Results 161 to 170 of about 550,312 (276)

Effects of Myristica fragrans and Alpinia conchigera oils against Callosobruchus maculatus

open access: yesJulius-Kühn-Archiv, 2018
Suthisut, Duangsamorn   +4 more
doaj   +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

open access: yesAdvanced 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   +3 more
wiley   +1 more source

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

open access: yesAdvanced 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   +2 more
wiley   +1 more source

Assessing cotton boll-opening concentration for harvest decision-making via foundation model-enhanced cross-scale phenotyping. [PDF]

open access: yesPlant Phenomics
Chen M   +12 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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

open access: yesAdvanced 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   +5 more
wiley   +1 more source

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