Deborah Cohen is a senior natural scientist at the Rand Corp and the author of the book A Big Fat Crisis: The Hidden Forces Behind the Obesity Epidemic and How We Can End It. According to the book, there are lots of misunderstandings of obesity.

1).If you're obese, blame your genes.

    Obesity rates have increased. Yet, between 1980 and 2000, the number of Americans who are obese has doubled—too quickly for genetic factors to be responsible.

    At restaurants, a dollar puts more calories on our plates than ever before, because restaurant meals usually have more calories than what we prepare at home, so people who eat out more frequently have higher rates of obesity than those who eat out less.

2).If you're obese, you lack self-control.

    Research shows that if we are faced with too much information, we have a tendency to make poor dietary choices. Our world has become so rich in temptation that we can be led to consume too much in ways we can't understand. Even the most vigilant (警觉的) people may not be up to the task of controlling themselves.

3).Lack of access to fresh fruits and vegetables is responsible for obesity.

    Although the US Department of Agriculture estimates that fewer than 5 percent of Americans live in the “food deserts”, about 65 percent of the nation's population is overweight or obese. For most of us, obesity is not related to access to more fresh fruits and vegetables, but to the choices we make in supermarkets.

4).The problem is not that we eat too much, but that we don't exercise.

    Michelle Obama's “Let's Move” campaign is based on the idea that if kids exercise more, childhood obesity rates will decrease. But there was no significant decrease in physical activity levels as obesity rates climbed in the 1980s and 1990s. In fact, although a drop in work-related physical activity may account for up to 100 fewer calories burned, leisure physical activity appears to have increased. The problem is that we eat too much.

    Sound travels very well through water-much better, in fact, than it does through air. So it shouldn't be surprising that many ocean animals make noise. They use sound to communicate and hunt. As biologist Brandon Southall says, “Their whole world is related to sound.”

    Dolphins whistle, organizing hunts. Lovesick whales sing so loudly they can be heard hundreds of miles away. But these days they aren't the only ones sounding off. They have more and more competition from human machines.

    Every day, thousands of huge container ships sail across the world's oceans. On top of the engine noise, the ships' propeller (螺旋桨) make a loud noise all the time. All that can make it hard for ocean animals trying to listen out for friends, or dinner. Animals swimming nearby a ship can be deafened or even killed.

    Underwater construction can also be dangerously loud. When construction machines called pile drivers were used during repairs to the San Francisco-Oakland Bay Bridge, dead fish appeared.

    Geologist (地质学家) pound on the seafloor too, trying to find oil wells and map Earth's surface. The results are useful lo science, but all that hammering probably gives ocean animal a headache.

    As people realize how important sound is to ocean animals, they are looking for ways to reduce human noise. Ships could get quieter just by slowing down. Engineers are also trying to find quieter propeller ships.

    Now some companies are using a simple invention called a bubble curtain, which makes sound waves passing through it lose energy and gel quieter. It seems to work - when bubble curtains were fixed on the San Francisco bridge project fish deaths dropped.

    We still have a lot to learn about sound in the oceans, but together we can help keep the sea a quieter place.

        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.

    The City of Christchurch, New Zealand was struck by a 7.1­magnitude earthquake on the early morning of Saturday, September 4, 2010.

    No tsunami alert was reported. The country's army troops were on standby to assist victims and disaster recovery operation. New Zealand's Prime Minister John Key, flew to the affected area to inspect and assess the situation of the damaged city. The Prime Minister said that the full assessment of the damages would possibly take months to know the severity of damages. Based from his assessment on what he saw in the area, it could cost at least 2 billion New Zealand dollars or US$1.4 billion for reconstruction.

    "An absolute miracle that no one died," Prime Minister John Key said. Two were seriously injured from this quake and thousands of local residents were awakened after being shaken at 4:35 a.m. of that Saturday.

    There were people trapped inside the damaged buildings but fortunately none were reported dead from the rubble of the damaged buildings.

    "We're all feeling scared—we've just had some significant aftershocks," a survivor told TV One News. "Tonight we're just people in the face of a massive natural disaster, trying to help each other and we're grateful we haven't lost a life."

    GNS Science reported 29 aftershocks within the 14 hours after the quake, with strength from magnitude 3.7 to 5.4.

    New Zealand is no stranger to earthquakes. The country experiences more than 14,000 earthquakes a year—but only about 150 are felt by people.

    "Many buildings here were built with earthquake protection measures. However, in most cities in developing countries, people build how they want to and there're no building controls to force them to build to a higher standard that's safe," Andrew Charleson, an architecture professor at Victoria University of Wellington told CNN.

Crocodiles today look very similar to ones from 200 million years ago. There are also very few species alive today—just 25. Other animals such as lizards (蜥蜴) and birds have achieved a diversity of many thousands of species in the same amount of time or less.

Prehistory also saw types of crocodile we don't see today, including giants as big as dinosaurs, plant-eaters, fast runners and snake-like forms that lived in the sea. The rate of their evolution is generally slow, but occasionally they evolve more quickly because the environment has changed. In particular, their evolution speeds up when the climate is warmer, and their body size increases.

The body size of crocodiles is important because it interacts with how fast animals grow, how much food they need, how big their populations are and how likely they are to become extinct. The limited diversity of crocodiles and their apparent lack of evolution is a result of a slow evolutionary rate. It seems the crocodiles arrived at a body plan that was very efficient and perfect enough that they didn't need to change it in order to survive. This perfection could be one explanation why crocodiles survived Cretaceous period (白垩纪), in which the dinosaurs died out.

Crocodiles generally develop better in warm conditions because they cannot control their body temperature and require warmth from the environment. The climate during the age of dinosaurs was warmer than it is today, and that may explain why there were many more varieties of crocodiles than we see now. Being able to draw energy from the sun means they do not need to eat as much as a warm-blooded animal like a bird or a mammal (哺乳动物).

New research from the University of Portsmouth has shown a marked increase in shipping in the North East Atlantic. Scientists now warn that more monitoring is required to help protect sea life. 

Researchers at the University of Ponsmouth have discovered that rates (率)of shipping in the North East Atlantic area rose by 34 per cent in a five-year period. The research is the first detailed survey of shipping activity in the North East Atlantic. Researchers used data from over 530 million vessel(船)positions recorded by Automatic Identification System(AIS). They looked at the change in shipping between 2013 and 2017 across ten different vessel types. In total the study area covered 1.1 million km², including waters off Belgium, Denmark, France, Germany,Iceland, Ireland, The Netherlands, Norway, Portugal. Spain, and the UK. 

Lead author, James Robbins said:"This change is likely to put more pressure on the marine(海 洋的)environment, and may influence the protection of at-risk species. Renewed monitoring effort is needed to make sure that protective measures are enough to save species under threat in a changing environment. "

Some of the greatest shipping increases were found in areas close to the Spanish coast. The Espacio Marino de la Costa da Morte saw a rise of 413 percent in vessel activity. It is an area used to protect seabirds. 

Dr. Sarah Marley, Visiting Researcher at the University of Portsmouth, said:"Shipping is the most widespread human activity in our oceans, carrying a set of threats-from unnoticeable effects like underwater noise pollution to serious results when ships hit whales. "

Professor Alex Ford. from the University's Institute of Marine Sciences, said:"Given the well- documented effects that shipping can have on the marine environment, it is necessary that this situation continues to be monitored-particularly in areas used to protect vulnerable(脆弱的)species which may already be under pressure. "