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.

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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.

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.

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.

10 . What do you want to be when you grow up? My answer has always been a vet.

We didn’t have pets growing up because my mother was scared of animals. She passed on some of this fear to me. It’s not common you find someone who’s scared of animals but wants to be a vet. Still, I knew this is what I wanted.

Vet school was nothing like I had imagined. Within the first few weeks, any fears I had about being a vet vanished (消失). In the fourth year, we were introduced to surgery. I loved it. Stitching (缝) wounds was like a satisfying game of Tetris (俄罗斯方块), where all the pieces fit beautifully together to make something broken whole again. It solidified my belief that this was the right fit for me.

These were the most challenging and rewarding two years of my life, and before I knew it, they were over. I was officially a veterinary surgeon (兽医). Surprisingly, I felt empty after I finished. Why wasn’t I excited to move on? I had completely forgotten to think about what comes next. I panicked! I felt as if I had spent the last decade of my life writing exams and working crazy hours only to come out on the other side, completely clueless.

There were so many options to choose from. I could start a clinic, work at another practice or even pursue further studies. It was my father who suggested I travel to gain some perspective. I hesitantly decided to spend some time in New Zealand with my aunt who also happens to be a vet.

New Zealand was beautiful! I finally had a chance to think about what I wanted. One of the vets there allowed me to observe their practice. Working with vet nurses really stood out for me. We don’t have vet nurses in India! It is a blessing (幸事) to have such experienced and dedicated individuals as a part of your support system. After a whole year of what felt like aimless wandering (徘徊), this experience helped me decide I wanted to work overseas.

So, to all the other confused vets out there who haven’t figured things out: It’s completely okay to feel confused and lost! Most people feel the same way at some point in their careers. Don’t be afraid to try new things even if you feel difficult or impossible.