1 . As we all know, insects can be remarkably agile (灵活的) in flight. This is really hard to build into flying robots, but MIT Assistant Professor Kevin Yufeng Chen has developed an insect-sized drone (无人机) that approaches insects’ agility.
Typically, drones require wide open spaces. “If we look at most drones today, they’re usually quite big,” says Chen. “Most of their applications involve flying outdoors. The question is: Can you create an insect-sized drone that can move around in very crowded and complex spaces?”
According to Chen, he overcame many problems when building the drone. The insect-sized drone requires a fundamentally different construction from a larger one. The large drone is usually powered by a motor, but the motor loses efficiency as you shrink it. So, Chen says, “For an insect-sized drone, you need to look for alternatives.” The principal alternative until now has been employing a small, rigid actuator (执行器) built from new materials. Chen designed a more agile tiny drone using soft actuators instead of hard ones.
......
1. What can we know about the actuator designed by Chen?| A．It weighs about six grams. |
| B．It drives the insect-sized drone. |
| C．It loses efficiency too much. |
| D．It employs conventional materials. |
2 . Scientists say they have developed a system that uses machine learning to predict when and where lightning will strike. The research was led by engineers from the Swiss Federal Institute of Technology in Lausanne, Switzerland.
Lightning is a strong burst of electricity in the atmosphere. It can strike between clouds or between a cloud and the ground. Since lightning carries an extremely powerful electrical charge, it can be destructive and deadly. It is difficult to know exactly how many people die of lightning-related causes. European researchers have estimated that between 6,000 and 24,000 people are killed by lightning worldwide each year. The strikes can also cause power failure, destroy property, damage electrical equipment and start forest fires.
For this reason, climate scientists have long sought to develop methods to predict and control lightning. The system tested in the experiments uses a combination of data from weather stations and machine learning methods. The researchers developed a prediction model that was trained to recognize weather conditions that were likely to cause lightning. The model was created with data collected over a 12-year period from 12 Swiss weather stations in cities and mountain areas. The data related to four main surface conditions: air pressure, air temperature, relative humidity (湿度) and wind speed. The atmospheric data was placed into a machine learning algorithm (计算程序), which compared it to records of lightning strikes. Researchers say the algorithm was then able to learn the conditions under which lightning happens.
“Once trained, the system made predictions that proved correct almost 80 percent of the time,” the Swiss Federal Institute of Technology said in a statement. “It can now be used anywhere.”
Amirhossein Mostajabi, a PhD student at the institute, said current systems for gathering such data are slow and complex and require costly collection equipment like radar or satellites. “Our method uses data that can be obtained from any weather station,” he said. “This will improve data collection in very remote areas not covered by radar and satellite or in places where communication systems have been cut,” he added.
The researchers plan to keep developing the technology in partnership with a European effort that aims to create a lightning protection system. Scientists working on the Paris-based project are experimenting with a laser technology that could someday control lightning activity. The idea is that powerful, ground-based lasers can be positioned in the sky to direct energy from lightning.
Which is the correct order of how the system works?
① develop a prediction model.
② learn to recognize weather conditions.
③ collect related data.
④ input the data onto the computer.
⑤ make predictions.
| A．①→②→③→④→⑤ | B．③→④→①→②→⑤ |
| C．①→②→④→③→⑤ | D．③→①→②→⑤→④ |
3 . Cuaya and her colleagues decided to use brain images from MRI scanning to shed light on her hunch. They worked with dogs of various ages that had, until the experiment, only heard their owners speak just one of the two languages, Spanish or Hungarian. Not surprisingly, getting the dogs to happily take part in the experiment took some creative coaxing and animal training! The researchers first needed to teach Kun-kun and her 17 fellow participating dogs including a labradoodle, a golden retriever and Australian shepherds, to lie still in a brain scanner. Their pet parents were always present, and they could leave the scanner at any point.
What did Cuaya consider when choosing dogs for study?
| A．Age limits. | B．Brain patterns. |
| C．Language exposure. | D．Owners' commands. |
4 . Goffin’s cockatoos, a kind of small parrot native to Australasia, have been shown to have similar shape-recognition abilities to a human two-year-old. Though not known to use tools in the wild, the birds have proved skilful at tool use while kept in the cage. In a recent experiment, cockatoos were presented with a box with a nut inside it. The clear front of the box had a “keyhole” in a geometric shape, and the birds were given five differently shaped “keys” to choose from. Inserting the correct “key” would let out the nut.
