1 . Some songs might speak to your soul even if you don't know the words. The almost magical way that music reflects and influences our emotions led American poet Henry Wadsworth Longfellow to declare it the “universal language of mankind”. But how universal is it really?

A team of more than a dozen researchers and countless undergraduates set out to collect and interpret descriptions and recordings of musical performances around the world. Their first finding: Music is indeed universal. Or at least statistical modeling strongly suggests that more than 99% of societies have music. Then, they analyzed the song descriptions for sixty very different societies and looked at different qualities related to song performance.

As they classified the songs, they found that three dimensions (方面) accounted for more than a quarter of the variability between songs. The first was how formal or informal a song was. Songs high in formality had large audiences and lots of instruments, often involved ceremonial events, and frequently had adult-only audiences. Informal events had smaller audiences, including children, or no audience at all. The second was how arousing a song was to its listeners. Lively events involving lots of dancing were high on this dimension, while a low value reflected a calmer event, like someone singing to themselves or a baby. The last was how religious song was. Songs used in ceremonies were high in religiosity, while those without a spiritual context scored low.

The researchers applied their findings to four widespread categories of music: lullabies (摇篮), dance songs, love songs and healing songs, and found clear trend. Most dance was highly arousing and formal, but low in religiosity. Lullabies were mostly low in formality and low in arousal. And healing songs scored high in all dimensions while love songs were low in all dimensions. Even more interesting, the distribution of these behaviors was similar in all societies studied.

Scholars say that their database could fuel future research into even more inspiring questions about music universals. And their method might be used to pick out patterns in other hard-to-analyze fields, like storytelling or visual art.

1. How was the research conducted?

A．By making comparison and contrast.	B．By finding similarities.
C．By collecting and analyzing data.	D．By illustrating examples.

2. Which kind of music may involve the most audiences and instruments?

A．Lullabies.

B．Dance songs.

C．Love songs.

D．Healing songs.

3. How is the future of their research findings according to the scholars?

A．Promising.

B．Unpredictable.

C．Impractical.

D．Limited.

4. What can be concluded from the passage?

A．Songs can speak to your soul only if you know their words.

B．Differences in formality lead to the variability between songs.

C．Music is classified by the number of audience and instruments.

D．Research on the universals of music can help explore other fields.

2 . Do you have a brain for math? New research indicates that levels of two key neurotransmitters (脑神经传递素) — glutamate (谷氨酸) and gamma-aminobutyric acid (GABA)can predict mathematical abilities, suggesting brain chemistry may be playing a role in those who find math easy.

The new study, published in the journal PLOS Biology, recruited 255 subjects extending a range of six-year olds in primary school to university students. The research focused on glutamate and GABA, known to play a role in brain plasticity (可塑性) and learning. Based on prior research, the focus was on two brain regions linked with mathematical abilities — the left intraparietal sulcus (IPS 顶叶内沟) and the left middle frontal gyrus (MFG 脑额中回).

The results were interestingly different. In the youngest subjects high GABA levels and low glutamate levels in the left IPS were consistently associated with high math skills. But in the older university group the exact opposite was seen: low GABA and high glutamate were linked with strong mathematical abilities. Levels of both neurotransmitters in the MFG did not associate with math skills.

The group was tested twice over 18 months, allowing the researchers to see if these neurotransmitter levels could predict mathematical ability into the future. And it worked, with neurotransmitter levels effectively predicting one’s success on math tests completed a year and a half later.

Another recent study from the same research team looked specifically at GABA levels in MFG of 14 to 18 year olds. That research indicated MFG GABA levels could effectively predict whether a student was still studying maths or had ceased that subject years prior.

Cohen Kadosh, one of the researchers working on the study, says this may indicate math education can help stimulate the development of key brain regions. Further research will work on whether certain learning interventions can help those children less interested in math so these brain regions still get the developmental workout they need.

