Results 141 to 150 of about 6,372,670 (283)

Deep‐Learning‐Based Denoising for Improved Phase Precision in Electron Holography of Electromagnetic Fields in Nanoscale Materials

Advanced Science, EarlyView.
Low‐dose electron holography is limited by shot noise, which buries weak phase signals. HoloDenoiser, a physics‐informed network that works simultaneously in the spatial and frequency domains, locates and protects the holographic sideband while suppressing noise in the hologram.
Ye Luo, Luyang Wang, Zhiling Yu, Xiaowen Chen, Xiaoyu Wang, Ya‐Hui Jia, Thibaud Denneulin, Yu Han, Rafal E. Dunin‐Borkowski, Fengshan Zheng, Qi Liu   +10 more
wiley   +1 more source

MethyAnno: An Interpretable Automated Annotation Method Leveraging Multi‐Scale Information and Metric Learning Framework for scDNAm Data

Advanced Science, EarlyView.
MethyAnno enables robust and interpretable annotation of single‐cell DNA methylation data by integrating multi‐scale epigenetic information, bidirectional cross‐attention, and prototype‐based metric learning. The framework resolves rare and novel cell types across datasets while revealing cell‐type‐specific epigenetic signatures associated with disease
Yuhang Jia, Siyu Li, Songming Tang, Keju Gu, Shengquan Chen   +4 more
wiley   +1 more source

Temporal Trajectories of the Tau Aggregate Interactome Reveal Stage‐Specific Vulnerabilities in Alzheimer's Disease

Advanced Science, EarlyView.
Tau populations with different aggregation states associate with distinct sets of proteins in the Alzheimer's disease brain. Proteomic discovery combined with single‐molecule analysis in neurons reveals dynamic associations involving proteostasis, metabolism and RNA biology.
Dorothea Böken, Paula Beltran Lobo, Yunzhao Wu, Lyla A. Rowe, Emre Fertan, Cara L. Croft, Maria Jimenez‐Sanchez, Dezerae Cox, David Klenerman   +8 more
wiley   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Combinatorial Survey of Structural Phase Distribution and Magnetism in Fe‐Ge‐Te Composition‐Spread Thin Film Libraries

Advanced Electronic Materials, EarlyView.
ABSTRACT Magnetic 2‐dimensional (2D) van der Waals (vdW) materials have garnered tremendous attention. The vdW ferromagnet Fe5Ge1Te2 has a Curie temperature Tc of ≈ 270 K, which is tailorable by tuning the stoichiometry and the Fe deficiency to reach room temperature.
Chih‐Yu Lee, Takahiro Yamazaki, Peng Yan, Ryan Kim, Masato Kotsugi, Efrain E. Rodriguez, Joseph W. Bennett, Ichiro Takeuchi   +7 more
wiley   +1 more source

Behavioral Coping With Food Price Inflation: Patterns Among U.S. Households

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Recent food price inflation has placed substantial pressure on household budgets, food security, and mental well‐being. Using Household Pulse Survey data, we combine k‐modes clustering and Double Machine Learning to identify distinct household coping groups and examine differences in how households respond to rising food prices across groups ...
Yuxiang Zhang, Yizao Liu
wiley   +1 more source

Import Wheat Tenders and the Effects of the Russian Invasion

Agribusiness, EarlyView.
ABSTRACT Risk and volatility for many commodities escalated sharply following the Russian invasion of Ukraine, creating numerous uncertainties for trading firms and importers. The purpose of this study is to analyze the bidding behavior in Egyptian wheat import tenders in the pre‐ and post‐invasion periods.
William W. Wilson, Sumadhur Shakya, Isaac Dubovoy   +2 more
wiley   +1 more source

Mapping Alzheimer's disease heterogeneity through exploratory unsupervised learning. [PDF]

Front Aging Neurosci
Xavier C, Correia AP, Lopes J, Fernandes J, Laranjinha I, Pinto N.   +5 more
europepmc   +1 more source

Learning regime‐dependent governing equations: A symbolic decision tree approach

AIChE Journal, EarlyView.
Abstract Many chemical engineering systems are governed by mechanisms that switch across operating regimes, making the data‐driven discovery of regime‐dependent governing equations essential for predictive modeling, optimization, and control. We propose symbolic decision trees for the data‐driven discovery of regime‐dependent governing equations.
Ilias Mitrai, Tongjia Liu, Gabriel E. Sanoja   +2 more
wiley   +1 more source

A Novel Unsupervised Learning Model with Bayesian Hyperparameter Optimization for Predicting Substrates of Promiscuous Enzymes. [PDF]

ACS Omega
Gao R, Duan C, Qin N, Liu Y, Liu K, Tsuboi T, Chen Z.   +6 more
europepmc   +1 more source