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Öğe Machine Learning-Based Classification of Albanian Wines by Grape Variety, Using Phenolic Compound Dataset(MDPI, 2025) Topi, Ardiana; Kasaj, Agim; Hudhra, Daniel; Kelebek, Hasim; Guclu, Gamze; Selli, Serkan; Topi, DritanWine phenolics serve as robust chemical signatures correlated to grape variety, processing, and regional identity. This study explores the potential of machine learning algorithms, combined with the phenolic profiles of Albanian wines, to classify them according to grape variety. Geographic origin analysis was conducted as a preliminary exploration. The dataset of phenolic compounds included white and red wines, spanning the 2017 to 2021 vintages. Using five supervised algorithms-Support Vector Machine (SVM), Random Forest, XGBoost, Logistic Regression, and K-Nearest Neighbors-a high classification accuracy was achieved, with SVM reaching 100% under Leave-One-Out Cross-Validation (LOOCV). To address class imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) and stratified cross-validation were applied. Random Forest feature importance consistently highlighted trans-Fertaric acid and Procyanidin B3 as dominant discriminants. Parallel coordinates plots demonstrated clear varietal patterns driven by phenolic differences, while PCA and hierarchical clustering confirmed unsupervised grouping consistent with wine type and maceration level. Permutation testing (1000 iterations) confirmed the non-randomness of model performance. These findings show that a small set of phenolic markers can offer high classification accuracy, supporting chemically based wine authentication. Although the dataset is relatively small, thorough cross-validation, non-redundant modeling, and chemical interpretability provide a solid foundation for scalable methods. Future work will expand the dataset and explore sensor-based phenolic measurement to enable rapid authentication in wine.Öğe An Examination of Can Yücel'sTranslation of Sonnet 66 within the Framework of Habitus(Rector CIU Cyprus Int Univ, 2025) Uysal, AysegulThis study aims to explain the poet-translator Can Y & uuml;cel's translation strategies, focusing on his translation of the 66th Sonnet by the English poet William Shakespeare. The study employs a descriptive analysis method and scrutinizes the poet-translator Y & uuml;cel's writings, as well as his social environment, his father's activities, and the period in which they lived. To conduct the descriptive analysis, I employed the concept of habitus as developed by Pierre Bourdieu, one of the most influential sociologists of the post-World War II Era. Hasan Acirc;li Y & uuml;cel, then the Minister of Education, initiated a 'Translation Movement', which can be marked as a turning point for language studies in the Republican Era. This movement aimed to establish a cultural repertoire by translating works from both Eastern and Western literatures into Turkish, contributing to the establishment of a national identity. Educated in England and having studied German philology in Turkey, the son of Minister Y & uuml;cel, Can Y & uuml;cel, also translated English classics into the Turkish language. He called himself a Turkish teller rather than a translator. His translation strategies were considered unique. By comparing his translation of Sonnet 66th with two other Turkish translations, this study identifies his characteristic translation strategies. The findings indicate that Can Y & uuml;cel's habitus shaped his translation strategies, reflecting the norms of his social environment and his aim to reach his people through his style.Öğe The relationship between perinatal depression, anxiety, and sexist beliefs(Klinik Psikiyatri Dergisi, 2025) Karaman, Imran Gokcen Yilmaz; Gunduez, Tugce; Kocabacak, Hale; Velipasaoglu, Melih; Kacar, Cennet Yastibas; Alamanac, Blanca BoleaObjective: Exposure to sexism is negatively associated with women's mental health. On the other hand, there is limited research in the literature on sexism and mental health during pregnancy. This study aimed to investigate the relationship between common mental disorders during pregnancy, such as depression and anxiety, and sexist beliefs. Method: For this scope, 170 pregnant women over 18 were contacted. All participants completed information forms measuring sociodemographic and clinical characteristics, the Tilburg Pregnancy Distress Scale, the Multidimensional The correlation coefficient was calculated for the relationships between variables. Two separate hierarchical regression models were tested to determine the predictors of depression and anxiety. Results: Depression and anxiety had different characteristics in terms of predictive variables. Consistent with the literature, negative affect, partner involvement, and perceived social support significantly predict both depression and anxiety. Negative affect and partner involvement are factors of the Tilburg Pregnancy Distress Scale. However, there is no common predictive variable other than those three. In addition to this common triad, internalized hostile sexism significantly predicts depression. Moreover, low education and health problems related to pregnancy are significant variables in predicting only anxiety levels but not depression. In this respect, the findings show that there are variables that predict prenatal depression and anxiety in common, as well as different predictors of these two mental health problems observed in the perinatal period. Discussion: Hostile sexist beliefs of pregnant women are not associated with anxiety but predict perinatal depression.