“Not every adolescent enjoys maths so we need to investigate possible alternatives, such as training in logic and reasoning that engage the same brain area as maths,” says Cohen Kadosh.

1. What is the new study aimed at?

A．Exploring mental development of the subjects.

B．Finding the tie between brain chemistry and math.

C．Testing the link between brain regions.

D．Revealing the structure of brain.

2. What can be learned from the findings?

A．The levels of GABA decide one’s math skills.

B．Low MFG glutamate means poor math ability.

C．Neurotransmitters in the MFG affect math skills.

D．Math education may help with brain development.

3. What can better math education according to Cohen Kadosh?

A．Studying more possible options.

B．Tracing slow learners’ early learning.

C．Training math learners respectively.

D．Developing key relevant brain areas.

4. What can be the best title of the text?

A．Factors Affecting Math Skills

B．Ways to Promote Math Education

C．Brain Activities Involved in Math Study

D．Math Ability Predicted by Neurotransmitters

3 . The Surprising Strength of “Weak” Social Ties

It’s long been known that a community of supportive relationships improves our quality of life and can even help us recover from illness.     1    . Regularly interacting with a wide variety of social ties, both “weak” and “strong”, enhances our satisfaction. A rich diversity of ties provides more significant benefits to well-being, and “weak” social ties can prove just as important to life satisfaction as core, or “strong” ties.     2    . There you can find the people who cheer, serve, support, comfort, educate, motivate, and entertain you.

Claire gets cheered up by going to the library and chatting with her favorite librarian every week. Sherry gets great joy from her Sunday breakfasts at a local diner because the manager and her favorite waitress are nice to her.     3    . I remember discussing Anna Karenina on an airplane with a wise economics professor, and finding meaningful moments of joy with street musicians and performers.

    4    . When you show kindness to a stranger, your seemingly small act might stay in their memory as a source of support and positivity. Everyone needs to feel significant in the eyes of another. You could be that person for someone in your extended circle. That’s why it’s so important to reach out to people around you, especially when they’re going through hard times.

When we feel blue or lonely, we tend to turn down social engagements, either to avoid the imagined embarrassment of being the only sad person in a group or because socializing with people we don’t know well can be awkward at first.     5    . Being open to both our strong and weak ties allows us to benefit from the comfort, connection, and community they provide.

A．All of those connections matter — and so do you

B．Harvard researcher Hanne Collins discovered something new

C．Even those we meet only once can leave a lasting impression

D．Our shared kindness and familiarity offer me a sense of community

E．Interacting with the weak ties encourages us to behave more professionally

F．But saying yes, despite the hesitation, offers an opportunity to feel less lonely

G．So notice, pay attention to, and be grateful for your big, wide world of loose social ties

4 . “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.

2. The strategy of “assuming you are wrong” may contribute to ______.

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

3. The underlined word “demoralizing” in Paragraph 5 means ______.

A．discouraging

B．ineffective

C．unfair

D．misleading

4. The tone the author uses in talking about the untested hypothesis is ______.

A．doubtful but sincere	B．disapproving but soft
C．authoritative and direct	D．reflective and humorous

5 . Art Builds Understanding

Despite the long history of scholarship on experiences of art, researchers have yet to capture and understand the most meaningful aspects of such experiences, including the thoughts and insights we gain when we visit a museum, the sense of encounter after seeing a meaningful work of art, or the changed thinking after experiences with art. These powerful encounters can be inspiring, uplifting, and contribute to well-being and flourishing.

    1     It contributes to facilitating a better understanding of ourselves, the human condition, and moral and spiritual concepts. The question is how that happens — what are the attributes of meaningful experiences of art?

