1. How long is a laundromat usually open?
| A．7 hours. | B．10 hours. | C．15 hours. |
| A．Buy it from a machine. |
| B．Ask the employees for help. |
| C．Borrow it from other people. |
| A．Reading rooms. | B．Free Wi-Fi. | C．Cafes. |
2 . “Assume you are wrong.” The advice came from Brian Nosek, a psychology professor, who was offering a strategy for pursuing better science.
To understand the context for Nosek’s advice, we need to take a step back to the nature of science itself. You see despite what many of us learned in elementary school, there is no single scientific method. Just as scientific theories become elaborated and change, so do scientific methods.
But methodological reform hasn’t come without some fretting and friction. Nasty things have been said by and about methodological reformers. Few people like having the value of their life’s work called into question. On the other side, few people are good at voicing criticisms in kind and constructive ways. So, part of the challenge is figuring out how to bake critical self-reflection into the culture of science itself, so it unfolds as a welcome and integrated part of the process, and not an embarrassing sideshow.
What Nosek recommended was a strategy for changing the way we offer and respond to critique. Assuming you are right might be a motivating force, sustaining the enormous effort that conducting scientific work requires. But it also makes it easy to interpret criticisms as personal attacks. Beginning, instead, from the assumption you are wrong, a criticism is easier to interpret as a constructive suggestion for how to be less wrong — a goal that your critic presumably shares.
One worry about this approach is that it could be demoralizing for scientists. Striving to be less wrong might be a less effective motivation than the promise of being right. Another concern is that a strategy that works well within science could backfire when it comes to communicating science with the public. Without an appreciation for how science works, it’s easy to take uncertainty or disagreements as marks against science, when in fact they reflect some of the very features of science that make it our best approach to reaching reliable conclusions about the world. Science is reliable because it responds to evidence: as the quantity and quality of our evidence improves, our theories can and should change, too.
Despite these worries, I like Nosek’s suggestion because it builds in cognitive humility along with a sense that we can do better. It also builds in a sense of community — we’re all in the same boat when it comes to falling short of getting things right.
Unfortunately, this still leaves us with an untested hypothesis (假说): that assuming one is wrong can change community norms for the better, and ultimately support better science and even, perhaps, better decisions in life. I don’t know if that’s true. In fact, I should probably assume that it’s wrong. But with the benefit of the scientific community and our best methodological tools, I hope we can get it less wrong, together.
1. What can we learn from Paragraph 3?| A．Reformers tend to devalue researchers’ work. |
| B．Scientists are unwilling to express kind criticisms. |
| C．People hold wrong assumptions about the culture of science. |
| D．The scientific community should practice critical self-reflection. |
| A．the enormous efforts of scientists at work | B．the reliability of potential research results |
| C．the public’s passion for scientific findings | D．the improvement in the quality of evidence |
| A．discouraging | B．ineffective | C．unfair | D．misleading |
| A．doubtful but sincere | B．disapproving but soft |
| C．authoritative and direct | D．reflective and humorous |
I worked at a local station of the Berlin fire department. We got an alert (警报) around 8:25pm that Friday and rushed to the fire engine, where the printout from the dispatcher (调度员) said there was a nine-year-old boy locked in a safe.
I asked myself: if it were a safe, would it be airtight? I was aware that it might already be too late by the time we arrived. I had to plan for a bad outcome. On the other hand, if we were in time, how long would it take us to open the safe? I knew it would be an incredibly difficult task. It’s what safes are designed for—not to be opened.
It took less than five minutes to reach the property. When I saw a woman crying on the street,
I knew the situation was serious. She was the boy’s mother and she led us into the basement. She told us the boy was alive and we started talking to him; he was very calm. We asked how it had happened: during a game of hide and seek with his five-year-old brother, he had thought the safe would be a good place to hide.
The boy’s parents had got the house from his mother’s father. The unlocked safe had been there when they moved in and was in an area they didn’t use much. The boy’s little brother had shut the safe, then, when he couldn’t open it again. The only person who knew the combination was the boy’s late grandfather.
From the outset, the biggest priority was getting oxygen to the boy. We got oxygen from the hospital. The boy said that he could feel a thin stream of air. I asked his parents if anyone had opened the safe before and they said no. So we had to guess a six-digit code (密码). We started typing them in—but we had to wait 10 minutes between each attempt before we could try again. So quickly we tried them all. No luck.
