Results 111 to 120 of about 467,084 (261)

Exploring the mechanism of artificial selection signature in Chinese indigenous pigs by leveraging multiple bioinformatics database tools. [PDF]

BMC Genomics, 2023
Feng X, Diao S, Liu Y, Xu Z, Li G, Ma Y, Su Z, Liu X, Li J, Zhang Z.   +9 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

Inverse Identification of Energy‐Dependent Laser Absorptivity in NiTi Laser Powder‐Bed Fusion via Calibrated Melt Pool Simulation

Advanced Engineering Materials, EarlyView.
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi, Hadi Moutablaleh, Ignatius A. Setiawan, Mehrshad Mehrpouya   +3 more
wiley   +1 more source

Convergent Genomic Signatures of Cashmere Traits: Evidence for Natural and Artificial Selection. [PDF]

Int J Mol Sci, 2023
Wang W, Li Z, Xie G, Li X, Wu Z, Li M, Liu A, Xiong Y, Wang Y.   +8 more
europepmc   +1 more source

Selective action of artificial membranes [PDF]

Nature, 1989
openaire   +2 more sources

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

Artificial selection reveals complex genetic architecture of shoot branching and its response to nitrate supply in Arabidopsis. [PDF]

PLoS Genet, 2023
Tavares H, Readshaw A, Kania U, de Jong M, Pasam RK, McCulloch H, Ward S, Shenhav L, Forsyth E, Leyser O.   +9 more
europepmc   +1 more source

Natural and artificial selection and suffering and well-being

Frontiers in Genetics, 2014
Jeroen eVan Rooijen
doaj   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

The concepts of "domestication" and "artificial selection" and their significance in the work of Charles Darwin. [PDF]

Hist Cienc Saude Manguinhos
Reyes MRAT, Juárez-Barrera F, Bueno-Hernández A.   +2 more
europepmc   +1 more source