1 . Get up at 6 am, arrive at the hospital one hour earlier to help patients check in, and accompany patients during consultations… In recent years, “patient escorts” has emerged as a new industry, and those who have taken on this career are known as “people who sell time”, 26-year-old Zhang Tian is one of them.
September 4 was a lucky day for Zhang Tian. On this day, Zhang Tian saw a video about patient escorts on a short video platform. The daily routine of patient escorts shown in the video fascinated her and gradually inspired her to take this on as a business. She browsed through many platforms and read multiple information and found there indeed exists a certain demand for patient escorts, especially for the elderly, children, and pregnant women. Since she had never engaged in this kind of work before, she spent two days in major hospitals in Wuhan, in order to familiarize herself with all the departments on different floors, as well as the processes of medical consultation and preparation for surgery.
After preliminary preparatory (预备的) work, Zhang Tian posted a video of myself-introduction on major social platforms, talking about the help and services a patient escort provides, as well as some tips for a quick and convenient medical consultation. At first, she was a little worried that her video would go unnoticed. However, after she uploaded the video, it got over 100 likes and she received her first ever offer as a patient escort.
The memory of her first task is still alive and fresh in her mind. She received a phone call on September 9 from a man whose father was seriously ill and might need surgery. He wanted Zhang Tian to accompany his father through his consultation and treatment.” Zhang Tian made full preparations before meeting her first client and did a very good job despite her nervousness.
“Later, the family expressed their gratitude to me over and over again, which warmed my heart and gave me a sense of achievement.” Zhang Tian said.
1. What do patient escorts do?| A．They assist doctors in hospitals. |
| B．They arrive at hospitals early to check in. |
| C．They take on this career to sell their time. |
| D．They help patients get treated in hospitals. |
| A．she enjoyed seeing an interesting video |
| B．she got inspiration for her own career |
| C．she found a demand for medical workers |
| D．she was well received on social platforms |
| A．She got familiar with the routine work in hospitals. |
| B．She spent two days in major hospitals to meet patients. |
| C．Her video on social platforms attracted her first client. |
| D．The man’s father was seriously ill and might need a surgery. |
| A．Hardworking and considerate. | B．Humorous and careful. |
| C．Ambitious and imaginative. | D．Talkative and positive. |
2 . When Elinor Lobel was 16, a “smart” insulin (胰岛素) pump was attached to her body. Powered by AI, it tracks her glucose levels and administers the right dose of insulin at the right time to keep her healthy. It is one of the new ways that data and AI can help improve lives.
Books that criticize the dark side of data are plentiful. They generally suggest there is much more to fear than fete in the algorithmic(算法的)age.
But the intellectual tide may be turning. One of the most persuasive supporters of a more balanced view is Elinor Lobel’s mother, Orly, a law professor. In The Equality Machine she acknowledges AI’s capacity to produce harmful results. But she shows how, in the right hands, it can also be used to fight inequality and discrimination.
A principle of privacy rules is “minimization”: collect and keep as little information as possible, especially in areas such as race and gender. Ms Lobel flips the script, showing how in hiring, pay and the legal system, knowing such characteristics leads to fairer outcomes.
Ms Lobel’s call to use more, not less, personal information challenges data-privacy orthodoxy(正统观念). But she insists that “tracking differences is key to detecting unfairness.” She advocates g loosening of privacy rules to provide more transparency(透明)over algorithmic decisions.
The problems with algorithmic formulae(公式) are tackled in depth in Escape from Model Land by Erica Thompson of the School of Economics. These statistical models are the backbone of big data and AL. Yet a perfect model will always be beyond reach. “All models are wrong,” runs a wise saying. “Some are useful.”
Ms Thompson focuses on a challenge she calls the Hawkmoth Effect. In the better known Butterfly Effect, a serviceable model, Vin the prediction of climate change, becomes less reliable over time because of the complexity of what it is simulating(模拟), or because of inaccuracies in the original data. In the Hawkmoth Effect, by contrast, the model itself is flawed; it might fail to take full account of the interplay between humidity, wind and temperature.