注意：1.续写词数应为150左右;
2. 请按如下格式在答题卷的相应位置作答。
We were fully prepared at this point to open the safe by force, starting with a drill.
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________Then, just as we started to make the first cut, my workmate typed in the correct code.
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________4 . Last week, I sent the same request to ChatGPT, the latest artificial-intelligence chatbot from OpenAI. “Upon the Firth of Forth, a bridge doth stand,” it began. In less than a minute, the program had created in full a rhyming Shakespearean sonnet (莎士比亚十四行诗). Tools like ChatGPT seem poised to change the world of poetry — and so much else — but poets also have a lot to teach us about artificial intelligence. If algorithms (算法) are getting good at writing poetry, it’s partially because poetry was always an algorithmic business.
Even the most rebellious (叛逆的) poets follow more rules than they might like to admit. When schoolchildren are taught to imitate the structure of sonnet, they are effectively learning to follow algorithmic constraints. Should it surprise us that computers can do so, too?
But considering how ChatGPT works, its ability to follow the rules for sonnets seems a little more impressive. No one taught it these rules. It is based on a newer kind of AI known as a large language model (LLM). To put it simply, LLMs analyze large amounts of human writing and learn to predict what the next word in a string of text should be, based on context. One frequent criticism of LLMs is that they do not understand what they write; they just do a great job of guessing the next word.
When a private verse by Dickinson makes us feel like the poet speaks directly to us, we are experiencing the effects of a technology called language. Poems are made of paper and ink — or, these days, electricity and light. There is no one “inside” a Dickinson poem any more than one by ChatGPT. Of course, every Dickinson poem reflects her intention to create meaning. When ChatGPT puts words together, it does not intend anything. Some argue that writings by LLMs therefore have no meaning, only the appearance of it. If I see a cloud in the sky that looks like a giraffe, I recognize it as an accidental similarity. In the same way, this argument goes, we should regard the writings of ChatGPT as merely imitating real language, meaningless and random as cloud shapes.
When I showed my friends the sonnet by ChatGPT, they called it “soulless and barren.” Despite following all the rules for sonnets, the poem is predictable. But is the average sonnet by a human any better? If we now expect computers to write not just poems but good poems, then we have set a much higher bar.
1. What is the main idea of paragraph 1 and paragraph 2?| A．ChatGPT will make a difference to poetry based on algorithms. |
| B．There is no doubt that AI can copy the grammatical rules of poetry. |
| C．Poetry guidelines provide a possibility for AI’s poetry writing. |
| D．There is a similarity between algorithms and poetry. |
| A．ChatGPT is trained to follow the rules by LLMs. |
| B．ChatGPT can analyze and predict human languages. |
| C．ChatGPT is technologically supported by LLMs. |
| D．ChatGPT itself learn to follow the rules. |
| A．He talks about cloud to describe the meaninglessness of AI’s poetry. |
| B．He tells of Dickinson to describe the meaninglessness AI’s poetry. |
| C．He mentions cloud to suggest its close relationship with AI’s poetry. |
| D．He refers to Dickinson to suggest her close relationship with AI’s poetry. |
| A．Acceptable and favorable | B．Amazed and admiring |
| C．Indifferent and uncaring | D．Doubtful and uneasy |
In a small village called Brightville, there lived three friends: Kimberley, John and Alicia. They were all students at Brightville High School. Kimberley was a hardworking and determined girl; John was a curious and creative boy; and Alicia was a kind and helpful girl. They shared a common dream of achieving their goals through education.
On a sunny day, the three friends gathered at their favorite spot near the village river. They often met there to discuss their dreams and motivate each other. Kimberley always emphasized (强调) the importance of studying and setting goals. John loved exploring new things and finding creative ways to learn. Alicia, with her caring nature, always supported and encouraged her friends.
One day, they came across an old abandoned library in the heart of Brightville. The library was filled with dust-covered books. Kimberley saw this as an opportunity for their dreams to come true. She suggested turning the library into a learning center for the village.
The three friends spent months cleaning, organizing and renewing the library. They reached out to the villagers, and soon, volunteers joined them to set up the learning center. They created a friendly and welcome environment where students could come to study, read books, and seek help.
Word about the learning center spread throughout the village. Students from all ages and backgrounds started attending. Kimberley, John and Alicia devoted their after-school hours to tutoring (指导) the students. They understood that education was not just about memorizing facts but also about nurturing curiosity and passion for learning.