Öğe A Modular Hybrid SOC-Estimation Framework with a Supervisor for Battery Management Systems Supporting Renewable Energy Integration in Smart Buildings(MDPI, 2025) Kurucan, Mehmet; Michailidis, Panagiotis; Michailidis, Iakovos; Minelli, FedericoAccurate state-of-charge (SOC) estimation is crucial in smart-building energy management systems, where rooftop photovoltaics and lithium-ion energy storage systems must be coordinated to align renewable generation with real-time demand. This paper introduces a novel, modular hybrid framework for SOC estimation, which synergistically combines the predictive power of artificial neural networks (ANNs), the logical consistency of finite state automata (FSA), and an adaptive dynamic supervisor layer. Three distinct ANN architectures-feedforward neural network (FFNN), long short-term memory (LSTM), and 1D convolutional neural network (1D-CNN)-are employed to extract comprehensive temporal and spatial features from raw data. The inherent challenge of ANNs producing physically irrational SOC values is handled by processing their raw predictions through an FSA module, which constrains physical validity by applying feasible transitions and domain constraints based on battery operational states. To further enhance the adaptability and robustness of the framework, two advanced supervisor mechanisms are developed for model selection during estimation. A lightweight rule-based supervisor picks a model transparently using recent performance scores and quick signal heuristics, whereas a more advanced double deep Q-network (DQN) reinforcement-learning supervisor continuously learns from reward feedback to adaptively choose the model that minimizes SOC error under changing conditions. This RL agent dynamically selects the most suitable ANN+FSA model, significantly improving performance under varying and unpredictable operational conditions. Comprehensive experimental validation demonstrates that the hybrid approach consistently outperforms raw ANN predictions and conventional extended Kalman filter (EKF)-based methods. Notably, the RL-based supervisor exhibits good adaptability and achieves lower error results in challenging high-variance scenarios.Öğe Improving road safety in rural areas: An examination of the traffic safety climate in rural Wales(Elsevier Sci Ltd, 2025) Tekes, Burcu; Musselwhite, Charles; Bicaksiz, PinarAlthough there is a body of research conducted on traffic safety and driver behaviors in the UK, studies on traffic safety climate, particularly in rural Wales, are limited. In this study, the effect of traffic safety climate in Wales on several driving-related characteristics was investigated and expected to find a difference between rural and urban Wales. The model investigated the moderator role of rural/urban areas on the relationship between traffic safety climate and driver behaviors, driver anger, anger expression, and driver risk. Using data from 346 participants, we found that drivers in rural areas perceive traffic as having more internal requirements, but also engage in more risk-taking, whereas drivers in urban areas score higher in aggressive violations and verbal aggressive expression. In the following steps, we found links between traffic safety climate and various driver-related outcomes, and this link differs across drivers living in rural and urban areas. These findings suggest the need for tailored strategies to address road safety in rural areas in Wales.Öğe Impregnation of Melaleuca Family Essential Oil Nanoemulsions into Pectin:Polyvinyl Alcohol Patches to Provide an Antibacterial Environment for Infected Wounds(Wiley-VCH GmbH, 2025) Demir, Didem; Ceylan, Seda; Ipek, Semih Latif; Aslan, Deren; Oezbolat, VeliEssential oils have long been utilized in food, cosmetic, and medicinal applications. Recently, their biomedical use for wound healing, skin repair, and tissue regeneration has gained considerable attention. In this study, tea tree oil (TTO) and niaouli oil (NIO) were formulated into aqueous nanoemulsions (NEs) and incorporated into pectin/polyvinyl alcohol (PP) thin films to develop antibacterial wound dressing patches. The NEs were characterized by dynamic light scattering (DLS), and their morphological and chemical structures were also analyzed. The patches' morphology, hydrophilicity, swelling ratio, and mechanical properties were evaluated to assess the effect of NEs on material performance. Antibacterial activity assessed by plate count and agar diffusion methods against six bacteria commonly associated with infected wounds showed significant efficacy of NEs-loaded patches against Gram-negative strains and Escherichia coli. Direct and indirect cytotoxicity tests, using Mouse embryonic fibroblast (MEF) cells, confirmed that NEs incorporation maintained cell viability within acceptable limits and promoted their biocompatibility. These findings suggest that TTO and NIO-based nanoemulsion patches are promising candidates for antibacterial wound dressings.