Đề thi vào lớp 10 môn Anh Chuyên - Sở GD&ĐT Ninh Bình năm 2026

GYROSCOPES

Applications
- In laser and 2.1
- In consumer appliances

Strong points
- A practical, 2.2 beneficial consumer product
- A cheap and effective muscle-strengthening aid

Operation
- Shaped into palm-sized 2.3
- Set in motion by the movements of the arm and wrist in synch

Purposes
- Create considerable 2.4
- Aid to strengthen the lower arm
- Could be used as an everyday toning and exercise device

Targeted customers
- Those suffering from serious lower-arm 2.5
- High-performance athletes

The Transcontinental Railroad

The Union Pacific and Central Pacific railroad presidents gathered on May 10, 1869, in Promontory, Utah, to drive a ceremonial final spike into a rail line that 3.1uniteddirectedrelatedcooperated approximately 2,000 miles of track. For the first time in American history, 3.2making this travelling possibleit made possible travellingthis made it possible to traveltravelling made it possible by railroad over the country. Travellers headed towards the West would no longer have to 3.3persistsustainwithstandendure the exhausting and hazardous voyages by wagon train or by boat.

Statesmen in the East and the West had 3.4discoveredbelievedapprovedrecognized the necessity for a connection between the two coasts at least since 1832. However, Congress did not approve funding 3.5onofuntilat 1853.

Conditions for the Union Pacific workforce were 3.6apprehensiveappealingappallingapparent because of harsh winters, excruciating summer heat, and the lawless, 3.7hand-to-mouthout-of-pocketblow-by-blowrough-and-tumble nature of newly established western cities. 3.8ProvidedHoweverWithoutDespite all the hardships they faced, the Union Pacific and Central Pacific employees were able to complete the railroad by 1869, 3.9furtherforwardaheadbehind of schedule and under budget by 3.10buildingbeing builtbeing buildinghaving been built approximately 2,000 miles of track.

Travelling by wagon train took months, and travelling by water took weeks. Now, it took only days.

IT'S ONLY SKIN DEEP

We are the only animal that chooses what it will look like. True, the chameleon changes colour - but not (WILL) 4.1. Unlike us, it doesn't get up in the morning and ask itself, "What shall I look like today?", but we can and do.

Indeed, the (ANTIQUE) 4.2 of body decoration points to the conclusion that it is a key factor in our development as the dominant life-form on our planet. By (CUSTOM) 4.3 their physical appearance, our ancestors distanced themselves from the rest of the animal kingdom. Within each tribe this helped them to mark out differences of role, status, and kinship. Our ancestors apparently developed (ORDINARY) 4.4 techniques of body decoration for practical reasons. How to show where one tribe ends and another begins? How to underline in a lasting way the significance of an individual becoming an adult member of society? Arguably, without the expressive capabilities of such 'body language' we would have been (FINITE) 4.5 less successful as a species.

The Hamster's Body Clock

Hamsters have no need for alarm clocks. In the strange world of circadian rhythms - the twenty-four-hour cycle which governs almost every biological process in every living thing, 6.1 body temperature to digestion to sleeping and waking - the hamster is the equivalent of the Swiss watch.

According to Professor Michael Antle from the University of Calgary's Department of Psychology, you can predict to within a minute when a hamster is going to wake up. Humans, however, are more 6.2 a cheap supermarket wall-clock, since their sleeping patterns are less reliable. Professor Antle is studying the group of 20,000 cells in the brain that 6.3 up the circadian clock. He's hoping to explain something astonishing that's happening to his hamsters. By turning on their light for fifteen minutes in the middle of the night, he can make them wake up an hour earlier the next day. But if 6.4 he gives them a new drug that he's experimenting with, they're up and about eight hours early. They will still need their usual fourteen hours' sleep, but their biological clocks appear to have been set back. When he saw the effect initially in his laboratory, Antle was shocked at how big it was. An eight-hour adjustment is something useful - it means that a hamster could be transported from its home in Canada all the way to London without suffering from jetlag. If it could do 6.5 for people, Antle really would be on to something.

Venus

In the history of astrology, the first maps of Venus were made using radar beams transmitted from Earth. Radar was the only way to map its surface, because the clouds on Venus are so thick that the surface cannot be seen through them. The results of these early attempts were relatively crude and difficult to interpret, although the regions known as Alpha and Beta Regions were discovered. This created a challenging mission for astronauts in the early twentieth century. The first direct view of the surface came from probes, which were landed on Venus in 1975 by the spacecraft Venera 9 and 10, and showed a dry rock-strewn surface.

With much effort, maps of the surface improved dramatically in 1978, when the Pioneer-Venus 1 spacecraft went into orbit around Venus, furnished with a radar altimeter. It showed huge rolling plains stretching right around the planet, some lowland areas, and two highland regions called Ishtar and Aphrodite.

