3 . When we’re on the treadmill (跑步机), we’re more likely to bethinking about whether we’re going to make it another mile than’what’s in our workout clothing. But our favorite sports ch ab are likely to be made from synthetic (合成的) fabrics, all of which are essentially plastic often created with harmful chemical additives. Now, a study conducted by the University of Birmingham shows the chemical additives from our workout clothing are available to be absorbed through our skin.

Previously, researchers have tended to focus on our exposure to plastic through diet,but the new study raises awareness that humans can be expesed to plastic chemicals through our skin, too. And because harmful chemicals accumulate lowly and stick around in our bodies, repeared and multi-source exposure can result in having high concentrations of chemicals inside us, potentially contributing to health effects.

The Birmingham study focused on a class of compounds(化合物)called brominated flame retardants(BFRs), which are used to prevent burning in a wide range of consumer products including fabries, and are linked to adverse health effects such as hormonal disorders and mental problems.

It’s known that sweat contains oil. Researchers found the oil has a chemical nature that encourages the chemicals in plastic to dissolve and spread.“In short, oil substances in our sweat help the bad chemicals to come out of the microplastic fibers and become available for human absorption,”says Dr. Abdallah of the Urnversity of Birmingham. An easy way to avoid exposure to these chemicals is to wear clothing made of sustainably produced textiles, which dont contain the bad chemicals associated with plastic materials. Check fabric labels for items that are mostly organic cotton, he mp or merino wool. Visit brand websites to see if they make an effort to list their suppliers, and where their products come from, including their dye houses and mills. Abdallah says he minimizes synthetic fabrics in his home, meanwhile wearing natural fibers like cotton. “Why be exposed to these chemicals even at low levels?”he says.“Why not avoid the risks?”

4 . It is a small step for a plant, and a giant leap for plant kind. A sprouting (发芽) cotton seed on China’s Chang’e-4 lunar lander is the first plant ever to grow in another world, indicating a new era for life in space.

Seeds, including cotton, arabidopsis (拟南芥), oilseed rape (油菜) and potato were carried to the Moon as a part of biological experiment, along with fruit fly eggs and some yeasts (酵母).

Pictures sent back by the probe show the cotton seeds sprouting on January 7, 2019, a few days after Chang’e-4 landed on the far side of the Moon.

The organisms (生物) are in a sealed can, protected from the extreme temperatures and radiation on the surface. “Understanding how to grow plants in space will help lay the foundation for human settlement on the Moon,” a scientist leading the experiment told the South China Morning Post.

The six organisms are intended to form a mini-ecosystem, with the plants making oxygen and food to sustain the fruit flies. Yeasts could process the flies’ waste and dead plants to provide another food source.

In a future human settlement, potatoes could provide food, rapeseed could be a source of oil and cotton could be used for clothing. A study in 2014 reported that plants could sprout and grow in lunar soil for 50 days without any additional nutrients (营养物). Over longer periods, human waste could help support plants’ nutritional needs.

These lunar green shoots aren’t the first plants in space. Astronauts on the International Space Station have grown crops including peas, radishes and cucumbers. They got their first bites of space-grown romaine lettuce in 2015.

The China National Space Administration eventually hopes to put humans on the Moon. “We are studying the program of sending astronauts to the Moon, but it’s still in very early stages,” a deputy director told the South China Morning Post. “We haven’t got the approval yet.”

5 . Baidu, a Chinese search engine and artificial intelligence firm, announced its latest electric autonomous driving vehicle, Apollo RT6, on Thursday. The new vehicle is a fully electric vehicle with a steering wheel (方向盘) that can be removed when not required. It will cost ¥250,000 per unit.

“The steering-wheel-free design allows more space for extra seating or other additions and the massive cost reduction will enable us to put tens of thousands of autonomous vehicles into operation across China,” Robin Li, co-founder and CEO of Baidu, said at the firm's Baidu World Conference Thursday. “We are moving towards a future where taking a robotaxi will be half the cost of taking a taxi today.”

