Jeanne Calment, a French woman, became a record breaker on 17 October of 1995, when at the age of 120 years and 238 days, she became the longest-lived human being on record. A Japanese man died in 1986 at the age of 120 years and 237 days.

    Jeanne Calment lives in a small old people's home in the south of France; her husband, her only child and her grandson have all died. She is nearly blind and deaf and is always in a wheelchair, but her doctor describes her as being more like a 90-year-old in good health than someone of 120. She still has a lively sense of humor. When asked on her 120th birthday what she expected of the future, she replied: A very short one. She also remarked that she thought the good Lord had forgotten all about her.

    So what is the key to a long life? According to some doctors, diet, exercise and no smoking are the three important factors. Jeanne Calment has followed two of the tips. She has always eaten a healthy diet, and she used to do exercise every day until she broke her leg at the age of 115. However, until recently she drank two glasses of strong red wine a day, and she does smoke (now only a little). Besides, Jeanne Calment might have got very good genes from her parents. Her father lived to the age of 94 and her mother to 86.

    A local lawyer bought her house when she was 80 under an agreement that he would pay her some money every year until her death. It must have seemed a good move at the time, but so far the lawyer has paid her at least three times the value of the house. Every year on her birthday Jeanne Calment sends him a card saying: Sorry, I'm still alive!

    After a year of examining many studies concerning whether homework is effective, NYC P. S. Elementary School decided that math worksheets and essay assignments were actually a waste of time. In February, Principal Jane Hsu sent a letter to parents stating that the Pre-K(学前班) through fifth grade students wouldn't be given any traditional homework to encourage kids to free time for reading, playing outside, or doing activities they enjoy.

    “The negative effects of homework have been well established.” Hsu wrote in a note to parents. “They include, children's frustration and exhaustion, lack of time for other activities and family time and, sadly for many, loss of interest in learning.”

    Some parents, however, disagree with the policy change, believing that a lack of focus will cause children to fall behind. Homework has been part of education from the beginning, and has increased in amount in recent years.

    Hsu's advice that children should read and spend time with their families has upset some parents to the point of considering pulling their children out of the school. This group feels that homework gives children a goal to work toward. Others feel so strongly about the importance of homework that they have begun giving their own homework to their children.

    An Australian Childhood Foundation survey finds that 71% of Australian parents feel they don't spend enough quality time with their children mainly because of the time spent running the household or the time spent helping with homework. Education experts in Australia are saying that parents should stop helping. Doing so will give kids more independence, give parents more free time, and help reduce the number of arguments caused by homework in the family.

    While some research suggests that homework has little academic benefit for elementary students, other researches show homework can help kids develop independence, and confidence. It can also contribute to a sense of belonging or control over their lives. When parents try to help their children with homework, the assistance can take away that feeling and can also make working parents more tired.

    Several times my daughter had telephoned to say, "Mum, you must come and see the daffodils (水仙花) before they are over."

    I wanted to go, but it was a two-hour drive from Lake Arrowhead. "I will go next Tuesday," I promised, a little unwillingly, on her third call.

    The next Tuesday dawned cold and rainy. Still, I had promised, and so I drove there. When I finally walked into Carolyn's house and hugged and greeted my grandchildren, I said, "Forget the daffodils, Carolyn! The road is invisible (看不见的) in the cloud and fog, and there is nothing in the world except you and these children that I want to see!"

    My daughter smiled calmly and said, "We drive in such weather all the time, Mum. You will never forgive yourself if you miss this experience."

    After about twenty minutes, we turned onto a small road and on the far side of a small church, I saw a hand-lettered sign that read "Daffodil Garden". We got out of the car and each took a child's hand, and I followed Carolyn down the path. Then, we turned a corner of the path, and I looked up amazed. Before me lay the most beautiful sight. Flows of flowers of different colors seemed poured down the peak and slopes. There were five acres of flowers! A sea of daffodil! It was like a fairyland all beyond description.

    "But who has done this?" I asked Carolyn. "It's just one woman," Carolyn answered. That's her home. "Carolyn pointed to a well-kept A-frame house that looked small and modest in the midst of all that glory. We walked up to the house. On the patio (露台), we saw a poster. “Answers to the Questions I Know You Are Asking" was the headline. The first answer was a simple one. "50,000 bulbs (鳞茎)" it read. The second answer was, "One at a time, by one woman." The third answer was, "Began in 1958."

    I thought of this woman whom I had never met, who, more than fifty years before, had begun--one bulb at a time--to bring beauty and joy to this remote mountain top. Just planting one bulb at a time, year after year, had changed the world where she lived and created something of magnificence, beauty, and inspiration.

    When we multiply tiny pieces of time with small amounts of daily effort, we too can accomplish great things. Everyone can do something to change the world.

