A new deep-learning model, AngleNet, significantly improves the retrieval accuracy of atmospheric relative humidity (RH) profiles from ground-based microwave radiometers (MWRs).

Could a simple blood test reveal how well someone is aging? A team of researchers led by Wolfram Weckwerth from the University of Vienna, Austria, and Nankai University, China, has combined advanced metabolomics with cutting-edge machine learning and a novel network modeling tool to uncover the key molecular processes underlying active aging. Their study, published in the Nature Journal npj Systems Biology and Applications, identifies aspartate as a dominant biomarker of physical fitness and maps the dynamic interactions that support healthier aging.

By combining physics-based methods with machine learning, a team at the Institute of Thermodynamics and Sustainable Propulsion Systems at TU Graz is developing models that deliver better results despite less training data.

Big Yao, Dan Doulet Early Career Assistant Professor in the Department of Industrial and Systems Engineering at the University of Tennessee, Knoxville, is part of a research team developing a physics-informed machine learning system to personalize atrial fibrillation (AF) ablation procedures. Their 3D heart simulation model predicts electrical signal spread, optimizing sequential treatments and improving clinical relevance through collaboration with medical professionals, aiming for better outcomes in AF patients.

In two recent studies, University of Texas at Dallas researchers demonstrated how artificial intelligence (AI) and machine learning can be used to address a variety of issues from a social science policy perspective.

Researchers with the Department of Energy’s Oak Ridge National Laboratory and the University of Tennessee, Knoxville, have created an innovative method to visualize and analyze atomic structures within specially designed, ultrathin bilayer 2D materials. When precisely aligned at an angle, these materials exhibit unique properties that could lead to advancements in quantum computing, superconductors and ultraefficient electronics.