Results 121 to 130 of about 1,864,069 (342)
Inverse Engineering of Mg Alloys Using Guided Oversampling and Semi‐Supervised Learning
End‐to‐end design of engineering materials such as Mg alloys must include the properties, structure, and post‐synthesis processing methods. However, this is challenging when destructive mechanical testing is needed to annotate unseen data, and the processing methods for hypothetical alloys are unknown.
Amanda S. Barnard
wiley +1 more source
Information Dense and Industry Scalable Accelerated Formation
Pulsed formation can reduce lithium‐ion battery formation time by over 50% while maintaining or enhancing performance. Validated on 25 Ah prismatic cells, this industry‐scalable method yields thinner, more homogeneous solid electrolyte interphases (SEIs).
Leon Merker+3 more
wiley +1 more source
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod+10 more
wiley +1 more source
This article presents the artificial synapse based on strontium titanate thin films via spin‐coating followed by forming gas annealing to introduce oxygen vacancies. Characterizations (X‐ray photoelectron spectroscopy, electron paramagnetic resonance, Ultraviolet photoelectron spectroscopy (UPS)) confirm increased oxygen vacancies and downward energy ...
Fandi Chen+16 more
wiley +1 more source
AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley +1 more source
Application of a Size Measurement Standard for Data Warehouse Projects
ABSTRACTMethodologyIn this research, we conducted a case study to establish a foundation for size measurement and effort estimation in DWH projects. We first applied a productivity‐based estimation approach using linear regression with the ISBSG repository to assist organizations without historical data.
Hüseyin Ünlü+3 more
openaire +3 more sources
Tracking Report 2008 Puma, Vietnam 360084100G [PDF]
This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide.
Fair Labor Association
core +1 more source
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob+2 more
wiley +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Machine‐Learning‐Guided Analysis of Breast Tumor Malignancy Based on Nuclear Morphological Features
Through statistical and machine learning approaches, we evaluate a clinically relevant dataset comprising more than 500 instances of patient breast tumor nuclei with 10 size and shape features. Our study underscores the significance of nuclear morphological features as potential breast tumor malignancy biomarkers and their combined use with statistical
Aditi Birwadkar+3 more
wiley +1 more source