Results 181 to 190 of about 428,811 (315)
Agribusiness, EarlyView.ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani +3 more
wiley +1 more source
Neuropsychiatric Disease and Treatment, 2013 Audrey McKinlay,1,2 Michelle Albicini,2 Phillip S Kavanagh31Department of Psychology, University of Canterbury, Christchurch, New Zealand; 2Department of Psychology and Psychiatry, Monash University Clayton, VIC, Australia; 3School of Psychology, Social ...
McKinlay A, Albicini M, Kavanagh PS
doaj
, 2002 Working with multi-species allometric relations and drawing on mammalian theorist Denenberg’s works, I provide an explanatory theory of the mammalian dual-brain as no prior account ...
Reid, Mark D
core
Affective theory of mind in patients with
Psychiatry and Clinical Neurosciences, 2013 SANTANGELO, Gabriella +5 more
openaire +5 more sources
Agribusiness, EarlyView.ABSTRACT This study investigates how consumer taste and brand equity perceptions shape the acceptance of plant‐based milk products. Using a blind/informed tasting experiment, we evaluated consumers' willingness to buy (WTB) and taste perception of a plant‐based milk alternative produced by a traditional dairy brand, compared with competing plant‐based ...
Federico Parmiggiani +6 more
wiley +1 more source
AI in chemical engineering: From promise to practice
AIChE Journal, EarlyView.Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob +2 more
wiley +1 more source
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 +6 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
Robot‐Assisted Measurement of the Critical Micelle Concentration
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The study introduces (SIMO) smart integrator for manual operations, a robotic platform for precise, repeatable determination of (CMC) critical micelle concentration in surfactants. SIMO reduces standard deviation by 80% compared to manual methods. Surfactant, dye, and diluent selection, robotic protocols, and data handling are detailed.
Vincenzo Scamarcio +3 more
wiley +1 more source