Evidence map›Paper›PMID 25345502›Full record

ArticleScientific reports2014

An MFC-based online monitoring and alert system for activated sludge process.

Gui-Hua Xu, Yun-Kun Wang, Guo-Ping Sheng, Yang Mu, Han-Qing Yu

Abstract read
In one paragraph

Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Gui-Hua Xu1] CAS Key Laboratory of Urban Pollutant Conversion, Department of Chemistry, University of Science and Technology of China, Hefei 230026, China [2] Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China.
Yun-Kun WangCAS Key Laboratory of Urban Pollutant Conversion, Department of Chemistry, University of Science and Technology of China, Hefei 230026, China.
Guo-Ping ShengCAS Key Laboratory of Urban Pollutant Conversion, Department of Chemistry, University of Science and Technology of China, Hefei 230026, China.
Yang MuCAS Key Laboratory of Urban Pollutant Conversion, Department of Chemistry, University of Science and Technology of China, Hefei 230026, China.
Han-Qing YuCAS Key Laboratory of Urban Pollutant Conversion, Department of Chemistry, University of Science and Technology of China, Hefei 230026, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, based on a simple, compact and submersible microbial fuel cell (MFC), a novel online monitoring and alert system with self-diagnosis function was established for the activated sludge (AS) process. Such a submersible MFC utilized organic substrates and oxygen in the AS reactor as the electron donor and acceptor respectively, and could provide an evaluation on the status of the AS reactor and thus give a reliable early warning of potential risks. In order to evaluate the reliability and sensitivity of this online monitoring and alert system, a series of tests were conducted to examine the response of this system to various shocks imposed on the AS reactor. The results indicate that this online monitoring and alert system was highly sensitive to the performance variations of the AS reactor. The stability, sensitivity and repeatability of this online system provide feasibility of being incorporated into current control systems of wastewater treatment plants to real-time monitor, diagnose, alert and control the AS process.

Indexed as

Bioelectric Energy SourcesOnline SystemsSewageWaste ManagementSewage

Identifiers

PMID25345502
PMCPMC4209466

What OpenQuestion holds

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Registered trials

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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.