. Bumble to Mr. Cream on the phone. About an hour later, Dr. Bumble arrived with four people in long white coats. He introduced them to the Creams. Dr. Bumble: "This is Dr. Grop, Dr. Sponge, Dr. Cricket, and Dr. Young." Narrator 1: Then the Specialists went to work on Camilla. They squeezed and jabbed, tapped and tested. It was very uncomfortable. Dr. Grop: "Well, it's not the mumps." Dr. Sponge: "Or the measles." Dr. Cricket:"Definitely not chicken pox." Dr. Young: "Or sunburn." Narrator 2: replied the Specialists. Specialists:"Try these. Take one of each before bed." Narrator 4: said the specialists. They each handed her a bottle filled with different colored pills. Then they filed out the front door followed by Dr. Bumble. Narrator 1: That night, Camilla took her medicine. It was awful. Narrator 2: When she woke up the next morning, she did feel different, but when she got dressed, her clothes didn't fit right. She looked in the mirror, and there, staring back at her, was a giant, multi-colored pill with a face on it. Narrator 3: Dr. Bumble rushed over as soon as Mrs. Cream called. But this time, instead of the Specialists, he brought the Experts. Narrator 4: Dr. Gourd and Mr. Mellon were the finest scientific minds in the land. Once again, Camilla was poked and prodded, looked at and listened to. Narrator 1: The Experts wrote down lots of numbers. Then they huddled together and whispered. Dr. Gourd finally spoke. Dr. Gourd: "It might be a virus," Narrator 2: he announced with authority. Suddenly, fuzzy little virus balls appeared all over Camilla. Mr. Mellon: "Or possibly some form of bacteria," Narrator 3: said Mr. Mellon. Out popped squiggly little bacteria tails. Dr. Gourd: "Or it could be a fungus," Narrator 4: added Dr. Gourd. Instantly, Camilla was covered with different colored fungus blotches. The experts looked at Camilla, then each other. Experts: "We need to go over these numbers again back at the lab. We’ll call you when we know something," Narrator 1: said the Experts. But the Experts didn't have a clue, much less a cure. Narrator 2: By now, the T.V. news had found out about Camilla. Reporters from every channel were outside her house, telling the story of "The Bizarre Case of the Incredible Changing Kid." Narrator 3: Soon a huge crowd was camped out on the front lawn. Narrator 4: The Creams were swamped with all kinds of remedies from psychologists, allergists, herbalists, nutritionists, psychics, an old medicine man, a guru, and even a veterinarian. Narrator 1: Each so-called cure only added to poor Camilla's strange appearance until it was hard to even recognize her. She sprouted roots and berries and crystals and feathers and a long furry tail. But nothing worked. Narrator 2: One day, a woman who called herself an Environmental Therapist claimed she could cure Camilla. She said, Environmental Therapist: "Close your eyes, breathe deeply, and become one with your room." Camilla: "I wish you hadn't said that," Narrator 3: Camilla groaned. Slowly, she started to melt into the walls of her room. Her bed became her mouth, her nose was a dresser, and two paintings were her eyes. The therapist screamed and ran from the house. Mother: "What are we going to do? It just keeps getting worse and worse!" Narrator 4: cried Mrs. Cream. She began to sob. Narrator 1: At that moment, Mr. Cream heard a quiet little knock at the front door. He opened it, and there stood an old woman who was just as plump and sweet as a strawberry. Old Woman: "Excuse me, but I think I can help." Narrator 2: she said brightly. Narrator 3: She went into Camilla's room and looked around. Old Woman: "My goodness, what we have here is a bad case of the stripes. One of the worst I've ever seen!" Narrator 4: she said with a shake of her head. She pulled a container of small green beans from her bag. She said, Old Woman: "Here. These might do the trick." Mother: "Are those magic beans?" Narrator 1: asked Mrs. Cream. The old woman replied, Old Woman: "Oh my, no, there's no such thing. These are just plain old lima beans. I'll bet you'd like some, wouldn't you?" Narrator 2: she asked Camilla. Camilla wanted a big, heaping plateful of lima beans more than just about anything, but she was still afraid to admit it. She said, Camilla: "Yuck! No one likes lima beans, especially me!" Old Woman: "Oh, dear, I guess I was wrong about you." Narrator 3: said the old woman sadly. She put the beans back in her bag and started toward the door. Narrator 4: Camilla watched the old woman walk away. Those beans would taste so good. And being laughed at for eating them was nothing, compared to what she'd been going through. She finally couldn't stand it. Camilla: "Wait! The truth is...I really love lima beans." Narrator 1: she cried. The old woman smiled, popping a handful of beans into Camilla's mouth, and said, Old Woman: "I thought so." Camilla: "Mmmmmmm," Narrator 2: said Camilla. Suddenly the branches, feathers, and squiggly tails began to disappear.Then the whole room swirled around. When it stopped, there stood Camilla, and everything was back to normal. Camilla: "I'm cured!" Narrator 3: she shouted. The old woman said, Old Woman: "Yes, I knew the real you was in there somewhere." Narrator 4: She patted Camilla on the head and went outside and vanished into the crowd. Narrator 1: Afterward, Camilla wasn't quite the same. Narrator 2: Some of the kids at school said she was weird, but she didn't care a bit. Narrator 3: She ate all the lima beans she wanted, and she never had even a touch of stripes again.

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