Faculty of Technology and Metallurgy

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    Recent Advances in Textile Functionalization Using Essential Oil-Based-Microcapsules with Antimicrobial Properties
    (University of Ljubljana, 2025)
    Georgievska, Tamara
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    Trajkovikj, Stefan
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    Editor-in-Chief Tatjana Rijavec; Assistant Editor Tatjana Kreže; Associate Editors Matejka Bizjak, Katja Burger Kovič, Andrej Demšar, Mateja Kos Koklič, Alenka Pavko Čuden, Andreja Rudolf, Barbara Simončič, Dunja Šajn Gorjanc, Sonja Šterman, Brigita Tomšič;Executive Editor for Databases Irena Sajovic; International Editorial Board Matej Bračič, Maribor, SI Snježana Brnada, Zagreb, HR Andrea Ehrmann, Bielefeld, DE Petra Forte Tavčer, Ljubljana, SI Jelka Geršak, Maribor, SI Marija Gorjanc, Ljubljana, SI Lubos Hes, Moka, MU Aleš Hladnik, Ljubljana, SI Svjetlana Janjić, Banja Luka, BA Mateja Kert, Ljubljana, SI Dragana Kopitar, Zagreb, HR Yordan Kostadinov Kyoshev, Dresden, DE Petra Komarkova, Liberec, CZ Mateja Kos Koklič, Ljubljana, SI Mirjana Kostić, Beograd, RS Manja Kurečič, Maribor, SI Boris Mahltig, Niederrhein, DE Subhankar Maity, Kanpur, IN Małgorzata Matusiak, Łódź , PL Ida Nuramdhani, Bandung, ID Alenka Ojstršek, Maribor, SI Roshan Paul, Aachen, DE Tanja Pušić, Zagreb, HR Ivana Salopek Čubrić, Zagreb, HR Snežana Stanković, Beograd, RS Jovan Stepanović, Leskovac, RS Dunja Šajn Gorjanc, Ljubljana, SI Mohammad Tajul Islam, Dhaka, BD Antoneta Tomljenović, Zagreb, HR
    Antimicrobial textiles are functionalized textiles designed to inhibit or terminate the growth of microorganisms. In light of the increasing emphasis on eco-friendly processes, the application of essential oils presents a viable alternative to synthetic drugs (antibiotics). The aim of this study was to evaluate recent advances in microencapsulation methods of essential oils with antimicrobial activity that can be applied on medical textile for dermal use by employing the PRISMA methodology. Essential oils have been microencapsulated using various methods: coacervation, spray-drying, emulsion method and in situ polymerization. Among these, coacervation is still extensively utilized, though associated scale-up challenges persist. Many essential oils have demonstrated antibacterial properties against Gram-positive (Staphylococcus aureus, Bacillus subtilis) and Gram-negative (Pseudomonas aeruginosa, Escherichia coli, Klebsiella pneumoniae) bacteria, as well as antifungal activity (Candida albicans). The growth inhibition of these microorganisms was assessed in the presence of the following essential oils and their active substances with the highest biological-antimicrobial activity: cinnamon (transcinnamaldehyde), lime (α-terpineol, terpineol, and limonene), tea tree (terpinen-4-ol), rosemary (1,8-cineole and α-pinene), peppermint (l-menthol, menthone, methyl acetate and limonene), lavender (linalool and linalyl acetate), thyme (carvacrol) and clove (eugenol). The findings indicate that functionalized textile with microcapsules exhibits enhanced antibacterial activity against Gram-positive bacteria compared to Gram-negative bacteria (Escherichia coli), which could be attributed to the bacteria’s thick wall. However, there is a notable lack of data regarding cytotoxicity and the sensory evaluation of functionalized textile. The potential utilization of essential oils was explored in the development of eco-friendlier functionalized textile with antimicrobial properties. However, additional research is required to maximize the antimicrobial activity of microcapsules to overcome challenges in the scale-up to pilot process, and to improve the immobilization in textiles. Keywords: antimicrobial properties, sustainability, essential oils, microcapsules, textile functionalization
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    Smartphone-Based Digital Image Processing for Fabric Drape Assessment, Textiles, 2025, 5(4), 63; https://doi.org/10.3390/textiles5040063
    (MDPI, 2025)
    Emilija Toshikj, Nina Mladenovikj
    Fabric drape characterization is vital for textile performance and aesthetics, but the conventional Cusick method is labor-intensive and incompatible with digital workflows. This study assesses a smartphone-enabled digital image processing (DIP) method for fabric drape coefficient (DC) measurement, providing an accessible, low-cost alternative to the Cusick method. Draped specimens of light, medium, and heavy fabrics were imaged at three diameters (24, 30, and 36 cm) using a smartphone positioned at three vertical distances (22, 32, and 42 cm). DCs were determined through pixel-based analysis in Adobe Photoshop®, ImageJ®, and MATLAB®. Statistical comparison against the Cusick method employed F-tests for variance, two-sample t-tests for mean differences, and skewness analysis. No statistically significant differences were found between smartphone DIP (with either the iPhone or Samsung device) and Cusick measurements (p > 0.05). Neither imaging height nor software platform significantly influenced outcomes, though a 22 cm height consistently provided the most stable conditions. ImageJ® was identified as an effective open-source option for reliable analysis. The findings establish a reliable, cost-effective, and portable method for drape evaluation, reducing technical and economic barriers while aligning with Industry 4.0 digitalization. This approach enables broader adoption of reliable textile characterization across research, industry, and domains.
