Evidence map›Paper›PMID 35069717›Full record

ArticleComputational intelligence and neuroscience2022

Broken-Edge Decision-Making Strategy for COVID-19 over Air Railway Composite Network.

Hui Sun, Yicong Qin, Zhicheng Mu, Rui Wang

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hui SunCollege of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China.ORCID https://orcid.org/0000-0001-7199-9059
Yicong QinCollege of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China.ORCID https://orcid.org/0000-0002-2339-9304
Zhicheng MuCollege of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China.ORCID https://orcid.org/0000-0003-3018-3154
Rui WangCollege of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China.ORCID https://orcid.org/0000-0003-4452-6795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to control the spread of the COVID-19 virus, this study proposes an ARCN-SUTS (air railway composite network susceptible-untested-tested-susceptible) model based on the correlation characteristics of the air railway composite network in mainland China. Furthermore, this study also puts forward a broken-edge decision-making strategy for the purpose of making decision about the edge efficiently broken and avoiding the second outbreak of the virus spread to minimize the economic losses for railway and civil aviation companies. Finally, simulation results demonstrate that the proposed strategy can effectively control the spread of the virus with minimal economic losses.

Indexed as

COVID-19ChinaHumansSARS-CoV-2

Identifiers

PMID35069717
PMCPMC8767395

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.