Evidence map›Paper›PMID 34767127›Full record

ArticleJournal of fluorescence2022

Experimental Analysis on the Optimal Excitation Wavelength for Fine-Grained Identification of Refined Oil Pollutants on Water Surface Based on Laser-Induced Fluorescence.

Ming Xie, Yunpeng Jia, Ying Li, Xiaohua Cai, Kai Cao

Abstract read
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In one paragraph

Article in Journal of fluorescence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 44% 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

2 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
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

5 authors at 1 institution in 1 country.

Ming XieNavigation College, Dalian Maritime University, Dalian, China.
Yunpeng JiaNavigation College, Dalian Maritime University, Dalian, China.
Ying LiNavigation College, Dalian Maritime University, Dalian, China. yldmu@dlmu.edu.cn.ORCID http://orcid.org/0000-0002-4318-591X
Xiaohua CaiNavigation College, Dalian Maritime University, Dalian, China.
Kai CaoNavigation College, Dalian Maritime University, Dalian, China.
Dalian Maritime University · CN

Funding

China National Key R&D Program 2020YFE0201500Liaoning Revitalization Talents Program XLYC2001002Postdoctoral Research Foundation of China 2020M670730
6 · The paper itself

Abstract

Laser-induced fluorescence (LIF) is an effective and all-weather oil spill identification method that has been widely applied for oil spill monitoring. However, the distinguishability on oil types was seldom considered while selecting the excitation wavelengths. This study is intended to find the optimal excitation wavelength for fine-grained classification of refined oil pollutants using LIF by comparing the distinguishability of fluorometric spectra under various excitation wavelengths on some typical types of refined oil samples. The results show that the fluorometric spectra of oil samples significantly vary under different excitation wavelengths, and the four types of oil applied in this study are most likely to be distinguished under the excitation wavelengths of 395 nm and 420 nm. This study is expected to improve the ability of oil types identification using LIF method without increasing time or other cost, and also provide theoretical basis for the development of portable LIF devices for oil spill types identification.

Indexed as

Fine-grained classificationFluorometric spectra analysisLaser-induced fluorescenceOil spillOil types classification

Identifiers

PMID34767127
OpenAlexW3192805614

What OpenQuestion holds

Textmetadata
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.