Results 201 to 210 of about 14,700,185 (245)

Evaluation of Dried Plasma Spot‐Based Quantification of Glial Fibrillary Acidic Protein as a Disease‐Associated Biomarker in Neuromyelitis Optica Spectrum Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the diagnostic accuracy of glial fibrillary acidic protein (GFAP) measured in dried plasma spots versus conventional plasma‐ and serum‐GFAP testing for assessment of disease severity in aquaporin‐4 immunoglobulin G–positive neuromyelitis optica spectrum disorder (AQP4‐IgG+ NMOSD).
Felix Wohlrab, Evelyn Alvarez, Roua Hamdi, Bingqing Zhang, Hayeun Ji, Niyati Jhaveri, Patrick Schindler, Pedro Sanchez, Pia S. Sperber, Tanja Schmitz‐Hübsch, Frederike C. Oertel, Nisa Vorasoot, Najib Kissani, Falko Böhringer, Jens Kuhle, Anne‐Katrin Pröbstel, Xiao‐Jun Ma, Péter Körtvelyessy, Patrick Waters, Friedemann Paul   +19 more
wiley   +1 more source

Modeling Progressive Brain Volume Losses in Chronic Moderate Severe Traumatic Brain Injury: Extensive, but Attenuating

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Progressive brain atrophy has now been widely observed in the chronic stages of moderate–severe traumatic brain injury (msTBI), but there is only coarse information regarding its prevalence and magnitude, and whether rate of atrophy accelerates or attenuates across time. We examined these questions in a Canadian inception cohort from
Robin E. A. Green, Brenda Colella, Alana Changoor, David J. Mikulis, Adrienne Li, Kadeen Johns, Georges A. Monette   +6 more
wiley   +1 more source

Bayesian Operator Inference for Data-Driven Reduced-Order Modeling [PDF]

Computer Methods in Applied Mechanics and Engineering, 2022
This work proposes a Bayesian inference method for the reduced-order modeling of time-dependent systems. Informed by the structure of the governing equations, the task of learning a reduced-order model from data is posed as a Bayesian inverse problem ...
Mengwu Guo, Shane A McQuarrie, Karen Willcox   +2 more
exaly   +4 more sources

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Reduced order modeling in iTOUGH2

Computers & Geosciences, 2014
The inverse modeling and uncertainty quantification capabilities of iTOUGH2 are augmented with reduced order models (ROMs) that act as efficient surrogates for computationally expensive high fidelity models (HFMs). The implementation of the ROM capabilities involves integration of three main computational components.
George Shu Heng Pau, Yingqi Zhang, Stefan Finsterle, Haruko M. Wainwright, Jens T. Birkholzer   +4 more
openaire   +2 more sources

Reduced Order and Surrogate Models for Gravitational Waves

Living Reviews in Relativity, 2022
AbstractWe present an introduction to some of the state of the art in reduced order and surrogate modeling in gravitational-wave (GW) science. Approaches that we cover include principal component analysis, proper orthogonal (singular value) decompositions, the reduced basis approach, the empirical interpolation method, reduced order quadratures, and ...
Aaron Villanueva, Manuel Tiglio
exaly   +5 more sources

On Synthesis of Reduced Order Models

2011
A framework for model reduction and synthesis is presented, which enables the re-use of reduced order models in circuit simulation. Two synthesis techniques are considered for obtaining the circuit representation (netlist) of the reduced model: (1) by means of realizing the reduced transfer function and (2) by unstamping the reduced system matrices ...
Ionutiu, R., Rommes, J.
openaire   +1 more source

Centroidal Voronoi Tessellation-Based Reduced-Order Modeling of Complex Systems

SIAM Journal of Scientific Computing, 2006
A reduced-order modeling methodology based on centroidal Voronoi tessellations (CVTs) is introduced. CVTs are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi ...
Hyung-Chun Lee, Max Gunzburger, John Burkardt   +2 more
exaly   +1 more source

Reduced-order modeling for hyperthermia control

IEEE Transactions on Biomedical Engineering, 1992
This paper analyzes the feasibility of using reduced-order modeling techniques in the design of multiple-input, multiple-output (MIMO) hyperthermia temperature controllers. State space thermal models are created based upon a finite difference expansion of the bioheat transfer equation model of a scanned focused ultrasound system (SFUS).
J. Kyle Potocki, Hal S. Tharp
openaire   +3 more sources

Reduced-Order Models for MEMS Applications

Nonlinear Dynamics, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nayfeh, Ali H., Younis, Mohammad I., Abdel-Rahman, Eihab M.   +2 more
openaire   +2 more sources

Reduced-Order Modeling

2014
In this chapter, the full-order state-space models presented in Chap. 3 are reduced in order and parametrized in the main parameters of the flight envelope. Order reduction is achieved by a multistep procedure: A modal reduction is followed by a reduction of the complete aeroelastic model and finally a balanced reduction is performed.
M. Valášek, Z. Šika, T. Vampola, S. Hecker   +3 more
openaire   +1 more source