The author calls on data geeks to improve their solutions to real-world issues, not merely refine their formulae—in other words, to escape from model land. “We do not need to have the best possible answer,” she writes, “only a reasonable one.”
Both these books exhibit a healthy realism about data, algorithms and their limitations. Both recognize that making progress involves accepting limitations, whether in law or coding. As Ms Lobel puts it: “It’s always better to light a candle than to curse the darkness.”
1. Ms Lobel intends to convey that| A．minimisation is a good privacy rule to go by |
| B．algorithms are currently challenged by data privacy |
| C．employing more personal data should be encouraged |
| D．identifying algorithms’ problems leads to better outcomes |
| A．It develops from Butterfly Effect. |
| B．It emphasizes accuracy of original data. |
| C．It enjoys popularity in climate research field. |
| D．It is mentioned to show the model can be faulty. |
| A．Using algorithms to detect differences is hard. |
| B．The application of data and algorithms is limited. |
| C．The reliability of data should be attached importance to. |
| D．Improving algorithms involves accepting its imperfection. |
| A．The Algorithm’s Prospect | B．The Algorithm’s Mercy |
| C．The Algorithm’s Complexity | D．The Algorithm’s Recognition |
3 . I was lucky enough to test into the best high school in the city. But then came my
I knew I had to work to ground myself. My earliest strategy involved keeping quiet and trying to
Fortunately, my first round of grades turned out to be
I loved any subject that involved writing and labored through math. I had classmates who were always a step or two ahead of me, whose achievements seemed effortless, but I tried not to let that get to me. I was beginning to understand that if I put in extra hours of studying, I could often
| A．excitement | B．satisfaction | C．anger | D．worry |
| A．freed | B．dogged | C．warmed | D．guided |
| A．observe | B．admire | C．support | D．calm |
| A．Or | B．So | C．But | D．For |
| A．guess | B．doubt | C．interest | D．risk |
| A．excellent | B．average | C．different | D．unique |
| A．responsibility | B．friendship | C．confidence | D．teamwork |
| A．suddenly | B．frequently | C．accidentally | D．slowly |
| A．close | B．notice | C．locate | D．create |
| A．expecting | B．trying | C．wondering | D．suffering |
4 . Debate about artificial intelligence (AI) tends to focus on its potential dangers: algorithmic bias (算法偏见) and discrimination, the mass destruction of jobs and even, some say, the extinction of humanity. However, others are focusing on the potential rewards. Luminaries in the field such as Demis Hassabis and Yann LeCun believe that AI can turbocharge scientific progress and lead to a golden age of discovery. Could they be right?
Such claims are worth examining, and may provide a useful counterbalance to fears about large-scale unemployment and killer robots. Many previous technologies have, of course, been falsely hailed as panaceas (万灵药). But the mechanism by which AI will supposedly solve the world’s problems has a stronger historical basis.
In the 17th century microscopes and telescopes opened up new vistas of discovery and encouraged researchers to favor their own observations over the received wisdom of antiquity (古代), while the introduction of scientific journals gave them new ways to share and publicize their findings. Then, starting in the late 19th century, the establishment of research laboratories, which brought together ideas, people and materials on an industrial scale, gave rise to further innovations. From the mid-20th century, computers in turn enabled new forms of science based on simulation and modelling.
All this is to be welcomed. But the journal and the laboratory went further still: they altered scientific practice itself and unlocked more powerful means of making discoveries, by allowing people and ideas to mingle in new ways and on a larger scale. AI, too, has the potential to set off such a transformation.
Two areas in particular look promising. The first is “literature-based discovery” (LBD), which involves analyzing existing scientific literature, using ChatGPT-style language analysis, to look for new hypotheses, connections or ideas that humans may have missed. The second area is “robot scientists”. These are robotic systems that use AI to form new hypotheses, based on analysis of existing data and literature, and then test those hypotheses by performing hundreds or thousands of experiments, in fields including systems biology and materials science. Unlike human scientists, robots are less attached to previous results, less driven by bias—and, crucially, easy to replicate. They could scale up experimental research, develop unexpected theories and explore avenues that human investigators might not have considered.
