Results 81 to 90 of about 3,178 (169)
Coarse‐to‐Fine Spatial Modeling: A Scalable, Machine‐Learning‐Compatible Framework
ABSTRACT This study proposes coarse‐to‐fine spatial modeling (CFSM) as a scalable and machine learning‐compatible alternative to conventional spatial process models. Unlike conventional covariance‐based spatial models, CFSM represents spatial processes using a multiscale ensemble of local models.
Daisuke Murakami +5 more
wiley +1 more source
This study evaluated the antimicrobial activity of 11 natural agents against eight STEC serotypes by determining their MIC and MBC at different pH and temperature conditions. Five agents demonstrating the strongest inhibitory activity in vitro were then tested at various concentrations in beef burgers inoculated with Escherichia coli O157 and stored ...
Angelos Papadochristopoulos +4 more
wiley +1 more source
A review of the main placenta histopathological findings reported in coronavirus disease 2019. [PDF]
Almohammadi NH.
europepmc +1 more source
Price Indices Rekindled, 1970s–1990s: Theory and Practice at Cross Purposes?
ABSTRACT This paper revisits the discussions on price indices during a period marked by theoretical advancements and practical challenges in measuring inflation. Index‐number theorists sought to improve accuracy, yet national statistical offices largely maintained established practices due to concerns over data availability, stability, and public trust.
Victor Cruz‐e‐Silva, Bert M. Balk
wiley +1 more source
Entropy considerations in improved circuits for a biologically-inspired random pulse computer. [PDF]
Stipčević M, Batelić M.
europepmc +1 more source
Mesh and Model Adaptivity for Multiscale Elastoplastic Models With Prandtl‐Reuss Type Material Laws
ABSTRACT Homogenization methods simulate heterogeneous materials like composites effectively, but high computational demands can offset their benefits. This work balances accuracy and efficiency by assessing model and discretization errors of the finite element method (FEM) through an adaptive numerical scheme.
Arnold Tchomgue Simeu +2 more
wiley +1 more source
Homogenization With Guaranteed Bounds via Primal‐Dual Physically Informed Neural Networks
ABSTRACT Physics‐informed neural networks (PINNs) have shown promise in solving partial differential equations (PDEs) relevant to multiscale modeling, but they often fail when applied to materials with discontinuous coefficients, such as media with piecewise constant properties. This paper introduces a dual formulation for the PINN framework to improve
Liya Gaynutdinova +3 more
wiley +1 more source
Orienteering with One Endomorphism. [PDF]
Arpin S +5 more
europepmc +1 more source
We curate laccase‐substrate datasets and train five classifiers, from regularized logistic regression to tree‐based models and ChemBERTa, to predict whether a substrate will be oxidized. Feature importance and attention maps projected onto molecular substructures make the predictions interpretable and useful for pre‐screening before the bench ...
Yulia Kulagina +3 more
wiley +1 more source
Idiopathic pulmonary fibrosis beyond the lung: understanding disease mechanisms to improve diagnosis and management. [PDF]
Luppi F +4 more
europepmc +1 more source

