WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Activation and Avoidance Mediate the Relationship Between Depression and Life Satisfaction: Insights from Behavioral Activation Therapy(Springer, 2026) Koşan, Yavuz; Kaya, M. SiyabendBehavioral activation therapy has been increasingly used in depression intervention in recent years. It aims to increase the activation level and decrease the avoidance level. In this way, the individual's life satisfaction is expected to increase while trying to reduce depression. However, the relationship between depression and life satisfaction in behavioral activation therapy-based interventions has not been sufficiently revealed. Furthermore, the effects of activation and avoidance, which are the most basic concepts of behavioral activation therapy, and their underlying mechanisms are not well understood. Therefore, this study focused on this gap and aimed to explore the mediating roles of activation and avoidance variables in the relationship between depression and life satisfaction. Participants (N = 440) from a non-clinical sample group completed various self-report scales on depression, behavioral activation, and life satisfaction. Our results showed that depression and life satisfaction negatively predicted each other, and that activation and avoidance variables mediated this relationship in parallel. Accordingly, increasing activation and decreasing avoidance in young people with depressive symptoms may be an effective way to improve life satisfaction and reduce depression. Effective prevention efforts that reduce depression can increase the life satisfaction levels of young adults. In summary, behavioral activation and avoidance can be used to prevent depression and increase life satisfaction. The current study provides more information about the applicability of activation and avoidance, two important elements of behavioral activation therapy, in depression intervention.Article Production of Waste-Based Lightweight Geopolymer Concretes Using Calcined Bentonite, Fly Ash, Slag, and Expanded Polystyrene Granules(Taylor & Francis Inc, 2026-03-19) Top, Soner; Nussrat Shukur Shukur, Yasir; Vapur, HüseyinThis study investigates the production of environmentally friendly lightweight geopolymer concretes utilizing fly ash (FA) as the primary precursor with calcined calcium bentonite (CCB), ferrochrome slag (SG), and expanded polystyrene (EPS) as supplementary components. A Box-Behnken design was employed to investigate the combined effects of CCB and SG additions, along with the solid-to-liquid ratio, on the compressive strength. Moderate CCB incorporation, particularly around 10%, improved mechanical performance, achieving strengths above 48 MPa, with a maximum of 51.33 MPa at 90 degrees C for a mix containing 5% CCB and 5% SG. Higher CCB dosages (>20%) reduced strength due to matrix dilution, while SG showed limited contribution at elevated levels. Incorporation of EPS granules reduced density to as low as 1292 kg/m & sup3;, yet compressive strengths between 25 and 30 MPa were maintained in mixes with 10% CCB and 0.3% EPS. SEM-EDX analysis confirmed dense geopolymer matrices in FA-CCB composites, whereas SG particles appeared less integrated. These results confirm the potential for producing high-strength, lightweight geopolymer concretes through the effective valorization of waste. The combined use of FA, CCB, SG, and EPS offers a sustainable pathway for resource-efficient construction that supports circular resource utilization.Article Wireless Communication System Design for Point Machine Detection and Monitoring in Railways(Springer, 2026-03-09) Talu, Burak; Cetin, Fatih; Kilic, Veli Tayfun; Elden, Burakhan; Sanlier, Saban DuranThis paper reports on a wireless communication system that is used in railways to instantly detect and continuously monitor point machine positions. Also, with the system the position information is transmitted wirelessly to a train driver. The designed system is composed of TX and RX units. It has a compact structure and is fully modular. The TX unit of the system is placed near the railway point machines and the RX unit is located on a train. The designed system was constructed, and measurements were obtained on-site. Results show that the system point machine position data were accurately transmitted at 1350 m range which is much longer than the safe braking distance of a train. In addition, the measured 1 s data sampling time of the system allows the driver to continuously monitor current RPM positions as well as state changes. The maximum delay was found to be 3 s in the