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Cellular Level In-silico Modeling of Blood Rheology with An Improved Material Model for Red Blood Cells

Overview of attention for article published in Frontiers in Physiology, August 2017
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Title
Cellular Level In-silico Modeling of Blood Rheology with An Improved Material Model for Red Blood Cells
Published in
Frontiers in Physiology, August 2017
DOI 10.3389/fphys.2017.00563
Pubmed ID
Authors

Gábor Závodszky, Britt van Rooij, Victor Azizi, Alfons Hoekstra

Abstract

Many of the intriguing properties of blood originate from its cellular nature. Therefore, accurate modeling of blood flow related phenomena requires a description of the dynamics at the level of individual cells. This, however, presents several computational challenges that can only be addressed by high performance computing. We present Hemocell, a parallel computing framework which implements validated mechanical models for red blood cells and is capable of reproducing the emergent transport characteristics of such a complex cellular system. It is computationally capable of handling large domain sizes, thus it is able to bridge the cell-based micro-scale and macroscopic domains. We introduce a new material model for resolving the mechanical responses of red blood cell membranes under various flow conditions and compare it with a well established model. Our new constitutive model has similar accuracy under relaxed flow conditions, however, it performs better for shear rates over 1,500 s(-1). We also introduce a new method to generate randomized initial conditions for dense mixtures of different cell types free of initial positioning artifacts.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 97 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 22%
Researcher 11 11%
Student > Master 10 10%
Student > Bachelor 9 9%
Student > Doctoral Student 5 5%
Other 16 16%
Unknown 25 26%
Readers by discipline Count As %
Engineering 26 27%
Computer Science 8 8%
Physics and Astronomy 5 5%
Agricultural and Biological Sciences 4 4%
Chemistry 3 3%
Other 10 10%
Unknown 41 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 August 2017.
All research outputs
#20,441,465
of 22,996,001 outputs
Outputs from Frontiers in Physiology
#9,468
of 13,754 outputs
Outputs of similar age
#277,089
of 317,618 outputs
Outputs of similar age from Frontiers in Physiology
#200
of 274 outputs
Altmetric has tracked 22,996,001 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,754 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,618 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 274 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.