Results 61 to 70 of about 1,346,541 (251)

Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher, Charles B. Malpas, Stuart J. McDonald, William T. O’Brien, Craig Despott, Kelly L. Bertram, Matthew P. Pase, Lukas Frontzkowski, Meng Law, Terence J. O’Brien, Lucy Vivash   +10 more
wiley   +1 more source

Use of a Molecular Signature Response Classifier to Inform Treatment Selection Improves Clinical Disease Activity Among Patients with Rheumatoid Arthritis Initiating a Biologic or Targeted Synthetic Disease‐Modifying Antirheumatic Drug

Arthritis Care &Research, EarlyView.
Objective We assessed the effectiveness of PrismRA to improve clinical outcomes among patients with rheumatoid arthritis (RA) initiating treatment with a biologic or targeted synthetic disease‐modifying antirheumatic drug (b/tsDMARD). Methods PrismRA incorporated 19 gene expression features and four clinical features to assess a patient's likelihood of
Fenglong Xie, Timothy Beukelman, Nicholas P. McCormick, Jeffrey R. Curtis   +3 more
wiley   +1 more source

A Comparative and Experimental Study on Gradient and Genetic Optimization Algorithms for Parameter Identification of Linear MIMO Models of a Drilling Vessel

International Journal of Applied Mathematics and Computer Science, 2015
The paper presents algorithms for parameter identification of linear vessel models being in force for the current operating point of a ship. Advantages and disadvantages of gradient and genetic algorithms in identifying the model parameters are discussed.
Bańka Stanisław, Brasel Michał, Dworak Paweł, Jaroszewski Krzysztof   +3 more
doaj   +1 more source

Sim-to-real transfer in reinforcement learning-based, non-steady-state control for chemical plants

SICE Journal of Control, Measurement, and System Integration, 2022
We present a novel framework for controlling non-steady situations in chemical plants to address the behavioural gaps between the simulator for constructing the reinforcement learning-based controller and the real plant considered for deploying the ...
Shumpei Kubosawa, Takashi Onishi, Yoshimasa Tsuruoka   +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

Improved Almost-Orthogonal Neural Network for Nonlinear System Identification with Application to Anti-Lock Braking Systems

Applied Sciences
Accurate modelling of nonlinear dynamical systems remains a fundamental challenge in control engineering, particularly in applications characterized by strong nonlinearities, uncertainty, and varying operating conditions such as anti-lock braking systems
Staniša Perić, Dragan Antić, Jianxun Cui, Saša S. Nikolić, Marko Milojković, Nikola Danković   +5 more
doaj   +1 more source

Parameter Identification of Weakly Nonlinear Vibration System in Frequency Domain

Shock and Vibration, 2004
A new method of identifying parameters of nonlinearly vibrating system in frequency domain is presented in this paper. The problems of parameter identification of the nonlinear dynamic system with nonlinear elastic force or nonlinear damping force are ...
Jiehua Peng, Jiashi Tang, Zili Chen
doaj   +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

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

Nonlinear system identification using modified variational autoencoders

Intelligent Systems with Applications
This research proposes a methodology for identifying nonlinear systems using input/output data and deep learning generative models. Our framework integrates Variational Autoencoders (VAE) with Nonlinear Autoregressive with exogenous input (NARX) in a ...
Jose L. Paniagua, Jesús A. López
doaj   +1 more source