Thermal imaging wearables used in China to detect COVID-19 symptoms could soon be deployed in the U.S.

 

Hangzhou based AI startup Rokid is in talks with several companies to sell its T1 glasses in America, according to Rokid’s  U.S. Director Liang Guan.

 

Rokid  is among a wave of Chinese companies creating technology to address the coronavirus pandemic, which has dealt a blow to the country’s economy.  Per info Guan provided, Rokid’s T1 thermal glasses use an infrared sensor to detect the temperatures of up to 200 people within two minutes from as far as three meters. The devices carry a Qualcomm  CPU, 12 megapixel camera and offer augmented reality features — for hands free voice controls — to record live photos and videos.

 

The Chinese startup (with a San Francisco office) plans B2B sales of its wearable devices in the U.S. to assist businesses, hospitals and law enforcement with COVID-19 detection, according to Guan.

Rokid is also offering IoT and software solutions for facial recognition and data management, as part of its T1 packages.

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Total deaths in seven states that have been hard hit by the coronavirus pandemic are nearly 50 percent higher than normal for the five weeks from March 8 through April 11 2020, according to new death statistics from the Centers for Disease Control and Prevention. That is 9,000 more deaths than were reported as of April 11 in official counts of deaths from the coronavirus.

 

The new data is partial and most likely undercounts the recent death toll significantly. But it still illustrates how the coronavirus is causing a surge in deaths in the places it has struck, probably killing more people than the reported statistics capture. These increases belie arguments that the virus is only killing people who would have died anyway from other causes. Instead, the virus has brought a pattern of deaths unlike anything seen in recent years.

 

If you look at the provisional deaths from all causes, death counts in New York, New Jersey, Michigan, Massachusetts, Illinois, Maryland and Colorado have spiked far above their normal levels for the period. In New York City, the home of the biggest outbreak, the number of deaths over this period is more than three times the normal number. Recent data suggests it could have reached six times higher than normal.

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Researchers at Switzerland-based Empa, ETH Zurich and Zurich University Hospital have developed a sensor that has the potential to identify SARS-CoV-2, the novel coronavirus that causes COVID-19, in the air. The work is led by Jing Wang at Empa, who usually works on measuring and analyzing airborne pollutants.

 

The sensor has reliably shown the sensor can identify the first SARS-CoV virus that was responsible for the SARS pandemic in 2003. It has numerous similarities to SARS-CoV-2. “Tests showed that the sensor can clearly distinguish between the very similar RNA sequences of the two viruses,” Jing Wang said. And the results appear in minutes.

 

Sourced through Scoop.it from: www.biospace.com

The Pentagon has officially released three short videos showing "unidentified aerial phenomena" that had previously been released by a private company. The videos show what appear to be unidentified flying objects rapidly moving while recorded by infrared cameras. Two of the videos contain service members reacting in awe at how quickly the objects are moving. One voice speculates that it could be a drone.

 

The Navy previously acknowledged the veracity of the videos in September of last year. They are officially releasing them now, "in order to clear up any misconceptions by the public on whether or not the footage that has been circulating was real, or whether or not there is more to the videos," according to Pentagon spokesperson Sue Gough.

 

"After a thorough review, the department has determined that the authorized release of these unclassified videos does not reveal any sensitive capabilities or systems," said Gough in a statement, "and does not impinge on any subsequent investigations of military air space incursions by unidentified aerial phenomena."

 

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More than 90 vaccines are being developed against SARS-CoV-2 by research teams in companies and universities across the world. Researchers are trialling different technologies, some of which haven’t been used in a licensed vaccine before. At least six groups have already begun injecting formulations into volunteers in safety trials; others have started testing in animals. Nature’s graphical guide explains each vaccine design.

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"It’s not rocket science" may be a tired cliché, but that doesn’t mean designing rockets is any less complicated. Time, cost and safety prohibit testing the stability of a test rocket using a physical build "trial and error" approach. But even computational simulations are extremely time consuming. A single analysis of an entire SpaceX Merlin rocket engine, for example, could take weeks, even months, for a supercomputer to provide satisfactory predictions.

 

One group of researchers at The University of Texas at Austin is developing new "scientific machine learning" methods to address this challenge. Scientific machine learning is a relatively new field that blends scientific computing with machine learning. Through a combination of physics modeling and data-driven learning, it becomes possible to create reduced-order models – simulations that can run in a fraction of the time, making them particularly useful in the design setting.

 

Sourced through Scoop.it from: www.eurekalert.org