Results 211 to 220 of about 723 (258)

Modeling the separation of water‐in‐oil emulsions in continuously fed gravity settlers using millifluidic experiments

AIChE Journal, EarlyView.
Abstract Emulsion separation remains a persistent challenge in chemical and process industries due to the metastable nature of dispersed droplets. In gravity separators, the overall separation rate is governed by the formation of a densely packed zone (DPZ) of deforming and coalescing droplets that mediates between the dispersed and continuous phases ...
Andrei Zlobin, José Esteban Andino‐Enriquez, Thomas Gouëzec, Maurice Bourrel, Enric Santanach‐Carreras, Nicolas Passade‐Boupat, Laurence Talini, François Lequeux, Pascal Panizza   +8 more
wiley   +1 more source

Role of immigrant males and muzzle contacts in the uptake of a novel food by wild vervet monkeys. [PDF]

Elife
Dongre P, Lanté G, Cantat M, Canteloup C, van de Waal E.   +4 more
europepmc   +1 more source

Understanding community context and adult health changes in China: development of an urbanicity scale. [PDF]

Soc Sci Med, 2010
Jones-Smith JC, Popkin BM.
europepmc   +1 more source

Resolving passive heat transfer and phase‐change heat in cryogenic CO2 deposition (Desublimation) from CO2/N2 mixtures

AIChE Journal, EarlyView.
Abstract In cryogenic CO2 desublimation systems where phase change dominates both heat transfer and separation, conventional lumped thermal‐resistance treatments embed interfacial latent heat into an overall heat‐transfer coefficient, obscuring how phase‐change heat is partitioned between the gas phase and the coolant and limiting diagnostic insight ...
Shengwen Xiao, Hiroshi Machida, Koyo Norinaga   +2 more
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Differential development of visual attention skills in school-age children. [PDF]

Vision Res, 2010
Dye MW, Bavelier D.
europepmc   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Incentives for smoking cessation. [PDF]

Cochrane Database Syst Rev, 2019
Notley C, Gentry S, Livingstone-Banks J, Bauld L, Perera R, Hartmann-Boyce J.   +5 more
europepmc   +1 more source

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

Advanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz, Gisya Abdi, Andrzej Sławek, Marlena Gryl, Konrad Szaciłowski   +4 more
wiley   +1 more source

Epidemiology of participation: an Australian community study. [PDF]

J Epidemiol Community Health, 2000
Baum FE, Bush RA, Modra CC, Murray CJ, Cox EM, Alexander KM, Potter RC.   +6 more
europepmc   +1 more source