Results 121 to 130 of about 2,764 (264)
Background: Generativity has been associated with resilience and life satisfaction in older age, including among lesbian, gay, bisexual, and transgender (LGBT+) older adults. Objective: To examine the psychometric properties of the Loyola Generativity
Tatiana Casado +4 more
doaj
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
There appears to be a mounting consciousness in academia that knowledge production and the scholarly dissemination of knowledge do not necessarily lead to general well-being or improvement in society. In this article we start with ourselves by initiating
Kathleen Pithouse-Morgan +1 more
doaj
Targeting Lilrb4a in Apolipoprotein E4 (APOE4)‐associated Alzheimer's disease (AD) reprograms microglia toward a beneficial, phagocytic state. Genetic deletion or antisense inhibition of Lilrb4a suppresses p‐SHP2/NF‐κB/STAT1 signaling, restores PPAR‐linked lipid and energy metabolism, and reduces amyloid plaque burden and cerebral amyloid angiopathy ...
Changxu Nie +12 more
wiley +1 more source
Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao +9 more
wiley +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu +5 more
wiley +1 more source
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei +7 more
wiley +1 more source

