Results 61 to 70 of about 123,697 (193)

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

From Cell‐Free Transcriptomes to Single‐Cell Landscapes: Biomarker Discovery and Originating Cell Alteration Analysis via Graph Matrix Factorization

Advanced Science, EarlyView.
CellFreeGMF traces plasma cfRNA to likely originating cell types by integrating single‐cell atlases with graph‐regularized matrix factorization. The method decomposes cfRNA profiles into sample–cell contributions to reconstruct pseudo single‐cell expression.
Wenxiang Zhang, Wenjing Zhang, Hang Wei, Shiyan Liu, Junliang Shang, Weijie Gong, Hanwen Cheng, Xiujuan Lei, Yuhui Kou, Baoguo Jiang   +9 more
wiley   +1 more source

Linking Plant Metabolomics with Fungal Functional Dynamics Reveals a Noncanonical S‐R‐C Adaptive Trajectory

Advanced Science, EarlyView.
Using field‐based holo‐omics, we demonstrate that developmental shifts in sorghum leaf metabolomes drive a noncanonical fungal succession from stress tolerators (S) through ruderals (R) to competitors (C). Antifungal metabolites in young leaves select for S strategists with expanded genomes, transient maltose pulses during flowering favor fast‐growing ...
Peilin Chen, John W. Taylor, Cheng Gao
wiley   +1 more source

Decoding Structure‐Property Relationships in Anion Exchange Membranes via a Chemically Informed Dual‐Channel Graph Attention Network

Advanced Science, EarlyView.
SPARK decodes structure‐property relationships in anion exchange membranes (AEMs) via a chemically informed dual‐channel graph attention network (DEGAT) that explicitly captures microphase separation. It outputs five‐level grades for hydroxide conductivity and alkaline stability and highlights relevant key structural units, enabling robust pre ...
Wanting Chen, Ye Hu, Zijun Xiao, Deming Xia, Bo Pang, Xuemei Wu, Gaohong He   +6 more
wiley   +1 more source

Defect‐Functionalization‐Mediated Tunneling Drives Nonlinear Photoemission in Perovskites

Advanced Science, EarlyView.
This cover illustration depicts CsPbBr3 perovskite nanocrystals embedded with functionalized defect vacancies, where electrons migrate through defect‐mediated pathways and emit as lightning‐like beams. The imagery visualizes the core discovery of our work—defect‐functionalization‐mediated tunneling enabling nonlinear photoemission, where deep‐level ...
Hang Ren, Xi Zhang, Yicheng Wang, Shuai Wang, Zhi Wang, Yumeng Li, Jikai Yang, Xin Wang, Weijun Chen, Yining Mu   +9 more
wiley   +1 more source

Ultra‐Wide‐Field Noninvasive Imaging Through Scattering Media Via Physics‐Guided Deep Learning

Advanced Science, EarlyView.
We propose a physics‐guided adaptive dual‐domain learning method for ultra‐wide‐field noninvasive imaging through scattering media, namely UNI‐Net. Our method not only reduces the requirement for real experimental data by an order of magnitude but also enables clear imaging of complex scenes with an ultra‐large field of view, which is 164 times the OME
Lintao Peng, Mingwei He, Jeff Zhu, Sujit K. Sahoo, Liheng Bian, Cuong Dang   +5 more
wiley   +1 more source

Revisiting Target‐Aware de novo Molecular Generation with TarPass: Between Rational Design and Texas Sharpshooter

Advanced Science, EarlyView.
TarPass provides a rigorous benchmark for target‐aware de novo molecular generation by jointly evaluating protein‐ligand interactions, molecular plausibility, and drug‐likeness on 18 well‐studied targets. Results show that current models often fail to consistently surpass random baseline in target‐specific enrichment, while post hoc multi‐tier virtual ...
Rui Qin, Zijie Chen, Yurong Li, Meijing Fang, Longji Shen, Yilong Su, Odin Zhang, Qinghan Wang, Qun Su, Jike Wang, Tingjun Hou, Yu Kang   +11 more
wiley   +1 more source

Progress in Strain Engineering of 2D‐Integrated Heterostructures for Ultrasensitive Sensors

Advanced Science, EarlyView.
 . ABSTRACT Two‐dimensional (2D) integrated heterostructures have emerged as a cornerstone in the advancement of next‐generation sensor technologies. These heterostructures, which combine materials with different dimensionalities, have led to significant breakthroughs in sensing performance and device integration.
That Buu Ton, Tuan Sang Tran, Duc Khanh Tran, Van Thanh Dau, Dzung Viet Dao   +4 more
wiley   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

Advanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu, Rui Qiao, Ying Li, Junhong Li, Nuoya Yue, Jing Ge, Jiao Wang, Luonan Chen, Peiluan Li   +8 more
wiley   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

Advanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu, Shuli Sun, Zhengliang Lv, Xinyu Liu, Yihua Wang, Bingqiang Liu   +5 more
wiley   +1 more source