1 . For Western designers, China and its rich culture have long been an inspiration for Western creators (创造者).

“It’s no secret that China has always been a source (来源) of inspiration for designers,” says Amanda Hill, chief creative officer at A+E Networks, a global media company and home to some of the biggest fashion (时尚) shows.

Earlier this year the China Through A Looking Glass exhibition in New York exhibited 140 pieces of China-inspired fashionable clothing alongside Chinese works of art , with the aim of exploring the influence of Chinese aesthetics (美学) on Western fashion and how China has fueled the fashionable imagination for centuries. The exhibition had record attendance, showing that there is huge interest in Chinese influences.

“China is impossible to overlook,” says Hill. “Chinese models are the faces of beauty and fashion campaigns that sell dreams to women all over the world, which means Chinese women are not just consumers of fashion —they are central to its movement.” Of course, only are today’s top Western designers being influenced by China — some of the best designers of contemporary fashion are themselves Chinese. “Vera Wang, Alexander Wang, Jason Wu are taking on Galiano, Albaz, Marc Jacobs—and beating them hands down in design and sales,” adds Hill.

For Hill, it is impossible not to talk about China as the leading player when discussing fashion. “The most famous designers are Chinese, so are the models, and so are the consumers,” she says. “China is no longer just another market; in many senses it has become the market. If you talk about fashion today, you are talking about China —its influences, its direction, its breathtaking clothes, and how young designers and models are finally acknowledging that in many ways.

2 . Davis Smith was born into a family of travel agents. It offered him the chance to_________ places such as Nepal, Laos and Nigeria during his childhood, according to Times magazine. He began saving up at the age 13 to_________ his goal of visiting all countries By his 19th birthday, he had travelled to 81 nations. In September, 2015, he realized he could see the_________ nations on his list in time to set an official record. Many people _________ his travel on social media platform Instagram, so he decided to chase the world record partly to_________ others. “Honestly, in the beginning, I_________ wanted to push the_________ of what I thought I could do with my life and see as much of the world as possible in the_________,” he told Times. “It wasn’t until things started getting really_________ that I realized I was inspiring people around me, especially the__________.”

“I also loved visiting Sri Lanka, for the natural beauty of the mountains, and the kindness of the locals were astonishing,” Davis Smith said. “The most pleasant surprise about travelling to all these misunderstood areas of the world was that the countries that I had the __________ expectation for__________ being the most incredible.”

“My__________ for young people is to believe that you can do anything you set your mind to do. If you want to travel, you have to__________ sacrifices to travel around the world. And it’s only a matter of__________ until you can make it a reality.”

Charlie Chaplin as the Little Tramp eats his shoe for Thanksgiving dinner while trapped in a snowstorm in this endearing silent film classic from 1925. Watch this one if you’re in the mood to see a leather shoe prepared and eaten as if it were a delicious turkey. It makes you thankful for what you have!

Return to the iconic moment when Lucy pulls the football away from Charlie Brown right as he’s about to kick it. Life is hard, but in this animated film, sweetness wins when the Peanuts group prepares a Thanksgiving feast, complete with jelly beans.

This John Hughes comedy starring Steve Martin and John Candy is already a Thanksgiving classic for many. Neal ends up rerouting the plane because of a snowstorm. As he struggles to find a way home for Thansksgiving, he gets stuck with extremely positive Del.

Mery1 Streep was nominated (提名) for an Academy Award for her performance in this movie as a wife and mom who struggles with cancer. Rente Zellweger plays the grown daughter who has to come home to help with the holiday. The two try to hold the family together, especially during a tense Thanksgiving meal when guests get all the attention.

9 . A study published recently shows that tomato fruits are able to transmit alerts to their mother plant when attacked by caterpillars.

Plants have a large number of chemical and hormonal signaling pathways, which are generally transmitted through the sap (树液). Given the fact that fruits just hang from the main plant before ultimately falling off and sap typically only runs from the plant to the fruit — not back and forth between the two — it has long been unclear whether or not fruits can transmit information to the plant.

To address that question, scientists at Brazil’s Federal University of Pelotas placed tomato plants in a Faraday cage. Electrodes (电极) were attached to the ends of the plants’ branches at the points where they connected to the fruits. Then they measured electrical responses within the branches before, during and after a 24-hour period in which the fruits were attacked by caterpillars. Machine-learning-based algorithms were used to identify patterns in the signals.     

It was found that there was a “clear difference” between the signals before and after caterpillar attacks. Additionally. defensive biochemical responses were observed throughout the plants’ bodies, suggesting that they had been triggered by signals sent by the fruits. There searchers gave the following explanation. The tomato fruit, sensing a nearby insect, released electrical signals to reach the rest of the plant. These warnings impulses were received by the main plant and as a result, the rest of the plant got prepared to fight off the unwanted invaders. The tomato fruit made sure that the plant produced chemicals that were unpleasant to taste, so that hungry caterpillars stayed off the fruit.

The scientists now plan on investigating whether other fruiting plants behave in the same manner as tomatoes, and whether their fruits respond to threats other than insects. They believe understanding how the plant interacts with its fruits, and the fruits among themselves, may bring insights into how to make use of this communication for enhancing fruit quality, resistance to pests and shelf life after harvest.

10 . Mogao Grottoes is located at the western end of the Hexi Corridor along the ancient Silk Road in Dunhuang, China. Until now, most mural paintings at Mogao Grottoes have been dated by directly referring to the mural texts or historical documents. However, some are still left with the creation era (年代) uncertain due to the lack of reference materials or the disagreement of art experts.

The drawing style of mural paintings was changing throughout history and can be learned and quantified (量化) through painting data. A new dating method has been developed by encoding (编码 )the drawing styles using visual codes learned through deep learning. This new method successfully discovered the creation era of six mural paintings at Mogao Grottoes.

With the help of experts from Dunhuang Academy, seven mural paintings from two grottoes (No. 205 and No. 206) were chosen as subjects for this dating research.

To figure out the creation era of these paintings, Qin Zou, a researcher from Wuhan University, collected 3,860 mural paintings from 194 different grottoes with confirmed creation-era labels. To find the visual codes that can identify the era in these paintings, the authors built a deep convolutional neural network(卷积神经网络)and classified these painting images into the right eras. Based on the classification model, a dating method was built and applied to date the seven paintings.

Six of the new dating results were approved by experts from Dunhuang Academy. “These dating results are correct and the method is great,” said Mr. Hui-Min Wang, a distinguished expert from the Archaeological Institute of Dunhuang Academy.

“To the best of our knowledge,” wrote the researchers,“ this work represents the first account of a scientific and quantitative manner to support the era prediction and reduce the uncertainties in dating ancient paintings by using deep learning.