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 Citation - WoS: 1Citation - Scopus: 1Predictive Modeling and SHAP-Based Interpretability of Manganese and Iron Dissolution in Multi-Acid Leaching Systems Using Hybrid Machine Learning(Multidisciplinary Digital Publishing Institute (MDPI), 2026) Top, Soner; Altiner, Mahmut; Kursunoglu, Sait; Kuzu, EmrahHydrometallurgical leaching processes contain complex and nonlinear parameter interactions that are difficult to capture with conventional empirical models. In this study, a multiple hybrid machine learning approach was developed to predict manganese (Mn) and iron (Fe) dissolution efficiency in leaching systems and performed using sulfuric acid (H2SO4), hydrochloric acid (HCl), and nitric acid (HNO3). A large-format dataset consisting of 204 independent leaching experiments was generated in which acid type, acid concentration (0.5-5 M), temperature (25-90 degrees C), solid/liquid ratio (100-200 g/L), leaching time (1-4 h), and eight different reducing agent types were systematically varied. XGBoost, LightGBM, CatBoost, and Random Forest algorithms were individually trained and subsequently combined with a Soft Voting Ensemble architecture. Hyperparameters were optimized using the RandomizedSearchCV method with 3-fold cross-validation. The XGBoost model achieved the highest prediction accuracy for Mn dissolution (R-2 = 0.8993, RMSE = 8.06%), while CatBoost demonstrated the best performance in Fe dissolution (R-2 = 0.8415, RMSE = 4.43%). SHAP analysis suggested that the dosage and type of reducing agents are the most influential predictive features for Mn dissolution, while acid molarity and temperature were identified as the dominant predictors for Fe leaching. Friedman test confirmed that performance differences among both Mn and Fe models were statistically significant (Mn: chi(2) = 32.76, p < 0.001; Fe: chi(2) = 25.96, p < 0.001). The developed models contribute significantly to hydrometallurgical process optimization by predicting the nonlinear effects of leaching parameters on metal dissolution with high accuracy. This study presents a comprehensive and interpretable machine learning framework supported by an extensive experimental dataset, a substantial portion of which has not been previously utilized or comparatively analyzed within a unified multi-acid framework, enabling systematic modeling of selective Mn-Fe dissolution across multiple acid systems and reducing agents.Article Effects of Alkanolamines on Calcium Sulfoaluminate Belite Cement Hydration and Fresh Properties(Emerald Group Publishing Ltd, 2026) Uzal, Burak; Wilkinson, Angus P.; Qoku, Elsa; Nguyen, Tu-Nam; Kurtis, Kimberly E.Calcium sulfoaluminate belite cements have found widespread use in specialised applications but have not been applied broadly due to rapid setting times. Conventional set retarders such as citric and tartaric acids modify hydration kinetics, introducing ancillary effects that alkanolamines may avoid. This study examined the effects of three alkanolamines, triisopropanolamine (), triethanolamine () and diisopropanolamine (), on early hydration at 0.02% dosage; was also tested across a broader dosage range. Reaction kinetics and phase evolution were examined in pastes by calorimetry, thermogravimetric analysis () and in situ quantitative X-ray diffraction () for 72 h of hydration, along with setting time and amplitude-sweep rheometry. Calorimetry showed that and delayed and reduced the main cement hydration peak, while all alkanolamines delayed and enhanced the shoulder and secondary hydration peaks. In situ and suggested that alkanolamines decrease ettringite and alumina gel formation by 24 h and may lead to poorly crystallised ettringite that cannot be quantified by . Alkanolamine-containing samples demonstrated increased storage and loss moduli and extended linear viscoelastic ranges. A consistent grouping of similar behaviour emerged: control/TIPA versus TEA/DIPA, suggesting distinct mechanisms. Finally, among the alkanolamines, was the most effective, increasing the setting time by 18 min.Article A Machine-Learning-Based Multi-Hazard GIS-AHP Framework for Wind Turbine Siting under Earthquake–Landslide Coupling(IOP Publishing Ltd, 2026) Dinçer, Ali Ersin; Demir, Abdullah; Öztürk, Şevki; Kalpakcı, Volkan; Dilmen, ÖmerThis study presents a machine-learning-based multi-hazard geographical information system (GIS)-analytical hierarchy process (AHP) framework for wind turbine siting that explicitly accounts for the coupled effects of earthquake and landslide hazards. The primary innovation lies in the development of a conditional weighting algorithm that integrates machine-learning-derived hazard assessments with structural engineering logic. Landslide susceptibility is first modeled using a random forest classifier trained on a comprehensive inventory of historical landslide data and 12 geo-environmental conditioning factors, producing a high-resolution susceptibility map with excellent predictive performance (AUC = 0.86). Feature importance analysis indicates that slope, hydrological indices, and geological conditions are the dominant controls on landslide occurrence. This data-driven map is then integrated with earthquake hazard zones and additional environmental and technical constraints within a GIS-AHP framework to generate a comprehensive wind turbine suitability assessment. Results show that explicitly accounting for earthquake-landslide coupling leads to a nearly 20% reduction in high and very high suitability areas, accompanied by an expansion of low and moderate suitability zones, highlighting the limitations of single-hazard