Results 111 to 120 of about 8,505 (259)

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

Arthritis Care &Research, EarlyView.
Objective JAK inhibitors (JAKi) have shown promising effects in early‐phase studies of systemic sclerosis (SSc). We aimed to assess the safety and explore the effectiveness of JAKi compared to conventional immunosuppressants in SSc. Methods A longitudinal retrospective study of the European Scleroderma Trials and Research Group (EUSTAR) cohort was ...
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

Anorectal Dysfunction in Systemic Sclerosis: Clinical Phenotypes and Functional Patterns

Arthritis Care &Research, EarlyView.
Objective The aim of this study was to characterize specific physiologic defects in anorectal dysfunction in systemic sclerosis (SSc) using anorectal manometry (ARM), evaluate associations with gastrointestinal (GI) and extraintestinal clinical phenotypes, and explore potential serologic markers for risk stratification.
Timothy Kaniecki, Alireza Amindarolzarbi, Tsion Abdi, John Clarke, Michael Hughes, Ami A. Shah, Zsuzsanna H. McMahan   +6 more
wiley   +1 more source

CEEMDAN-FTEA-GCN-Transformer: A Transformer-based model for dam deformation prediction with frequency-spatial feature integration

Results in Engineering
Dam deformation is a critical indicator for assessing the operational status of dams, making deformation prediction models increasingly valuable in structural health monitoring.
Yuanhang Jin, Xiaosheng Liu, Xiaobin Huang   +2 more
doaj   +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

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +1 more source

High-order WCNS scheme with a constrained weighted least squares immersed boundary method for inviscid compressible flow simulations

Advances in Aerodynamics
Robust and accurate numerical methods for numerical simulations of compressible fluid flows featuring discontinuities around complex geometries are challenging and of increasing practical interest.
Yanqun Jiang, Huanhuan Yang, Qinghong Tang, Yixin Zhu   +3 more
doaj   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga   +2 more
wiley   +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

Low‐Temperature Imidization of Polyimides (PI) for Scalable Manufacturing of Flexible Wearable Electronics

Advanced Engineering Materials, EarlyView.
Low‐temperature imidization of PEG‐modified polyimide enables fully screen‐printed, roll‐to‐roll fabrication of flexible electrodes on PET substrates, delivering robust mechanical durability and reliable ECG/EMG signal performance for wearable electronics.
Akib Abdullah Khan, Jong‐Hoon Kim
wiley   +1 more source