注意：1. 续写词数应为150左右;
2. 请按如下格式在答题卡的相应位置作答。
As days turned into months, they saw the effect of their hard work.
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________The success of the learning center in Brightville caught the attention of the local government.
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________6 . Atomic shapes are so simple that they can’t be broken down any further. Mathematicians are trying to turn to artificial intelligence (AI) for help to build a periodic table of these shapes, hoping it will assist in finding yet-unknown atomic shapes.
Tom Coates at Imperial College London and his colleagues are working to classify atomic shapes known as Fano varieties, which are so simple that they can’t be broken down into smaller components. Just as chemists arranged element s in the periodic table by their atomic weight and group to reveal new insights, the researchers hope that organizing these atomic shapes by their various properties will help in understanding them.
The team has given each atomic shape a sequence of numbers based on its features such as the number of holes it has or the extent to which it bends around itself. This acts as a bar code (条形码) to identify it. Coates and his colleagues have now created an AI that can predict certain properties of these shapes from their bar code numbers alone, with an accuracy of 98 percent.
The team member Alexander Kasprzyk at the University of Nottingham, UK, says that the AI has let the team organize atomic shapes in a way that begins to follow the periodic table, so that when you read from left to right, or up and down, there seem to be general patterns in the geometry (几何) of the shapes.
Graham Nib lo at the University of Southampton, UK, stresses that humans will still need to understand the results provided by AI and create proofs of these ideas. “AI has definitely got unbelievable abilities. But in the same way that telescopes (望远镜) don’t put astronomers out of work, AI doesn’t put mathematicians out of work,” he says. “It just gives us new backing that allows us to explore parts of the mathematical landscape that are out of reach.”
The team hopes to improve the model to the point where missing spaces in its periodic table could point to the existence of unknown shapes.
1. What is the purpose of building a periodic table of shapes?| A．To gain deeper insights into the atomic shapes. |
| B．To create an AI to predict the unknown shapes. |
| C．To break down atomic shapes into smaller parts. |
| D．To arrange chemical elements in the periodic table. |
| A．Its holes. | B．Its bends. |
| C．Its atomic weight. | D．Its properties. |
| A．Design. | B．Help. | C．Duty. | D．Threat. |
| A．Thanks to AI, new atomic shapes have been discovered. |
| B．Mathematicians turn to AI to create more atomic shapes. |
| C．AI helps build a relationship between chemistry and maths. |
| D．A periodic table of shapes can be built with the help of AI. |
7 . On March 7, 1907, the English statistician Francis Galton published a paper which illustrated what has come to be known as the “wisdom of crowds” effect. The experiment of estimation he conducted showed that in some cases, the average of a large number of independent estimates could be quite accurate.
This effect capitalizes on the fact that when people make errors, those errors aren’t always the same. Some people will tend to overestimate, and some to underestimate. When enough of these errors are averaged together, they cancel each other out, resulting in a more accurate estimate. If people are similar and tend to make the same errors, then their errors won’t cancel each other out. In more technical terms, the wisdom of crowds requires that people’s estimates be independent. If for whatever reasons, people’s errors become correlated or dependent, the accuracy of the estimate will go down.
But a new study led by Joaquin Navajas offered an interesting twist (转折) on this classic phenomenon. The key finding of the study was that when crowds were further divided into smaller groups that were allowed to have a discussion, the averages from these groups were more accurate than those from an equal number of independent individuals. For instance, the average obtained from the estimates of four discussion groups of five was significantly more accurate than the average obtained from 20 independent individuals.
In a follow-up study with 100 university students, the researchers tried to get a better sense of what the group members actually did in their discussion. Did they tend to go with those most confident about their estimates? Did they follow those least willing to change their minds? This happened some of the time, but it wasn’t the dominant response. Most frequently, the groups reported that they “shared arguments and reasoned together”. Somehow, these arguments and reasoning resulted in a global reduction in error. Although the studies led by Navajas have limitations and many questions remain, the potential implications for group discussion and decision-making are enormous.
1. What is paragraph 2 of the text mainly about?| A．The methods of estimation. | B．The underlying logic of the effect. |
| C．The causes of people’s errors. | D．The design of Galton’s experiment. |
| A．the crowds were relatively small | B．there were occasional underestimates |
| C．individuals did not communicate | D．estimates were not fully independent |
| A．The size of the groups. | B．The dominant members. |
| C．The discussion process. | D．The individual estimates. |
| A．Unclear. | B．Dismissive. | C．Doubtful. | D．Approving. |
It was a rather crowded day at the subway station. Seeing the busy passers-by stopped by his performance, Eric, a music lover who just graduated from college, wore a big smile on his face. With deep passion for music, he showed up in the station in his spare time, singing and playing the guitar to people travelling to and from the subway station.
