When I was in my third year at university, my roommates were American footballers, so I decided to join them. I remember seeing them in front of me wearing pads (防护垫), and thinking they were going to kill me. I got tackled (阻截) so hard that I was frightened. But then I realized it was just physical contact. I've been addicted since.

The fundamental aim of the game is to score by running with the ball into, or receiving the ball inside the opposition's end zone. Every player on the field has a set responsibility. I'm a running back. My job is using my speed, strength and skill to carry the ball and keep running until either I score or I get put down. And it does hurt.

I've broken two fingers and hurt my shoulder, but the worst was when I trapped the ligaments (韧带) in the back of my leg. I had to take a year out. But none of that put me off- all I could think was how I was going to come back stronger. Besides training with the team, I now have my gym routine to get fitter, faster and stronger.

Although people think American football is aggressive, there's much more to it. Every team has its own playbook, outlining everyone's role in different scenes. My playbook was 73 pages long. Words can't describe how it feels when it all comes together on the field.

American football has changed my life for the better. I've learned time management, how to take responsibility for my action, and how much I treasure being part of a team. Within the four lines of the field, it is physical. Emotions run high. If you're on the opposing team, you are my enemy. But once the game is done, we're like a big family.

    James Gross, a psychology professor at Stanford University, has a 13-year-old daughter who loves math and science. “It hasn't occurred to her yet that's unusual,” he says. “But I know in the next couple of years, it will.”

    She's already being pulled out of class to do advanced things with a couple of other kids, who are guys. And as someone who studies human emotion for a procession, Gross says, “I know as time goes on, she will feel increasingly lonely as a girl who's interested in math and science, and be at risk of narrowing her choices in life before finding out how far she could have gone.''

    Gross' concern clearly shows what has been a touchy subject in the world of science for a long time: Why are there still so few women in science, and how might that affect what we learn from research?

    Women now make up half the national workforce, earn more college and graduate degrees than men, and by some estimates represent the largest single economic force in the world. Yet the gender gap in science persists, to a greater degree than in other professions, particularly in high-end, math-intensive fields such as computer science and engineering.

    According to US Census Bureau statistics, women in fields commonly referred to as STEM (science, technology, engineering, mathematics) made up 7 percent of that workforce in 1970, a figure that had jumped to 23 percent by 1990. But the rise essentially stopped there. Two decades later, in 2011, women made up 26 percent of the science workforce.

    Exactly five years ago, on New Year's Eve, I was invited to a children's ball by a man high up in the business world, who had his connections, his circle of acquaintances, and his close friends. So it seemed as though the children's ball was merely an excuse for the parents to come together and discuss matters of interest to themselves, quite innocently and casually.

    I was an outsider, and, as I had no special matters to air, I was able to spend the evening independently of the others. There was another gentleman present who like me had just stumbled upon (偶然发现) this affair of domestic happiness. He was the first to attract my attention. His appearance was not that of a man of noble birth. He was tall, rather thin, very serious, and well dressed. Obviously he had no heart for the family celebration. The instant he went off into a corner by himself the smile disappeared from his face, and his thick dark brows knitted into a frown(皱眉). He knew no one except the host and showed every sign of being bored to death, though bravely keeping the role of thorough enjoyment to the end. Later I learned that he was a provincial, had come to the capital on some important business, had brought a letter of recommendation to our host, and our host had taken him under his protection, not at all with love. It was merely out of politeness that he had invited him to the children's ball.

    They did not play cards with him. They did not offer him cigars. No one entered into conversation with him. Possibly they recognized the bird by its feathers from a distance. Thus, my gentleman, not knowing what to do with his hands, was compelled(迫使) to spend the evening stroking (抚摸) his whiskers(胡须). His whiskers were really fine, but he stroked them so eagerly that one got the feeling that the whiskers had come into the world first and afterwards the man in order to stroke them.

A Chinese legend—A pretty maiden is trapped by a dragon. A prince must slay（杀死）the dragon to save her. Then, magically, they fall in love and live happily ever after. Traditional stories tend to emphasize the fantastic, magical side of love. Fate plays matchmaker. Strangers see each other from across a room and instantly know that they are destined to be together.

    It isn't difficult to imagine two strangers coming together and falling in love despite their differences. It suggests that love is challenging, uncertain, and incomprehensible.

