Knowing variants of concern can spike rates of illness and death around the globe, scientists using the APS are concentrating efforts on mutations of the virus that causes COVID-19.
Creating a machine learning agent to ease interactions between participants in virtual and augmented reality environments —such as the metaverse— in order to help them achieve their goals and address conflict situations. This is the main objective of GuestXR, the European project under the coordination of professor Mel Slater, from the Faculty of Phycology and the Institute of Neurosciences of the University of Barcelona (UBNeuro).
There's a huge urgency worldwide to find new therapies that help patients with amyotrophic lateral sclerosis (ALS), that's why Deepti Lall, PhD, a project scientist in the Cedars-Sinai Board of Governors Regenerative Medicine Institute is looking beyond neurons to find possible new treatments for the deadly disease.
Through her research of Pennsylvania’s Marcellus Shale play, Kyung Jae Lee, an assistant professor of petroleum engineering at the University of Houston’s Cullen College of Engineering found that highly concentrated lithium was found in the produced water (water produced as a byproduct during the extraction of oil and natural gas) along with produced natural gas and oil.
- Energy Reports
Software technology from a University of Cincinnati Venture Lab-backed startup that focuses on records management and data analytics is helping law enforcement agencies more efficiently manage and share data to help solve crime.
A new control system shows promise in making millions of homes contributors to improved power grid operations, reaping cost and environmental benefits.
Pivotal discoveries at Argonne’s Advanced Photon Source make the world better every day. Here are six that help us, inspire us and add to the promise of a brighter tomorrow.
Anybody who gets an annual checkup knows that heart health is often at the top of the list, which is why measuring blood cholesterol, blood sugar, and blood pressure is important. These and other indicators, like family history, can help tell who’s at risk for problems like heart attacks and stroke down the road.
For the first time, a team of Idaho National Laboratory (INL) and University of Idaho researchers has successfully applied machine learning to characterizing the microstructure of metallic nuclear fuel, the fine details only visible under powerful magnification.
- Materials Characterization
- Department of Energy’s Office of Nuclear Energy