Results 41 to 50 of about 31,305 (267)

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Predicting Key Properties of 5-Fluorouracil Anticancer Drug Carrier Nanocomposites Using Machine Learning: A Multi-Objective Approach [PDF]

مجله دانشگاه علوم پزشکی خراسان شمالی
Introduction: The drug 5-fluorouracil is commonly used in cancer treatment, but its clinical effectiveness is limited due to systemic toxicity, a short half-life, and insufficient tumor tissue uptake.
Abbas Rahdar, Maryam Shirzad, Mehrab Pourmadadi   +2 more
doaj  

Application of Machine Learning Algorithms in Predicting Major Adverse Cardiovascular Events after Percutaneous Coronary Intervention in Patients with New-Onset ST-Segment Elevation Myocardial Infarction

Reviews in Cardiovascular Medicine
Background: This study aimed to develop and validate a predictive model for major adverse cardiovascular events (MACE) following percutaneous coronary intervention (PCI) in patients with new-onset ST-segment elevation myocardial ...
Min Chen, Cuiling Sun, Li Yang, Ting Zhang, Jing Zhang, Chunli Chen   +5 more
doaj   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +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

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

Advanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang, Zexi Chen, Yuanxiang Miao, Zuolin Shen, Deyu Cai, Shijie Tang, Yun Xue, Weifeng Guo, Hongbin Ji, Jian Liu, Kazuyuki Aihara, Luonan Chen   +11 more
wiley   +1 more source

SHAP Analysis of Teacher Job Satisfaction: Evidence from Korea Using PISA 2022 Data

KEDI Journal of Educational Policy
Teacher job satisfaction is a key concept for understanding teacher retention, instructional quality, and school organizational stability. However, much of the existing literature relies on linear analytical frameworks, often overlooking the complex and ...
Jeongwoo Park
doaj   +1 more source

SHAP Parameter Sensitivity Analysis of Rock Mechanics Parameters

International Journal of Computer Science and Information Technology
Accurate determination of the rock mass's mechanical parameters directly affects engineering projects' safety and cost-effectiveness. Based on an extensive literature review, a dataset containing 318 sets of rock mass parameters is compiled to support our research.
Lei Dong, Longfei Wang
openaire   +1 more source

Advancing the Design of High‐Efficiency Printable Hole‐Conductor‐Free Mesoscopic Perovskite Solar Cells Through Machine Learning

Advanced Science, EarlyView.
Based on the largest printable mesoscopic perovskite solar cells database we established, stacking model achieved precise PCE prediction (R2 = 0.73, MAE = 2.18%). Multiple experiments verified the accuracy of the model, which guided the fabrication of high‐PCE devices with an efficiency of 19.36%.
Hao Meng, Jingzi Zhang, Xu Zhu, Yuelin Wang, Antai Yang, Kailong Hu, Chengquan Zhong, Jiakai Liu, Menghan Dun, Xi Lin   +9 more
wiley   +1 more source

Differentiated impacts of urban streetscapes on green mobility experiences

Journal of Asian Architecture and Building Engineering
Against the backdrop of accelerating urbanization and the growing emphasis on healthy city development, understanding the differentiated impacts of street spatial environments on human mobility and their perceived friendliness is essential for ...
Wangyao Jiang, Qingqing Li, Junjie Li, Zunling Zhu   +3 more
doaj   +1 more source