    Selena Gomez and I are scheduled to meet at a low-key coffee shop in Encino. Not wanting to keep the superstar waiting，I arrived at nine,20 minutes early. As I was catching up on e-mails，Selena quietly scooted into the seat next to me. No bodyguard. Not even a drop of make-up. She was ten minutes early and so inconspicuous that no one else in the restaurant looked up so much. Elena was wearing Bebe shorts. She had a baby face and ordered a hot chocolate.

    After making a small talk about what she wore for the shoot，she dived into the subject of her career. Elena declared 2012 the year of movies. She filmed three：SpringBreakers ， a drama；The  Getaway ， an action flick；and HotelTransylvania ， a comedy. Each is a marked move away from the teen style that made her a household name.

    Now that her Disney days are behind her，Selena is at that unstable point in a child star's career where she is trying to grow up—both as a person(she turned 20 in July) and as an artist. "Being part of the Disney Channel was such a blessing，and I'm super happy with what my show accomplished，but acting is something I would like to take on more seriously." She continued，"I don't necessarily feel accomplished. I want to create a whole different persona when it comes to acting."

    Selena has been working full-time since she was seven years old and scored a role on Barney & Friends. In 2007 when she was offered the lead in WizardsofWaverlyPlace ， Selena，her mother，and her stepfather uprooted from Grand Prairie，Texas，to L．A.，where they are settling now.

        Let us all raise a glass to AlphaGo and the advance of artificial intelligence. AlphaGo, DeepMind's Go-playing AI, just defeated the best Go-playing human, Lee Sedol. But as we drink to its success. We should also begin trying to understand what it means for the future.

    The number of possible moves in a game of Go is so huge that in order to win against a player like Lee. AlphaGo was designed to adopt a human—like style of gameplay by using a relatively recent development--deep learning. Deep learning uses large data sets, “machine learning” algorithms （计算程序） and deep neural networks to teach the AI how to perform a particular set of tasks. Rather than programming complex Go rules and strategies into AlphaGo, DeepMind designers taught AlphaGo to play the game by feeding it data based on typical Go moves. Then, AlphaGo played against itself, tirelessly learning from its own mistakes and improving its gameplay over time. The results speak for themselves.

    Deep learning represents a shift in the relationship humans have with their technological creations. It results in AI that displays surprising and unpredictable behaviour. Commenting after his first loss, Lee described being shocked by an unconventional move he claimed no human would ever have made. Demis Hassabis. one of DeepMind's founders, echoed this comment：“We're very pleased that AlphaGo played some quite surprising and beautiful moves.”

    Unpredictability and surprises are—or can be—a good thing. They can indicate that a system is working well, perhaps better than the humans that came before it. Such is the case with AlphaGo. However, unpredictability also indicates a loss of human control. That Hassabis is surprised at his creation's behaviour suggests a lack of control in the design. And though some loss of control might be fine in the context of a game such as Go, it raises urgent questions elsewhere.

    How much and what kind of control should we give up to AI machines? How should we design appropriate human control into AI that requires us to give up some of that very control? Is there some AI that we should just not develop if it means any loss of human control? How much of a say should corporations, governments, experts or citizens have in these matters? These important questions, and many others like them, have emerged in response, but remain unanswered. They require human, not human - like, solutions.

    So as we drink to the milestone in AI, let's also drink to the understanding that the time to answer deeply human questions about deep learning and AI is now.

    A study found wireless signals are able to pass through bags and suitcases to judge the sizes of dangerous metal objects and identify them." These items could include weapons, chemicals, laptops and batteries for bombs, "the research team said on Tuesday.

    Research suggested that Wi-Fi can now be used to estimate the volume of liquids such as water, acid, alcohol and other chemicals for explosive material. The study led by researchers at the Wireless Information Network Laboratory (WINLAB) in the School. of Engineering showed a wireless device with two to three antennas(天线)that could be fitted in existing Wi-Fi networks.

    The detection system analyzes what happens when wireless signals go through and bounce off objects or materials. The approach, which the paper states, works by separating the wireless interference(干扰)caused by two factors of objects-the material and shape." Most dangerous objects such as weapons are usually metal or liquid, which have significant interference," researchers said.

    When it was tested on a backpack, the accuracy rate topped 95 percent. "But the accuracy dropped to about 90 percent when objects inside bags are wrapped. And the tech could save lives if used in museums, stadiums, theme parks or schools," the team said, noting its design can inspect bags or luggage without being an exposure to privacy.

    It uses channel state information (CSI) that is readily available in low-cost Wi-Fi devices." This could have a great impact on protecting the public from dangerous objects," said Yingying Chen, a co-author of the study," There's a growing need for that now. In large public areas, it's hard to set up expensive screening equipment like what's in airports. Manpower is always needed to check bags and we want to develop a method to try to reduce manpower.”

    The peer-reviewed study, which recently won a best paper award at the 2018 IEEE Conference on Communications and Network Security, is now published online." Future work will continue to focus on ameliorating the accuracy of identifying objects and imaging shapes and volumes," researchers said.