1 . Urban agriculture, the practice of farming within the restrictions of a city, is becoming increasingly popular and is viewed as a sustainable alternative to big industrial farms. By some estimates, between 20% and 30% of the global urban population engages in some form of urban agriculture. But until recently, its carbon footprint remains understudied.
Using data from 73 low-tech city farms, community gardens and personal plots of land, Newell and his team compared the average carbon emissions of food produced at low-tech urban agriculture sites to those of conventionally grown crops. The team found that because of urban gardens’ relatively low yields, along with the energy used in constructing the planting beds, big-city spuds (马铃薯) were significantly more carbon-intensive than commercially grown ones. This held true even when the researchers factored in emissions from transporting commercially grown produce to often distant grocery stores. That doesn’t mean that growing vegetables in big cities is totally bad, however. “Urban farming is great, ” if imperfect, says Carola Grebitus, a food choice expert. It can be a powerful tool for job creation and education, she says, and a good way to introduce fresh produce to urban “food deserts” where healthy fruits and vegetables are hard to come by. Community gardens can also provide a place to connect with nature, and the added green space can reduce the risks of heat and flooding.
Conscious of these benefits, Newell’s team highlighted several ways to make urban agriculture more sustainable. One option is to be selective about what crops are grown. For instance, tomatoes grown in the soil of open-air urban plots had a lower carbon intensity than tomatoes grown in conventional greenhouses. Another strategy is to rely on existing constructions. Include old structures into a new garden’s design instead of taking down old buildings. Finally, take the local climate, water quality and soil into account. Growing plants that are ill-suited to an area requires more water, energy and pesticides (杀虫剂), all of which affect the environment.
1. What can we know about urban agriculture from paragraph 1?| A．It is thoroughly researched. | B．It is welcomed by city people. |
| C．It is environmentally friendly. | D．It is limited to industrial farms. |
| A．By making a comparison. | B．By telling a story. |
| C．By giving a definition. | D．By using a quote. |
| A．It adds variety to urban people’s diet. | B．It provides recreational opportunities. |
| C．It strengthens the bonds of community. | D．It helps to contain drought and flooding. |
| A．Reconstructing gardens. | B．Developing greenhouse crops. |
| C．Selecting pesticide-free vegetables. | D．Growing plants suited to local conditions. |
2 . It wasn’t until after I graduated from college, and realized that there’s no such thing as all-encompassing (包罗万象) knowledge, that I was able to read for pleasure. A sense of curiosity directed me and I started to see dictionaries as field guides to the life of language. Looking up words felt less like a failing than an admission that there are lots of things I don’t know and an opportunity to discover just how many.
I prize my 1954 copy of Webster’s New International Dictionary, Second Edition. I often consult it, during evening games of Scrabble or midday magazine reading. When I come across unfamiliar words while reading novels, I look them up. When I start encountering these words elsewhere, the linguistic (语言的) universe seems to shrink to the size of a small town.
Dictionaries heighten my senses: They direct my attention into a conversation with language. They make me wonder what other things I’m blind to because I haven’t taught myself to notice them yet. Recently spotted examples include orrery, “a mechanical model, usually clockwork, devised to represent the motions of the moon and Earth (and sometimes also other planets) around the sun.” The Oxford English Dictionary (OED) also tells me that the word comes from the fourth Earl of Orrery, for whom a copy of the first machine was made, around 1700. Useful? Obviously not. Satisfying? Deeply.
Wikipedia and Google answer questions with more questions, opening up pages you never asked for. But a dictionary builds on common knowledge, using simple words to explain complex ones. Using one feels as if I’m prying open an oyster (蚝) rather than falling down a rabbit hole. Why leave solvable mysteries up to guesswork?
For me, dictionaries are a door into that kind of uncalculated knowledge-seeking. They remind me that following your curiosity instead of brushing it aside is one of the best ways I know to feel connected to more than what’s right in front of you.
1. What can we know about the author?| A．He merely read for fun before graduation. |
| B．He longed to learn about all knowledge. |
| C．He considered dictionaries chances of enrichment. |
| D．He admitted being a failure when learning languages. |
| A．To introduce a word. | B．To indicate a finding. |
| C．To clarify a concept. | D．To support a statement. |
| A．Encountering new problems. | B．Entering a different world. |
| C．Acquiring essential common sense. | D．Simplifying tough questions. |
| A．Jaw-dropping. | B．Eye-opening. | C．Mind-numbing. | D．Labour-saving. |
3 . Building artificial intelligences that sleep and dream can lead to more dependable models, according to researchers who aim to mimic (模仿) the behavior of the human brain.
