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Effects of Escitalopram and Bupropion on Oxidative Stress Parameters and Blood Count Findings in Female Rats
(Yuzuncu Yil Universitesi Tip Fakultesi, 2025) Arihan, Okan; Ergül Erkeç, Ozlem; Doǧan, Abdulahad; Yıldırım, Abdullah
In this study, the effects of two antidepressants with different mechanisms on rat blood oxidative stress parameters and blood count findings were studied. Escitalopram is a selective serotonin reuptake blocker (SSRI) derivative and bupropion has a mechanism of action on noradrenaline and dopamine and increases their synaptic amount by inhibiting their uptake. Adult, female, Wistar-albino rats were divided into 3 different groups with a total of 24 animals. Rats in escitalopram group were administered with 20 mg/kg/day escitalopram and rats in the bupropion group were administered with 20 mg/kg/day bupropion for 28 days via gastric gauge. The rats in the control group were given tap water via gastric gauge. Hematocrit and hemoglobin parameters were significantly higher in Escitalopram and Bupropion than control group. No significant difference was observed in weight gain at the end of 28 days. In this experimental model, 28 days of 20 mg/kg escitalopram or bupropion use did not cause a significant increase in total oxidant status or a significant decrease in total antioxidant status. Oxidative stress index which combines these two findings imply a possible oxidative stress in female rat blood due to Escitalopram treatment. © 2025 Elsevier B.V., All rights reserved.
Impact of E-Service Quality on Direct Booking Intentions in Hotels: The Mediating Effects of E-Satisfaction and E-Trust
(Emerald Publishing, 2025) Rol, Serkan; Alaeddinoğlu, Faruk
Purpose Despite the increasing trend of online hotel bookings, understanding the factors that influence consumers’ intentions to book directly through hotel websites remains essential. This study aims to investigate the effect of e-service quality in hotel websites on consumers’ direct booking intention, as well as the underlying mechanism involving e-satisfaction and e-trust perceptions. Design/methodology/approach This study used a quantitative methodology using a structured online survey approach. To quantify the role of mediation, PROCESS macro was used. Since the study aimed to examine multiple mediation effects, Model 4 with a parallel mediation model was applied. Findings Based on a survey of 393 participants, this study reveals a significant relationship between e-service quality and consumers’ direct booking intention. In addition, perceptions of e-satisfaction and e-trust partially mediate the impact of e-service quality, underscoring its pivotal role in enhancing direct bookings for accommodation businesses. Practical implications Hoteliers should prioritize enhancing e-service quality and fostering positive e-satisfaction and e-trust perceptions to increase direct bookings; in doing so, they can lessen their reliance on intermediaries. Originality/value This study contributes significantly to existing knowledge of direct booking intention by examining the associations between e-service quality, e-satisfaction, e-trust and direct booking intention on hotel websites. © 2025 Elsevier B.V., All rights reserved.
A Lightweight Mobile Deep Learning Framework for Real-Time Plant Disease Detection in Smart Agriculture
(Institute of Electrical and Electronics Engineers Inc., 2025) Avcı, İsa; Koca, Murat; Khan, Yahya Zakrya
It is imperative to detect plant diseases early to enhance agricultural productivity and ensure food security. Conventional diagnostic techniques, which rely on the analysis of experts, are often laborious, expensive and less accessible, particularly in isolated regions. The present study proposes an automated plant disease detection system optimized using deep learning. The system utilizes Convolutional Neural Networks (CNNs). The proposed approach integrates advanced preprocessing techniques, including data augmentation, resizing, and normalization, to enhance model robustness and generalization. To facilitate deployment on mobile devices with limited resources, the MobileNetV2 architecture was optimized through quantization and conversion to TensorFlow Lite (TFLite). This approach resulted in a substantial reduction in computational complexity while maintaining an elevated level of classification accuracy. The mobile application, developed using Kotlin, facilitates the capture or upload of plant images and the execution of real-time disease detection directly on the device, thus obviating server communication. The experimental results demonstrate that the MobileNetV2 (Optimized) model achieved an accuracy of 99.48%, an F 1-score of 99%, and an AUC of 1.00, thus confirming its effectiveness for real-world agricultural applications. This study demonstrates the considerable potential of lightweight and efficient AI-driven solutions to transform the realm of plant disease detection, thereby rendering precision agriculture more accessible, particularly in resourceconstrained environments. © 2025 Elsevier B.V., All rights reserved.
High-Frequency Link Voltage Multiplexing for Multi-Level Inverters With Optimized Transformer Windings
(Institute of Electrical and Electronics Engineers Inc., 2025) Hataş, Hasan
The need for more than one voltage source in multilevel inverters (MLI) increases the system cost and circuit complexity. In this study, a voltage multiplexing method with a high frequency link (HFL) structure is proposed as a solution to the problem in question. Unlike the traditional HFL application, a half H -bridge is added to the input of the transformer and thus the obtained voltage is diversified. The output voltage is provided by a separate H-bridge circuit by preserving the isolation of the input and output voltages. The winding ratios of the transformer are determined by optimizing the total harmonic distortion (THD) of the output voltage with the NLC method. The proposed topology provides a low THD value of 1 1. 7 3% despite different voltage steps. In addition, simulations performed under various amplitude and frequency conditions using the SPWM technique have shown that the proposed method is effective and applicable. © 2025 Elsevier B.V., All rights reserved.
Green Synthesis of Silver Nanoparticles From Melanoleuca Grammopodia: Changes in Bioactive Components, Antidiabetic Properties and Bioaccessibility
(TUBITAK, 2025) Acar, İsmail; Okumus, Emine; Karatas, Arzu
Green synthesis of silver nanoparticles (AgNPs) using plant materials allows the production of low-cost and biocompatible nanoparticles without the use of toxic compounds or solvents. In this study, biogenic AgNP/Mg nanoparticles were synthesized using the Melanoleuca grammopodia mushroom. Vitamin C and E contents of the mushroom were 42.6 mg/g and 26.82 mg/g, respectively. FTIR analysis revealed the reducing and stabilizing effects of bioactive components present in M. grammopodia mushroom extract. SEM micrographs showed that the nanoparticles were spherical in form and the EDX spectrum confirmed the presence of the characteristic metallic silver peak at 3.0 keV. A significant reduction in the amounts of phenolic compounds in the mushroom extract and nanoparticles was observed after in vitro gastrointestinal digestion (p < 0.05). The bioaccessibility values of nanoparticles for gallic acid, caffeic acid, syringic acid and protocatechuic acid were determined as 33.46%, 43.25%, 32.18% and 41.49%, respectively. A significant increase in thermal resistance, antioxidant activity (22.50 mg/mL), antilipid peroxidation (4.41 mg/mL), antidiabetic properties (6.02 mg/mL) and bioaccessibility of AgNP/Mg compared to the mushroom extract was detected. This is the first study in which the bioactive components of the M. grammopodia mushroom species were determined and changes and developments in the synthesized nanoparticles were compared with the mushroom extract. The results revealed that this mushroom species and its silver nanoparticles may be a natural and valuable resource with potential applications, especially in the fields of chemistry, pharmacology, and medicine. © 2025 Elsevier B.V., All rights reserved.