Results 171 to 180 of about 387,064 (296)

SAGE: Spatially Aware Gene Selection and Dual‐View Embedding Fusion for Domain Identification in Spatial Transcriptomics

Advanced Science, EarlyView.
SAGE is a unified framework for spatial domain identification in spatial transcriptomics that jointly models tissue architecture and gene programs. Topic‐driven gene selection (NMF plus classifier‐based scoring) highlights spatially informative genes, while dual‐view graph embedding fuses local expression and non‐local functional relations.
Yi He, Yunpei Xu, Liqing Ding, Hong‐Dong Li, Yaohang Li, Shaokai Wang   +5 more
wiley   +1 more source

Transcription Factor Promiscuity Drives Regulatory Rewiring and Evolvability in Gene Networks in Bacteria

Advanced Science, EarlyView.
ABSTRACT This special issue marking the University of Bath's 60th anniversary offers an opportunity to reflect on nearly a decade of research into the evolution of gene regulatory networks (GRNs) from members of the lab and elsewhere. Our goal is to understand how GRNs rewire and how new transcription factor (TF) functions evolve. Using an experimental
Tiffany B. Taylor, Alan M. Rice
wiley   +1 more source

Hierarchical Reinforcement Learning for Fair Operating Room Scheduling in Plastic Surgery. [PDF]

Plast Reconstr Surg Glob Open
Wallner C, Puscz F, Schmidt SV, Reinkemeier F, Lehnhardt M, Drysch M.   +5 more
europepmc   +1 more source

3D‐Printed Ion‐Conductive Hydrogels with Tunable Mechanical–Electrical Properties for Multimodal Sign Language Recognition

Advanced Science, EarlyView.
This work successfully fabricated ion‐conductive hydrogels with low hysteresis and high conductivity using 3D printing technology. By adjusting the component ratios, the properties of the hydrogels can be tuned to meet diverse sensing requirements. Finally, a multimodal sensing sign language recognition system was constructed based on this hydrogel ...
Quan Hu, Longya Xiao, Peiqi Zhang, Qiurui Zhang, Guangsen Liu, Xinglin Qin, Zhuhui Yin, Xian Li, Yuling Wang, Hongjie Jiang   +9 more
wiley   +1 more source

Beyond Traditional RAFT Polymerization: Emerging Strategies and Future Perspectives; A Third Update

Advanced Science, EarlyView.
This review explores recent advances in the past five years for non‐traditional RAFT polymerization, focusing on new activation strategies, sustainable depolymerization, and integration with automated and AI‐driven synthesis. Together, these innovations advance polymer chemistry and reveal how the pieces of the non‐traditional RAFT puzzle are steadily ...
Vianna F. Jafari, James L. Grace, Jiajia Li, Joji Tanaka, Glen R. Jones, Athina Anastasaki, Wei You, Jian Zhu, Masami Kamigaito, Cyrille Boyer, Greg G. Qiao   +10 more
wiley   +1 more source

Disease Diagnosis On Ships Using Hierarchical Reinforcement Learning [PDF]

Annals of computer science and information systems
Farwa Batool, Tehreem Hasan, Giancarlo Tretola, Zaib Ullah, Musarat Abbas   +4 more
doaj   +1 more source

Computing power network dynamic resource scheduling integrating time series mixing dynamic state estimation and hierarchical reinforcement learning. [PDF]

Sci Rep
Liu H, Zhang S, Li L, Sun T, Xue W, Yao X, Xu Y.   +6 more
europepmc   +1 more source

Machine Learning Driven Window Blinds Inspired Porous Carbon‐Based Flake for Ultra‐Broadband Electromagnetic Wave Absorption

Advanced Science, EarlyView.
Inspired by the regulation mechanism of window blinds, this study designs an electromagnetic wave‐absorbing metamaterial. By introducing the magneto‐electric coupling concept and integrating it with an artificial intelligence‐based data‐driven collaborative optimization strategy, the material optimizes impedance matching performance and enhances loss ...
Zhe Wang, Wanchong Li, Lu Feng, Zaiqing Yang, Shicheng Jin, Dongxu Zhao, Xiaoyong Wu, Yan Wang, Yu Mao, Jinsong Zhang   +9 more
wiley   +1 more source

Chemotactic navigation in robotic swimmers via reset-free hierarchical reinforcement learning. [PDF]

Nat Commun
Xiong T, Liu Z, Wang Y, Ong CJ, Zhu L.
europepmc   +1 more source

Unsupervised Hierarchical Symbolic Regression for Interpretable Property Modeling in Complex Multi‐Variable Systems

Advanced Science, EarlyView.
UHSR translates complex chemical behavior into clear and explainable equations. Applied to thin‐layer chromatography, it automatically uncovers the mathematical rules linking a molecule's structure to its polarity. This approach matches the accuracy of advanced AI while providing interpretable results, earning greater trust from chemists. The method is
Siyu Lou, Chengchun Liu, Dongxiao Zhang, Yuntian Chen, Fanyang Mo   +4 more
wiley   +1 more source