Results 131 to 140 of about 4,620,316 (300)

Machine learning driven many‐objective moving horizon scheduling optimization

AIChE Journal, EarlyView.
Abstract Industrial electrification can decarbonize chemical manufacturing, but it exposes operations to volatile electricity prices and carbon intensities. This work develops a machine learning‐enhanced many‐objective moving horizon scheduling framework that predicts objective correlation groupings from 48‐hour price and emission‐intensity profiles ...
Hongxuan Wang, Andrew Allman
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Pills, pluralism, risk and citizenship: Theorising e-pharmacies

, 2012
This article uses the theoretical concepts of risk, imagination and pharmaceutical citizenship to understand the growing popularity of e-pharmacies and online health-seeking.
Bianca Brijnath (23310511)
core  

An implementation science focused practice‐based research network for rural community pharmacies: RURAL‐CP

Clinical and Translational Science
Practice‐based research networks (PBRNs) support the translation and evaluation of evidence‐based practices and interventions on a large scale and have primarily been used in primary care settings. Few pharmacy PBRNs exist.
Delesha M. Carpenter, Stephanie Kiser, Megan Smith, Patricia Mashburn, Salisa C. Westrick, Tessa J. Hastings, Ashley Hannings, Meagen Rosenthal, Jure Baloh, Abigail Gamble, Tyler C. Melton, Geoffrey M. Curran   +11 more
doaj   +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

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

DataSheet_1_Transformation of Australian Community Pharmacies Into Good Clinical Practice Compliant Trial Pharmacies for HIV Pre-Exposure Prophylaxis.pdf

, 2019
Background: In Australia, clinical trial drugs are conventionally dispensed through clinical trial pharmacies only, while community pharmacies dispense drugs approved by Australia’s regulatory body.
Kie Lim (7831049), Wan Lim (4783326), Bharathy Naidoo (7831061), Anne Mak (7831079), Johnny Phu (7831058), Alexander Hardman (7831076), John Silverii (7831052), Edwina J. Wright (7831082), Matthew Rundle (7831067), Craig Cooper (7831073), Ivette Aguirre (7831040), Iris Yi Liu (7831034), Timmy Lockwood (7831037), Joseph Tesoriero (7831055), Nick Russell (7831064), Brian Price (7212515), Luxi Lal (7831031), Peter Slobodian (7831043), Kathleen Ryan (2930367), Martin Quinn (7585751), Rowan Sewell (7831070), Manoj Vassan (7831046), Ada Lam (5776226)   +22 more
core   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
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