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The mysterious ways cancer spreads through the body, a process known as metastasis, is what can make it such a difficult enemy to keep at bay. Researchers at Princeton University working in this area have been tugging at a particular thread for more than 15 years, focusing on a single gene central to the ability of most major cancers to metastasize. They’ve now discovered what they describe as a “silver bullet” in the form of a compound that can disable this gene in mice and human tissue, with clinical trials possibly not too far away.

Metastatic cancer is a key focus for researchers and with good reason, as it is actually the primary cause of death from the disease. While surgery or chemotherapy might be effective at eliminating an initial tumor, cells that have broken away can discreetly make their way around the body and give rise to new tumors, months or even years later.

“Metastatic breast cancer causes more than 40,000 deaths every year in the US, and the patients do not respond well to standard treatments, such as chemotherapies, targeted therapies and immunotherapies,” says Minhong Shen, member of the Princeton team behind the new discovery. “Our work identified a series of chemical compounds that could significantly enhance the chemotherapy and immunotherapy response rates in metastatic breast cancer mouse models. These compounds have great therapeutic potential.”

When astronauts left the International Space Station in early November to return home on the Crew Dragon Endeavour, they took the opportunity to do a fly-around of the ISS and take photos. NASA just released the new images, and they are a stunning look at both the orbiting outpost and our home planet.

The person behind the camera was ESA astronaut Thomas Pesquet. He began taking photos after Crew Dragon undocked from the Harmony module. Also on board were NASA astronauts Shane Kimbrough and Megan McArthur, and JAXA astronaut Aki Hoshide. They had spent six months aboard the ISS.

“Bittersweet feeling about leaving the ISS,” Pesquet tweeted. “When you think about it, it’s really a magical place, almost impossible to reach and which gives you superpowers like flying, or going around the world in 1h30 … It still looks a bit like a daydream.”

There were some speculations in the comment section that we probably have large air compressor or some other kind of too huge powering system for our robotic arm that we supposedly don’t show you.

So we packed our Clone in a suitcase and filmed a little presentation for you. The whole thing weights 8kg (18 lbs). We could fit everything inside but we separated the electricity from the water. And this is still just the beginning of the miniaturization process, we must and we will make it portable enough so humanoid robots can help people in everyday life.

After a year of development we have finished the robotic arm 11th prototype. We are starting a new one from scratch, more biomimetic and powerful than ever!

Sorry for the strange colours on the video! We are testing a new film camera!

Western intelligence agencies fear Beijing could within decades dominate all of the key emerging technologies, particularly artificial intelligence, synthetic biology and genetics.

China’s economic and military rise over the past 40 years is considered to be one of the most significant geopolitical events of recent times, alongside the 1991 fall of the Soviet Union which ended the Cold War.

MI6, depicted by novelists as the employer of some of the most memorable fictional spies from John le Carré’s George Smiley to Ian Fleming’s James Bond, operates overseas and is tasked with defending Britain and its interests.

The current talk addresses a crucial problem on how compositionality can be naturally developed in cognitive agents by having iterative sensory-motor interactions with the environment.

The talk highlights a dynamic neural network model, so-called the multiple timescales recurrent neural network (MTRNN) model, which has been applied to a set of experiments on developmental learning of compositional actions performed by a humanoid robot made by Sony. The experimental results showed that a set of reusable behavior primitives were developed in the lower level network that is characterized by its fast timescale dynamics while sequential combinations of these primitives were learned in the higher level, which is characterized by its slow timescale dynamics.

This result suggests that adequate functional hierarchy necessary of generating compositional actions can be developed by utilizing timescale differences imposed at different levels of the network. The talk will also introduce our recent results on applications of an extended model of MTRNN to the problem of learning to recognize dynamic visual patterns on a pixel level. The experimental results indicated that dynamic visual images of compositional human actions can be recognized by self-organizing functional hierarchy when both spatial and temporal constraints are adequately imposed on the network activity. The dynamical systems’ mechanisms for development of the higher-order cognition will be discussed upon reviewing the aforementioned research results.

Jun Tani — Professor, Department of Electrical Engineering, KAIST