planning approaches. The main contribution of this study lies in advancing renewable energy planning through the explicit integration of interdependent natural hazards, demonstrating how earthquake-resistant foundation strategies can simultaneously mitigate landslide risks.Article Citation - WoS: 1Citation - Scopus: 1The Discouraged Worker Effect during the Covid-19 Pandemic in Türkiye(Cambridge Univ Press, 2026) Demirtaş, Burak Kağan; Güney, GülThe Covid-19 pandemic has negatively affected labour markets, among other aspects of life. This study examines the impact of the discouraged worker effect during the pandemic, focusing on the Turkish labour market from 2018 to 2021. Although few studies exist on this topic, they rely on labour force participation rates, whereas our dataset includes direct questions and data specifically related to the discouraged worker effect, allowing for a microeconomic analysis. Probit regression results show that the discouraged worker effect was stronger during the pandemic, with job seekers being 1.6% more likely to become discouraged than before. Higher education levels generally reduce this likelihood, both before and during the pandemic. While age negatively correlates with discouragement, this effect diminishes with increasing age. Single women were more adversely affected than single men and married women than married men. Higher unemployment rates increase discouragement, as expected, while an increase in the unemployment rate has a greater effect on individuals during the pandemic period. Findings suggest that the pandemic had a disproportionate impact on certain individuals, particularly with respect to education level and gender, while Türkiye's societal structure may help explain the observed gender-based differences.Article Optimizing Nanoclay-Enhanced Membranes for Oil Rejection Using Response Surface Methodology(Wiley, 2026) Gul, Ayse; Baris, Mesut; Boyraz, Pınar; Senol-Arslan, Dilek; Alibaz, Name NurThe efficient separation of waste oil from contaminated water is critical due to its challenges in environmental and industrial applications. This study investigated the production and optimization of polysulphone (PSF) membranes using two different types of clay (nanomer clay/CN and commercial nanoclay/NC). Response Surface Methodology (RSM) was applied to optimize the basic production parameters and nanoclay concentrations systematically to maximize oil rejection and permeability flow. The experimental results showed that NC and CN significantly increased the hydrophilicity, permeability, and fouling resistance of the membrane compared to pure PSF membranes. The contact angle significantly decreased from 64.34 degrees (pristine PSF) to 36.23 degrees (2% NC), indicating highly improved hydrophilicity. Consequently, the pure water flux increased from 177.2 L/m2 h to a maximum of 248.6 L/m2 h (1% NC). Furthermore, the modified membranes exhibited outstanding anti-fouling properties; the flux recovery ratio (FRR) improved from 88.09% to 96.20% (1% CN), while the decline ratio (DR) drastically dropped from 60.89% to 32.14%. The optimized condition for maximum removal efficiency using a modified quadratic model revealed that 2572 mg/L oil can be treated with a PSF membrane containing 2.0% CN to remove 98.271% of the oil. The model also suggests superiority of CN over NC with desirability factors of 0.978 and 0.900, respectively, while both demonstrated high efficiency. This theoretically modeled experimental comparative study highlights the importance of PSF membrane technology for efficient and sustainable oil-water separation and demonstrates the promising potential of nanoclay modifications.Article Identification of Potential Dual HDAC6 and HSP90 Inhibitors for the Treatment of Cancer Using Molecular Docking, Molecular Dynamics and MM/PBSA Studies: A Comprehensive In Silico Study(Bentham Science Publ Ltd, 2026) Yucel, Muhsin Samet; Akcok, IsmailBackground Histone deacetylase 6 (HDAC6) and heat shock protein 90 (Hsp90) are crucial therapeutic targets in cancer research with their interconnected roles in regulating protein homeostasis and cellular processes. The interaction of these proteins within the cytosolic complex plays a critical role in regulating cancer cell survival and progression. Notably, current studies highlight that the simultaneous inhibition of HDAC6 and Hsp90 can produce synergistic effects and offer a promising therapeutic potential for combating malignant cancers.Objective The objective of this study was to explore potential compounds that can inhibit both HDAC6 and Hsp90 proteins.Methods In this study, a number of in-silico computational techniques were employed. A total of 791 molecules, sharing at least 30% similarity with previously identified four HDAC inhibitors, were obtained from the ZINC15 database and subjected to docking on HDAC6 and Hsp90 proteins. The top eight ligands demonstrating the best binding scores against both targets, with panobinostat and ganetespib serving as reference compounds for HDAC6 and Hsp90, respectively, were selected for further analysis. Subsequently, ADME prediction and molecular dynamics simulations were conducted on the selected ligands.Results A detailed molecular docking, molecular dynamics simulations and ADME studies have revealed that ZINC27653366 exhibited the highest inhibitory potential against both Hsp90 and HDAC6 target proteins, making it the most promising inhibitor.Conclusion In conclusion, although additional in vitro and in vivo studies are required for the validation, in silico evaluation of ZINC27653366 may position it as a promising candidate for the