We developed methods to characterize soft contractile actuators using force–displacement measurements in the passive state and the total force in the active state and define the operational range of thermal, electrothermal, and pneumatic muscles. A graphical method enables the selection of an actuator based on the required mechanical force–displacement
Qiong Wang +5 more
wiley +1 more source
Proto-Biosignatures and Planetary Geochemical Metabolism: A Thermodynamic Screening Model of Prebiotic Geochemical Organization. [PDF]
Spoto SE.
europepmc +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
Behaviorally Adaptive and Inclusive Advanced Driver‐Assistance Systems
Advanced driver‐assistance systems (ADASs) are mapped as evolving human‐centered, adaptive technologies linking sensing, driver monitoring, AR/HUD interfaces, patents, regulation, and inclusive design. The review identifies gaps in real‐world evidence, diverse‐driver validation, gaze metrics, and governance, outlining a roadmap for safer, behaviorally ...
Jana Skirnewskaja +2 more
wiley +1 more source
Video-based hand gesture recognition via SPD manifold spatial representation and optical flow motion features. [PDF]
Bai Z +6 more
europepmc +1 more source
Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley +1 more source
Efficient and interpretable maximal frequent fuzzy pattern mining with multi phase pruning and ternary search. [PDF]
Al-Wagih K, Abdullah MA, Senan EM.
europepmc +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Abstract Germany's Renewable Energy Sources Act (REA), enacted in 2000 and subsequently amended, subsidized national renewable energy production with fixed feed‐in tariffs for renewable energy sources (RE) from wind, solar, and biogas. Empirical studies suggest that the policy was creating windfall effects for landowners and attribute farmland use ...
Lars Isenhardt +6 more
wiley +1 more source
Distribution-informed machine learning for flash flood susceptibility: integrating weibull extreme value theory with interpretable models. [PDF]
Chishtie FA +4 more
europepmc +1 more source