The idea is therefore feasible. But the main barrier is sociological: it can happen only if human scientists are willing and able to use such tools. Governments could help by pressing for greater use of common standards to allow AI systems to exchange and interpret laboratory results and other data. They could also fun d more research into the integration of AI smarts with laboratory robotics, and into forms of AI beyond those being pursued in the private sector. Less fashionable forms of AI, such as model-based machine learning, may be better suited to scientific tasks such as forming hypotheses.
1. Regarding Demis and Yann’s viewpoint, the author is likely to be ______.| A．supportive | B．puzzled | C．unconcerned | D．doubtful |
| A．LBD focuses on testing the reliability of ever-made hypotheses. |
| B．Resistance to AI prevents the transformation of scientific practice. |
| C．Robot scientists form hypotheses without considering previous studies. |
| D．Both journals and labs need adjustments in promoting scientific findings. |
| A．Official standards have facilitated the exchange of data. |
| B．Performing scientific tasks relies on government funding. |
| C．Less popular AI forms might be worth paying attention to. |
| D．The application of AI in public sector hasn’t been launched. |
| A．Transforming Science. How Can AI Help? |
| B．Making Breakthroughs. What Is AI’s Strength? |
| C．Reshaping History. How May AI Develop Further? |
| D．Redefining Discovery. How Can AI Overcome Its Weakness? |
5 . It was a week after my mom had passed away and I didn’t know how to go on with life. So when I received an email from a friend about a race benefiting cancer research, I ignored it. It seemed to prick my heart, as cancer was the disease that had taken my mother away from me.
But something about my friend’s words—“I can help organize the whole thing”—stuck with me. I felt obliged（有义务的）to agree. In the weeks to come, I managed to re-enter the world of the living. I checked our team’s website daily, feeling proud each time a donation ticked up our total. I knew my mom would have wanted it that way. She was the type who never got defeated. It was this very spirit that helped me get by.
When the race ended, I noticed the runners all had one thing in common: There were big smiles on their faces. They made it look so rewarding and effortless. I wanted in.
So I enrolled in another race two months later. Considering I could barely run a mile, it was ambitious. But my friend and I made a training plan so I wouldn’t come in last. I followed it religiously and didn’t let anything get in my way.
Running up and down the city’s hills, I was flooded with memories. I had lived there after college and my mother had visited often. I passed Bloomingdale’s, recalling the time she and I had gotten into a screaming argument there.
I was about to beat myself up when I remembered what Mom had said after her diagnosis of cancer. “I don’t want you to feel guilty about anything.” Her paper-thin hands had held me tightly. A weight lifted from my shoulders.
When the race day arrived, I gave it my all for my mom and for all she had taught me and continued to teach me. As I ran, whenever I felt like slowing down, I pictured her cheering me on.
Crossing the finish line, I was filled with her love and a sense of peace.
1. Why did the author ignore the email in the beginning?
| A．She felt it hard to finish the race. |
| B．She had no time to join in the event. |
| C．She thought the research meaningless. |
| D．She was reminded of her mother’s death. |
| A．The company of her friends. | B．The inspiration from her mom. |
| C．The pleasure in going for a run. | D．The success in organizing an event. |
| A．Considerate and polite. | B．Brave and humorous. |
| C．Strong-willed and caring. | D．Outgoing and patient. |
| A．How I Got Healed in Running | B．The Loss of Sweet Memories |
| C．What Matters Most in Running | D．The Rewards of Great Friendship |
6 . Many people would answer the question of what makes us human by insisting that we are cultural beings. There is no doubt that we are. But one definition of culture is the totality of traditions acquired in a community by social learning from other individuals, and many animal species have traditions. Can we then say that some animals are cultural beings too?
One approach to study culture in animals is the so-called Method of Exclusion (排除), in which scientists investigate behavioral variations across populations of one species. In a famous study, scientists learned that chimpanzee (黑猩猩) behaviors were socially passed on as they were present at some sites but not at others, despite having same ecological settings. For example, chimpanzees in Tai National Park in Ivory Coast are well-known for their nut-cracking skills. Chimpanzees in Gombe national part in Tanzania, on the other hand, do not crack nuts, although nuts exist in their environment too.
