【推荐1】If you haven’t heard or seen anything about Road Rage in the last few months, you’ve probably been avoiding the media. There have been countless stories about this new and scary phenomenon, considered a type of aggressive driving. You have most likely encountered aggressive driving or Road Rage recently if you drive at all.

While drunk driving remains a critical problem, the facts about aggressive driving are surely as disturbing. For instance, according to the National Highway Transportation Safety Association, 41,907 people died on the highway last year. Of those deaths, the agency estimates that about two-thirds were caused at least in part by aggressive driving behavior.

Why is this phenomenon occurring more than ever now, and why is it something that seemed almost nonexistent a few short years ago? Experts have several theories, and all are probably partially correct. One suggestion is extreme overcrowding. In the last decade, the number of cars on the roads has increased by more than 11 percent, and the number of miles driven has increased by 35 percent. However, the number of new road miles has only increased by 1 percent. That means more cars in the same amount of space; and the problem is severe in urban areas. Also, people have less time and more things to do. With people working and trying to fit extra chores and activities into the day, stress levels have never been higher. Stress creates anxiety, which leads to short tempers. These factors, when combined in certain situations, can spell Road Rage.

You may think you are the last person who would drive aggressively, but you might be surprised. For instance, have you ever yelled out loud at a slower driver, sounded the horn long and hard an another car, or sped up to keep another driver from passing? If you recognize yourself in any of these situations, watch out!

Whether you are getting angry at other drivers, or another driver is visibly upset with you, there are things you can do to avoid any major conflict. If you are easily influenced by Road Rage, the key is to release your emotion in a healthy way. If you are the target of another driver’s rage, do everything possible to get away from the other driver safely, including avoiding eye contact and getting out of their way.

【推荐2】Traffic Regulation and Accident Prevention

We live in a remarkable time, and many of the once fatal diseases can now be cured with modern medicine and surgery. It is almost certain that one day a cure will be found for the rest of the diseases. Expectations of life have greatly increased. But though the possibility of living a long and happy life is greater than ever before, every day we witness the incredible killing of men, women and children on the roads. Man fights against the motor-car. It is a never-ending battle which man is losing.     1    

Nothing can seriously increase your risk of potentially fatal car accidents other than speeding and failing to pay due attention to weather conditions.     2     There is no doubt that the motor-car often brings out a man’s very worst qualities. Usually quiet and pleasant people, when they are behind the steering wheel, will become unrecognizable. They are impolite, aggressive, self-willed like two-year-old, completely selfish. All their hidden frustrations, disappointments, and jealousy seem to be caused by driving.

    3     It’s all for his own convenience. Due to a serious tragedy, the city is almost uninhabitable and the huge parking lot makes the town ugly. The destruction of rural areas and the annual mass killings are just a statistic, easily forgotten. With regard to driving, the laws of some countries are not strict and even the strictest are not strict enough.

Traffic rules are for everyone to follow under any circumstances, and no one can make an exception unless you make a joke of your own life. Universally accepted standards can only have a significant beneficial on the incidence of accidents. Governments should develop safety codes for manufacturers.     4     These measures may sound cruel. However, if these measures result in a reduction in the loss of life every year, they should certainly not be considered serious. After all, the world belongs to humans, not cars.

【推荐3】This month, Germany’s transport minister, Alexander Dobrindt, proposed the first set of rules for autonomous vehicles (自主驾驶车辆). They would define the driver’s role in such cars and govern how such cars perform in crashes where lives might be lost.

The proposal attempts to deal with what some call the “death valley” of autonomous vehicles: the grey area between semi-autonomous and fully driverless cars that could delay the driverless future.

Dobrindt wants three things: that a car always chooses property (财产) damage over personal injury; that it never distinguishes between humans based on age or race; and that if a human removes his or her hands from the driving wheel — to check email, say — the car’s maker is responsible if there is a crash.

“The change to the road traffic law will permit fully automatic driving,” says Dobrindt. It will put fully driverless cars on an equal legal footing to human drivers, he says.

