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    Item type:Publication,
    Optimization of Textile SCs Design and Planning: A Bibliometric Analysis
    (Springer Nature Switzerland, 2025)
    Leandro L. Lorente-Leyva
    ;
    María del Mar Eva Alemany
    ;
    Diego H. Peluffo-Ordóñez
    This study provides a comprehensive overview of the current state of research in the design and operations planning optimization of textile supply chains. This paper includes a bibliometric analysis of 42 selected papers that reveals a focus on tactical decision-making, with an emphasis on the manufacturing stage. The bibliometric analysis exposes the influence of prominent authors and journals in this field. A co-occurrence map graphically represents the keywords used in the papers. The literature review results suggest that models are primarily developed in a deterministic context, with a focus on cost minimization and limited use of artificial intelligence techniques. The solution context exhibits a preference for static approaches and periodic replanning.
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    Effect of Optimizing the Black Plum Peel Extract as Natural Antioxidant and Storage Time on Oxidative Stability of Sunflower Oil
    (United Scientific Group, 2024-07-02)
    Toktam Mohammadi-Moghaddam
    ;
    Mohaddeseh Kariminejad
    ;
    Afsaneh Morshed
    ;
    VALDES ALARCON, MARCOS EDUARDO  
    Today, the use of natural antioxidants is attracting the attention of consumers. Black plum peel is the waste of plum processing and is the source of antioxidants. In this research, the effect of black plum peel extract (BPPE) (0, 400, and 800 ppm) as a natural antioxidant and storage time (0, 8, and 16 days) on the oxidative stability parameters (peroxide value, free fatty acids, thiobarbituric acid, conjugated dienes, and carbonyl value) of sunflower oil with response surface methodology (RSM) method was studied. The predominant polyunsaturated and monounsaturated fatty acid (MUFA) in sunflower oil were C18:2C (63.77%) and C18:1C (24.86%), respectively. Increasing the storage time up to 8 days caused to increase the peroxide value and thiobarbituric acid and there were reduced from 8 to 16 days (p < 0.05). Increasing the storage time increased the conjugated dienes sharply, however it was reduced very slow by increasing the BPPE (p < 0.05). Free fatty acid content and carbonyl value of the oil increased non-linearly by the storage time (p < 0.05). The best conditions for sunflower oil were 3 days and 472.73 ppm black plum peel concentration (R2 = 0.71). The RSM was usable for determining the optimal concentration of BPPE for oxidative stability of sunflower oil.
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    Response surface optimization and support vector regression modeling of microwave-assisted essential oil extraction from cumin seeds
    (Elsevier BV, 2024-02)
    Ali Asif Khan
    ;
    Sadaf Zaidi
    ;
    Fazil Qureshi
    ;
    Mohammad Yusuf
    ;
    Abdullah A. Al-Kahtani
    The current research involved creating models using Response Surface Methodology (RSM) and Support Vector Regression (SVR) to forecast the amount of extractable essential oil that can be obtained from powdered cumin seeds. Influence of microwave power (140–280–420–560–700 W), amount of water (500–600–700–800–900 ml), duration of distillation (30–45–60–75–90 min) and soak time (15–30–45–60–75 min) on essential oil yield were investigated. Microwave Assisted Extraction (MAE) allowed higher recoveries compared to conventional Soxhlet extraction, without altering the chemical components of the extract. A five-level four FCC experimental design was developed using Minitab (15.1.20.0). A total of 31 runs were performed in microwave-assisted extraction apparatus. Experimental data obtained was then used for developing RSM and SVR models for the prediction of the yield of essential oil. The optimum conditions for maximum yield of cumin oil were given by RSM. Maximum yield of 3.4 ml (0.017 ml/g) was found at 140 W of microwave power, 500 ml of water, 90 min duration of distillation, and 15 min of soak time. In this work, epsilon SVR with RBF kernel was used. The grid search (depth-first search) methodology was applied for tuning the values of epsilon, gamma, and cost using the LIBSVM module on the MATLAB interface. The statistical parameters namely, average absolute relative error (AARE), coefficient of determination (R2), standard deviation (SD), and root mean square error (RMSE) were selected as the performance parameters. The developed SVR model was compared with the RSM model. The AARE values of 2.27% and 1.29%, R2 values of 0.86 and 0.99, SD values of 1.73 and 0.29, and RMSE values of 0.0284 and 0.0132 were obtained for RSM and SVR models respectively. It is found that SVR is more accurate and better tool for modeling of MAE process.