Results 141 to 150 of about 5,376 (222)

Machine Learning‐Driven Prediction of Microplastic Aging Processes and Environmental Risk Assessment Across Multi‐Media Systems

open access: yesAdvanced Science, EarlyView.
This perspective proposes a cohesive machine learning strategy to decode microplastic aging. It advocates for Federated Learning to dismantle global data silos and introduces the TRACE framework (TRansport, Aging, Corona, Ecotoxicity). By integrating physics‐informed modeling with causal discovery, this approach bridges the laboratory‐field gap to ...
Yaping Lyu   +6 more
wiley   +1 more source

Academic program recommendations for graduate degrees in medical physics: AAPM Report No. 365 (Revision of Report No. 197). [PDF]

open access: yesJ Appl Clin Med Phys, 2022
Burmeister JW   +19 more
europepmc   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

open access: yesAdvanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram   +4 more
wiley   +1 more source

Electromagnetic Radiation Stimulated Learning in Perovskite Nickelates

open access: yesAdvanced Science, EarlyView.
ABSTRACT Biological plasticity refers to the ability of synapses to strengthen or weaken over time. These adaptive properties play a fundamental role in learning and memory, spanning many orders of magnitude in timescales. Short‐term plasticity (STP) arises from rapid correlative activity, while long‐term plasticity (LTP) is governed by slower ...
Ranjan Kumar Patel   +8 more
wiley   +1 more source

AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling

open access: yesAdvanced Science, EarlyView.
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy