The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research such as drug design and energy storage. However, the lack of a ...

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Understanding the quantum universe is not an easy thing. Intuitive notions of space and time break down in the tiny realm of subatomic physics, allowing for behavior that seems, to our macro ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

As part of "shift left" to incorporate security discussions earlier in the software development life cycle, organizations are beginning to look at threat modeling to identify security flaws in ...

DETROIT ARSENAL—The Center for Army Analysis has given two of its prestigious Modeling & Simulation awards to the U.S. Army DEVCOM Ground Vehicle Systems Center. Both awards, in the team category—one ...