Results 131 to 140 of about 166,325,679 (283)

Triangular Index Ratio as an Alternative Method to the Alpha Angle for Defining the Presence of Cam Morphology: A Prospective Cohort Study

Arthritis Care &Research, EarlyView.
Objective Cam morphology, which is a significant risk factor for hip osteoarthritis, is commonly quantified by the alpha angle (AA). This study aims to explore the potential of the triangular index ratio (TIR) to quantify cam morphology on anteroposterior radiographs by assessing the association between TIR‐defined cam morphology and the development of
Jinchi Tang, Fleur Boel, Michiel M. A. van Buuren, Noortje S. Riedstra, Myrthe A. van den Berg, Jos Runhaar, Sita Bierma‐Zeinstra, Rintje Agricola   +7 more
wiley   +1 more source

Convergence of Numerical Method for Solving Hyperbolic Equation

Journal of Mathematics Research
In this parer,we investigate the convergence of explicit schemes for solving hyperbolic equations. Traditionally, the well-known (CFL)(Couryant-Friedrichs-Lewy)condition imposes a restriction on the ratio of step size, specifically k h≤C where k is time step-size and h is the spatial step size. This is crucial for ensuring the convergence of the
openaire   +1 more source

Discordance Between Systemic Lupus Erythematosus Disease Activity Index Domain Weights and Their Association With Organ Damage Accrual

Arthritis Care &Research, EarlyView.
Objective Studies of damage accrual in patients with systemic lupus erythematosus (SLE) show associations with disease activity measured by the SLE Disease Activity Index 2000 (SLEDAI‐2K), but these associations are imperfect. SLEDAI scores are powerfully influenced by weightings (1–8) assigned to each domain.
Kevin Zhang, Eric F. Morand, Sarah E. Boyd, François Petitjean, Alberta Hoi, Rachel Koelmeyer, Iolanda Miceli, Julie A. Monk, Hieu T. Nim   +8 more
wiley   +1 more source

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

Arthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah, Melanie Morris, Cristina Daraban, Sophia Johnson, Susan L. Murphy   +4 more
wiley   +1 more source

Extending Service Beyond Active Duty: Generalizability of Rheumatoid Arthritis Research Conducted Among U.S. Veterans

Arthritis Care &Research, Accepted Article.
Biomedical research involving United States Veterans continues to advance healthcare beyond the Veterans Health Administration. This is particularly true in rheumatoid arthritis (RA), where Veteran‐centric research has uncovered novel insights into pathogenesis, risk factors, and disease manifestations, informing clinical care and research across both ...
Austin M. Wheeler, Joshua F. Baker, Jennifer L. Barton, Maria I. Danila, Tate M. Johnson, Kamini Kuchinad, Kaleb Michaud, Amir A. Razmjou, J. Steuart Richards, Namrata Singh, Isaac D. Smith, Katherine D. Wysham, Grant W. Cannon, Bryant R. England, Amy Joseph, Deana Lazaro, Katherine P. Liao, Courtney Loecker, Andreas Reimold, Beth I. Wallace, Ted R. Mikuls   +20 more
wiley   +1 more source

Validation of Patient‐Reported Outcomes Measurement Information System (PROMIS) Pediatric Measures for Children With Chronic Nonbacterial Osteomyelitis

Arthritis Care &Research, EarlyView.
Objective To assess the validity of the Patient‐Reported Outcomes Measurement Information System (PROMIS) Pediatric measures in patients with chronic nonbacterial osteomyelitis (CNO). Methods Within the longitudinal patient registry of CNO, English‐speaking patients aged 8 years and older self‐reported PROMIS Pediatric measures of fatigue, pain ...
Mary M. Eckert, Eveline Y. Wu, Melissa Oliver, Joshua Scheck, Sivia Lapidus, Ummusen Kaya Akca, Shima Yasin, Aleksander Lenert, Sara Stern, Antonella Insalaco, Manuela Pardeo, Gabriele Simonini, Edoardo Marrani, Xing Wang, Bin Huang, Leonard K. Kovalick, Natalie Rosenwasser, Erin Balay‐Destrude, Gabriel Casselman, Adriel Liau, Ava Klein, Yurong Shao, Claire Yang, Molly Briggs, Ethan Mueller, Emily Deng, Paige Rhiannon Trunnell, Iris Hamilton, Elise Machrone, Doaa Mosad Mosa, Lori Tucker, Hermann Girschick, Ronald M. Laxer, Georgina Tiller, Jonathan Akikusa, Christian M. Hedrich, Karen Onel, Fatma Dedeoglu, Marinka Twilt, Seza Ozen, Polly J. Ferguson, Laura Schanberg, Bryce B. Reeve, Yongdong Zhao   +43 more
wiley   +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

Finite-time and predefined-time dynamical systems for solving strongly pseudomonotone mixed equilibrium problems. [PDF]

PLoS One
Wen Q, Khan VK, Cai QB, Ahmad MK.
europepmc   +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, Marco Zaffalon   +3 more
wiley   +1 more source