Results 41 to 50 of about 2,497 (173)

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

Advanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong, Xueru Zheng, Xiao Zhou, Zhengheng Tao, Wan Han, Jingyi Pan, Dian Wu, Ning Gao, Lei Liu, Zhongyang Wang, Fanchao Meng, Tongxiang Fan   +11 more
wiley   +1 more source

A Dual‐Modal Wearable PPG Smartwatch with AI‐Enhanced Correction for High‐Accuracy and Continuous AF Burden Assessment

Advanced Science, EarlyView.
ABSTRACT Atrial fibrillation (AF) increases the risk of stroke and heart failure, yet accurate quantification of AF burden in daily life remains difficult. Although smartwatch photoplethysmography (PPG) supports continuous monitoring, complex rhythms and signal noise can impair burden estimation.
Song Zuo, Jinglei Wang, Xin Wang, Han Feng, Yize Zhao, Fadong Li, Shaobin Wei, Le Zhou, Zixu Zhao, Songjie Chen, Xiangyi Kong, Jue Wang, Liu He, Shijun Xia, Xin Li, Junmeng Zhang, Xiaoxia Liu, Xueyuan Guo, Ning Zhou, Songnan Li, Chenxi Jiang, Ribo Tang, Caihua Sang, Deyong Long, Xin Du, Jianzeng Dong, Wenwu Zhu, Changsheng Ma   +27 more
wiley   +1 more source

Hypomethylation of GNA15 Promotes Pancreatic Ductal Adenocarcinoma Progression and Macrophage M2 Polarization via STAT3‐CXCL8 Axis

Advanced Science, EarlyView.
A schematic model summarizing GNA15's mechanism in mediating macrophage M2 polarization and Gemcitabine resistance. ABSTRACT The complexity of pancreatic ductal adenocarcinoma (PDAC) progression, coupled with the lack of effective immunotherapy, underscores the imperative to deepen our understanding of its mechanisms and identify suitable immune ...
Weihui Guo, Zhenyuan Qian, Lei Wang, Weilang Xu, Yuxin Weng, Kai Jiang, Zaiyuan Ye, Ji Xu, Guangyuan Song   +8 more
wiley   +1 more source

Single‐Cell Profiling Reveals a Protective WNT5A‐ATF3‐FOSB Signaling Axis in Hair Follicle Stem Cells During Androgenetic Alopecia

Advanced Science, EarlyView.
Androgenetic alopecia (AGA) is a common form of hair loss with limited treatment options. Silencing of WNT5A signaling, which is widely known as the trigger of the ncWNT signaling pathway, happens in hair follicle stem cells from balding areas. It leads to downregulation of ATF3 and its target FOSB.
Ruiyu Luo, Ke Fang, Changjiang Zhao, Jiachao Xiong, Yuan Zhu, Mingyang Lu, He Yan, Zihan Li, Baojin Wu, Hua Jiang, Yufei Li   +10 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

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Disorder‐Driven Ionic Mobility Edge and Localization‐Driven Dendrite Formation in Solid Electrolytes

Advanced Energy Materials, EarlyView.
Migration‐barrier disorder localizes ionic transport into a sparse percolation backbone. Current and electric‐field focusing at filament tips promote fractal dendrite growth and suppress the critical current density according to jcrit = j0 exp(−σEeff/kBT).
Dongwook Lee, Jiwon Seo
wiley   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source