In humans, babies can put a round shape in a round hole from around one year of age, but it will be another year before they are able to do the same with less symmetrical (对称的) shapes. This ability to recognize that a shape will need to be turned in a specific direction before it will fit is called an “allocentric frame of reference”. In the experiment, Goffin’s cockatoos were able to select the right tool for the job, in most cases, by visual recognition alone. Where trial-and-error was used, the cockatoos did better than monkeys in similar tests. This indicates that Goffin’s cockatoos do indeed possess an allocentric frame of reference when moving objects in space, similar to two-year-old babies.
1. How did the cockatoos get the nut from the box in the experiment?| A．By following instructions. | B．By using a tool. |
| C．By turning the box around. | D．By removing the lid. |
| A．Using a key to unlock a door. | B．Telling parrots from other birds. |
| C．Putting a ball into a round hole. | D．Grouping toys of different shapes. |
5 . Psychologist Susan Levine, an expert on mathematics development in young children the University of Chicago, found children who play with puzzles between ages 2 and 4 later develop better spatial skills. Puzzle play was found to be a significant predictor of cognition(认知) after controlling for differences in parents’ income, education and the amount of parent talk, Levine said.
1. In which aspect do children benefit from puzzle play?| A．Building confidence. | B．Developing spatial skills. |
| C．Learning self-control. | D．Gaining high-tech knowledge. |
| A．Parents’ age. | B．Children’s imagination. |
| C．Parents’ education. | D．Child-parent relationship. |
6 . It’s common knowledge that the woman in Leonardo da Vinci’s most famous painting seems to look back at viewers, following them with her eyes no matter where they are in the room. But this common knowledge turns out wrong.
A new study finds that the woman in the painting is actually looking out at an angle of 15.4° off to the viewer’s right — well outside the range that people normally believe when they think someone is looking right at them. In other words, said the study author, Horstmann, “She’s not looking at you.”
This is ironic (讽刺), because the entire phenomenon of a person’s gaze (凝视) in a photograph or painting seeming to follow the viewer is called the “Mona Lisa effect”, which is absolutely real. If a person is illustrated or photographed looking straight ahead, even people viewing the portrait from an angle will feel they are being looked at. As long as the angle of the person’s gaze is no more than about 5 degrees off to either side, the Mona Lisa effect occurs.
Horstmann and his co-author were studying this effect for its application in the creation of artificial-intelligence avatars (虚拟头像) when Horstmann took a long look at the “Mona Lisa” and realized she wasn’t looking at him.
To make sure it wasn’t just him, the researchers gathered 24 people to view images of the “Mona Lisa” on a computer screen. They set a ruler between the viewer and the screen and asked the participants to note which number on the ruler intersected (相交) Mona Lisa’s gaze. To calculate the angle of Mona Lisa’s gaze as she looked at the viewer, they moved the ruler farther from or closer to the screen during the study. Consistently, the researchers found, participants judged that the woman in the “Mona Lisa” portrait was not looking straight at them, but slightly off to their right.
So why do people repeat the belief that her eyes seem to follow the viewer? Horstmann isn’t sure. It’s possible, he said, that people have the desire to be looked at, so they think the woman is looking straight at them. Or maybe the people who first coined the term “Mona Lisa effect” just thought it was a cool name.
1. It is generally believed that the woman in the painting “Mona Lisa” ________.| A．attracts the viewers to look back |
| B．seems mysterious because of her eyes |
| C．fixes her eyes on the back of the viewers |
| D．looks at observers wherever they stand |
| A．The Mona Lisa effect does not really exist. |
| B．The mystery of the woman’s smile in the painting. |
| C．The angle of the gaze in Mona Lisa effect. |
| D．Mona Lisa effect does not occur with Mona Lisa. |
| A．confirm Horstmann’s belief |
| B．create artificial-intelligence avatars |
| C．calculate the angle of Mona Lisa’s gaze |
| D．show how the Mona Lisa effect can be applied |
| A．Horstmann thinks it cool to coin the term “Mona Lisa effect”. |
| B．The Mona Lisa effect contributes to the creation of artificial intelligence. |
| C．Feeling being gazed at by Mona Lisa may be caused by the desire for attention. |
| D．The position of the ruler in the experiment will influence the viewers’ judgement. |
7 . Because the commercial internet has been developed with so little regard for privacy, tech companies have been able to turn personal data into considerable profits, raising billions of dollars off their ability to collect and sell information about anyone who has wandered within shouting distance of their software. This week, Google announced a step in the right direction-but not a huge step, nor one that will stop Google from continuing to collect immense amounts of personal data.
