Most adults firmly believe that as kids reach their teens, they start to take crazy risks that get them in trouble. Do teenagers simply love taking all risks much more than adults? A recent study suggests otherwise.
Scientists designed a simple experiment involving 33 teenagers and three other age groups. In the experiment, the researchers tried to distinguish between two very different kinds of risk-taking. The first they called a willingness to take known risks (when the probability of winning is clear) and the second they called a willingness to take unknown risks (when the possibility of success is uncertain).
The study offered participants the opportunity to play two kinds of games. They had the chance to win money, with one game offering a known risk and the other offering an unknown risk. On each round of the game, each participant had to choose between taking a sure $5 and known or unknown risks of winning a lot more. If on one particular round they had picked the $5 for sure choice, then they got $ 5. But if on that round they had chosen to take a risk, the rules of the game will determine whether or not they had won. If they did win, they went home with between $8 and $125. And, of course, if they lost, they went home with nothing.
What the scientists found was really quite surprising. It turned out that the average teenager was very hesitant when risks were known¡ªmore careful than college students or parents-aged adults, and about as careful as grandparent-aged adults. This means that when the risks were known, teenagers were not risky in their behavior at all. Only when the risks were unclear did teenagers choose them more often than other groups. Under those kinds of conditions, they were much more willing to take a risk than any other group.
So, what does all of this mean? The research suggests that adults should probably focus more energy on trying to educate teenagers about risks than
limiting them. Teenagers who understand the risks associated with a decision are more likely to be careful in their behavior. 38. This experiment was carried out by A. dividing the teens into three groups B. comparing the reactions to different risks C. giving equal amount of awards to the participants D. observing the emotional changes of the teenager
39. When facing known risks, teenagers tended to be ________. A. ambits C. anxious
B. cautious D. curious
40. Which group in the study were more likely to take unknown risks? A. Teenagers.
C. Parent-aged adults.
B. College students. D. Grandparent-aged adults.
41. According to the study, parents should focus on ________. A. guaranteeing children to be careful B. setting age limits on dangerous activities C. respecting teens to make their own choices
D. guiding teens to learn more about the effect of risks ¡¾´ð°¸¡¿38. B 39. B 40. A 41. D ¡¾½âÎö¡¿
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Shark attacks not only disturb beach activities, but can affect associated tourist industries. Shark nets are a common solution to preventing shark attacks on beaches, but they cause dangers to sea ecosystems.
Seeking a cost-effective way to monitor beach safety over large areas, we have developed a system called Shark Spotter. It combines artificial intelligence (AI), computing power, and drone (ÎÞÈË»ú) technology to identify and warn lifesavers to sharks near swimmers. The project is a cooperation between the University of Technology Sydney and The Ripper Group, which is pioneering the use of drones¡ªcalled ¡°Westpac Little Ripper Lifesavers¡±¡ªin the search and rescue movement in Australia.
SharkSpotter can detect sharks and other potential threats using real-time aerial imagery. The system analyses video from a camera attached to a drone to monitor beaches for sharks, send warnings, and conduct rescues. Developed with techniques known as ¡°deep learning¡±, the Shark Spotter system receives imagery from the drone camera and attempts to identify all objects in the scene. Once certain objects are detected, they are put into one of 16 categories: shark, whale, dolphin, rays, different types of boats, surfers, and swimmers.
If a shark is detected, Shark Spotter provides both a visual sign on the computer screen and an audible warning to the operator. The operator confirms the warning and sends text messages from the Shark Spotter system to the Surf Life Savers for further action. In an emergency, the drone is equipped with
a lifesaving flotation pod (Ư¸¡²Ö) together with an electronic shark repellent (ÇýÖð×°ÖÃ) that can be dropped into the water in cases where swimmers are in severe trouble, trapped in a rip, or if there are sharks close by.
In January 2020, the Westpac Little Ripper Lifesavers was used to rescue two young swimmers caught in a rip at Lennox Head, NSW. The drone flew down the beach some 800 meters from the lifeguard station, and a lifesaving flotation pod was dropped from the drone. The complete rescue operation took 70 seconds.
We believe Shark Spotter is a win-win for both marine life and beachgoers. This unique technology combines dynamic video image processing AI and advanced drone technology to creatively deal with the global challenge of ensuring safe beaches, protecting environments, and promoting tourism. 42. A Shark Spotter is ________. A. a solution to monitor sharks B. an equipment to identify lifesavers C. a technology to prevent shark attacks D. a project to pioneer the use of drones
43. When a shark is spotted near a swimmer, the system will ________. A. take timely action
C. classify the identified objects
B. analyze the visual data D. turn on ¡°deep learning¡± mode
44. The example in the 5th paragraph shows us that the system is A. efficient in saving lives C. smart in driving sharks away area
45. What is the author¡¯s attitude towards the future of SharkSpotter? A. Doubtful.
B. Optimistic.
B. effective in detecting sharks D. practical over the whole sea