Results 91 to 100 of about 4,582 (213)

Comparison of statistical approaches for analyzing incomplete longitudinal patient-reported outcome data in randomized controlled trials

Patient Related Outcome Measures, 2018
Ines Rombach,1,2 Crispin Jenkinson,3 Alastair M Gray,1 David W Murray,2 Oliver Rivero-Arias4 1Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK; 2Nuffield Department of Orthopaedics, Rheumatology
Rombach I, Jenkinson C, Gray AM, Murray DW, Rivero-Arias O   +4 more
doaj  

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

Association between hand grip strength and mortality: The North West, South Africa Prospective Urban Rural Epidemiology (PURE) study.

Epidemiology, Biostatistics and Public Health
Hand Grip Strength (HGS) is employed in epidemiological contexts to measure muscle strength because it’s inexpensive, easy to perform and interpret.
Kelebogile Motlhamme, Herculina S Kruger, Sarah J Moss, Marlien Pieters, Matteo C Malvezzi, Daniela Schmid, Carlo La Vecchia, Cristian Ricci   +7 more
doaj   +1 more source

Achieving High‐Density and Stress‐Resilient Maize Breeding Via Germplasm Innovation

Advanced Science, EarlyView.
Global population growth and climate change have exacerbated the global food crisis. This perspective presents a conceptual framework focusing on enhancing population advantages. Several novel breeding objectives are proposed to improve density tolerance and stress resistance for yield improvement.
Xinlong Li, Yongqiang Chen, Dong Ding, Xuehai Zhang, Xuxiang Jia, Zhanhui Zhang, Yafei Wang, Weihua Li, Hui Zhang, Jihua Tang   +9 more
wiley   +1 more source

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

Advanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao, Yiming Ma, Baihao Shao, Molly M. Stevens   +3 more
wiley   +1 more source

Chitosan‐Carbon Dot Composite Materials Form a Leaf Surface Barrier to Mitigate the Enrichment and Invasion of Nanoplastics: From Leaf Interface to Systemic Response

Advanced Science, EarlyView.
Foliar spraying of CS‐CDs can form a film on the leaves of Brassica rapa, effectively reducing the enrichment and absorption of PS in the leaves, while increasing the biomass and nutrient content of the plants. In addition, CS‐CDs can also enrich the interfoliar microbial community and activate the plant's own defense metabolic pathways.
Beibei Zhao, Mei Li, Mengjiao Fan, Chuanhuan Liu, Jie Jiang, Jia Song, Yingzhu Liu   +6 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Decoupling Intrinsic Molecular Efficacy From Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery

Advanced Science, EarlyView.
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang, Ziyuan Li, Shan Gao, Zhen Zhu, Jing Wang, Xiangmei Duan   +5 more
wiley   +1 more source

GreenMix-pareto: Uncertainty-aware, physics-guided multi-objective optimization of low-carbon concrete mix designs

Ain Shams Engineering Journal
Concrete mix design increasingly requires balancing mechanical performance with climate and resource impacts. Most existing data-driven studies either optimize a single target (often strength) or report point predictions without calibrated uncertainty ...
Tarek Salem Abdennaji, Amel Ksibi, Aymen Flah, Vandna Batra, Rupesh Kumar Tipu   +4 more
doaj   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source