Concetto Spampinato and his research members at the University of Catania, Italy, were looking for ways to avoid a phenomenon known as “disastrous forgetting”, where an AI model trained to do a new task loses the ability to carry out jobs it previously excelled at. For instance, a model trained to identify animals could learn to spot different fish species, but then might lose its ability to recognize birds. They developed a method of training AI called Wake-Sleep Consolidated Learning (WSCL), which mimics the way that our brains reorganize short-term memories of daily learning when we are asleep.
Besides the usual training for the “awake” phase, models using WSCL are programmed to have periods of “sleep”, where they analyze awake data from earlier lessons. This is similar to human spotting connections and patterns while sleeping.
WSCL also has a period of “dreaming”, which involves novel data made from combining previous concepts. This helps to integrate previous paths of digital “neurons (神经元)”, freeing up space for future concepts. It also prepares unused neurons with patterns that will help them pick up new lessons more easily.
The researchers tested three AI models using a traditional training method, followed by WSCL training. Then they compared performances for image identification. The sleep-trained models were 2 to 12 percent more likely to correctly identify the contents of an image. They also measured an increase in how much old knowledge a model uses to learn a new task.
Despite the results, Andrew Rogoyski at the University of Surrey, UK, says using the human brain as a blueprint isn’t necessarily the best way to boost AI performance. Instead, he suggests mimicking dolphins, which can “sleep” with one part of the brain while another part remains active. After all, an AI that requires hours of sleep isn’t ideal for commercial applications.
1. WSCL was developed to help improve AI’s ______.| A．reliability | B．creativity | C．security | D．popularity |
| A．Generate new data. | B．Process previous data. |
| C．Receive data for later analysis. | D．Save data for the “awake” phase. |
| A．The application of WSCL. | B．The benefits of AI research. |
| C．The findings of the research. | D．The underlying logic of WSCL. |
| A．Cautious. | B．Prejudiced. | C．Pessimistic. | D．Unconcerned. |
| A．A time conflict. | B．A troublesome accountant. | C．An undecided marketing plan. |
1. Why did the man stop watching the program last night?
| A．It was aired too late. | B．It lasted too long. | C．It was full of ads. |
| A．Issuing cash cards. | B．Buying products. | C．Running a series of ads. |
| A．Striking. | B．Disturbing. | C．Astonishing. |
1. How many parts does the speaker’s diving training consist of?
| A．Two. | B．Three. | C．Four. |
| A．Academic stuff. | B．Practical skills. | C．Classroom work. |
| A．She got her ears blocked up. |
| B．She enjoyed the freezing water. |
| C．She went under the water smoothly. |
| A．Proud. | B．Lucky. | C．Confident. |
1. What tour does the man decide to take today?
| A．A three-hour tour. | B．A half-day tour. | C．A one-day tour. |
| A．10:00 a. m. | B．10:30 a. m. | C．11:00 a. m. |
| A．Buckingham Palace. | B．Westminster Abbey. | C．Windsor Castle. |
| A．£15. | B．£ 90. | C．£105. |
8 . Kelli Boehle says her son Nik was an amazing and caring person. Nik was diagnosed(诊断) with cancer in 2008 when he was 17. He passed away in 2012. But Nik’s kindness and generosity have lived on long after his death.
After he was diagnosed and started treatment, Nik was granted (给予) a wish experience from the Make-A-Wish Foundation. “For just this period of time, we didn’t think about cancer, ”Kelli Boehle said. “All we thought about was enjoying our time together. ”
In 2009, Nik met another young man Nate, who was also going through cancer treatment. He’d been diagnosed a month after turning 18, and Nik learned he was too old to qualify for a wish. The night before Nik passed away, he asked his mother to help ensure that young adults fighting cancer could have their wishes come true too.
“It was like a seed he planted that just wouldn’t stop coming into my mind, ” she said. In 2012, Kelli Boehle started Nik’s Wish. The nonprofit grants wishes to young adults between the ages of 18 and 24 who are battling cancer. Nate was the organization’s first wish recipient. “It’s meant to bring them joy and know that they’re loved and that we’re fighting for them, too, ”Kelli Boehle said.
Recently, 19-year-old Jordan Morrow received her wish to attend a Taylor Swift concert as part of a trip to Los Angeles. For Morrow, who has spent the last year battling brain cancer, going to the concert has done more than lift her spirits. “I think it’s something to get me through whatever comes my way, ”she said. “And I’m thankful for Nik’s Wish for that. ”
In the 11 years since Nik passed away, the organization has granted more than 300 wishes across more than 30 states. In the beginning, Kelli Boehle says she wasn’t sure she could be a wish maker and work closely with the young adults. But now, it’s her favorite thing to do.