limit range of the communication. It is found that the system has a low power consumption and the designed system can work for long hours. The findings indicate that the designed wireless communication system has a high potential to be used in railways to prevent accidents and contribute to the overall safety and efficiency of operations.Article Non-Contact Acoustic Screening for Sleep Apnea: A Subject-Aware Deep Learning Approach(Springer Science and Business Media Deutschland GmbH, 2026-02-11) Aygün Çakıroğlu, M.; Kizilkaya Aydoǧan, E.; Bolatturk, Ö.F.; Aydoğan, S.; Ismailoǧullari, S.; Delice, Y.Purpose: To explore the feasibility of using camera-derived, non-contact audio synchronized with PSG for clinically relevant sleep-apnea classification, and to benchmark compact deep models under a subject-aware design using a previously unstudied, real-world dataset. Methods: Thirty-two adults underwent simultaneous polysomnography (PSG) and camera-based non-contact audio recording. The synchronized audio segments were used to train and compare three compact deep-learning architectures (convolutional, attention-augmented, and transformer-based) under a subject-aware evaluation design that prevented identity leakage. Model performance and calibration were assessed at both segment and subject levels using standard statistical tests. Results: Subject-level evaluation was based on a very small, imbalanced test set of six subjects (one positive). Within this limited yet previously unstudied local dataset, the CNN_trans model achieved an apparent perfect ranking performance (AUC = 1.00; 95% CI 0.00–1.00), though this likely reflects the small, imbalanced test cohort, with recall = 1.00 and precision = 0.55. The wide confidence interval reflects substantial statistical uncertainty, and DeLong comparisons showed no significant AUC difference between CNN_trans and CNN_att (ΔAUC = − 0.042; p = 0.43). Conclusion: PSG-synchronized, non-contact audio supports accurate and well-calibrated sleep-apnea classification with compact deep models. This subject-aware evaluation suggests that contactless acoustic monitoring may have potential clinical relevance, motivating larger, multi-site validation. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026.Article Process Optimization of Buckwheat Starch Myristic Acid Complex Film(John Wiley and Sons Inc, 2026-02) Koca, E.; Oskaybaş-Emlek, B.; Kahraman, K.; Özbey, A.; Aydemir, L.Y.; Oskaybas Emlek, BetulIn this study, it was aimed to develop an edible film from an amylose-lipid complex with better mechanical properties and water vapor barrier. For this purpose, the buckwheat starch (BS) is modified with myristic acid (MA) and the edible film production process was optimized by using central composite design with 4 center points where film forming solution's glycerol concentration, pH, and the temperature of as dependent variable and tensile strength (TS), elongation at break (EAB) value and Young's modulus (YM) as response. The models were significant for TS and YM, and the glycerol concentration and temperature had a significant effect on the TS of the films. The edible film produced in validated optimized conditions had better EAB (149%) and TS (1.064 MPa), and lower water solubility (44.7%) and water vapor permeability (0.39 g × mm/m2 × h × kPa) than control film (p < 0.05). There was no significant change in color values, but an increase in opacity (2.14). With the formation of the BS-MA complex, increased surface roughness and more hydrophilic (contact angle = 92.4°) films were obtained. These findings demonstrate that the BS-MA complex film has significant potential for practical applications as an edible film. © 2026 Wiley-VCH GmbH.Article Citation - Scopus: 1Noninvasive Condition Monitoring for Eccentricity Fault Detection in Large Hydro Generators(TÜBİTAK Scientific & Technological Research Council Turkey, 2026-01-16) Lemeski, Atena Tazikeh; Tekgun, Didem; Keysan, Ozan; Leblebicioglu, Kemal; Gol, Murat; Leblebicioglu, Mehmet KemalEccentricity faults in electric machines remain a critical concern, as they generate uneven magnetic forces that increase vibration and noise, ultimately raising the risk of premature motor failure. This study proposes a method for the early detection of dynamic eccentricity (DE) faults in hydropower plants through an advanced optimization-based parameter identification technique integrated with finite element analysis (FEA). Finite element modeling (FEM) is first used to analyze an existing salient-pole synchronous generator (SPSG) from a hydroelectric power plant in T & uuml;rkiye. The