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    Item type:Publication,
    Smartphone-Based Digital Image Processing for Fabric Drape Assessment, Textiles, 2025, 5(4), 63; https://doi.org/10.3390/textiles5040063
    (Textiles, 2025)
    Emilija Toshikj, Nina Mladenovikj
    Fabric drape characterization is vital for textile performance and aesthetics, but the conventional Cusick method is labor-intensive and incompatible with digital workflows. This study assesses a smartphone-enabled digital image processing (DIP) method for fabric drape coefficient (DC) measurement, providing an accessible, low-cost alternative to the Cusick method. Draped specimens of light, medium, and heavy fabrics were imaged at three diameters (24, 30, and 36 cm) using a smartphone positioned at three vertical distances (22, 32, and 42 cm). DCs were determined through pixel-based analysis in Adobe Photoshop®, ImageJ®, and MATLAB®. Statistical comparison against the Cusick method employed F-tests for variance, two-sample t-tests for mean differences, and skewness analysis. No statistically significant differences were found between smartphone DIP (with either the iPhone or Samsung device) and Cusick measurements (p > 0.05). Neither imaging height nor software platform significantly influenced outcomes, though a 22 cm height consistently provided the most stable conditions. ImageJ® was identified as an effective open-source option for reliable analysis. The findings establish a reliable, cost-effective, and portable method for drape evaluation, reducing technical and economic barriers while aligning with Industry 4.0 digitalization. This approach enables broader adoption of reliable textile characterization across research, industry, and domains.
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    Tailoring multipurpose capabilities of jute (Corchorus) with a focus on the cleaner production and “zero waste” concept
    (Springer, 2025)
    Aleksandra Ivanovska
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    Marija Milošević
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    Željko Mravik
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    Zorica Svirčev
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    Thermoplastic Polyurethane/Polylactic Acid Blend Foams Loaded With Curcuma longa L. and Hypericum perforatum Extracts Towards Wound Dressing Applications
    (Wiley, 2025)
    Bužarovska, A., Petreska Stanoeva, J., Karamanolevski, P., Daniela Popa, A., Dinescu, S., Avérous L.
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    Valorization of tomato processing by-products: Predictive modeling and optimization for ultrasound-assisted lycopene extraction
    (Elsevier BV, 2024-11)
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    Stojchevski, Martin
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    Lycopene is a carotenoid highly valuable to the food, pharmaceutical, dye, and cosmetic industries, present in ripe tomatoes and other fruits with a distinctive red color. The main source of lycopene is tomato crops. This bioactive component can be successfully isolated from tomato processing waste, commonly called tomato pomace, mostly made from tomato skins, seeds, and some residual tomato tissue. The main investigative focus in this work was the application of green engineering principles in each stage of the optimized ultrasound-assisted extraction (UAE) of enzymatically treated tomato skins to obtain functional extracts rich in lycopene. The experimental plan was designed to determine the influence of studied operating parameters: enzymatic reaction time (60, 120, and 180 min), extraction time (0, 5, 10, 15, 30, 60, and 120 min), and temperature (25, 35 and 45 ℃) on lycopene yield. Process optimization was performed based on the yield of lycopene [1018, 1067, and 1120 mg/kg] achieved at optimal operating conditions. An artificial neural network (ANN) model was developed and trained for predictive modeling of the closed extraction system, with operating parameters used as input neurons and experimentally obtained values for lycopene content defined as the output neural layer. Applied ANN architecture provided a high correlation of experimental output with ANN-generated data (R=0.99914) with a model deviation error for the entire data set of RMSE=5.3 mg/kg. The k-Nearest Neighbor algorithm was introduced to predict lycopene yield using experimental key features: operating temperature, extraction time, and time of enzymatic treatment, split into training and testing sets with an 85/15 ratio. The model interpretation was conducted through the SHAP (SHapley Additive exPlanations) methodology.
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    ANN modeling and RSM optimization of ultrasound-assisted extraction of protodioscin-rich extracts from Tribulus terrestris L
    (Elsevier BV, 2024-12)
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    Dimitrievska, Isidora
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    Stojchevski, Martin
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    Tribulus terrestris L. is a herb renowned for its abundance of saponins, flavonoids, and alkaloids, which are utilized in treating various health conditions. Protodioscin functions by enhancing the conversion of testosterone into potent dihydrotestosterone, stimulating an increase in libido, red blood cell production from the bone marrow, and muscle development. Contemporary ultrasound-assisted-extraction (UAE) process employing green extraction solvents was selected to design the required separation system. The experimental plan was developed based on the independent operating variables - extraction time, operating temperature and solvent system composition in order to determine the influence of defined parameters and their interactions on the extraction yield and the presence of protodioscin. The 3D-RSM approach was introduced to determine the optimal values of studied independent variables in the area of maximal extraction yield. UAE process performed at optimal operating conditions generated maximal extraction yield (31 %, w/w) and protodioscin content of 5.9 mg/g dry plant matrix. Experimental data was used to develop an ANN for the defined extraction system using the operating variables values as the input matrix and observed yield as target matrix. Successfully designed and trained ANN generated high correlation (r = 0.9992) between observed data and predictive model' outputs, and MSE value of 0.29107.
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    A step towards tuning the jute fiber structure and properties by employing sodium periodate oxidation and coating with alginate
    (Elsevier, 2024-02)
    Aleksandra Ivanovska,
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    Marija Milošević,
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    Jelena Lađarević,
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    Tamara Matić,
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    Cantor’s Intersection Theorem in (3, 1, ∇)-G-metrizable spaces
    (Codema, 2023)
    Dimovski, Pavel
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    Dimovski, Tomi
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    ON SEQUENCE CONVERGENCE IN (3, j)-METRIC SPACES, j ∈ {1, 2}
    (Matematicki Bilten, 2024)
    Dimovski, Pavel
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    Dimovski, Tomi
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    Dimovski, Donco