Browsing by Author "Erkan G."

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    Development of antibacterial textiles by cyclodextrin inclusion complexes of volatile thyme active agents
    (John Wiley and Sons Ltd, 2022) Türkoğlu G.C.; Sarıışık A.M.; Erkan G.; Erden E.; Pazarlıoğlu N.
    The study aims to develop wash-resistant antibacterial cotton fabrics without using synthetic chemicals. Therefore, natural active agents of thyme, thymol and carvacrol were selected. The inclusion complexes were formed with β-cyclodextrin using kneading method which is a simple and reproducible method for the encapsulation with high production yield. Differential scanning calorimeter analysis showed that 1:1 and 1:2 β-CD: Guest Molecule (M:M) for thymol and carvacrol from different ratios studied has the highest complexation degree as 50% and 100%, respectively. It is also revealed that the volatile agents are retained and showed better thermal stability as a result of complexation. Carvacrol inclusion complexes were found relatively more stable (Zeta potential: −28.2 mV) than thymol complexes with smaller particle sizes (204.9 nm). Chemical structures of the inclusion complexes were revealed with Fourier transform-infrared spectroscopy and nuclear magnetic resonance analyses. The optimum formulations for each active agent were applied to cotton fabrics as per the impregnation method and the capsule treated fabrics were washed 1, 10 and 20 times. The images exhibited the presence of inclusion complexes on the fabrics after 20 washing cycles. Although the antibacterial efficacy of fabrics decreased with increasing washing, the fabrics showed the antibacterial effect after 20 washes against Klebsiella pneumoniae and Staphylococcus aureus. This study showed that the developed products can be an alternative to the other products in the market as the long-lasting fragrant natural antibacterial. © 2022 John Wiley & Sons Ltd.
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    The Comparison of Classical and Bayesian Structural Equation Models Through Ordered Categorical Data: A Case Study of Banking Service Quality
    (Gazi Universitesi, 2023) Erkan G.; Dogan M.; Tatlidil H.
    This study aims to compare classical Structural Equation Modeling (SEM) and Bayesian Structural Equation Modeling (BSEM) in terms of ordered categorical data. In order to show the relationship between service dimensions and banks’ customers’ satisfactions, a data were analyzed with classical SEM and BSEM parameter estimation methods. In the Banking Service Quality Scale (SERVQUAL), which consists of sequential categorical data, classical SEM and BSEM were compared to evaluate customer satisfaction. In classical SEM, parameter estimations were made according to the Maximum Likelihood (ML) estimation method. In most of the studies using SERVQUAL in the literature, the results found in previous studies could not be used as prior informative because the service dimensions consisted of different number of factors. For this reason, considering that the results could yield similar results with the ML estimation method due to the high sample size, the use of conjugate prior was preferred instead of the non-informative prior due to the ordinal categorical nature of the data in the BSEM analysis. Since the questionnaire used in the study had a Likert type scale structure, the threshold values were calculated for ordered categorical data and used as prior informative. Thus, by using the threshold values obtained from the data set, a faster convergence of the parameters was achieved. As a result, service dimensions affecting satisfaction according to the ML parameter estimation method were found, Assurance, Physical Appearance, and Accessibility. In addition to these, Reliability as a service dimension was found to be also statistically significant in BSEM. © 2023, Gazi Universitesi. All rights reserved.