effects of DE faults on the SPSG's magnetic equivalent circuit parameters are then examined under various fault severities. A comprehensive hydropower plant model-including the synchronous generator, governor, and excitation system-is developed in MATLAB/Simulink, with all input parameters obtained from real plant data and equivalent circuit variations extracted from FEA. After completing the modeling stage, including fault scenarios, MATLAB and Simulink are employed together to estimate key magnetic equivalent circuit parameters using a modified particle swarm optimization (MPSO) algorithm, achieving highly accurate parameter estimation. Since the hydropower system allows measurement of the three-phase output currents, parameter estimation is performed based on current variations under different fault conditions. The simulation results verify the method's ability to detect faults with high accuracy; thus, this integrated and noninvasive approach provides a robust framework for ensuring the operational reliability and longevity of large hydro generators.Article Deep-Learning Detection of Open-Apex Teeth on Panoramic Radiographs Using YOLO Models(Springer, 2025-12-23) Edik, Merve; Celebi, Fatma; Cukurluoglu, AykaganObjectivesThe use of deep learning in detecting teeth with open apices can prevent the need for additional radiographs for patients. The presented study aims to detect open-apex teeth using You Only Look Once (YOLO)-based deep learning models and compare these models.MethodsA total of 966 panoramic radiographs were included in the study. Open-apex teeth in panoramic radiographs were labeled. During the labeling process, they were divided into 6 classes in the maxilla and mandible, namely incisors, premolars, and molars. AI models YOLOv3, YOLOv4, and YOLOv5 were used. To evaluate the performance of the three detection models, both overall and separately for each class in the test dataset, precision, recall, average precision (mAP), and F1 score were calculated.ResultsYOLOv4 achieved the highest overall performance with a mean average precision (mAP) of 87.84% at IoU (Intersection over Union) 0.5 (mAP@0.5), followed by YOLOv5 with 85.6%, and YOLOv3 with 84.46%. Regarding recall, YOLOv4 also led with 90%, while both YOLOv3 and YOLOv5 reached 89%. Moreover, the F1 score was the highest for YOLOv4 (0.87), followed by YOLOv3 (0.86) and YOLOv5 (0.85).ConclusionsIn this study, YOLOv3, YOLOv4, and YOLOv5 were evaluated for the detection of open-apex teeth, and their mAP, recall, and F1 scores exceeded 84%. Deep learning-based systems can provide faster and more accurate results in the detection of open-apex teeth. This may help reduce the need for additional radiographs from patients and aid dentists by saving time.Article Modeling and Simulation of Dynamic Energy Management Systems for Smart Buildings(TÜBİTAK, 2025-11-25) Ozel, O.; Rıfat Boynueğrİ, A.; Yigit, H.; Tekgun, B.; Boynuegri, Ali RifatThis study presents a dynamic energy management system tailored for smart residential buildings, integrating thermal and electrical models to achieve both natural gas and electricity bill cost reduction. By harnessing wind and solar energy sources, the system aims to meet the diverse energy needs of modern homes. Through load shifting and thermal storage strategies, known as power-to-heat (P2H) approaches, the system ensures efficient renewable energy utilization while maintaining resident comfort. Validation of the proposed system was conducted using real-world data from the Yıldız Technical University Smart Home Laboratory, demonstrating its practical applicability and effectiveness. Results indicate significant reductions in both natural gas and electricity consumption, leading to substantial cost savings. Specifically, the proposed system reduced natural gas consumption by 3.79% and electricity consumption by 35.62%, highlighting its potential to enhance energy efficiency and sustainability in residential settings. © This work is licensed under a Creative Commons Attribution 4.0 International License.Conference Object Bioinformatics Analysis of Antifungal Mechanisms in Serratia Fonticola: Protein-Protein Interaction with Botrytis Cinerea BAG1 and Genome-Encoded Enzyme Reportoire(Wiley, 2025) Bozkurt, E. B.; Baysal, O.; Marzec-Grzadziel, A.; Silme, R. S.; Can, A.; Belen, I. N.; Korkut, A.Conference Object The Role of X-Inactive Specific Transcript (XIST) in Neuronal Development, Neuroinflammation, Myelination, and Therapeutic Responses in Cerebral Organoids(Wiley, 2025) Pepe, N. Aktas; Acar, B.; Zararsiz, G. Erturk; Guner, S. Ayaz; Sen, A.