A neural network‐enabled permittivity engineering paradigm is introduced, transcending traditional trial‐and‐error design. By decoupling electromagnetic parameters and screening a high‐throughput feature space, an ultrathin (1.0 mm) magnetic absorber is inversely designed, experimentally achieving a superior and customizable 5.1 GHz bandwidth and ...
Chenxi Liu +9 more
wiley +1 more source
Unsupervised learning of spatially varying regularization for diffeomorphic image registration. [PDF]
Chen J +7 more
europepmc +1 more source
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen +9 more
wiley +1 more source
Exploiting the Kumaraswamy distribution in a reinforcement learning context. [PDF]
Picchi D, Brell-Çokcan S.
europepmc +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
Adaptive demand forecasting framework with weighted ensemble of regression and machine learning models along life cycle variability. [PDF]
Hammam IM, El-Kharbotly AK, Sadek YM.
europepmc +1 more source
How AI Shapes the Future Landscape of Sustainable Building Design With Climate Change Challenges?
This review examines how artificial intelligence reshapes sustainable building design faced with climate change challenges. The authors synthesize existing studies to demonstrate AI's transformative potential across design lifecycle phases from climate‐aware form generation to performance optimization.
Pengyuan Shen +5 more
wiley +1 more source
Chiller sensor fault diagnosis based on circle mapping and adaptive t-distribution Runge-Kutta algorithm optimized LSTM. [PDF]
Wang Y, Liu J, Liu F, Duan X.
europepmc +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Quantitative Elemental Oxides Analysis of Rock Cuttings Using Laser-Induced Breakdown Spectroscopy Coupled with Bayesian Optimization and Support Vector Machine. [PDF]
Abu Alsaud S, Swanson A.
europepmc +1 more source

