Results 181 to 190 of about 75,216 (280)

Collaborative filtering models an experimental and detailed comparative study. [PDF]

Sci Rep
Rajesh DB, Kumar A.
europepmc   +1 more source

Clinical, histological, and serological predictors of renal function loss in lupus nephritis.

Arthritis Care &Research, Accepted Article.
Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang, Laurence Magder, Daniel Goldman, Judith A. James, Joel M Guthridge, Carla Guthridge, Peter Izmirly, Jill P Buyon, H.Michael Belmont, Richard A. Furie, Noa Schwartz, Chaim Putterman, Jennifer L. Barnas, Jennifer H. Anolik, Sarah French, Maria Dall'era, Avi Z. Rosenberg, Jeffrey Hodgin, Dawit S. Demeke, the Accelerating Medicines Partnership RA/SLE Network, Michelle Petri, Andrea Fava   +21 more
wiley   +1 more source

Joint modeling of cellular heterogeneity and condition effects with scPCA in single-cell RNA-seq. [PDF]

Commun Biol
Vöhringer H.
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Learning Continuous Decomposable Models Using Mutual Information and Statistical Copulas. [PDF]

Entropy (Basel)
Desuó Neto L, de Oliveira Caetano H, de Souza Sant'Anna Fogliatto M, Dias Maciel C.   +3 more
europepmc   +1 more source

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi, Ebrahim Norouzi, Kostiantyn Hubaiev, Jörg Waitelonis, Harald Sack   +4 more
wiley   +1 more source

Connecting Brown Carbon Composition and Physicochemical Properties of Aqueous Urban PM_2.5 to their Photosensitized Production of Singlet Oxygen and Organic Triplet Excited States. [PDF]

Environ Sci Technol
Lyu Y, Li Y, Ma R, Zhou T, Borduas-Dedekind N, Nah T.   +5 more
europepmc   +1 more source

On the absolute summability factors [PDF]

Kodai Mathematical Journal, 1954
openaire   +3 more sources

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source