Results 171 to 180 of about 1,205,834 (315)

Essential oil-based hydrogels for oral candidiasis: preliminary formulation development, antifungal efficacy, and computational analysis via Monte Carlo simulation. [PDF]

Front Cell Infect Microbiol
Kola-Mustapha AT, John FT, Bello RH, Adedeji OJ, Ghazali YO, Khalid-Salako FA, Ambrose GO.   +6 more
europepmc   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Comparative reliability assessment of PET and UTCI thermal comfort indices using Monte Carlo simulation in urban microclimates. [PDF]

Sci Rep
Sargazi MA, Heidari A, Davtalab J, Piri J.   +3 more
europepmc   +1 more source

Compact Modeling of Volatile‐Switching Electrochemical Metallization Memory Cells by Means of the Electromotive Force

Advanced Intelligent Systems, EarlyView.
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad, Solomon Amsalu Chekol, Julius Rasbach, Susanne Hoffmann‐Eifert, Stephan Menzel   +4 more
wiley   +1 more source

Probabilistic carcinogenic and health risk assessment of heavy metals in lettuce and cabbage from Behbahan, Iran, using Monte Carlo simulation. [PDF]

Sci Rep
Armand R, Rafati L, Mohammadi H, Armand N.   +3 more
europepmc   +1 more source

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

Carcinogenic and non-carcinogenic risk assessment of elemental impurities and bioactive compounds in six wild mushrooms using Monte Carlo simulation. [PDF]

Sci Rep
Canbolat F, Acar İ, Okumuş E, Ayata F.
europepmc   +1 more source

Accurate condensed history Monte Carlo simulation of electron transport. I. EGSnrc, the new EGS4 version.

Medical Physics (Lancaster), 2000
I. Kawrakow
semanticscholar   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Health risk assessment of penconazole fungicide residues in grapes: insights from Monte Carlo simulation. [PDF]

Sci Rep
Peirovi-Minaee R, Zarei A, Alami A, Afsharnia M.   +3 more
europepmc   +1 more source