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Super Nintendo World opening in February with interactive Mario Kart ride

FOX News

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Universal Studios Japan has announced an opening date for its Super Nintendo World – and you won't have to fall through any sewer pipes to get in. The theme park will open February 4. (Universal Studios Japan) The specialty video game-themed park will be opening February 4, 2021 in Osaka. The world's first Super Nintendo World will consist of a "highly themed and immersive land featuring Nintendo's legendary worlds, characters and adventures where guests will be able to play inside their favorite Nintendo games," according to a press release shared with Fox News.


China set to bring back rocks from the Moon

Science

On Earth, deep time is an open book. By measuring trace radioactive compounds in rocks that decay with metronomic regularity, dating experts have learned when oceans opened, volcanoes erupted, and mass extinctions struck. But the story is muddled elsewhere in the Solar System because records are sparse. Scientists estimate ages on the Moon and the rocky planets from the number of craters that pock their surfaces. They have fixed dates from just nine places, all on the Moon: the six Apollo and three Soviet Luna sites from which samples were returned to laboratories on Earth. China's Chang'e-5 mission, set to launch on 24 November, aims to make it 10, by returning the first Moon rocks since the last Luna mission in 1976. Getting a firm date from another location will improve the shaky crater counting scheme, says Kentaro Terada, a cosmochemist at Osaka University. It will also sharpen the picture of the Moon's history. A fresh sample date “is the most important and exciting new finding [that will come] from the Chang'e-5 samples,” Terada says. Getting it will require a tour-de-force, round-trip space flight that has not been attempted for more than 40 years. Chang'e-5's target is Mons Rümker, a 70-kilometer-wide volcanic mound on the Moon's near side, which may have erupted as recently as about 1.3 billion years ago. It is “the youngest mare basalt on the Moon,” says Xiao Long, a planetary geoscientist at the China University of Geosciences, referring to the dark lava also seen in the Moon's maria, or seas. Brett Denevi, a planetary geologist at Johns Hopkins University's Applied Physics Laboratory and science chair of a NASA lunar analysis group, says China has picked a spot where it can have a big scientific impact. “Understanding the age of those samples and all of the Solar System–wide implications that flow from that result will be a big leap forward for planetary science,” she says. The crater counting method for determining age relies on the notion that surfaces scarred with fewer craters are younger than those that have accumulated more. Regions dated with Apollo and Luna samples have helped calibrate the method. But except for one young outlier, all of those dates cluster between 3.2 billion and 3.9 billion years, leaving the method unanchored, and highly uncertain, for surfaces younger than 3 billion years old, Terada says. “Chang'e-5 samples will provide another data point,” he says. Getting a firm date for Mons Rümker will also shed light on how lunar volcanism changed over time. Evidence suggests numerous eruptions in the first billion years of the Moon's existence blanketed the surface with volcanic basalts, forming the dark maria, before tapering off about 3 billion years ago. If Mons Rümker material proves to be just 1.3 billion years old, it will raise questions about how the interior of a small planetary body remained hot enough to erupt so long after formation, says Romain Tartese, a planetary scientist at the University of Manchester. Retrieving the samples will require a complex deep-space ballet. After launch from the Wenchang launch center in southern China, Chang'e-5 will arrive at the Moon about 3 days later, where an orbiter will release a lander. Over the course of 14 days, the lander's robotic arm will scoop up surface samples and a drill will retrieve cores down to 2 meters. Scientists are hoping for 2 kilograms of material. (NASA's Apollo program brought back more than 380 kilograms; three Soviet robotic Luna missions returned 301 grams.) An ascent vehicle will ferry the samples to the orbiter, where they will be packed into a re-entry capsule for return to Earth and a touchdown in the grasslands of Inner Mongolia. Xiao says international investigators will have access to the samples, but U.S. scientists may not because of limits on cooperation with China set by the U.S. Congress. Chang'e-5 is the latest in a set of increasingly ambitious Moon missions from the China National Space Administration, all named after Chang'e, a Chinese Moon goddess. A pair of orbiters, launched in 2007 and 2010, focused on mapping and remote observations. The lander-rover Chang'e-3 mission, in 2013, carried the first ground-penetrating radar to the lunar surface. In 2019, Chang'e-4, another lander-rover, was the first spacecraft to soft-land on the far side of the Moon. Three more Chang'e missions and a robotic scientific research station are planned by 2035. Results from Chang'e-4, still trundling along after having traveled nearly 600 meters, are raising questions for later missions. The craft landed in the South Pole–Aitken basin, the Moon's largest, deepest, and oldest impact crater, at perhaps 4 billion years. Scientists have calculated that the impacting body likely burrowed 70 kilometers into the Moon and churned material from the mantle up to the surface. In a study published in 2019 in Nature , one group of Chinese scientists said the rover's instruments had detected mantle minerals, but other groups, including Xiao's, have challenged that interpretation. Patrick Pinet, a planetary geophysicist at France's Astrophysics and Planetology Research Institute, says researchers are debating why such an enormous impact apparently did not exhume mantle material—or whether the mantle composition is somehow unexpected. Zou Yongliao, a geochemist at the Chinese Academy of Sciences's National Space Science Center, says China is making the South Pole the focus of its near-term lunar plans. And although the target site has not been revealed for Chang'e-6, another sample return mission, planetary scientists are rooting for South Pole–Aitken. A basin sample would provide clues to the mantle puzzle. It would also anchor the older end of the crater-counting curve, says Carolyn van der Bogert, a planetary geologist at the University of Münster, and “illuminate the early history of the Moon.”


