Results 211 to 220 of about 1,094,599 (317)

A Systematic Evaluation of Protein Phase Separation Predictors across Diverse Protein Landscapes. [PDF]

Comput Struct Biotechnol J
Gilroy KE, Barr JN.
europepmc   +1 more source

Real‐World Safety and Effectiveness of JAK Inhibitors in Systemic Sclerosis: A Propensity‐Matched Study from the EUSTAR Cohort

Arthritis Care &Research, Accepted Article.
Objective JAK inhibitors (JAKis) have shown promising effects in early‐phase studies of SSc. We aimed to assess the safety and explore effectiveness of JAKis compared to conventional immunosuppressants in SSc. Methods A longitudinal retrospective study of the EUSTAR cohort was performed.
Stefano Di Donato, Marie‐Elise Truchetet, Marco Minerba, Oliver Distler, Juan José Alegre Sancho, Yolanda Braun‐Moscovici, Christina Bergmann, Petros Sfikakis, Jeska K de Vries‐Bouwstra, Murray Baron, Silvia Bellando‐Randone, Lorenzo Dagna, Christopher P Denton, Madelon C Vonk, Vanessa Smith, Ivan Castellvi, Gabriela Riemekasten, Andra Balanescu, Masataka Kuwana, Maria De Santis, Kamal Solanki, Anastas Batalov, Vahan Mukuchyan, Marco Matucci‐Cerinic, Yannick Allanore, Francesco Del Galdo, Michael Hughes, EUSTAR Collaborators   +27 more
wiley   +1 more source

An Algorithm at the Table at Multidisciplinary Diagnostic Meetings: A Dramaturgical Analysis. [PDF]

Sociol Health Illn
Dingelstad J, Grommé F, Hoeven CT, Wallenburg I.   +3 more
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Explainable machine learning reveals diverse yield-determining factors among Thai rice farmer cohorts: Implications for targeted agricultural support. [PDF]

PLoS One
Suriyalaksh M, Prommawin B, Hannanta-Anan P, Sreewongchai T, Promchote P, Nakasathien S.   +5 more
europepmc   +1 more source

Adaptive Observer for Coupled Wave PDE and Infinite ODE With Sampled Data and Unknown Input: Application to Brain Hemodynamics Estimation

International Journal of Adaptive Control and Signal Processing, EarlyView.
This article proposes a convergent adaptive observer for a damped wave PDE and an infinite‐dimensional ODE coupled in cascade using sampled‐in‐space ODE state measurements. The proposed observer estimates the distributed states of the PDE and ODE along with unknown PDE parameters and spatial input.
Zehor Belkhatir, Sarah Mechhoud, Taous‐Meriem Laleg‐Kirati   +2 more
wiley   +1 more source

The impact of a novel deep learning reconstruction algorithm on image quality in ultralow-dose CT: a quantitative phantom study. [PDF]

Eur Radiol Exp
Su T, Jia Y, Shen Y, Zhang 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

Classification of soft decision-making methods via fuzzy parameterized fuzzy soft matrices and their performance-based statistical analysis in machine learning. [PDF]

PLoS One
Karakoç Ö, Memiş S, Sennaroglu B.
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source