Percentile-based slope-constrained linear interpolation for robust imputation of highly volatile PM2.5 time series. [PDF]
Somnugpong S, Butploy N, Khiewwan K.
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
A time-domain Runge-Kutta dual reciprocity boundary element method for scalar wave propagation problem. [PDF]
Zhou F +6 more
europepmc +1 more source
Objective Orofacial manifestations are significantly impactful in patients with systemic sclerosis (SSc) yet remain understudied, with no dedicated clinical guidelines to inform their management. Methods An international online survey comprised38 questions addressing orofacial manifestations of SSc, including patients’ confidence in their treating ...
Eleni Deligianni +4 more
wiley +1 more source
Isogeometric suitable coupling methods for partitioned multiphysics simulation with application to fluid-structure interaction. [PDF]
Li JY +3 more
europepmc +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
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 +2 more
wiley +1 more source
Existence, Stability, and Control of Glucose-Insulin Dynamics via Caputo-Fabrizio Fractal-Fractional Operators. [PDF]
Saber S, Alahmari AA.
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
A stereo dataset of annotated budgerigar flight trajectories for multi-agent collision avoidance studies. [PDF]
Tawhid SM +6 more
europepmc +1 more source