With the melodious (悦耳的) song coming to an end, hearty applause burst out. As usual, Eric expressed his gratitude, nodding his head with a smile. “Man, awesome! An outstanding performance!” Approached a man, holding the hand of a little girl in a ponytail (马尾辫), aged about four.
“Park, a producer of a record company.” The man introduced himself, holding out his hand. “Would you like to give it a try in my company?” Out of politeness, Eric shook hands with him in amazement.
“I haven’t seen somebody this good in a long time! You are a beautiful scenery of this city, with such a beautiful voice!” Park admired. Suddenly, a phone call interrupted their conversation. Park briefly invited Eric to meet later in the same place and walked away to answer the call. Seeing Park off, Eric did realize what had happened, with warm current flowing from his head to toes. It was the first time that he had earned such kind of recognition, which was totally out of his expectation.
“A beautiful scenery of the city, with a beautiful voice!” Eric repeated the words, cleaning his guitar and preparing for the next performance. At that time, he caught sight of a little girl in a ponytail standing in a corner, weeping and looking around. Carrying his guitar, Eric approached her and squatted (蹲) down, “What’s wrong with you, honey?”
注意：1. 续写词数应为150左右；
2. 请按如下格式在答题卡的相应位置作答。
“I can’t find my daddy.” The girl burst out crying.
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________The girl calmed down in Eric’s song when a man rushed into the office of the subway station.
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________When I started karate (空手道) class a few years ago, I didn’t know a single person. I felt ashamed of having no idea how to do any of the moves. Even though I liked the learning part, I did not like the feeling-worse-than-everyone part!
But one day after class while I was putting my shoes on, a girl named Abigail said, “That last kick we practiced is so hard for me, and you’re so good at it.”
“You must have confused me with someone else,” I replied. “I’m not good at any of it.”
“In that case, I’m in trouble,” she joked, “because you’re the one I stand behind and copy in class.”
I laughed, “Seriously?”
“Seriously!” she laughed, too. After that, we became great friends. However, a few months later when Abigail’s mom got a job in a different state and she had to move away, I was rather sad. I had a tough time dragging myself to karate for a while after that I missed Abigail so much.
Then, a girl named Ava joined my class. She was always quiet. Until one day we finally had a conversation.
“It must be weird (怪异的) being the new one in class.” I said.
“So weird!” said Ava. “You do things really differently than we did at my old dojo (柔道馆).”
I suddenly realized she’d been silent only because she was new. We started talking more, and we got along so well that we started hanging out after class. Then, almost a year later, guess who showed up at karate.
“This is so cool.” I said, giving Abigail a huge hug. “What are you doing here?”
“My mom’s job in New York didn’t work out,” she explained. “So we got to move back.”
“That’s the best news ever!” I said. “You have to meet my dear friend Ava. And Ava, meet my dear friend Abigail.”
I put my arms around their shoulders. Feeling very excited, I told them I hoped we could get along well and be close friends, while Abigail and Ava stared at each other with some hesitation and an uncertain smile.
注意：1. 续写词数应为150词左右；
2. 请按如下格式在答题卡的相应位置作答。
Things seemed all right at first.
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________One day, I simply could not take it anymore.
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________第一段：
①为了提高学生对太空科学（space science）的热爱，我非常高兴听到你们将要为太空爱好者（space lover）组织一个夏令营（summer camp）。（参考词汇：in order to，improve，I'm glad/excited to hear that…）
②我对这个活动很感兴趣。（参考词汇：be interested in）
③我想成为其中一员。（参考词汇：want to/would like to become/be）
第二段：
①作为高二三班的一名学生，我对太空的奥秘（mystery）很好奇。（参考词汇：as a…，be curious about…）
②我想和其他太空爱好者交流，和他们分享太空知识并且从他们那学到更多东西。
（参考词汇：communicate with sb, share sth with sb, learn sth from sb）
③我也对参观西昌发射塔感兴趣。
④我知道那将是很有趣和有益的。
第三段：（已给出）
Dear Sir,
___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
I would appreciate it if you could take my application into consideration. I am looking forward to hearing from you soon.
Yours,
Li Hua
