Results 181 to 190 of about 4,295 (220)

Solid particles focusing, orienting, and de‐focusing in planar Poiseuille flow

AIChE Journal, EarlyView.
Abstract Three‐dimensional, time‐dependent lattice‐Boltzmann simulations of neutrally buoyant particles in planar Poiseuille flow have been performed. The particles are spherical or cylindrical (the latter with a length over diameter ratios in the range 1/3 to 2) and have volume fraction ranging from virtually zero (one particle) to 0.15. The channel's
J. J. Derksen
wiley   +1 more source

A parametric similarity measure for neutrosophic set and its applications in energy production. [PDF]

Heliyon
Liu P, Azeem M, Sarfraz M, Swaray S, Almohsen B.   +4 more
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

Constructing the human brain metabolic connectome with MR spectroscopic imaging reveals cerebral biochemical organization. [PDF]

Nat Commun
Lucchetti F, Céléreau E, Steullet P, Alemán-Gómez Y, Hagmann P, Klauser A, Klauser P.   +6 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

Optimal locomotor strategy for predator avoidance in fish prey. [PDF]

J Exp Biol
Peterson AN, McHenry MJ.
europepmc   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Order parameters and phase transitions of continual learning in deep neural networks. [PDF]

Proc Natl Acad Sci U S A
Shan H, Li Q, Sompolinsky H.
europepmc   +1 more source

In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs

Advanced Intelligent Discovery, EarlyView.
A vision‐based add‐on transforms commercial spin coaters into autonomous modules of Self‐Driving Labs. Combining a width‐scaled U‐Net with classical geometric analysis, the system simultaneously measures contact angles and estimates substrate pose using a single camera.
Sven Fischer, Micha Hiegle, Holger Röhm
wiley   +1 more source

Determining the Origin of Deformity in Torsional Femoral Pathology: A Narrative Review and an Illustrative Pilot Study of a Novel Methodology. [PDF]

J Clin Med
Chiappe C, Roselló-Añón A, Más-Estellés J, Gil-Santos L, Monllau JC, Sanchis-Alfonso V.   +5 more
europepmc   +1 more source