Results 61 to 70 of about 15,278,073 (285)
Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Evaluation of Errors in Reduced Order Modeling
Transactions of the Society of Instrument and Control Engineers, 1999 The purpose of the paper is to make a comparison between the equation errors and the output errors which are used as criteria for measuring modeling errors in system identification. In many practical situations real systems have high system orders which are often unknown, and reduced order models are used for estimating the parameters of the systems ...
IKEDA, Fujio +2 more
openaire +2 more sources
Reduced-order modeling for unsteady transonic flows around an airfoil [PDF]
, 2007 High-transonic unsteady flows around an airfoil at zero angle of incidence and moderate Reynolds numbers are characterized by an unsteadiness induced by the von Kármán instability and buffet phenomenon interaction.
Rémi Bourguet +5 more
core +1 more source
Reconstructing enzyme evolution by protein engineering
FEBS Letters, EarlyView.Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
wiley +1 more source
Dissipativity-Preserving Reduced-Order Modeling from Data
, 2023 Reduced-order modeling from data with dissipativity preservation is discussed in this talk. Employing the data informativity framework, the dissipativity of all systems consistent with noisy data can be characterized by a data-based linear matrix ...
Besselink, Bart; id_orcid +3 more
core +1 more source
A DeepONet multi-fidelity approach for residual learning in reduced order modeling
Advanced Modeling and Simulation in Engineering Sciences, 2023 In the present work, we introduce a novel approach to enhance the precision of reduced order models by exploiting a multi-fidelity perspective and DeepONets.
Nicola Demo +2 more
doaj +1 more source
Reduced-Order Modeling of the Fluidic Pinball [PDF]
, 2019 The fluidic pinball is a geometrically simple flow configuration with three rotating cylinders on the vertex of an equilateral triangle. Yet, it remains physically rich enough to host a range of interacting frequencies and to allow testing of control laws within minutes on a laptop.
Pastur, Luc +3 more
openaire +4 more sources
Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Reduced-Order Modeling of a Lithium-Ion Lithium Iron Phosphate Battery
Chemical Engineering Transactions, 2021 Battery energy storage systems are essential for stabilizing the intermittent power generation of renewable energy (RE) technologies. Their integration into RE systems is typically studied using energy systems modeling software that utilize either ...
Michael T. Castro, Joey D. Ocon
doaj +1 more source
Estimating flow fields with reduced order models
Heliyon, 2023 The estimation of fluid flows inside a centrifugal pump in realtime is a challenging task that cannot be achieved with long-established methods like CFD due to their computational demands. We use a projection-based reduced order model (ROM) instead.
Kamil David Sommer +4 more
openaire +4 more sources