As AI pops up in more and more scientific computing, a new time test measures how fast a neural net can be trained

ZDNet

The world's most powerful computer, Fugaku, at the RIKEN Center for Computational Science in Kobe, Japan, built by Fujitsu. The computer, and many other top supercomputers, are increasingly incorporating neural networks used in artificial intelligence to work on the most sophisticated kinds of scientific research problems. The technology of artificial intelligence has become so prevalent in even the most complex domains of science that it now has its own suite of tests to measure its computing time on the world's most powerful computers. MLPerf, the industry consortium that serves the computer industry by measuring how long it takes to run machine learning, a subset of artificial intelligence, on Wednesday offered an inaugural suite of test results for high-performance computing, or HPC, systems running the machine learning tasks. The test results, submitted by a variety of research labs, include results for the world's fastest computer, Fugaku.


Researchers use machine learning algorithm to identify common respiratory pathogens

#artificialintelligence

The ongoing global pandemic has created an urgent need for rapid tests that can diagnose the presence of the SARS-CoV-2 virus, the pathogen that causes COVID-19, and distinguish it from other respiratory viruses. Now, common respiratory from Japan have demonstrated a new system for single-virion identification of common respiratory pathogens using a machine learning algorithm trained on changes in current across silicon nanopores. This work may lead to fast and accurate screening tests for diseases like COVID-19 and influenza. In a study published this month in ACS Sensors scientists at Osaka University have introduced a new system using silicon nanopores sensitive enough to detect even a single virus particle when coupled with a machine learning algorithm. In this method, a silicon nitride layer just 50 nm thick suspended on a silicon wafer has tiny nanopores added, which are themselves only 300 nm in diameter.


Sorting out viruses with machine learning – ScienceDaily

#artificialintelligence

The ongoing global pandemic has created an urgent need for rapid tests that can diagnose the presence of the SARS-CoV-2 virus, the pathogen that causes COVID-19, and distinguish it from other respiratory viruses. Now, researchers from Japan have demonstrated a new system for single-virion identification of common respiratory pathogens using a machine learning algorithm trained on changes in current across silicon nanopores. This work may lead to fast and accurate screening tests for diseases like COVID-19 and influenza.In a study published this month in ACS Sensors scientists at Osaka University have introduced a new system using silicon nanopores sensitive enough to detect even a single virus particle when coupled with a machine learning algorithm.In this method, a silicon nitride layer just 50 nm thick suspended on a silicon wafer has tiny nanopores added, which are themselves only 300 nm in diameter. When a voltage difference is applied to the solution on either side of the wafer, ions travel through the nanopores in a process called electrophoresis.The motion of the ions can be monitored by the current they generate, and when a viral particle enters a nanopore, it blocks some of the ions from passing through, leading to a transient …


AI-assisted camera system to monitor seabird behaviour

AIHub

Researchers from Osaka University have combined bio-logging cameras with a machine learning algorithm to help them to shed light on hidden aspects of the lives of seabird species, including gulls and shearwaters. Bio-logging is a technique involving the mounting of small lightweight video cameras and/or other data-gathering devices onto the bodies of wild animals. These systems allow researchers to observe various aspects of animals' lives, such as behaviours and social interactions, with minimal disturbance. However, the considerable battery life required for these high-cost bio-logging systems has proved limiting so far. "Since bio-loggers attached to small animals have to be small and lightweight, they have short runtimes and it was therefore difficult to record interesting infrequent behaviours," explains study corresponding author Takuya Maekawa.


