Results 241 to 250 of about 232,567 (314)

<i>GhA01EP1</i> of Upland Cotton Stimulates Precocity, Improved Water Deficit Tolerance, and High Seed Yield in Transgenic <i>Arabidopsis</i>. [PDF]

Genes (Basel)
Li D, Zhao C, Zhang X, Zhang H, Yuan C, Wang K, Liu S, Geng J, Guo B.   +8 more
europepmc   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Optimizing sowing time and weather conditions for enhanced growth and seed yield of chia (<i>Salvia hispanica</i> L.) in semi-arid regions. [PDF]

PeerJ
Harisha CB, Boraiah KM, Basavaraj PS, Halli HM, Singh RN, Rane J, Sammi Reddy K, Halagundegowda GR, Chaudhary A, Verma AK, Ravi Y, Asangi H, Senthamil E.   +12 more
europepmc   +1 more source

Workflow for Design of Experiments‐Based Modeling of Species Transport and Growth Kinetics in GaN Hydride Vapor Phase Epitaxy

Advanced Engineering Materials, EarlyView.
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič, G. Lukin, H. Torkashvand, A. Kerschbaum, M. Müller, S. Besendörfer, J. Heitmann, J. Friedrich   +7 more
wiley   +1 more source

Genome-Wide Association Study for Seed Yield of Tepary Bean Using Whole-Genome Resequencing. [PDF]

Int J Mol Sci
Ravelombola W, Manley A, Pham H, Brown M, Ruhl C, Ghosh P.   +5 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

Enhancing Alfalfa (<i>Medicago sativa</i>) Seed Yield: The Effect of Honey Bee (<i>Apis mellifera</i>) Supplementation and Efficiency of Other Pollinators. [PDF]

Biology (Basel)
Ejaz K, Ali M, Khan FZA, Mozūratis R.
europepmc   +1 more source

Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure

Advanced Engineering Materials, EarlyView.
Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari, Supharoek Sornsomrit, Muhammad Ayaz Akbar, Stephan Rudykh   +3 more
wiley   +1 more source

Optimizing boron application methods and dosages to enhance jute (Corchorus olitorius) seed yield and quality under sub-tropical climate. [PDF]

Heliyon
Kumar T, Tama PM, Kabir Hemel SA, Ghosh RK, Ali MI, Al-Bakky A, Alim A.   +6 more
europepmc   +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