According to the mirror model of art developed by Pablo P. L. Tinio, aesthetic reception corresponds to artistic creation in a mirror-reversed fashion. Artists aim to express ideas and messages about the human condition or the world at large.     2     This results in the build-up of layers of materials — from initial studies and sketches to the final, refined piece. A viewer’s initial interaction with an artwork starts where the artist has left off. Their interaction first involves the processing surface features, such as color, texture, and the finishing touches applied by the artist during the final stages of the creative process.     3    

In addition, art making and art viewing are connected by creative thinking. Research in a lab at Yale University shows that an educational program that uses art appreciation activities builds creative thinking skills. It showed that the more time visitors spent engaging with art and the more they reflected on it, the greater the correspondence with the artists’ intentions and ideas.     4    

Correspondence in feeling and thinking suggests a transfer — between creator and viewer — of ideas, concepts, and emotions contained in the works of art. Art has the potential to communicate across space and time.     5     What it takes for this to happen is active engagement with art in contexts that facilitate this engagement, especially museums.

A．The viewers gain a new perspective on the story.

B．The theory of aesthetic cognitivism describes the value of art.

C．This helps to create connections and insights that otherwise would not happen.

D．To do so, they explore key ideas and continually expand them as they develop their work.

E．After spending more time with the work, the viewer begins to access the ideas of the artist.

F．For example, in one activity, people are asked to view a work of art from different perspectives.

G．Participants were more original in their thinking when compared to those who did not take part in the program.

6 . 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.

2. How does ChatGPT write poems?

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.

3. Why does the author mention Dickinson and cloud in paragraph 4?

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.

4. Which of the following can best describe the author’s attitude towards AI poetry?

A．Acceptable and favorable	B．Amazed and admiring
C．Indifferent and uncaring	D．Doubtful and uneasy

7 . 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

2. What can we learn from the passage?

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.

3. What can be inferred from the last paragraph?

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.

4. Which would be the best title for the passage?

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?

8 . The high-tech revolution has inspired a pleasure endless stream of new and exciting electronic products that we just can’t live without. In fact, the speed of technological innovation can make last year’s must-have this year’s junk. And that’s the problem.

The average life span of a personal computer has been shortened to around 18 months and this has nothing to do with worn-mice or damaged disk drives. Simply put, electronic products can become out of date before you’ve even figured out how they work.

So what happens to all those old keyboards, monitors, organizers and CPUs? Most are stored away in a warehouse (仓库), taking up valuable space. But many end up in landfills, and that is where the trouble really begins. Computer monitors can contain up to 3.5 kg of dangerous waste once they are no longer in use.

Unfortunately, this problem is not going to disappear anytime soon. In fact, it is growing by the minute. In Japan alone, people throw away some 20 million TVs, washing machines, refrigerators and air conditioners each year. What is to be done with all this techno-trash?

One way to reduce waste is to avoid throwing away in the first place. Many companies reuse parts from old products in new models. This is not cheating-it makes both environmental and economic sense. Cannon, for example, has adopted a philosophy known as “kyosei”, meaning “living and working together for the common good?” — a goal of achieving balance between the environment and the corporate (公司的) activities. The company has even gone so far as to say that environmental assurance should come before all business activities, and that companies unable to achieve such assurance do not deserve to remain in business.

As part of that effort, the company has started a global recycling program with a goal to reduce, reuse and recycle more than 90% of its used products. In 1999, for example, Cannon collected 128, 000 copying machines and 12, 175 tons of toner cartridges (色粉盒) in Japan, Europe and the United States.

Some argue that electronic garbage can also be controlled during the design phase. This concept, called “design for the environment”. Not only does this make environmental sense, but it saves the customer money. IBM, meanwhile, recently planned programs in Canada and the US that, for a small fee, will take back not just an IBM but also any manufacturer’s computer. Depending on the age and condition, the equipment will then be either donated to charity, or broken down for reusable parts and recyclable materials.

1. With the rapid development of science and technology high-tech products can ____.

A．last for many years

B．become worn out soon

C．become old and useless soon

D．be used forever

2. What is not the problem caused by the out-of-date high-tech products?

A．Too much room is needed for their probable storage.

B．People do not know how to deal with them at all.