Who is responsible for the operation of such vehicles is not clear among car makers, consumers and lawyers. “The liability(法律责任) issue is the biggest one of them all,” says Natasha Merat at the University of Leeds, UK.

An assumption behind UK insurance for driverless cars, introduces earlier this year, insists that a human “ be watchful and monitoring the road” at every moment.

But that is not what many people have in mind when thinking of driverless cars. “When you say ‘driverless cars’, people expect driverless cars.”Merat says. “You know — no driver.”

Because of the confusion, Merat thinks some car makers will wait until vehicles can be fully automated without operation.

Driverless cars may end up being a form of public transport rather than vehicles you own, says Ryan Calo at Stanford University, California. That is happening in the UK and Singapore, where government-provided driverless vehicles are being launched.

That would go down poorly in the US, however. “The idea that the government would take over driverless cars and treat them as a public good would get absolutely nowhere here,” says Calo.

【推荐3】By analyzing the movement of the smile across a person’s face, the software developed by researchers at the University of Bradford can determine whether or not the expression is true. The most significant movements detected by the software were around the eyes, supporting popular theories that a true smile is one that can be seen in a person’s eyes.

“A smile is perhaps the most common of facial expressions and is a powerful way of signaling positive emotions (情绪)” says Hassan Ugail, Professor of Visual Computing at the University of Bradford, who led the research. “Techniques for analyzing human facial expressions have advanced a lot in recent years but distinguishing between true and false smiles remains a challenge because humans are not good at picking up the relevant messages.”

The software works by first mapping a person's face from within a video recording, and identifying the mouth, cheeks and eyes of the subject. It then measures how they move through the progress of the smile and calculates the differences in movement between the video pieces showing true and false smiles. They found significant differences in the way the subjects' mouths and cheeks moved when comparing the true and the false expressions. The movements around the subjects’ eyes, however, showed the most striking difference, with true smiles producing at least 10 percent more movement in these muscles (肌肉).

“We use two main sets of muscles when we smile — the zygomaticus major, which is responsible for the movements upwards of the mouth and the orbicularis oculi which causes movements around our eyes,” explains Professor Ugail. In false smiles it is often only the mouth muscles that move but, as humans we often don’t spot the lack of movement around the eyes.

He adds, “An objective way of analyzing whether or not a smile is true could help us develop improved interactions (互动) between computers and humans. It could also be important to scientists aiming to gain more understanding into human behavior and emotion.”

【推荐1】Many early approaches to language technology—and particularly translation—got stuck in a conceptual dead end: the rules-based approach. In translation, this meant trying to write rules to analyze the text of a sentence in the language of origin, breaking it down into a sort of abstract “interlanguage” and rebuilding it according to the rules of the target language. These approaches showed early promise. But language is full of ambiguities (歧义) and exceptions, so such systems were hugely complicated and easily broke down when tested on sentences beyond the simple set they had been designed for.

Nearly all language technologies began to get a lot better with the application of statistical methods, often called a “brute force” approach. This relies on software scanning vast amounts of data, looking for patterns and learning from precedent. For example, in parsing language (breaking it down into its grammatical components), the software learns from large bodies of text that have already been parsed by humans. It uses what it has learned to make its best guess about a previously unseen text. In machine translation, the software scans millions of words already translated by humans, again looking for patterns. In speech recognition, the software learns from a body of recordings and the transcriptions made by humans.

Thanks to the growing power of processors, falling prices for data storage and, most crucially, the explosion in available data, this approach eventually bore fruit. Mathematical techniques that had been known for decades came into their own, and big companies with access to enormous amounts of data were ready to benefit.

The final advance, which began only about five years ago, came with the arrival of deep learning through digital neural networks (DNNs). These are often claimed to have qualities similar to those of the human brain: “neurons” are connected in software, and connections can become stronger or weaker in the process of learning. But Nils Lenke, head of research for a language technology company, explains matter-of-factly that “DNNs are just another kind of mathematical model,” the basis of which had been well understood for decades. What changed was the hardware being used.

