Results 41 to 50 of about 44,636 (300)

Neural Active Manifolds: Nonlinear Dimensionality Reduction for Uncertainty Quantification

Journal of Scientific Computing
Abstract We present a new approach for nonlinear dimensionality reduction, specifically designed for computationally expensive mathematical models. We leverage autoencoders to discover a one-dimensional neural active manifold (NeurAM) capturing the model output variability ...
Andrea Zanoni, Gianluca Geraci, Matteo Salvador, Alison L. Marsden, Daniele E. Schiavazzi   +4 more
openaire   +3 more sources

Salmonella lipopolysaccharide‐containing supported lipid bilayers as platforms to study bacteriophage interactions

FEBS Letters, EarlyView.
We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace, Alyssa Borges, Charles Arnaud, Tove Karlsson, Nina K. Bröker, Stefanie Barbirz, Marta Bally   +6 more
wiley   +1 more source

Approach to prove the efficiency of the Monte Carlo method combined with the elementary effect method to quantify uncertainty of a beam structure with piezo-elastic supports

, 2022
S.441-455In this paper, a new approach is presented to prove the efficiency of the direct Monte Carlo method combined with the Elementary Effect method to quantify structural data uncertainty under uncertain input parameters of a beam structure. Normally,
Li, S., Platz, R., Goetz, B., Schaeffner, M.   +3 more
core   +1 more source

A Hybrid Dropout Method for High-Precision Seafloor Topography Reconstruction and Uncertainty Quantification

Applied Sciences
Seafloor topography super-resolution reconstruction is critical for marine resource exploration, geological monitoring, and navigation safety. However, sparse acoustic data frequently result in the loss of high-frequency details, and traditional deep ...
Xinye Cui, Houpu Li, Yanting Yu, Shaofeng Bian, Guojun Zhai   +4 more
doaj   +1 more source

Three phosphatase families form a community: The phosphohydrolases that act upon inositol pyrophosphates

FEBS Letters, EarlyView.
Inositol pyrophosphates are energy‐rich signaling molecules that perform critical functions in cells. Three different families of phosphatases hydrolyze the β phosphate of the inositol pyrophosphate molecules: two have narrow specificities and one is promiscuous.
Ronda J. Rolfes
wiley   +1 more source

Using Bayesian analysis to quantify and reduce uncertainty in experimental measurements — A narrow-angle radiometer case study

Measurement: Energy
Formal uncertainty analysis is an important but sometimes overlooked component of experimental work. Without quantified uncertainty, it is difficult to draw definitive conclusions from the experimental data, as a lack of formal uncertainty analysis ...
Teri S. Draper, Jennifer P. Spinti, Philip J. Smith, Terry A. Ring, Eric G. Eddings   +4 more
doaj   +1 more source

Solution-Space-Reduction-Based Evidence Theory Method for Stiffness Evaluation of Air Springs with Epistemic Uncertainty

Mathematics, 2023
In the Dempster–Shafer evidence theory framework, extremum analysis, which should be repeatedly executed for uncertainty quantification (UQ), produces a heavy computational burden, particularly for a high-dimensional uncertain system with multiple joint ...
Shengwen Yin, Keliang Jin, Yu Bai, Wei Zhou, Zhonggang Wang   +4 more
doaj   +1 more source

Modelling stem cell differentiation related processes—A practical overview for biologists

FEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar, Xinqi Yan, Lucas Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source

Real-time data assimilation and control on mechanical systems under uncertainties

Advanced Modeling and Simulation in Engineering Sciences, 2021
This research work deals with the implementation of so-called Dynamic Data-Driven Application Systems (DDDAS) in structural mechanics activities. It aims at designing a real-time numerical feedback loop between a physical system of interest and its ...
Paul-Baptiste Rubio, Ludovic Chamoin, François Louf   +2 more
doaj   +1 more source

Effect Of Mechanism Reduction On The Uncertainty Quantification Of Chemical Kinetics For Mild Combustion [PDF]

SIAM Sixteenth International Conference on Numerical Combustion, 2017
This work has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska- Curie grant agreement No 643134.
Fürst, Magnus, Frassoldati, Alessio, Parente, Alessandro   +2 more
openaire   +2 more sources