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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Towards Robust Hemolysis Modeling with Uncertainty Quantification: A Universal Approach to Address Experimental Variance

Research datakeyboard_double_arrow_right Dataset 25 Jul 2024Publisher:Zenodo
Authors: Christopher, Christopher; Neidlin, Michael; Steinseifer, Ulrich;

doi: 10.5281/zenodo.12820263 , 10.5281/zenodo.12820264

Towards Robust Hemolysis Modeling with Uncertainty Quantification: A Universal Approach to Address Experimental Variance

Abstract

This repository contains the implementation of Robust Hemolysis Modeling with Uncertainty Quantification: A Universal Approach to Address Experimental Variance. The provided Python script demonstrates the construction of the MCMC (Markov Chain Monte Carlo) method and illustrates how to use MCMC for generating hemolysis distributions. Please note that the actual hemolysis calculations should be performed using your preferred CFD (Computational Fluid Dynamics) software. If there are any questions, please contact: blum@ame.rwth-aachen.de 

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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