Almost by chance, DNN researchers discovered that the graphical processing units (GPUs) used to produce graphics in applications like video games were also brilliant at handling neural networks. The technique has already produced big leaps in quality for all kinds of deep learning, including decoding handwriting, recognizing faces and classifying images. Now they are helping to improve all manner of language technologies, often bringing enhancements of up to 30%. That has shifted language technology from usable at a pinch to really rather good. But so far no one has quite worked out what will move it on from merely good to reliably great.

【推荐2】Used electronics are piing up fast: they are filling up landfills with dangerous pieces of waste. Some e-waste is relatively large, such as air conditioners; other e-waste is more unnoticed, such as smart labels that contain disposable batteries and other equipment.

“It’s these small batteries that are big problems,” says University of California, Irvine, public health scientist Dele Ogunseitan, who is a green technology researcher and adviser for major tech companies and was not involved in developing the battery. “Nobody really pays attention to where they end up.” Researchers at the Cellulose & Wood Materials Laboratory at the Swiss Federal Laboratories for Materials Science and Technology are working to address this problem. Their new paper describes a water-activated paper battery developed from environmentally friendly materials that could eventually present a sustainable alternative to the more harmful batteries common in low-power devices.

The paper battery has the same key components as standard batteries but packages them differently. Like a typical chemical battery, it has a positively charged side and a negatively charged side. A traditional battery’s components are covered in plastic and metal; in the new battery, however, the positively and negatively charged sides are inks printed onto the front and back of a piece of paper. That paper is filled with salt, which dissolves (溶解) when the paper becomes wet. When the paper is dry, the battery is shelf-stable. Once the paper is wet, the battery starts working within 20 seconds. The new battery’s operating performance declines as the paper dries. When the scientists rewet the paper during testing, the battery regained function and lasted an hour before beginning to dry out again.

That future may not be so far off. It is hard to predict a time line for manufacturing such items at scale, but the head of the study says he is in contact with potential industry partners and believes these batteries could make their way into products within the next two to five years.

【推荐3】A secretive facial recognition program “could announce the end of public anonymity (匿名),” said Kashmir Hill in The New York Times. While police departments have used facial recognition tools for years, they’ve been limited to searching government-provided images, for example driver’s license photos. Now an app called Clearview AI can remove images of faces “from across the internet”—including social media sites like Facebook and Twitter, employment sites, even Venmo—gathering a database of more than 3 billion photos. “Until now, technology that readily identifies everyone based on his or her face has been forbidden because of its invasion of privacy.” Clearview licenses its technology to more than 600 law implementation agencies. New York City passed on the app after a 90-day test, worried about potential misuse. Clearview’s investors “predict that its app will eventually be available to the public.” Soon, “searching someone by face could become as easy as Googling a name.”

We’ve been building toward this moment for a long time, said Adrian Chen in The California Sunday Magazine. In the late 1800s, the French police officer Alphonse Bertillon devised the first “method for identifying criminals based on their physical features,” using 11 physical measurements. But scale changes everything. The Department of Homeland Security plans to scan “97 percent of all passengers on outgoing international flights.” And the technology has been improved and commercialized to the point where you can search a database and buy scans for as little as “40 cents an image if you opt for Amazon’s facial recognition software plan.”

All this has already led to growing fears about facial recognition, said Janosch Delcker and Cristiano Lima in Politico.com, but “efforts to check its spread are hitting a wall of resistance on both sides of the Atlantic.” A two-party push to limit the government’s use of facial recognition has been delayed in Congress. The European Union (EU) is discussing a five-year temporary ban, but European privacy rules contain “a broad carve-out for public authorities.” And authorities are using it: London’s police just last week enabled live facial recognition for cameras across the city.

Even if some bans on the technology succeed, said Bruce Schneier in The New York Times, we’re still building an “observation society.” Facial recognition is just one identification technology among many. An entirely unregulated data industry is already creating “descriptions of who we are and what our interests are” by tracking our movements, purchases, and interactions. “We are being identified without our knowledge, and society needs rules about when that is permissible.”