Characteristic in ground motions between the Mw7.9 Pazarcık earthquake and the Mw7.6 Elbistan earthquake in Türkiye. [PDF]
Xu P, Liu X, Li L.
europepmc +1 more source
The Lupus Damage Index Revision Program: Results From the Item Generation and Reduction Phases
Objective A data‐driven and expert/patient consensus‐based project to develop a revised Systemic Lupus International Collaborating Clinics (SLICC)/American College of Rheumatology (ACR) Damage Index (SDI) is under way supported by SLICC, ACR, and the Lupus Foundation of America. Our objective is to report the item generation and reduction phase results
Burak Kundakci +25 more
wiley +1 more source
Influence of near-fault ground motions' characteristics on the control performance of tuned viscous mass damper systems. [PDF]
Zhang L, Liu Z, Shi J.
europepmc +1 more source
Objective Systemic lupus erythematosus (SLE) significantly impacts employment capacity. This study aimed to investigate the impact of burden of disease activity, damage, and treatment on employment outcomes and transitions in patients with SLE. Materials and Methods Using data from a single center, we analyzed employment transitions, adjusted mean ...
Javier Mencia‐Ledo +4 more
wiley +1 more source
Study on dynamic response analysis of a long-span and asymmetrical suspension bridge subjected to uniform and nonuniform ground motions. [PDF]
Li J.
europepmc +1 more source
Characteristics of strong ground motions in the 2014 Ms 6.5 Ludian earthquake, Yunnan, China. [PDF]
Hu JJ +4 more
europepmc +1 more source
Objective Test the hypothesis that multi‐joint osteoarthritis would modify the relation between time and frailty progression, where more affected joints would lead to larger declines over 6‐years compared to those without osteoarthritis using data from the Canadian Longitudinal Study on Aging.
Carson Halliwell +2 more
wiley +1 more source
Predicting largest expected aftershock ground motions using automated machine learning (AutoML)-based scheme. [PDF]
Yu X, Wang M, Ning C, Ji K.
europepmc +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
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 +2 more
wiley +1 more source
Spatial correlation assessment of multiple earthquake intensity measures using physics-based simulated ground motions. [PDF]
Zolfaghari MR, Forghani M.
europepmc +1 more source