However, when applying the Method of Exclusion, one has to be very careful. There are other factors that could also explain the pattern of behavioral evaluation. For example, some of the chimpanzee techniques scientists evaluated occur in only one of the three subspecies. So it’s quite possible that these behaviors also have an innate component. This would mean that one chimpanzee subspecies uses a new technique not out of cultural tradition, but because the behavior is fixed to specific genes. Another factor that has to be excluded is of course the environment Chimpanzees in Mahale do not fish algae (水藻), simply because algae does not exist there.
But when we exclude all the variations that can be explained by genes or environment, we still find that animals do show cultural variations. Does that mean there is no real difference between them and us after all? Not exactly: There is a fundamental difference between human and animal culture. Only humans can build culturally on what generations before us have learned. This is called “cumulative culture”. We don’t have to keep reinventing the wheel. This is called the “ratchet (棘轮) effect”. Like a ratchet that can be turned forward but not back, people’s cultural techniques evolve.
It is likely that behaviors we see today in chimpanzee cultures could be invented over and over again by individual animals themselves. In contrast, a child born today would not be able to invent a computer without the knowledge of many past generations.
1. Why does the author mention the example of the chimpanzees in two parks in Paragraph 2?| A．To prove that culture does exist in animals. |
| B．To justify the uniqueness of the research method. |
| C．To compare how chimpanzees behave in different parks. |
| D．To stress the importance of environment in studying culture. |
| A．Advanced. | B．Inborn. | C．Adaptive. | D．Intelligent. |
| A．Cumulative culture is what sets humans apart from animals. |
| B．Culure in animals is as worthy to be valued as human culture. |
| C．Animals don’t have the ability to invent behaviors in a community. |
| D．The “ratchet effect” decides if humans can build on past experiences. |
7 . Expressive writing or journaling is one way to help you heal from trauma (创伤).
Why does a writing intervention work?
However, for most people, the thought of acknowledging emotions and admitting that there’s something wrong with us is difficult. This is because expressing emotions can bring up feelings of guilt and shame.
If you’re interested in trying out writing as a tool for healing, start your writing by setting a timer for ten minutes.
| A．Despite that, expressive writing remains an accessible tool. |
| B．Of course, expressive writing is hardly a panacea (灵丹妙药). |
| C．Also, seeking help for emotional stress is often seen as a sign of weakness. |
| D．It may seem abnormal that writing about negative experiences has a positive effect. |
| E．Once you have a better handle on your problems, you can move forward and get on with life. |
| F．It is writing from your heart and mind and about the emotion associated with a certain event. |
| G．Let your mind go to the detailed, specific moments to get to the feelings and truth of your experience. |
8 . A medical capsule robot is a small, often pill-sized device that can do planned movement inside the body after being swallowed or surgically inserted. Most models use wireless electronics or magnets or a combination of the two to control the movement of the capsule. Such devices have been equipped with cameras to allow observation and diagnosis, with sensors that “feel,” and even with mechanical needles that administer drugs.
But in practice, Biomechatronics engineer Pietro Valdastri has found that developing capsule models from scratch (从头开始) is costly, time-consuming and requires advanced skills. “The problem was we had to do them from scratch every time,” said Valdastri in an interview. “And other research groups were redeveloping those same modules from scratch, which didn’t make sense.”
Since most of the capsules have the same parts of components: a microprocessor, communication submodules, an energy source, sensors, and actuators (致动器), Valdastri and his team made the modular platform in which the pieces work in concert and can be interchanged with ease. They also developed a flexible board on which the component parts are snapped in like Legos. The board can be folded to fit the body of the capsule, down to about 14 mm. Additionally, they compiled (编译) a library of components that designers could choose from, enabling hundreds of different combinations. They arranged it all in a free online system. Designers can take the available designs or adapt them to their specific needs.
