Results 51 to 60 of about 63,859 (262)

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

Frailty Predicts Incident Osteoporotic Fractures in Veterans with Rheumatoid Arthritis

Arthritis Care &Research, Accepted Article.
Background/Objective Rheumatoid arthritis (RA) is associated with an increased risk of frailty and osteoporosis, but the relationship between frailty and incident osteoporotic fractures in RA is underexplored. Methods Data were from the Veterans Affairs Rheumatoid Arthritis (VARA) Registry.
Katherine D. Wysham, Hannah F. Brubeck, Aaron Baraff, Punyasha Roul, Namrata Singh, James S. Andrews, Grant W. Cannon, Gary A. Kunkel, Ted R. Mikuls, Bryant R. England, Dolores M. Shoback, Patricia P. Katz, Jose M. Garcia, Ariela R. Orkaby, Joshua F. Baker   +14 more
wiley   +1 more source

Learning-based Nonlinear Model Predictive Control

IFAC-PapersOnLine, 2017
This paper presents stabilizing Model Predictive Controllers (MPC) in which prediction models are inferred from experimental data of the inputs and outputs of the plant. Using a nonparametric machine learning technique called LACKI, the estimated (possibly nonlinear) model function together with an estimation of Holder constant is provided.
Limon, D, Calliess, J-P, Maciejowski, JM
openaire   +2 more sources

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

Planar Solid‐State Nanopores Toward Scalable Nanofluidic Integration Based on CMOS Technology

Advanced Engineering Materials, EarlyView.
We present a scalable silicon‐based fabrication strategy for planar solid‐state nanopores to enable their integration with complex nanofluidic systems. Prototype devices demonstrate normal voltage‐current characteristics, good noise performance, and appreciable streaming currents. Our CMOS‐compatible fabrication process offers precise geometric control
Ngan Hoang Pham, Chenyu Wen, Mohammad Hadi Khaksaran, Won‐Yong Lee, Javier Cruz, Klas Hjort, Dongping Wu, Shi‐Li Zhang   +7 more
wiley   +1 more source

Model Predictive Control of Non-Linear Systems Using Tensor Flow-Based Models

Applied Sciences, 2020
The present paper proposes an approach for the development of a non-linear model-based predictive controller (NMPC) using a non-linear process model based on Artificial Neural Networks (ANNs).
Rómulo Antão, José Antunes, Alexandre Mota, Rui Escadas Martins   +3 more
doaj   +1 more source

On the Lightweight Potential of Laser Additive Manufactured NiTi Triply Periodic Minimal Sheet Lattices

Advanced Engineering Materials, EarlyView.
This study explores the lightweight potential of laser additive‐manufactured NiTi triply periodic minimal surface sheet lattices. It systematically investigates the effects of relative density and unit cell size on surface quality, deformation recovery, compression behavior, and energy absorption.
Haoming Mo, Shuo Qu, Shiming Gao, Xu Song   +3 more
wiley   +1 more source

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

Advanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora, Tales V. Lisbôa, Axel Spickenheuer, Rogério J. Marczak, Jakson M. Vassoler   +4 more
wiley   +1 more source

A Sensitivity-Based Approach to Self-Triggered Nonlinear Model Predictive Control

IEEE Access
Self-triggered control aims to reduce resource utilization, particularly in networked systems, by sampling only when necessary to ensure a specific level of control performance.
Paulina Conrad, Knut Graichen
doaj   +1 more source

Air‐Pressure–Actuated Vibroacoustic Metamaterial With Tunable Bandgap: Design, Modeling, and Characterization

Advanced Engineering Materials, EarlyView.
This article presents the design, modeling, and characterization of air‐pressure–actuated programmable vibroacoustic metamaterials (PVAMM). The study focuses on leveraging air pressure to dynamically tune resonance frequencies for effective noise attenuation.
William Kaal, Michael M. Becker, Sarah C. L. Fischer   +2 more
wiley   +1 more source