Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution.

Mingzhi Wang, Yushi Liu, Beimeng Qi, Wei Wang

Abstract read

In one paragraph

Article in Powder technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mingzhi WangSchool of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China.

Yushi LiuSchool of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China.

Beimeng QiCollege of Quality & Safety Engineering, China Jiliang University, Hangzhou 310018, China.

Wei WangSchool of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computational analysis of virus dynamics provides a non-contact environment for the study of the vital object. Cluster modelling is an essential step to investigate the properties of a group of viruses, and an automatic approach is required for massive 3D data processing. The morphological complexity of individual virus limits the application of smooth function algorithms with a regular-shaped assumption. This paper proposed a voxel-based redistribution approach to generate the virus cluster with COVID-19 input automatically. Representative elementary volume analysis was performed to address the statistical influence from the digital sample size. Coordination number analysis and surface density measurement were conducted with COVID-19 input and spherical input for comparison. The proposed approach is in natural compatibility with the lattice Boltzmann method for fluid dynamics analysis. A virtual permeation simulation was performed with the COVID-19 cluster and spherical cluster to demonstrate the necessity to include spike protein structure in the cluster modelling.

Indexed as

COVID-19Irregular-shaped particleParticle distribution simulationRepresentative elementary volumeVoxel-based computation

Identifiers

PMID36313254

DOI10.1016/j.powtec.2021.05.083

PMCPMC9588143

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.