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Imagine a new type of security system that, rather than storing data or an encryption key on a USB drive, encodes information into a small piece of plastic that can be unlocked only via a chemical reaction using a specific type of substance. And the devices that can read this information think like human brains and have the ability to communicate seamlessly with today's electronics.

An antibody test for the virus that causes COVID-19, developed by researchers at The University of Texas at Austin in collaboration with Houston Methodist and other institutions, is more accurate and can handle a much larger number of donor samples at lower overall cost than standard antibody tests currently in use. In the near term, the test can be used to accurately identify the best donors for convalescent plasma therapy and measure how well candidate vaccines and other therapies elicit an immune response.

An elite prize among scientists worldwide is being given to Steven Weinberg, a professor of physics at The University of Texas at Austin, for his "continuous leadership in fundamental physics, with broad impact across particle physics, gravity and cosmology, and for communicating science to a wider audience."

The National Science Foundation has selected The University of Texas at Austin to lead the NSF AI Institute for Foundations of Machine Learning, bolstering the university's existing strengths in this emerging field. Machine learning is the technology that drives AI systems, enabling them to acquire knowledge and make predictions in complex environments. This technology has the potential to transform everything from transportation to entertainment to health care.

We asked you, dear listeners, to send us your most burning questions about COVID-19. And you didn't disappoint. You asked: When will it be safe for my 12-week-old baby to meet her grandparents? Can you catch it twice? Is the virus mutating and will that make it harder to develop vaccines? In today's episode, our three experts get to the bottom of these questions, and more.

The experimental vaccine against SARS-CoV-2 that was the first to enter human trials in the United States has been shown to elicit neutralizing antibodies and a helpful T-cell response with the aid of a carefully engineered spike protein that mimics the infection-spreading part of the virus.

Responding to a need to quickly develop billions of doses of lifesaving COVID-19 vaccines, a scientific team at The University of Texas at Austin has successfully redesigned a key protein from the coronavirus, and the modification could enable much faster and more stable production of vaccines worldwide.

The University of Texas at Austin's Scott Aaronson is an initial member of a new multi-institution collaboration called the NSF Quantum Leap Challenge Institute for Present and Future Quantum Computation. The institute will work to overcome scientific challenges to achieving quantum computing and will design advanced, large-scale quantum computers that employ state-of-the-art scientific algorithms developed by the researchers.

Being the strongest, biggest and most aggressive individual in a group might make you dominant, but it doesn't mean you make all the decisions.

When the first COVID-19 vaccine trial in the U.S. began on March 16, history was being made. Never before had a potential vaccine been developed and produced for human trials so quickly—just 66 days since scientists published the genome sequence of the virus that causes the disease. After news this week that Phase 1 of the vaccine's trial yielded promising results, the same candidate will enter the final phase of human trials later this month. This blindingly fast effort was only possible because a group of scientists and their partners in industry had already invested years in laying the groundwork.