Results 171 to 180 of about 176,597 (260)

Anesthesia isn't sleep: The neuronal dynamics of immobility in isoflurane-anesthetized C. elegans differ from the activity patterns of previously established sleep-like quiescent states. [PDF]

PLoS One
Chang AS, Mazuera L, Gabel CV, Connor CW.   +3 more
europepmc   +1 more source

Fatigue Crack Initiation and Growth in Nanocrystalline Ni at Multiple Length‐Scales

Advanced Engineering Materials, EarlyView.
Overview of miniaturized in situ SEM fatigue setup and resultant fatigue crack growth data for nanocrystalline Ni. The presented study focuses on the analysis of fatigue crack growth rate (FCGR) in focused ion beam‐notched microcantilevers prepared from nanocrystalline (NC) Ni as a model material.
Igor Moravcik, Alexander Jelinek, Markus Alfreider, Jutta Luksch, Anton Hohenwarter, Florian Schaefer, Christian Motz, Daniel Kiener   +7 more
wiley   +1 more source

Neuronal dynamics direct cerebrospinal fluid perfusion and brain clearance. [PDF]

Nature
Jiang-Xie LF, Drieu A, Bhasiin K, Quintero D, Smirnov I, Kipnis J.   +5 more
europepmc   +1 more source

Excitatory/Inhibitory Responses Shape Coherent Neuronal Dynamics Driven by Optogenetic Stimulation in the Primate Brain. [PDF]

J Neurosci, 2020
Shewcraft RA, Dean HL, Fabiszak MM, Hagan MA, Wong YT, Pesaran B.   +5 more
europepmc   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Modulation of neuronal dynamics by sustained and activity-dependent continuous-wave near-infrared laser stimulation. [PDF]

Neurophotonics
Garrido-Peña A, Sanchez-Martin P, Reyes-Sanchez M, Levi R, Rodriguez FB, Castilla J, Tornero J, Varona P.   +7 more
europepmc   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Time-varying generalized linear models: characterizing and decoding neuronal dynamics in higher visual areas. [PDF]

Front Comput Neurosci
Weng G, Clark K, Akbarian A, Noudoost B, Nategh N.   +4 more
europepmc   +1 more source

Predicting neuronal dynamics with a delayed gain control model. [PDF]

PLoS Comput Biol, 2019
Zhou J, Benson NC, Kay K, Winawer J.
europepmc   +1 more source