Evidence map›Paper›PMID 34072868›Full record

ArticlePolymers2021

An Empirical Model for Predicting Biodegradation Profiles of Glycopolymers.

Toma-Leonida Dragomir, Ana-Maria Pană, Valentin Ordodi, Vasile Gherman, Gabriela-Alina Dumitrel, Sorin Nanu

Abstract read
In one paragraph

Article in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Toma-Leonida DragomirFaculty of Automation and Computing, Politehnica University Timişoara, 2 Vasile Parvan bvd., 300223 Timişoara, Romania.
Ana-Maria PanăFaculty of Industrial Chemistry and Environmental Engineering, Politehnica University Timişoara, 6 Vasile Parvan bvd., 300223 Timişoara, Romania.
Valentin OrdodiFaculty of Industrial Chemistry and Environmental Engineering, Politehnica University Timişoara, 6 Vasile Parvan bvd., 300223 Timişoara, Romania.
Vasile GhermanFaculty of Civil Engineering, Politehnica University Timişoara, 2 Traian Lalescu str., 300223 Timişoara, Romania.
Gabriela-Alina DumitrelFaculty of Industrial Chemistry and Environmental Engineering, Politehnica University Timişoara, 6 Vasile Parvan bvd., 300223 Timişoara, Romania.
Sorin NanuFaculty of Automation and Computing, Politehnica University Timişoara, 2 Vasile Parvan bvd., 300223 Timişoara, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pollution caused by plastic materials has a great impact on the environment. The biodegradation process is a good treatment solution for common polymers and biodegradation susceptible ones. The present work introduces new insight into the biodegradation process from a mathematical point of view, as it envisions a new empirical model for this complex process. The model is an exponential function with two different time constants and a time delay, which follows the weight loss profile of the polymer during the biodegradation process. Moreover, this function can be generated as the output variable of a dynamic exogenous system described through state equations. The newly developed models displayed a good fit against the experimental data, as shown by statistical indicators. In addition, the new empirical model was compared to kinetics models available in the literature and the correlation coefficients were closest to 1 for the new empirical model in all discussed cases. The mathematical operations were performed in the MATLAB Simulink environment.

Indexed as

dynamic nonlinear systemempirical modelglycopolymer biodegradationmodel accuracy

Identifiers

PMID34072868
PMCPMC8199137

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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.