    But with more people using online dating services, a very different kind of love has emerged: one that is scientific, convenient, and self-directed. It minimizes risk and provides a choice, like on a menu. There is anonymity（匿名）and the avoidance of immediate rejection. Meeting terms are negotiated online.

    Online dating also allows the setting of preconditions. Computer algorithms（推算） exclude undesirable traits such as the wrong hair color, race, or age. But they also exclude randomness. They reduce the chances of meeting someone different, or someone who could challenge one's romantic ideals. Instead, they find the partner we think we want and exclude everyone else. As a result, we could be missing the opportunity of a lifetime, to meet someone we would never have expected to fall in love with.

    Perhaps this new way represents a more efficient form of romance. Traditional ideas of love may be enchanting - but are they useful? Loneliness and boredom are less exciting than chance encounters, but they represent the more realistic side of love. All too often people have suffered through bad dates and humiliations. If they could just choose what they wanted, wouldn't it save time and reduce suffering? However, by choosing partners based on our preconceived ideas, we may be indulging in our illusions. Instead of letting ourselves grow with someone, love becomes more about looking for ourselves in the other. What if we don't know ourselves as well as we think? Perhaps love isn't about knowing what we want. Perhaps it's about being open to unimagined possibilities.

    One day when I was 12, my mother gave me an order: I was to walk to the public library, and borrow at least one book for the summer. This was one more weapon for her to defeat my strange problem—inability to read.

    In the library, I found my way into the "Children's Room." I sat down on the floor and pulled a few books off the shelf at random. The cover of a book caught my eye. It presented a picture of a beagle. I had recently had a beagle, the first and only animal companion I ever had as a child. He was my secret sharer, but one morning, he was gone, given away to someone who had the space and the money to care for him. I never forgot my beagle.

    There on the book's cover was a beagle which looked identical (相同的)to my dog. Iran my fingers over the picture of the dog on the cover. My eyes ran across the title, Amos, the Beagle with a Plan. Unknowingly, I had read the title. Without opening the book, I borrowed it from the library for the summer.

    Under the shade of a bush, I started to read about Amos. I read very, very slowly with difficulty. Though pages were turned slowly, I got the main idea of the story about a dog who, like mine, had been separated from his family and who finally found his way back home. That dog was my dog, and I was the little boy in the book. At the end of the story, my mind continued the final scene of reunion, on and on, until my own lost dog and I were, in my mind, running together.

    My mother's call returned me to the real world. I suddenly realized something: I had read a book, and I had loved reading that book. Everyone knew I could not read. But I had read it. Books could be incredibly wonderful and I was going to read them.

    I never told my mother about my "miraculous" (奇迹般的) experience that summer, but she saw a slow but remarkable improvement in my classroom performance during the next year. And years later, she was proud that her son had read thousands of books, was awarded a PhD in literature, and authored his own books, articles, poetry and fiction. The power of the words has held.

Tests have shown robots can diagnose heart problems in as little as four seconds, as a review of artificial intelligence (AI) finds machines are now as good at spotting illness as doctors.

Analyzing a patient's heart function on a cardiac MRI (心脏磁共振成像) scan currently takes doctors around 13 minutes. But a new trial by University College London (UCL) showed an AI program could read the scans in less time with equal accuracy. There are approximately 150,000 such scans performed in the UK each year, and researchers estimate that fully using AI to read them could save 54 clinician-days (临床天数) at each cardiac centre per year. So it can make up for the shortage of doctors.

It is hoped that AI where computer systems are able to learn from data to identify new patterns with minimal human intervention will transform medicine by helping doctors spot diseases such as heart disease and cancer faster and earlier. However, most scans are still read by specially trained doctors.

Dr Charlotte Manisty, who led the UCL research, said, "Cardiovascular MRI offers in- comparable image quality for assessing heart structure and function. However, current manual analysis remains basic and outdated. Automated machine techniques offer the potential to change this and completely improve efficiency and accuracy, and we look forward to further research that could confirm the superiority to human analysis."

She added, "Our dataset of patients with a range of heart disease who received scans enabled us to demonstrate that the greatest sources of measurement errors arise from human factors. This indicates that automated techniques are at least as good as humans, with the potential soon to be 'super-human'—transforming clinical and research measurement precision."

Professor Alastair Denniston said, "Within those handful of high-quality studies, we found that by deep learning AI could indeed detect disease ranging from cancer to eye disease as accurately as health professionals. But it's important to note that it did not absolutely exceed human professional diagnosis. "