At issue is how online companies track internet users as they browse (浏览) from site to site online, typically through cookies (information that a website leaves in your computer so that the website will recognize you when you use it again). The most harmful version, “third-party” cookies, is the web alternative of a company posting security guards across the internet to monitor what you do, even when you’re on other companies’ sites.
Google declared in a blog post Wednesday that it would no longer use or support third-party cookies, nor would it create or use any other technology that tracks individual users across the web. Given that Google is a main supplier of online advertising technology, its change in approach will impact far and wide.
That’s welcome news, although with huge amounts of warning. As Lee Tien of the Electronic Frontier Foundation noted, third-party cookies were already on the retreat, with Apple and other makers of popular web browsers moving to block them. Meanwhile, Google, Facebook and other Big Tech companies continue to collect personal information in large quantities from people who use their sites and services through first-party cookies and similar techniques.
The concerns about personal data collection are the same whether it’s being collected through first-party or third-party techniques, said Michelle Richardson of the Center for Democracy and Technology. “Companies may use the information to discriminate among internet users, offering different goods, services and even prices to different users.”
Instead of helping advertisers track individuals, Google says, it is improving a technology that assigns users namelessly to large groups with common interests. That’s an improvement, even though it too may be at risk of abuse. But why do any form of tracking at all? Privacy advocates say pitches (兜售) can be targeted effectively by basing them on where the user is at the moment, not where he or she has browsed previously online.
Ultimately, lawmakers are going to have to lay down regulations giving people far more control over whether and how personal information is used online. Ideally the federal (联邦的) government will set a strong floor under online privacy protections, but until then it will be up to state lawmakers or voters to act, as this state has done with its groundbreaking online privacy laws. It’s good to see Google move the ball forward, but there’s much farther to go.
1. What does the underlined phrase “on the retreat” in Para 4 most probably mean?| A．Exposed. | B．Removed. | C．Emerging. | D．Fading. |
| A．is developing new technologies to stop data collection |
| B．refuses to work with companies tracking privacy |
| C．intends to abandon its advertising technologies |
| D．resolves to stop the use of third-party cookies |
| A．are still collecting personal information |
| B．are blocked by big companies like Apple |
| C．are mainly used by advertising companies |
| D．are less concerning than third-party cookies |
| A．It is less satisfactory than expected. |
| B．It needs to be more forceful to be effective. |
| C．It will accelerate the disappearance of cookies. |
| D．It has driven lawmakers to make new regulations. |
8 . Your best friend that follows you around when the sun comes out - your shadow - doesn’t serve an important function like your heart or brain, but what if you could use shadows to create electricity? When using solar panels (电池板) that are powered by light, shadows can be boring because it means electricity can’t be created. However, researchers from the National University of Singapore have engineered a way to create power from the shadows present everywhere.
A team of the university created a machine that can collect energy from shadows. It is created by placing a thin coating of gold onto silicon (硅). Like in a normal solar panel, when put in light, the silicon electrons (电子) become energized and the energized electrons then jump from the silicon to the gold. The voltage (电压) of the part of the machine that is placed in the light increases relative to the dark part and the electrons in the machine flow from high to low voltage. They are sent through an external circuit (外电路) creating a current that can be used to power another machine. The greater the contrast between light and dark, more energy is provided by the machine.
The team is working on improving the performance of the machine, borrowing approaches from solar panels to gather light. Increasing the amount of light the machines can receive allows them to better make use of shadows, as well as developing shadow energy collecting panels that can successfully gather from indoor lighting. The team is also researching the use of other materials other than gold to drop the price of the machine, meaning they would be more cost effective and easier to apply in society.
Shadows are present everywhere and perhaps one day in the future we will be able to collect energy from them by placing the shadow-effect energy machine around the world in places that have been considered unfit for solar panels to work, or indoors. “A lot of people think that shadows are useless,” Tan says, but “anything can be useful, even shadows.”