C．The amount of this techno-trash is increasing everyday without stop.

D．Harmful substances contained within may pollute the environment.

3. What idea can be learned through the example of Canon?

A．Business must be achieved at the cost of environment.

B．Environment holds great importance than business.

C．Business and environment has little impact on each other.

D．Recycling makes only environment sense instead of economic benefits.

4. When the author says, “electronic garbage can be controlled during the design phase”, he means ________.

A．while designing products, we must make something to contain garbage

B．while designing products, don’t throw away garbage away

C．while designing, we must work out how much garbage the new product will bring about

D．while designing, we must take environment into consideration.

5. What can be inferred from reading the passage?

A．The problem caused by high-tech products can’t be solved in short time

B．The techno-trash problem can easily be solved in big countries

C．The problem can be solved to some degree if enough attention is paid

D．It is still hard to say whether this problem can be solved or not

9 . When you look ahead at the year to come, I hope you focus on all the positives even if the negatives exist, because positive thinking can help you get where you want to go.

Positive thinking is not the same as optimism. Being optimistic means believing that everything is going to work out great. But positive thinking is more than that. It’s a mindset or a way of looking at the world and what you do.     1    

To think positively, first of all, we need to look at problems, mistakes and failures as normal. Imagine you bomb a big job interview. A negative thinker will be upset by the fact that he didn’t get the job.     2     He will analyze what he did and figure out how to do it better next time. And he’ll also think about what he did well and try to repeat and improve on those successes. This means focusing on the big picture.

One trick to positive thinking is to imagine how you’ll think back to things that are happening now.     3     There are bad things that happened last year that you can probably laugh about now. You understand what was a big deal and what was not. Try to do that in the present.

    4     A negative thinker will focus on the past, especially past failures. But the past cannot be changed. It’s done and dusted. The future, however, is yet to be written. And that’s where the positive thinker will focus his attention.

Positive thinking is a mental habit. It takes practice. Sometimes, we have to remind ourselves to focus on the future and on possibility.     5     But if you can do it, there are some great payoffs: greater confidence, a better chance of success, better health condition as well as a better quality of life.

A．A positive thinker will learn from the experience.

B．Negative thinkers will look at failures as end points.

C．Positive thinking often means separating the past and the future.

D．It’s a belief in possibility, solutions to problems and the big picture.

E．Sometimes, it’s hard to learn from our failures or see the big picture.

F．We can see the power of positive thinking when it comes to problem-solving.

G．You know from experience that the passing of time brings a fresh perspective.

10 . Travelling abroad can present many challenges, including long journeys, language problems, and culture shocks, plus the expense of transport and accommodation.     1     It is rewarding to get to experience life in different ways.

One of the wonderful benefits of going abroad is that you can learn history and culture without real effort. There’s a natural tendency to absorb other cultures and pick up historical concepts, while enjoying yourself at the same time.     2    

Another great benefit is that living in a foreign culture is the only real way to fully understand its language.     3     Even if you’re a complete beginner and only manage to pick up a few key phrases of the local language, you still know more than when you arrive.

    4     People in other countries can demonstrate different ways of doing things and alternative ways of being. It can open up your mind and generate new ideas. A direct encounter with a fresh expression of arts, religions, architecture, and food can contribute to an enlightening and valuable experience.

Removing yourself from the familiar and travelling to a new country can be a very powerful tool for gaining self-awareness and deeper understanding.     5     It can help you shift how you see yourself. Perhaps ironically, visiting a foreign country can also teach you things about your homeland. You get to view your land of birth from another perspective and have something to compare it with.

A．It’s far superior to learning it in a classroom.

B．The new land gives you a fresh social environment.

C．The direct experience helps you remember something easily.

D．Many people wonder what they should do in a foreign country.

E．Travelling abroad can also boost creativity and drive innovation.

F．Another benefit of travelling abroad is the relaxation you can get.

G．However, there’s rarely a dull moment when you’ re in a different country.