Results 131 to 140 of about 155,289 (268)

Gut microbiome predicts selenium supplementation efficiency across different Chinese adult cohorts using hybrid modeling and feature refining. [PDF]

Front Microbiol, 2023
Jiang S, Zhang B, Fan X, Chen Y, Wang J, Wu S, Wang L, Su X.   +7 more
europepmc   +1 more source

Simulation‐Based Analysis of Insert Pull‐Out in Nickel‐Polyurethane Hybrid Foams Using CT‐Derived Geometries

Advanced Engineering Materials, EarlyView.
CT‐based finite element simulations combined with in situ X‐ray computed tomography are used to analyze insert pull‐out in nickel‐coated polymer foams. Despite variations in material parameters, deformation consistently concentrates within a narrow annular region around the insert.
Yannik Bautz, Jonas Fell, Hendrik Jost, Stefan Diebels, Hans‐Georg Herrmann   +4 more
wiley   +1 more source

A Hybrid Modeling Framework for Predictive Digital Twins of CHO Cell Culture. [PDF]

Comput Struct Biotechnol J
Richelle A, Andersson D, Antonakoudis A, Jakobsson J, Pijeaud S, Vernersson A, Trygg J.   +6 more
europepmc   +1 more source

Fabrication Routes for Ionic Conducting Fiber Strain Sensors

Advanced Engineering Materials, EarlyView.
Ionic conducting fiber strain sensors (ICFSs) offer compliant, textile‐integrable sensing. Thus far, the commercialization of ICFSs has been constrained by fiber fabrication routes. This review provides a fabrication‐centric analysis of ICFSs correlating processing strategies with material properties and scalability.
Leo John Kershaw, Zhanhong Yang, Anne Ladegaard Skov, Magdalena Skowyra   +3 more
wiley   +1 more source

Multi-Scale Hybrid Modeling to Predict Cell Culture Process With Metabolic Phase Transitions. [PDF]

Biotechnol Bioeng
Wang K, Harcum SW, Xie W.
europepmc   +1 more source

Novel Hybrid Modeling and Analysis Method for Steam Reforming Solid Oxide Fuel Cell System Multifault Degradation Fusion Assessment. [PDF]

ACS Omega, 2023
Wu X, Xu Y, Peng J, Xia Z, Kupecki J, Li X.   +5 more
europepmc   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Hybrid modeling for industrial fermentation processes with an "Intra-Batch Experimental Design". [PDF]

J Ind Microbiol Biotechnol
Lemperle M, Ramin P, Kager J, Cassells B, Stocks S, Gernaey KV.   +5 more
europepmc   +1 more source

Quantifying postprandial glucose responses using a hybrid modeling approach: Combining mechanistic and data-driven models in The Maastricht Study. [PDF]

PLoS One, 2023
Erdős B, van Sloun B, Goossens GH, O'Donovan SD, de Galan BE, van Greevenbroek MMJ, Stehouwer CDA, Schram MT, Blaak EE, Adriaens ME, van Riel NAW, Arts ICW.   +11 more
europepmc   +1 more source

FROM HYBRID SIMULATION TO HYBRID SYSTEMS MODELLING [PDF]

2018 Winter Simulation Conference (WSC), 2018
Navonil Mustafee, John H. Powell
openaire   +2 more sources