Results 211 to 220 of about 48,518 (327)

INB3P: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

open access: yesAdvanced Science, EarlyView.
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv   +11 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
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

Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring

open access: yesAdvanced Science, EarlyView.
This study presents a semantic representation framework for clinically interpretable cardiac monitoring from contactless radio signals. It formulates radio semantic learning as an information‐bottleneck problem and approximates the objective via intra‐modal compression and cross‐modal alignment, structuring radio measurements into meaningful semantic ...
Jinbo Chen   +10 more
wiley   +1 more source

MGDP: Mastering a Generalized Depth Perception Model for Quadruped Locomotion

open access: yesAdvanced Science, EarlyView.
ABSTRACT Perception‐based Deep Reinforcement Learning (DRL) controllers demonstrate impressive performance on challenging terrains. However, existing controllers still face core limitations, struggling to achieve both terrain generality and platform transferability, and are constrained by high computational overhead and sensitivity to sensor noise.
Yinzhao Dong   +9 more
wiley   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

open access: yesAdvanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue   +6 more
wiley   +1 more source

Two‐Dimensional Triferroics: From Fundamental Couplings to Multifunctional Applications

open access: yesAdvanced Science, EarlyView.
This graphic summarizes the three main types of currently reported 2D triferroic couplings. From the structural perspective, existing systems can be broadly classified into two categories, which exhibit distinct symmetry features and coupling behaviors. Beyond the lattice difference, a third type involves the interplay among ferroelectricity, magnetism,
Yang Li, Jialin Gong, Zhiqing Li
wiley   +1 more source

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