Japan's 'healing robots' help ease COVID-19 isolation

The Japan Times

Nagoya – While many people have learned to stay in touch with loved ones, friends, and colleagues through videoconferencing during the COVID-19 pandemic, the reduction of face-to-face interaction has boosted a market for robots providing substitutes for physical human contact. "Healing robots," such as the cuddly humanoid Lovot developed by Groove X Inc., Sony Corp.'s Aibo robotic dog, and Qoobo, a furry cushion with a tail that moves in reaction to strokes developed by Yukai Engineering Inc., are seeing sharp sales rises, the companies say. Lovot and Aibo can gather data on the well-being of their owners and report it remotely, which is why some people are gifting the automatons to their older parents living far away whom they are refraining from visiting due to infection risks. "When people feel uneasy or lonely, they tend to yearn for a sense of physical touch," Hiroshi Ishiguro, a professor of intelligent robotics at Osaka University, said in explaining the reason behind the trend. "Through healing robots, they must be trying to confirm the actual existence of others, which is hard to really feel on the telephone or through videoconferencing," he said. Lovot, a mascot-like robot with round eyes that stands 43 centimeters tall, has even found its way into a kindergarten in Nagoya, to help young children who may be affected by the emotional stresses created by the pandemic.


FEATURE: "Healing robots" help ease COVID-19 isolation – IAM Network

#artificialintelligence

While many people have learned to stay in touch with loved ones, friends, and colleagues through videoconferencing during the COVID-19 pandemic, the reduction of face-to-face interaction has boosted a market for robots providing substitutes for physical human contact. "Healing robots," such as the cuddly humanoid Lovot developed by Groove X Inc., Sony Corp.'s Aibo robotic dog, and Qoobo, a furry cushion with a tail that moves in reaction to strokes developed by Yukai Engineering Inc., are seeing sharp sales rises, the companies say. Lovot and Aibo can gather data on the well-being of their owners and report it remotely, which is why some people are gifting the automatons to their elderly parents living far away whom they are refraining from visiting due to infection risks. "When people feel uneasy or lonely, they tend to yearn for a sense of physical touch," Hiroshi Ishiguro, a professor of intelligent robotics at Osaka University, said in explaining the reason behind the trend. "Through healing robots, they must be trying to confirm the actual existence of others, which is hard to really feel on the telephone or through videoconferencing," he said.


RoboCup-97: The First Robot World Cup Soccer Games and Conferences

AI Magazine

RoboCup-97, The First Robot World Cup Soccer Games and Conferences, was held at the Fifteenth International Joint Conference on Artificial Intelligence. There were two leagues: (1) real robot and (2) simulation. Ten teams participated in the real-robot league and 29 teams in the simulation league. Over 150 researchers attended the technical workshop. The world champions are CMUNITED (Carnegie Mellon University) for the small-size league, DREAMTEAM (University of Southern California) and TRACKIES (Osaka University, Japan) for the middle-size league, and AT-HUMBOLDT (Humboldt University) for the simulation league.


Local Kyoto Town Mascot Gets Artificial Intelligence

#artificialintelligence

Seika, a town located in the southern part of the Kyoto Prefecture, has a mascot anime girl character named Seika Kyomachi. The mascot is notable for employing various technological innovations in her mission to spread information about the town; she became a Voiceroid character in 2016, her 3D data is open source, and in July she became a Virtual YouTuber. Her latest foray is into artificial intelligence, which would allow her to respond to queries in real time. The "Narikiri AI" (Impersonation AI) project is a collaboration between the city of Seikai and NTT Communication Science Laboratories. The AI will be developed by taking feedback from a small group of users who are knowledgeable about the town and the mascot; they provide sample questions and answers, as well as vote on responses that sound the most in-character for the mascot.