Results 181 to 190 of about 8,559,198 (240)

Distinct roles of brain network flexibility in motor learning across age. [PDF]

Imaging Neurosci (Camb)
Uehara K, Hagihara M, Kitajo K.
europepmc   +1 more source

Symmetry‐Guided Multifunctional Acoustic System Based on Mechanically Actuated Sonic Crystals

Advanced Engineering Materials, EarlyView.
This study presents the design, simulation, and experimental validation of amultifunctional acoustic metamaterial based on rotationally engineered sonic crystals.By tuning cylinder orientations, controllable band gaps and six distinct functionalities—including switching, topological insulation, beam splitting, and logic operations—areachieved ...
Yuanyan Zhao, Sriram Subramanian, Gianluca Memoli   +2 more
wiley   +1 more source

Educating minds with generative AI. [PDF]

Commun Psychol
Di Paolo LD, Clark A, Wachter T.
europepmc   +1 more source

Complete Issue Volume 1 Issue 1

Journal of the Scholarship of Teaching and Learning, 2000
Editor, Journal of the Scholarship of Teaching and Learning
doaj  

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

Learning curves in orthopedic and trauma surgery: a systematic review. [PDF]

EFORT Open Rev
Bouché PA, Falkenrodt C, Nizard RS, Devriese F, Resche-Rigon M, Descamps J.   +5 more
europepmc   +1 more source

Complete Issue Volume 11 Issue 2

Journal of the Scholarship of Teaching and Learning, 2012
Editor, Journal of the Scholarship of Teaching and Learning
doaj  

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