Results 161 to 170 of about 2,009,217 (292)

The Ypresian ichthyofauna of the Monte Solane Lagerstätte (Verona, northern Italy): A deep dive into the western Tethys early Eocene mesopelagic setting. [PDF]

PLoS One
Calzoni P, Giusberti L, Fornaciari E, Luciani V, Boscolo-Galazzo F, Bernardi M, Tomasoni R, Carnevale G.   +7 more
europepmc   +1 more source

The Legacy of Parmenides [PDF]

, 1999
Johnson, Monte
core  

Artificial Intelligence (AI) and Agribusiness: From Automation to Augmentation in a Global Context

Agribusiness, EarlyView.
Alexis H. Villacis
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Commissioning and verification of a 3D Monte Carlo independent calculation software for O-ring linac systems. [PDF]

J Appl Clin Med Phys
Meng X, Dong T, Liang Y, Zhou Z, Wang Z, Qiu J, Zhao J, Zhang Z, Li W, Yang B.   +9 more
europepmc   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Raquianestesia em paciente anticoagulado

São Paulo Medical Journal
Fernando Lima Coutinho, Marcos Gonçalves Magalhães, Rodrigo Machado Saldanha, Mariana M. P. Neves, Fernando P. Araújo, José Francisco N. P. Neves   +5 more
doaj   +1 more source

Monte Carlo simulations of time-resolved blood flow index: times-of-flight beyond ∼1 ns are necessary for brain-dominated measurements. [PDF]

Neurophotonics
Hill DW, Behera A, Etard O, Zhang Y, Tran-Van-Minh A, Ruesch A, Ness L, Maine C, Salehi Lashkajani A, Parfentyeva V, Singh N, Antrobus A, Prudden R, Sanjurjo PV, Avtzi S, Dragojević T, Borycki D, Valley MT, Cooper RJ.   +18 more
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Probabilistic risk assessment of occupational exposure to respirable crystalline silica among ceramic workers in an industrial town in Iran: a Monte Carlo simulation approach. [PDF]

Sci Rep
Saeedizadeh S, Assari MJ, Ghorbani-Shahna F, Faradmal J, Karami Z, Mohraz MH.   +5 more
europepmc   +1 more source