Results 121 to 130 of about 1,331 (215)

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

stMixer for Scalable Mosaic Integration and Label Transfer in Spatial Histology and Multi‐Omics

Advanced Science, EarlyView.
stMixer is an unsupervised framework for scalable integration and label transfer across spatial histology and multi‐slide multi‐omics data with incomplete modality overlap. It combines self‐looped cross‐attention, multimodal metric learning, and graph‐guided cluster voting to align heterogeneous sections, correct batch effects, and propagate ...
Qixing Yang, Yan Wang, Luonan Chen, Chunman Zuo   +3 more
wiley   +1 more source

Femtosecond‐Laser‐Induced Physical Unclonable Random Maze Structure for Storage‐Free Encryption

Advanced Science, EarlyView.
Femtosecond‐laser‐induced gold random maze structures serve as multimodal physical unclonable functions for storage‐free encryption. Their stochastic optical, electrical, and Raman responses are generated by plasmon‐assisted Marangoni formation and converted into AES‐compatible keys without permanent secret‐key storage, offering a portable route toward
Shiru Jiang, Hongliang Li, Shengjie Ma, Sang‐Shin Lee, Lei Wang, Mengyun Hu, Heping Zeng   +6 more
wiley   +1 more source

Discriminator‐Guided Inverse Folding for Multi‐Property Protein Design

Advanced Science, EarlyView.
Discriminator‐Guided Inverse Folding (DGIF) integrates multiple property predictors trained from single‐property datasets to guide protein sequence generation from a backbone structure. DGIF enables simultaneous improvement of thermostability and solubility without requiring multi‐property annotated datasets and generates designs that move toward the ...
Yuchuan Zheng, Chuyi Liu, Zhaoming Liu, Mao Su, Chenyu Tang, Xiang Zheng, Hao Zhang, Jingyuan Li   +7 more
wiley   +1 more source

Large Language Model‐Informed Dual‐Track AI Framework for the Synergistic Design of Crack‐Free and High‐Strength Superalloys

Advanced Science, EarlyView.
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao, Junkang Wu, Jie Su, Fuzhu Wang, Zi Wang, Li Wang, Liming Tan, Lan Huang, Feng Liu, Yong Liu   +9 more
wiley   +1 more source

Nanopore‐Based Protein Deceleration and Sensing Using Graphene/Si3N4 Dual Membrane Cavity

Advanced Science, EarlyView.
A graphene/Si3N4 dual membrane cavity system achieves multi‐stage protein deceleration through spatial geometry. Multi‐level current traces provide high‐resolution spatial localization and early warning signals. ABSTRACT Sequencing of protein with nanopores has emerged as a powerful tool offering rapid readout, high accuracy, low cost, and portability.
Yubin Cao, Junzhou He, Wei Si
wiley   +1 more source

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

SPADE: A Deep Learning Framework for Spatial Mapping and Quantitative Cell–Cell Interaction Inference

Advanced Science, EarlyView.
SPADE integrates spatial transcriptomics with single‐cell RNA sequencing by using cell–cell communications (CCC) as a guide for spatial mapping. It improves cell‐type localization, enhances sparse gene‐expression signals, and reveals CCC programs at single‐spot resolution.
Xinyi Li, Ning Zhang, Zijie Jin
wiley   +1 more source

A Single‐Cell Transcriptomic Atlas of the Ovine Rumen Microbiome Characterizes Lineage‐Specific Metabolic Shifts Associated with Host Heat Tolerance

Advanced Science, EarlyView.
An optimized single‐cell transcriptomic framework profiles over 60 000 cells to map the ovine rumen microbiome, partitioning the ecosystem into seven cross‐species functional clusters. In heat‐resistant hosts, a lineage‐specific metabolic shift in Anaerovibrio lipolyticus toward a highly glycolytic phenotype contributes to a “nutritional sparing ...
Sanbao Zhang, Qinyang Jiang, Junjie Ma, Jianwei Zou, Fan Wang, Feifei Lv, Yanna Huang, Yongcheng Wang, Ziye Xu   +8 more
wiley   +1 more source

Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors

Advanced Science, EarlyView.
Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu, Fumiaki Iwane, Minsu Zhang, Leonardo G. Cohen, José del R. Millán   +4 more
wiley   +1 more source