treatment of different types of cancers.Article A Systematic Review of Symbolic Aggregate Approximation (SAX)(Ankara University Faculty of Science, 2026) Nalici, Mehmet Eren; Söylemez, İsmet; Ünlü, RamazanTime series data can be analyzed through various techniques to tackle classification or regression tasks. Symbolic Aggregate Approximation (SAX) is one such technique used for time series data reduction that converts the data into a symbolic representation, enabling more efficient storage, retrieval, and analysis by reducing the dimensionality while preserving the essential patterns within the time series. In this paper, we provide a systematic literature review of SAX by examining relevant literature from 2007 to 2025. The review includes 321 articles sourced from the Web of Science (WOS) database. However, the 85 most cited and recently published studies are summarized. Utilizing collaboration network analysis, the study identifies the nations, affiliations, and authors involved in SAX research, as well as their co-authors and commonalities. Additionally, an analysis is conducted to explore the potential relationship between the articles and the United Nations' Sustainable Development Goals. These findings provide insights into the current landscape of SAX research and offer potential avenues for future exploration. By pinpointing research gaps, scholars can use this review to anticipate forthcoming research trajectories.Article Minimization of Thermal Stresses in Instrumented Cutting Tools with Embedded Thin Film Thermocouples(Korean Society of Mechanical Engineers, 2026-04) Kesriklioglu, Sinan; Sivesoglu, AbdurrahmanThis study investigates the optimization of multilayer coatings on cutting tools to minimize thermal stress and temperature differences between the tool-chip interface and embedded thermocouples. The novelty of this study lies in directly linking coating architecture to temperature measurement accuracy, revealing that coatings not only affect heat dissipation and stress development but may also distort the apparent temperature recorded by embedded sensors. The types and thickness ranges of thin film layers in instrumented cutting tools were determined, and multi-physics finite element simulations were then used to evaluate coating configurations under thermal loading, assessing both stress distribution and temperature variance in the multilayer coating system. The Taguchi method, coupled with desirability analysis, identified optimal coating parameters that simultaneously minimize thermal stresses and temperature disparities, which are critical for accurate temperature measurements and extending the lifespan of cutting inserts. This framework enables a controllable trade-off between mechanical reliability and thermal measurement fidelity. The results reveal significant interactions among coating configurations (settings) and between thermal and mechanical properties of the materials used, demonstrating that careful selection of layer materials and thicknesses optimizes stress and temperature responses yielding thermal stress of 1628 MPa (second lowest and only 0.4 % higher than the minimum) and temperature difference of 12.1 degrees C (third lowest and 55 % lower than average). These findings underscore the potential of precise coating design to enhance tool performance and longevity in high temperature machining applications.Article Unveiling the Therapeutic Role of 3D-Cultured Mesenchymal Stem Cells in Diabetic Foot Ulcers through Transcriptomic Integration and Fibroblast Modulation(Springer, 2026-03-31) Ozturk, Esengul; Bicer, MesudeBackground Diabetic foot ulcers (DFUs) are among the most severe complications of diabetes mellitus and remain difficult to manage due to chronic inflammation, defective angiogenesis, delayed tissue repair, which increase the risk of recurrence and limb amputation. Standard treatments, such as debridement, infection management, pressure off-loading and revascularization, are commonly used, however; these interventions often inadequate to fully restore effective wound repair. Mesenchymal stem cells (MSCs) have attracted remarkable interest due to their potential regenerative ability and paracrine activity. Nevertheless, the molecular interaction between MSCs and fibroblasts under hyperglycemic conditions has not been fully elucidated. Objective This study aimed to examine differentially expressed genes (DEGs) associated with DFUs and MSC-related regenerative mechanisms using transcriptomic datasets (such as GSE143735, GSE199939, and GSE217709). Methods and results Differentially expressed genes and protein-protein interaction (PPI) network analysis were performed to determine central regulatory genes. Four key genes including CXCL1, MMP9, THBS1, and POSTN were recognized as hub genes related to inflammatory response, extracellular matrix reorganization, and angiogenesis. For experimental validation, L929 murine fibroblasts were exposed to high-glucose conditions to set-up an in vitro diabetic model and subsequently treated with MSCs with/without a 3D platform. Hyperglycemic conditions significantly reduced fibroblast proliferation and migration downregulated the expression of the identified hub genes and enhanced apoptotic activity. MSC treatment partially increased cellular function, while MSCs embedded into 3D culture enhanced a more pronounced recovery in both gene expression patterns and functional assays. Conclusions These findings suggest that high glucose impair fibroblast functions for wound repair, while 3D-cultured MSCs enhance regenerative responses and may represent a promising strategy for diabetic wound healing.