Evidence map›Paper›PMID 36396806›Full record

ArticleScientific reports2022

Comprehensive evaluation model for health grade of multi-component compound release materials based on fuzzy comprehensive evaluation with grey relational analysis.

Qifan Wang, Jianhui Du, Jun Shen, Yiming Wang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 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
0.7field-weighted citation impact, top 37% of its field
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, 4 citations in OpenAlex.

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 at 3 institutions in 1 country.

Qifan Wang *College of Material Science and Engineering, Northeast Forestry University, Harbin, 150040, China.
Jianhui Du *Beijing Baidu Netcom Science and Technology Co., Ltd, Beijing, 100085, China.
Jun ShenCollege of Material Science and Engineering, Northeast Forestry University, Harbin, 150040, China. shenjunr@126.com.
Yiming WangDepartment of Building Science, Tsinghua University, Beijing, 100084, China.
Tsinghua University · CNBaidu (China) · CNNortheast Forestry University · CN

Funding

National Natural Science Foundation of China 31971582
6 · The paper itself

Abstract

The selection of materials is a complex and elusive process due to the multiple factors related to health. For the effective selection of materials, a comprehensive model for evaluating the health grade of materials was proposed with the mathematical method of the fuzzy comprehensive evaluation (FCE) and grey relational analysis (GRA). A health evaluation procedure scheme of the AgBB as well as standards of the forestry industry of the People's Republic of China and standards of the health industry of the People's Republic of China were referred to during the process. Based on Qt technology, a computer program was developed to calculate the compound comprehensive evaluation models. The data of Choerospondias axillaris with different lacquers were used as practical examples firstly, and then, the emission and odor characteristics of Xylosma racemosum (Sieb. et Zucc.) Miq. with PU, UV, and waterborne coating were explored with the technology of GC-MS/O. Results showed that: a total of 21 odorants were identified from Xylosma racemosum with PU, UV, and waterborne coating. The health grade of three Xylosma racemosum samples was UV > waterborne > PU, with the health grade of UV coating being "A", and the boards with PU and the waterborne coating were "N", with a fuzzy comprehensive index of P

Indexed as

Air Pollution, IndoorChinaGas Chromatography-Mass SpectrometryHumansOdorants

Identifiers

PMID36396806
PMCPMC9672096
OpenAlexW4309515539

What OpenQuestion holds

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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.