In this scientific research project, the peaks of the highest mountains, Maxwell Montes, in the eastern part of Ishtar, were found to be 12,000 metres above the general surface level, so they are appreciably higher than the Himalayas. The second region, Aphrodite, which is larger than Ishtar, has a vast rift valley at its eastern end nearly 3,000 metres deep, 2,200 kilometres long, and 280 kilometres wide. Two shield volcanoes, broad volcanoes formed of successive outpourings of lava, which are much larger than any found on Earth, were also found isolated from the two upland areas. Six years later a great many impact craters and small volcanoes were found by Venera 15 and 16 orbiters.

Later yet, the Magellan spacecraft entered orbit around Venus in August 1990, and over the next two years completed a detailed radar mapping of the surface. It found that the surface is mostly volcanic, with large lava-flooded plains and thousands of volcanoes. There are also signs of tectonic activity, which has caused, for example, multiple faulting and deep fractures. Besides, there are a number of rift valleys, some of which have been partly flooded by molten lava, and a number of impact craters, the density of which has enabled the scientists to estimate how old various areas are. The absence of impact craters in an area suggests an age of no more than a few tens of millions of years.

Attitudes towards Artificial Intelligence

A. Artificial Intelligence (AI) can already predict the future. Police forces are using it to map when and where crime is likely to occur. Doctors can use it to predict when a patient is most likely to have a heart attack or stroke. Researchers are even trying to give AI imagination so it can plan for unexpected consequences. Many decisions in our lives require a good forecast, and AI is almost always better at forecasting than we are. Yet for all these technological advances, we still seem to deeply lack confidence in AI predictions. Recent cases show that people don't like relying on AI and prefer to trust human experts, even if these experts are wrong. If we want AI to really benefit people, we need to find a way to get people to trust it. To do that, we need to understand why people are so reluctant to trust AI in the first place.

B. Watson for Oncology, one of technology giant IBM's supercomputer programs promoted to cancer doctors, was perceived as a PR disaster. Although 80% effective recommendations on the treatment of 12 cancers were promised to deliver, doctors are in a rather difficult situation at the first time they interacted with Watson. On the one hand, if Watson provided guidance about a treatment that coincided with their own opinions, physicians did not see much point in Watson's recommendations. The supercomputer was simply telling them what they already knew, and these recommendations did not change the actual treatment. On the other hand, when Watson recommended an opposing point with the experts', particularly without any explanation why its treatment was plausible, it was considered to be incompetent. This is because its machine-learning algorithms were simply too complex to be fully understood by humans. Consequently, this has caused even more suspicion and disbelief, leading many doctors to ignore the seemingly outlandish AI recommendations and stick to their own expertise.

C. This is just one example of people's lack of confidence in AI and their reluctance to accept what AI has to offer. Trust in other people is often based on our understanding of how others think and having experience of their reliability. This helps create a psychological feeling of safety. AI, on the other hand, is still fairly new and unfamiliar to most people. Even if it can be technically explained (and that's not always the case), AI's decision-making process is usually too difficult for most people to comprehend. And interacting with something we don't understand can cause anxiety and give us a sense that we're losing control. Many people are also simply not familiar with many instances of AI actually working, because it often happens in the background. Instead, they are acutely aware of instances where AI goes wrong. Embarrassing AI failures receive a disproportionate amount of media attention, emphasizing the message that we cannot rely on technology. Machine learning is not foolproof, in part because the humans who design it aren't.

D. A recent study has been conducted to explore people's feelings regarding AI, in which participants watched a wide range of science-fiction films about automation, then answered some questions about AI in everyday life. Their attitudes about AI were polarized by just watching a cinematic vision of human technological future regardless of positive or negative light in the film they were exposed to. In other words, optimists became more extreme in their enthusiasm for AI and sceptics became even more guarded. This suggests that relevant evidence about AI is used in a biased manner to support their existing attitudes, a deep-rooted human tendency known as 'confirmation bias'. As AI is represented more and more in media and entertainment, it could lead to two groups in society, either benefiting from AI or rejecting it. More pertinently, refusing to accept the advantages offered by AI could place a large group of people at a serious disadvantage.

E. Fortunately, we already have some ideas about how to improve trust in AI. Simply having previous experience with AI can significantly improve people's consciousness about the technology. Evidence also suggests the more frequently users expose to other technologies such as the Internet, the more you trust them. In addition, to change people's attitudes about this tool, it is recommended that the algorithms which AI uses and the purpose they serve should be revealed more. Several high-profile social media companies and online marketplaces already release transparency reports about government requests and surveillance disclosures. A similar practice for AI could help people have a better understanding of the way algorithmic decisions are made.

F. Research suggests that allowing people some control over AI decision-making could also improve trust and enable AI to learn from human experience. For example, one study showed that when people were allowed the freedom to slightly modify an algorithm, they felt more satisfied with its decisions, more likely to believe it was superior and more likely to use it in the future. There is no need to understand the intricate inner workings of AI systems, but if people are given a degree of responsibility for how they are implemented, they will be more willing to accept AI into their lives.