Results 131 to 140 of about 3,448,461 (253)

Exploring Gray Matter Alterations in Post‐Stroke Patients: A Structural Covariance Analysis

Brain and Behavior
Background While structural covariance analysis is adept at assessing morphometric correlations among broadly distributed brain regions, limited research has focused on alterations in structural covariance networks post‐stroke.
Juan‐Juan Lu, Xiang‐Xin Xing, Jiao Qu, Jia‐Jia Wu, Jie Ma, Mou‐Xiong Zheng, Xu‐Yun Hua, Jian‐Guang Xu   +7 more
doaj   +1 more source

Metabolic Signatures for Liver Cancer Diagnosis and Mechanistic Insights: A Large‐Scale, Multicenter Study

Advanced Science, EarlyView.
A large‐scale multicenter serum metabolomics study (13 centers, n = 2,149) identified a 9‐metabolite + AFP diagnostic signature for liver cancer (AUC = 0.93). Among the signature, nicotinamide (NAM) was validated as an oncometabolite: NAM enhances NAD+ synthesis, activating SIRT1 to deacetylate and stabilize HIF1α, thereby driving glycolysis, MAPK ...
Yongjie Xu, Jiachen Wang, Chunmeng Ding, Changfa Xia, Yunyong Liu, Yuanjie Zheng, Sheng Chang, Shaokai Zhang, Yutong He, Ruifang Sun, Yunfeng Xi, Yan Liu, Kun Qian, Wanqing Chen   +13 more
wiley   +1 more source

Hardware Acceleration of Stochastic Neural Networks Enabled by Bit‐Cell Level Co‐Design of Magnetic Tunnel Junctions

Advanced Science, EarlyView.
An MTJ‐based probabilistic processing‐in‐memory architecture unites nonvolatile storage, local entropy generation, and stochastic computation within each memory cell. Stored multi‐bit weights are converted directly into programmable stochastic bitstreams, enabling neural‐network inference, adaptive Ising optimization, and uncertainty‐aware Bayesian ...
Qiuyuan Wang, Dooyong Koh, Brooke McGoldrick, Tudor Mocioi, Yabin Fan, Marc Baldo, Luqiao Liu   +6 more
wiley   +1 more source

Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models [PDF]

Estimating a covariance matrix efficiently and discovering its structure are important statistical problems with applications in many fields. This article takes a Bayesian approach to estimate the covariance matrix of Gaussian data.
Christopher K. Carter, Helen Armstrong, Robert Kohn, Kevin K. F. Wong   +3 more
core  

General covariance from the perspective of Noether's theorems [PDF]

, 2002
Analysis of Emmy Noether's 1918 theorems provides an illuminating method for testing the consequences of coordinate generality, and for exploring what else must be added to this requirement in order to give general covariance its far-reaching physical ...
Brading, Katherine, Brown, Harvey, Brading, Katherine A.   +2 more
core  

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

Advanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source

Controllable Superconductivity in Suspended NbSe2

Advanced Electronic Materials, EarlyView.
Suspended NbSe2${\rm NbSe}_2$ provides two complementary routes for controlling superconducting transport. Gate‐driven deformation strains the suspended crystal and tunes its critical temperature and current. Weak thermal anchoring enhances thermal feedback, contributing to multistep hysteresis and negative differential resistance.
Ruihuan Fang, Cuiju Yu, Youqiang Huang, Tosson Elalaily, Yuvraj Chaudhry, Yaoqiang Zhou, Andres Castellanos‐Gomez, Sanshui Xiao, Jiwon Park, Hyunyong Choi, Fida Ali, Hanlin Fang, Jose L. Lado, Pertti Hakonen, Zhipei Sun   +14 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

From Top to Bottom: Manufacturing Process‐Context Aware Resolution of Energy Device Electrodes Through a 3D Diffusion Generative Model

Advanced Energy Materials, EarlyView.
The application of a generative diffusion model, enhanced with a training data augmentation pipeline retaining the manufacturing process context of electrode microstructures, leads to improved fidelity of the through‐plane tortuosity factor in the AI generated samples.
Victor Ramirez‐Camacho, Siwar Ben Hadj Ali, Maxence Desnoyers, Francisco Fernandez, Nassima Benammar, Alejandro A. Franco   +5 more
wiley   +1 more source

Descriptor‐Guided Computational Screening of Non‐Fullerene Acceptor Cores for Organic Solar Cells

Advanced Energy Materials, EarlyView.
We screen over 4000 non‐fullerene acceptors using their ionization energy, electron affinity, quadrupole, and dipole moments to select the top‐ten candidates for a given donor polymer. The workflow recovers known high‐performance motifs and reveals how molecular components influence material properties.
Kun‐Han Lin, J. Terence Blaskovits, Wenlan Liu, Shu‐Yi Hu, Kuei‐Jhong Lin, Sandeep Sharma, Julien Gorenflot, Martin Heeney, Frédéric Laquai, Denis Andrienko   +9 more
wiley   +1 more source