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Prospective study on comparison of simulation-based mastery learning versus conventional apprentice-based learning for basic endoscopy training.
J Gastroenterol Hepatol
December 2024
Department of Dermatology and Venereology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia.
Background And Aim: The simulation-based mastery learning (SBML) method holds promise for improving the efficiency and effectiveness of endoscopy training. However, further study is required to establish its advantages over the traditional method. We aim to prospectively compare outcomes between gastrointestinal endoscopy trainees taught using SBML and those trained using conventional apprenticeship methods for upper endoscopy.
View Article and Find Full Text PDFIntelligent computing framework to analyze the transmission risk of COVID-19: Meyer wavelet artificial neural networks.
Comput Biol Chem
December 2024
Yuan Ze University, AI Center, Taoyuan 320, Taiwan. Electronic address:
The optimum control methods for the epidemiology of the COVID-19 model are acknowledged using a novel advanced intelligent computing infrastructure that joins artificial neural networks with unsupervised learning-based optimizers i.e., Genetic Algorithms (GA) and sequential quadratic programming (SQP).
View Article and Find Full Text PDFUsing Politeness Theory to Deconstruct How Preregistrant Pharmacists Approach Disagreement in the Workplace.
Am J Pharm Educ
December 2024
Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Victoria, Australia; Murdoch Children's Research Institute, Melbourne, Australia. Electronic address:
Article Synopsis
- This study looks at how student pharmacists handle arguments at work using something called politeness theory.
- Fifty-six students took part in pretend job situations where they had conflicts with coworkers, either those with less authority or those at the same level.
- The results showed that most students would speak up in these conflicts, but different situations led them to use different communication styles, and they could benefit from practicing these skills in safe settings before starting real jobs.
Pizza3: A general simulation framework to simulate food-mechanical and food-deconstruction problems.
Food Res Int
October 2024
UMR 0782 SayFood ParisSaclay Food and Bioproducts Engineering Research Unit, Group Modeling and Computational Engineering, INRAE, AgroParisTech, Paris-Saclay University, Palaiseau 91120, Ile-de-France, France. Electronic address:
Current mesh-based simulation approaches face significant challenges in continuously modeling the mechanical behaviors of foods through processing, storage, deconstruction, and digestion. This is primarily due to the limitations of continuum mechanics in dealing with systems characterized by free boundaries, substantial deformations, mechanical failures, and non-homogenized mechanical properties. The dynamic nature of food microstructure and the transformation of the food bolus, in relation to its composition, present formidable obstacles in computer-aided food design.
View Article and Find Full Text PDFDeconstructing Deep Active Inference: A Contrarian Information Gatherer.
Neural Comput
October 2024
University of Birmingham, School of Psychology and Computer Science, Birmingham B15 2TT, U.K.
Active inference is a theory of perception, learning, and decision making that can be applied to neuroscience, robotics, psychology, and machine learning. Recently, intensive research has been taking place to scale up this framework using Monte Carlo tree search and deep learning. The goal of this activity is to solve more complicated tasks using deep active inference.
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