Technological Advances in Science, Medicine, and Engineering 2025

A special issue of Technologies (ISSN 2227-7080).

Deadline for manuscript submissions: 31 January 2026 | Viewed by 2935

Special Issue Editors


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Guest Editor
Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1065 Military Trail, Scarborough, ON M1C 1A4, Canada
Interests: green chemistry; sustainable development; hydrogels; aerogels; water treatment; technology to recover nutrients from waste biomass; nanomaterials; nanocomposites; agriculture; medicinal and synthetic organic chemistry

E-Mail Website
Guest Editor
Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada
Interests: wireless communications; signal processing; optical–wireless communications; machine learning; IoT; tracking and localization; integrated sensing and localization; VANETs; aerial–terrestrial networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to showcase papers that emerged from the 29th Technological Advances in Science, Medicine, and Engineering (TASME) In-Person/Zoom Hybrid Conference (https://tasmeconference.org/) on July 5–6, 2025 at the University of Toronto’s Scarborough campus, focusing on technological advances in science, medicine, and engineering. Subject areas include, but are not limited to, the following:

  1. Civil and environmental engineering;
  2. Electrical, electronic, and communication engineering;
  3. Mechanical, aerospace, marine, and industrial engineering;
  4. Materials and (renewable) energy technology;
  5. Cancer and nervous systems;
  6. Immunity, lunch infection, and COVID;
  7. Internal medicine, mental health, public health, and healthcare systems;
  8. Life and environmental sciences;
  9. Physical sciences, tech innovation, and IoT applications;
  10. Medical technology, biotech and pharma, and drug design;
  11. Information technology (cybersecurity, data science, and e-learning);
  12. Machine/deep learning and artificial intelligence.

In addition, we will also include original research and review papers on these topics that were not part of the conference.

Dr. Nirusha Thavarajah
Prof. Dr. Xavier Fernando
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Technologies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • information systems
  • artifical intelligence
  • medical science
  • immunology
  • material science
  • intelligent communications
  • engineering
  • biosystems engineering
  • urban forestry
  • flow cytometry

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Related Special Issue

Published Papers (2 papers)

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Research

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26 pages, 3749 KB  
Article
Synthesis of Pectin Hydrogels from Grapefruit Peel for the Adsorption of Heavy Metals from Water
by Vinusiya Vigneswararajah, Nirusha Thavarajah and Xavier Fernando
Technologies 2025, 13(9), 403; https://doi.org/10.3390/technologies13090403 - 5 Sep 2025
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Abstract
The increasing presence of heavy metals in aquatic environments, driven by the production of industrial waste and consumer products, poses serious environmental and health risks due to their toxicity and persistence. Copper (Cu(II)) and nickel (Ni(II)) are particularly harmful, with high concentrations linked [...] Read more.
The increasing presence of heavy metals in aquatic environments, driven by the production of industrial waste and consumer products, poses serious environmental and health risks due to their toxicity and persistence. Copper (Cu(II)) and nickel (Ni(II)) are particularly harmful, with high concentrations linked to neurological, dermatological and carcinogenic effects. This proof-of-concept study explores the synthesis of sustainable hydrogels derived from grapefruit peel (biosorbents) for the adsorption of Cu(II) and Ni(II) from aqueous solutions. Pectin was extracted from the peels and was used to synthesize pectin-based hydrogels (PH) and pectin hydrogel metal–organic frameworks (PHM composites). The hydrogels were characterized using FT-IR, SEM, diameter size and water absorption capacity. Lyophilized hydrogels were significantly smaller than their wet counterparts, and adsorption performance was analyzed using FAAS. PHs demonstrated high Cu(II) removal efficiency, achieving 95.11% adsorption and 97.75 mg/g capacity at pH 5. PHM composites showed comparable Cu(II) adsorption with a maximum capacity of 67.53 mg/g. Notably, PHs also exhibited rapid Ni(II) adsorption, reaching 92.62% efficiency and 28.189 mg/g capacity within one minute. These findings highlight the potential of pectin-based hydrogels as an effective, low-cost and environmentally friendly method for heavy metal remediation in water. Full article
(This article belongs to the Special Issue Technological Advances in Science, Medicine, and Engineering 2025)
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Review

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36 pages, 1231 KB  
Review
Overview of Existing Multi-Criteria Decision-Making (MCDM) Methods Used in Industrial Environments
by Tanya Avramova, Teodora Peneva and Aleksandar Ivanov
Technologies 2025, 13(10), 444; https://doi.org/10.3390/technologies13100444 - 1 Oct 2025
Viewed by 1042
Abstract
The selection of an appropriate technological process is essential to achieve optimal results in manufacturing companies. This affects quality, efficiency and competitiveness. In the modern industry, multi-criteria decision-making (MCDM) methods are increasingly used to evaluate, optimize and solve various manufacturing challenges. In this [...] Read more.
The selection of an appropriate technological process is essential to achieve optimal results in manufacturing companies. This affects quality, efficiency and competitiveness. In the modern industry, multi-criteria decision-making (MCDM) methods are increasingly used to evaluate, optimize and solve various manufacturing challenges. In this review article, existing methodologies and patents related to optimization and decision making are investigated. The main characteristics and applications of the methods are outlined. The purpose of this article is to provide a systematic review and evaluation of the main MCDM methods used in industrial practice, including through an analysis of relevant methodologies and patents. The methodology involves a structured literature and patent review, focusing on applications of widely used MCDM techniques such as the AHP (analytic hierarchy process), ANP (analytic network process), FUCOM (full consistency method), TOPSIS (technique for order preference by similarity to ideal solution), and VIKOR (višekriterijumsko kompromisno rangiranje). The analysis outlines each method’s strengths, limitations and areas of applicability. Special attention is given to the potential of the FUCOM for process evaluation in manufacturing. The findings are intended to guide researchers and practitioners in selecting appropriate decision-making tools based on specific industrial contexts and objectives. In conclusion, from the comparative analysis made, the methodologies reveal their advantages and disadvantages as well as limitations that arise in their application. Full article
(This article belongs to the Special Issue Technological Advances in Science, Medicine, and Engineering 2025)
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