1. What is the goal of Nik’s Wish?| A．To make commercial profits. | B．To cure the youth of their cancer. |
| C．To ease young patients of pains. | D．To support young adults fighting cancer. |
| A．Intelligent. | B．Selfless. | C．Straightforward. | D．Ambitious. |
| A．She survived the deadly disease. | B．She was granted more than one wish. |
| C．She was motivated by the organization. | D．She lifted people’s spirits by performing. |
| A．Pay-It-Forward: A Mother’s Last Wish |
| B．Cancer Battles: Stories of Hope and Perseverance |
| C．Nik’s Wish: Fulfilling Wishes for Young Cancer Fighters |
| D．Make-A-Wish Foundation: Granting Dreams to Young Adults |
9 . Our species’ incredible capacity to quickly acquire words from 300 by age 2 to over 1, 000 by age 4 isn’t fully understood. Some cognitive scientists and linguists have theorized that people are born with built-in expectations and logical constraints (约束) that make this possible. Now, however, machine-learning research is showing that preprogrammed assumptions aren’t necessary to swiftly pick up word meanings from minimal data.
A team of scientists has successfully trained a basic artificial intelligence model to match images to words using just 61 hours of naturalistic footage (镜头) and sound-previously collected from a child named Sam in 2013 and 2014. Although it’s a small slice of a child’s life, it was apparently enough to prompt the AI to figure out what certain words mean.
The findings suggest that language acquisition could be simpler than previously thought. Maybe children “don’t need a custom-built, high-class language-specific mechanism” to efficiently grasp word meanings, says Jessica Sullivan, an associate professor of psychology at Skidmore College. “This is a really beautiful study, ” she says, because it offers evidence that simple information from a child’s worldview is rich enough to kick-start pattern recognition and word comprehension.
The new study also demonstrates that it’s possible for machines to learn similarly to the way that humans do. Large language models are trained on enormous amounts of data that can include billions and sometimes trillions of word combinations. Humans get by on orders of magnitude less information, says the paper’s lead author Wai Keen Vong. With the right type of data, that gap between machine and human learning could narrow dramatically.
Yet additional study is necessary in certain aspects of the new research. For one, the scientists acknowledge that their findings don’t prove how children acquire words. Moreover, the study only focused on recognizing the words for physical objects.
Still, it’s a step toward a deeper understanding of our own mind, which can ultimately help us improve human education, says Eva Portelance, a computational linguistics researcher. She notes that AI research can also bring clarity to long-unanswered questions about ourselves. “We can use these models in a good way, to benefit science and society, ” Portelance adds.
1. What is a significant finding of machine-learning research?| A．Vocabulary increases gradually with age. |
| B．Vocabulary can be acquired from minimal data. |
| C．Language acquisition is tied to built-in expectations. |
| D．Language acquisition is as complex as formerly assumed. |
| A．Facilitate. | B．Persuade. | C．Advise. | D．Expect. |
| A．Its limitations. | B．Its strengths. | C．Its uniqueness. | D．Its process. |
| A．Doubtful. | B．Cautious. | C．Dismissive. | D．Positive. |
10 . Los Angeles is home to a popular cycling culture. The following bike shops will help you see the city in a whole new light.
Los Angeles Bike Academy
Los Angeles Bike Academy is a bike shop with a critical mission: Provide resources and community for local underserved youth. Its initiative is its Earn-a-Bike program, where students spend time in the shop learning the basics of bike maintenance and running a store, and they graduate with their own bike. LABA also forms competitive cycling teams that race all around the country.
The Cub House
It’s a bike shop, a plant store and a nice place to wander through. It has something for everyone. Here you can play a game of ping-pong on the outdoor table, head into the mini greenhouse for a delicate plant, or just admire the vintage (老式的) cycling clothes hung on the walls. Finally, make sure to swing by the Cub House for the L. A. Invitational, a weekend party featuring multiple bike rides and a vintage car and bike show outside the store.
Frank’s
Some of the wildest bikes in L. A. are rolling out of Frank’s. The house specialty here is BMX, specifically luxury models with large 29-inch wheels. These bikes are as much fun to look at as they are to ride. Since 1992, Frank’s has found a business opportunity for itself as a destination for BMX builds and hard-to-find parts. The display counter has enough attractions to match a jewelry store.
The Bicycle Stand
This spacious store features classic vintage bikes. It’s worth making a trip to this store just to see their amazing collection. The store also specializes in vintage bike repainting and restorations. Besides, the Bicycle Stand team works on all kinds of rides, and the shop has a variety of refurbished (翻新的), ready-to-ride bikes for sale.
1. What is special about Los Angeles Bike Academy?| A．It aims at repairing local bikes. |
| B．It holds national cycling competitions. |
| C．It serves as a community for disabled youth. |
| D．It offers a program for students to earn a bike. |
| A．Los Angeles Bike Academy. | B．The Cub House. |
| C．Frank’s. | D．The Bicycle Stand. |
| A．To discuss benefits of riding. | B．To explain how bike shops work. |
| C．To promote bike shops in L. A. | D．To introduce a riding organization. |