Baidu already runs Apollo Go and Apollo Moon, taxi services using self-driving robotaxis with safety staff seated in the driver or passenger seat. They have been in operation in big cities like Beijing, Shanghai, Shenzhen and Guangzhou, although the service is limited to specific areas. The new vehicle will soon join those robotaxis.

The RT6 has reached the industry's Level 4 out of five possible levels of technology. That means its systems can operate without a driver but must be pre-loaded with a detailed map, thus limiting the areas where the vehicles can operate. Lower levels of self-driving technology have been available for decades. For example, many Level-3 vehicles allow hands-free highway driving. Other kinds of self-driving robot vehicles are already widely used in factories warehouses and other tightly controlled settings.

Compared to previous generations where the technology was mainly used on conventional vehicles, the Apollo RT6 was designed specifically with fully autonomous driving in mind.

Baidu is best known for its search engine and online advertising services, but in recent years it has invested heavily in autonomous driving and artificial intelligence technology, including automated personal assistants and AI chips.

6 . We sometimes think that everything was much better and easier in the past. It’s one of the tricks our minds play on us, especially when we are in low spirits.

Actually, it’s unlikely that things were objectively better in the past. This form of thinking is called rosy retrospection, which is a well-studied cognitive bias. It happens because when we think about the past, we are more likely to focus on positive generalities than annoying details.

If you think back to a holiday with your family five years ago, you’re likely to recall the beautiful views rather than the uncomfortable bed. In other words, the negative details disappear from our memory over time while the positive ones remain.

Rosy retrospection can influence how we make decisions, and it’s one of the reasons why we easily return into problematic relationships. The longer it is since we experienced the negative influence of a relationship, the more likely we are to let the good memories outweigh the bad memories and to perhaps forgive unforgivable behavior. It’s always a good idea to review our nostalgic (怀旧的) feelings with a healthy degree of doubt.

But rosy retrospection does serve an important purpose. It keeps us in a positive state of mind in the present and is important to our psychological wellbeing. In fact, people who tend to remember negative experiences more than positive ones are likely to exhibit psychological disorders. Research generally suggests that our happiest days are still to come. And even if they’re not, it’s still important to believe that they are. Don’t shy away from looking upon the past with a certain degree of nostalgia. But, for the same reason, don’t use the past as an excuse to be unhappy in the present.

7 . Predicting extreme weather events is a tricky business. Changing climate conditions have increased the frequency of severe storms, floods, and heatwaves, along with larger wildfires. As a result, scientists are using artificial intelligence (AI) techniques for more accurate forecasts that help to minimize damage and save lives.

Researchers at Pennsylvania State University have worked together with meteorologists (气象学家) to analyze more than 50,000 weather satellite images to quickly identify storms. They found comma-shaped cloud formations that often lead to severe weather such as hail, blizzards, high winds, and thunderstorms.

Computers were then taught using computer vision and machine learning to automatically detect these clouds from satellite images, with almost 100 percent accuracy, in less than a minute. By refocusing meteorologists’ attention on potential storm cloud formation the AI tool helped predict 64 percent of severe weather events and beat established detection systems.

Expensive supercomputers are often used to process vast amounts of data needed for accurate weather prediction. But powerful Al methods can run on smaller computers. Climate risk and planning company ClimateAI uses a technique to downscale global weather forecasts to a local scale, cutting down on costs and computing power.

It uses a machine learning technique that pits two neural networks against each other. The neural networks - designed to work like neurons connected in the brain-fight and train each other using global weather data until they get a result.

Using this method ClimateAI researchers generate highly accurate and inexpensive local forecasts for hours or days ahead. And because it is not as costly, it allows poorer countries affected by climate change to use forecasts to change the way they farm, build bridges, roads, or homes, and adapt to extreme weather.

Average costs associated with extreme weather events in the United States have increased steadily since 1980. These have costly impacts on cities’ basic services, infrastructure, housing, human livelihoods, and health. AI helps us to calculate that risk and can be used as a preventive measure.

Do you have some good advice for online safety? Post your comments below!