“Instead of redeveloping all the modules from scratch, people with limited technological experience can use our modules to build their own capsule robots in clinical use and focus on their innovation,” Valdastri said.
Now, the team has designed a capsule equipped with a surgical clip to stop internal bleeding. Researchers at Scotland’s Royal Infirmary of Edinburg have also expressed interest in using the system to make a crawling capsule that takes images of the colon(结肠). One research group, led by professors at the Institute of Digestive Disease of the Chinese University of HongKong, is making a swimming capsule equipped with a camera that pushes itself through the stomach.
One limitation of Valdastri’s system is that it’s only for designing models. Researchers can confirm their hypotheses (假设) and do first design using the platform, but will need to move to a custom approach to develop their capsules further and make them practical for clinical use.
1. According to the passage, Valdastri and his team created the platform to ________.| A．adopt the latest technologies |
| B．make their robots dream come true |
| C．help build specialized capsule robots |
| D．do preciser observation and diagnosis |
| A．Perform live. | B．Run independently. |
| C．Act in a cooperative way. | D．Carry on step by step. |
| A．Valdastri’s system can’t provide a complete capsule creation. |
| B．The modular platform is more useful than a custom approach. |
| C．The capsules can move in human’s body automatically. |
| D．It costs more to module the capsules on the board. |
9 . Rethinking Obesity(肥胖症)
In principle, it sounds simple: eat less and move more. This dietary advice for dealing with obesity has been around for decades.
One possibility is that we haven’t tried hard enough. Perhaps we have lacked the discipline and willpower to maintain healthy dietary and exercise habits—a challenge made more difficult today for those surrounded by inexpensive, tasty highly processed foods.
The key to how this works in obesity is insulin (胰岛素) processed, rapidly digestible carbohydrates (碳水化合物食品) raise our insulin level too high.
The two opposing views of cause and effect in obesity have very different implications for how to prevent and treat weight problems. The usual approach focuses on how much to eat, with prescriptions (处方) for daily calorie intake.
This way of thinking might help explain why calorie restriction usually fails long before a person with obesity approaches an ideal body weight. A low-calorie, low-fat diet further restricts an already limited supply of energy to the body, worsening hunger without addressing the underlying tendency to store too many calories in body fat.
Although much more research will be needed to test this idea, it is time to question the basic assumptions about cause and effect calories and weight gain that have controlled our thinking.
| A．Yet, worldwide obesity rates just keep going up. |
| B．In our view the emphasis should be place a on what to eat. |
| C．It is important to control the amount of food consumed by us. |
| D．Obesity is a disease that affects 650 million adults worldwide. |
| E．Or perhaps the problem is the focus on “calorie balance” itself. |
| F．Weight loss becomes a battle between mind and metabolism(新陈代谢). |
| G．This causes fat cells to take in to many calories, leaving fewer for the rest of the body. |
10 . It had been an interesting soccer match. Jerry was so absorbed in it that everyone
“Mom, I want a soccer uniform, he begged his mother.
“OK,” said his mother, “but you need to have
The days passed by, but he got no
He drew a circle with the help of a bowl and modified the soccer image onto the T-shirt. He also took
“Jerry! What are you doing?” his mother suddenly appeared.
“I may not get the uniform, but I can try to paint the image on my T-shirt, I thought.” He was
“It’s OK,” said Mom.
“If we had fulfilled your every want, your inborn
“Thank you, Mom.” He ran playfully.
1.| A．controlled | B．sensed | C．supported | D．expected |
| A．thirsty | B．realistic | C．cautious | D．selfish |
| A．confidence | B．motivation | C．inspiration | D．patience |
| A．decision | B．response | C．judgment | D．recognition |
| A．purchase | B．exchange | C．paint | D．sew |
| A．interest | B．energy | C．courage | D．care |
| A．eager | B．surprised | C．afraid | D．relieved |
| A．appreciated | B．blamed | C．rewarded | D．thanked |
| A．taste | B．fondness | C．talent | D．fear |
| A．willpower | B．honesty | C．responsibility | D．tolerance |
