Results 101 to 110 of about 307,150 (219)

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Integrated Single‐Cell and Spatial Analysis Reveals a Metabolic‐Immune Axis Driving Aortic Dissection

Advanced Science, EarlyView.
Single‐cell and spatial profiling of 110 human thoracic aortic samples reveals a stromal–immune circuit driving aortic dissection. An elastin‐rich fibroblast subset is depleted with age and markedly reduced in disease, weakening aortic wall integrity.
Jing Tao, Huanjie Yang, Jiahui Yong, Xueting Chen, Qiang Zhao, Xueli Wu, Lei Yan, Li Pang, Fan Luo, Mengjun Yu, Shanshan Pan, Deyang Li, Rouxi Chen, Juan Wang, Zhensheng Dong, Fan Yang, Yue Wang, Yang Chen, Hongjian Zheng, Zhimin Yang, Zijie Wang, Karsten Kristiansen, Hui Peng, Xiaodong Fang, Juan Shen, Yining Yang   +25 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

Multiple data set Bayesian analysis synergistically boosts ITC parameter precision. [PDF]

Biophys J
Otten L, Walker DR, Barbar EJ, Zuckerman DM.   +3 more
europepmc   +1 more source

A Data‐Driven Inverse Design Methodology for Magnetic Soft Millirobots Navigating in Confined Spaces

Advanced Science, EarlyView.
A data‐efficient inverse design framework automates the optimization of magnetic soft millirobots for confined‐space navigation. Integrating a physics‐based Cosserat rod model with Bayesian optimization efficiently identifies high‐performance geometries.
Ziyu Ren, Hong Wang, Chak Wang Tse, Yi Zheng, Xi Chen, Wenqi Hu   +5 more
wiley   +1 more source

Inferring genetic relationship among haplomes in Triticeae: The utility of the 5S DNA units with examples

Czech Journal of Genetics and Plant Breeding, 2005
B.R. Baum
doaj   +1 more source

Understanding the Catalytic Determinant role of Diaphorase‐Like Subunit in Formate Dehydrogenases via Redox Couples

Advanced Science, EarlyView.
A unique mechanism of catalytic bias regulated by diaphorase‐like subunit in formate dehydrogenase from Rhodobacter aestuarii is revealed. The diaphorase‐like subunit functions act as a biological “voltage rheostat” that controls the slow release of NADH to regulate redox balance, biasing the enzyme's catalytic preference toward CO2 reduction over ...
Kuncheng Zhang, Weisong Liu, Hao Su, Huijuan Cui, Yuanming Wang, Zhiguang Zhu, Chun You, Lingling Zhang   +7 more
wiley   +1 more source

The Association of Nocturia and Major Cardiovascular Events: A Bayesian Analysis. [PDF]

Urogynecology (Phila)
Sinha A, Arrington J, Bashi A, Greene SJ, Jelovsek JE, Amundsen CL.   +5 more
europepmc   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source