Evidence map›Paper›PMID 35056182›Full record

ArticleMicromachines2021

Electrically Tunable Lens (ETL)-Based Variable Focus Imaging System for Parametric Surface Texture Analysis of Materials.

Jorabar Singh Nirwan, Shan Lou, Saqib Hussain, Muhammad Nauman, Tariq Hussain, Barbara R Conway, Muhammad Usman Ghori

Abstract read
In one paragraph

Article in Micromachines, 2021. 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
–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

2 citing papers in PubMed.

  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

7 authors.

Jorabar Singh NirwanDepartment of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK.
Shan LouEPSRC Future Metrology Hub, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK.ORCID 0000-0002-8426-5596
Saqib HussainDepartment of Mathematics and Physics, Texas A&M International University, Laredo, TX 78041, USA.
Muhammad NaumanDivision of Mathematical and Physical Sciences, Institute of Science and Technology, 3400 Klosterneuburg, Austria.ORCID 0000-0002-2111-4846
Tariq HussainSystem Engineering Department, Military Technological College, Muscat 111, Oman.
Barbara R ConwayDepartment of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK.ORCID 0000-0001-5570-3318
Muhammad Usman GhoriDepartment of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield HD1 3DH, UK.ORCID 0000-0003-1884-6648

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrically tunable lenses (ETLs) are those with the ability to alter their optical power in response to an electric signal. This feature allows such systems to not only image the areas of interest but also obtain spatial depth perception (depth of field, DOF). The aim of the present study was to develop an ETL-based imaging system for quantitative surface analysis. Firstly, the system was calibrated to achieve high depth resolution, warranting the accurate measurement of the depth and to account for and correct any influences from external factors on the ETL. This was completed using the Tenengrad operator which effectively identified the plane of best focus as demonstrated by the linear relationship between the control current applied to the ETL and the height at which the optical system focuses. The system was then employed to measure amplitude, spatial, hybrid, and volume surface texture parameters of a model material (pharmaceutical dosage form) which were validated against the parameters obtained using a previously validated surface texture analysis technique, optical profilometry. There were no statistically significant differences between the surface texture parameters measured by the techniques, highlighting the potential application of ETL-based imaging systems as an easily adaptable and low-cost alternative surface texture analysis technique to conventional microscopy techniques.

Indexed as

electrically tunable lenshypromellosematerialspharmaceutical tabletsurface roughnesssurface texturesurface topographyvariable focus imaging

Identifiers

PMID35056182
PMCPMC8778955

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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.