Results 141 to 150 of about 6,816 (264)

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

open access: yesAdvanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena   +3 more
wiley   +1 more source

Material Before Morphology: Substrate‐Dependent Mechanical Tuning of Radular Teeth

open access: yesAdvanced Materials Interfaces, EarlyView.
Substrate‐dependent material tuning in Clausilia radular teeth. Closely related taxa retain a conserved gross tooth morphology, but differ in elemental composition and mechanical properties according to feeding substrate. Rock‐associated taxa show increased Ca–Si enrichment and higher stiffness and hardness, especially in the central radular region ...
Ida Lilienthal   +3 more
wiley   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

open access: yesAdvanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

DRIVE‐SAFE: Data‐Driven Robustness and Informed Validation for Evolving Specifications via Formal Evaluation

open access: yesAdvanced Robotics Research, EarlyView.
DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano   +3 more
wiley   +1 more source

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

open access: yesAdvanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu   +7 more
wiley   +1 more source

Impact of an educational intervention model on pesticide practices among farmers: a randomized controlled trial protocol. [PDF]

open access: yesBMC Public Health
Tejashree MU   +6 more
europepmc   +1 more source

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