Results 171 to 180 of about 155,905 (328)

The Challenge of Handling Structured Missingness in Integrated Data Sources

Advanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra   +6 more
wiley   +1 more source

ChatCFD: A Large Language Model‐Driven Agent for End‐to‐End Computational Fluid Dynamics Automation with Structured Knowledge and Reasoning

Advanced Intelligent Discovery, EarlyView.
Chat computational fluid dynamics (CFD) introduces an large language model (LLM)‐driven agent that automates OpenFOAM simulations end‐to‐end, attaining 82.1% execution success and 68.12% physical fidelity across 315 benchmarks—far surpassing prior systems.
E Fan, Kang Hu, Zhuowen Wu, Jiangyang Ge, Jiawei Miao, Yuzhi Zhang, He Sun, Weizong Wang, Tianhan Zhang   +8 more
wiley   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Climate change, marginalised communities and considered debate within Scotland’s climate emergency

, 2020
Climate Change amp Marginalised Communities Workshop Contributors
openalex   +2 more sources

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Language, listening and learning:critically reflective accountability for INGOs [PDF]

, 2013
Crack, Angela Maria
core   +1 more source

Seeds of change: The impact of Ethiopia's direct seed marketing approach on smallholders' seed purchases and productivity

American Journal of Agricultural Economics, EarlyView.
Abstract While multiple factors explain low adoption rates of improved varieties by small‐scale farmers in sub‐Saharan Africa, a key supply‐side constraint is the limited availability of seed embodying new traits in the volume, quality, price, and timeliness required by farmers. This constraint is partly attributable to classical failures in the market
Dawit Mekonnen, Gashaw T. Abate, Seid Yimam, Rui Benfica, David J. Spielman, Frank Place   +5 more
wiley   +1 more source

Understanding mental health and psychosocial support needs among marginalised communities in Uganda. [PDF]

BMC Public Health
Muwanguzi P, Nabunya R, Lugoloire H, Nalubega SJ.   +3 more
europepmc   +1 more source

How does the Kids SIPsmartER program impact the sugar‐sweetened beverage intake of students: An investigation beyond total treatment effect in randomized controlled trial

American Journal of Agricultural Economics, EarlyView.
Abstract This study develops and empirically estimates a structural framework to decompose the causal pathways of multilevel behavioral interventions targeting adolescent health behaviors. We apply this framework to the Kids SIPsmartER (KSS) program, a 6‐month, school‐based intervention evaluated through a clustered randomized controlled trial in rural
Naveen Abedin, Wen You, Annie Reid, Kathleen Porter, Brittany Kirkpatrick, Jamie Zoellner   +5 more
wiley   +1 more source