1. What is Paragraph 1 mainly about?| A．Your best friend always stays with you after the sunrise. |
| B．The shadow has the same function as the heart and brain. |
| C．Shadows can stop solar panels from creating electricity. |
| D．Researchers have found a way to create power from shadows. |
| A．The silicon produces electricity when it is in the light. |
| B．The gold produces power with the help of the silicon. |
| C．The energized electrons flow from high to low voltage. |
| D．An external circuit creates current using another machine. |
| A．Using solar panels in the machine. |
| B．Increasing the amount of light received. |
| C．Developing light energy collecting panels. |
| D．Bringing down the price of gold. |
| A．A gym. | B．A park. | C．A farm. | D．A playground. |
9 . In the magnificent range of mountains of northern California, 42 radio telescopes point towards the stars, scanning for signs of life. The Search for Extraterrestrial Intelligence （SETI） Institute has been listening for a signal here since it was founded in 1984. Jill Tarter, its co — founder, says the programmed aim is not just to communicate with remote civilisations. It is also to remind human beings of its own modest, fragile （脆弱的）place in the universe. Thus, for the first time, SETI is cocking its ear towards Earth to look for a signal that can be sent into space to represent the species.
Felipe Perez Santiago, a Mexican musician and composer, has an idea of what might work.Since songs, like the human voices, are common to all languages and nations, he and Ms. Tarter have designed the “Earthling Project”-a call to people everywhere to upload extracts （精华）of song that he plans to melt into a collective human chorus. An initial composition will be launched into space this summer, recorded on a virtually indestructible disk. Future plans and dreams include an eventual landing on Mars.
Human music has been sent to the heavens in 1977. Distant beings can in theory already enjoy Peruvian panpipes, a Navajo chant, Bach, Beethoven and more. But no previous offering, and perhaps no composition undertaken anywhere, has tried to encompass the entire diversity of human song.
Mr. Santiago says he is thrilled about bringing together contributors from around the globe. Unlike other recordings sent into space, says Mr. Santiago, “Everyone's invited. You don't have to be one of the main composers of our history like Beethoven, just someone singing in their shower.” Download the “Earthling Project" app, sing up to three songs of 30 seconds each, and your voice will be sent into the sky.
1. Why does SETI look for a signal to be sent into space?| A．To stand for species on the earth. |
| B．To scan for other liveable planets. |
| C．To respond to the call of the universe. |
| D．To stress the importance of the earth. |
| A．It is a world music organization. |
| B．It intends to create a human chorus. |
| C．It tries to develop a universal language. |
| D．It aims to search for signals from space. |
| A．Include. | B．Appreciate. |
| C．Work out. | D．Relate to. |
| A．To inspire people to become composers. |
| B．To call on people to protect our planet. |
| C．To encourage people to explore space. |
| D．To invite people to join a programme. |
10 . Just as a hungry brain craves (渴望) food, a lonely brain craves people. A new brain study demonstrates this. After being left alone, it shows people's brains would be activated at the sight of other people. The action was in the same brain region that speeds up when a hungry person sees food.
Livia Tomova, a neuroscientist, who studies how the brain produces mental activities, and her colleagues began this study. They recruited (招募) 40 people. On one day, the participants had to fast—not eat anything at all—for 10 hours. On another day, the same people were placed in a room for 10 hours. They couldn't see anyone. No friends, no family and no social media. They weren't even allowed to check their email. After both days, Tomova and her colleagues put the people in a MRI machine. It shows activity in the brain by tracking how much blood is flowing to each region.
At the end of each day, the participants showed high activity in a brain area called the midbrain. The scientists were interested in two, small areas within it. Both areas produce dopamine, a chemical that is important in craving and rewards. The two areas activated when hungry participants saw pictures of tasty pizza or juicy hamburgers. After the volunteers had been isolated, those brain areas became active when they saw social activities they missed. It might be playing sports or chatting with friends.
The midbrain plays an important part in people's motivation to seek food or friends. In fact, it responds to food and social signals even when people aren't hungry or lonely. But hunger and loneliness increased the reactions and made people's responses specific to the thing they were missing. And the more hunger or isolation the volunteers said they were experiencing, the stronger the activity in this part of the brain. Tomova and her colleagues published their results November 23 in Nature Neuroscience.
1. How does Tomova test out the result of the study?| A．By stimulating desire. | B．By controlling blood flow. |
| C．By monitoring brain activity. | D．By examining mental activities. |
| A．It consists of two areas. | B．It helps motivate desire for food. |
| C．It stops working when people are full. | D．It decreases responses to lost friends. |
| A．A midbrain area. | B．A social activity. | C．A volunteer. | D．A hamburger. |
| A．Dopamine—a Sure Sign of Age | B．Midbrain—a Nest for the Thoughts |
| C．Hunger Makes Mental Health Struggle | D．Loneliness Makes Our Brains Need People |