Öğe Fundamental frequency optimization of variable stiffness Multi-Region composite panels in Presence of geometrical nonlinearity(Academic Press Ltd - Elsevier Science Ltd, 2025) Farsadi, Touraj; Ahmadi, Majid; Jiffri, Shakir; Khodaparast, Hamed Haddad; Kurtaran, Hasan; Friswell, Michael I.; Fichera, SebastianoMulti-region laminate optimization offers a comprehensive approach to enhance aerospace structures, making them efficient, safe, and cost-effective. Similarly, Automated Fiber Placement (AFP) processes optimize toolpaths and fiber deposition, reducing waste, saving time, and improving composite quality. Strategically placing fibers where needed, it boosts structural performance and allows for innovative composite designs. This study, first, focuses on optimizing the Fundamental Natural Frequency (FNF) of composite panels, which feature various Curvilinear Fiber Paths (CFP) mathematically modeled using bilinear interpolation distributed across different regions of the panel with comparisons drawn against the conventional Unidirectional (UD) fiber layup. Secondly, a study is conducted to explore the Fundamental Amplitude-dependent Nonlinear Frequencies (FANF) within the context of the optimized configuration featuring curved fiber layup. The modulation of stiffness in composite laminates is achieved through continuous adjustments of fiber angles, governed by the CFP function. A nonlinear structural model, grounded in the principles of virtual work, is employed for this analysis. The formulation incorporates Green's nonlinear kinematic strain relations to accommodate geometric nonlinearities, and First-order Shear Deformation Theory (FSDT) is applied to extend the analysis to moderately thick cylindrical panels, including transverse shear deformations. The principal aim of this investigation is to evaluate the impact of Variable Stiffness (VS) parameters across multiple regions on the linear and nonlinear free vibration characteristics of the panel. This research examines symmetric eight-layered composite panel incorporating three distinct design regions and two boundary condition sets. The Generalized Differential Quadrature (GDQ) method is employed to solve the nonlinear equations of motion governing these structures. The numerical findings show the impact of fiber angle paths and boundary conditions on the FNF of cylindrical panels.Öğe Self-weighing and disordered eating among women: Exploring the moderating role of psychological resilience and self-compassion(SAGE Publications Inc, 2025) Turkcan, Tugba; Karakus, Duygu; Temiz, Yagmur; Colak, Ebru; Bicaksiz, Pinar; Tekes, BurcuBackground: Self-weighing is a common practice among women, often associated with both adaptive and maladaptive eating behaviours, yet its psychological implications remain unclear. Aim: This study aims to examine the potential moderating roles of psychological resilience and self-compassion in the relationship between self-weighing frequency and disordered eating behaviours among women. Method: The study sample consisted of 372 women with a mean age of 29.27 (SD = 7.24). The data were collected in T & uuml;rkiye using convenience sampling methods. Cross-sectional data were collected using a self-report questionnaire, which included the Self-Compassion Scale, the Three-Factor Eating Questionnaire, and the Connor-Davidson Psychological Resilience Scale, along with a single item to measure self-weighing frequency. Results: Four distinct moderating effects between self-weighing frequency and cognitive restriction were found to be significant. The association of self-weighing frequency with cognitive restriction was significantly positive for those reporting low levels of tenacity and personal competence, psychological resilience, and self-compassion. At the same time, it was nonsignificant for those with high levels of tenacity and personal competence, psychological resilience, and self-compassion. The relationship between self-weighing frequency and cognitive restriction was significantly positive at both low and high levels of self-compassion, but this association was stronger for those with low self-compassion than for those with high self-compassion. Conclusion: These findings highlight the significance of considering psychological factors such as psychological resilience and self-compassion in understanding the relationship between self-weighing frequency and disordered eating behaviours. They suggest that these variables can modify the strength and direction of this relationship, emphasising the importance of addressing psychological resilience and self-compassion in interventions targeting disordered eating behaviours related to self-weighing frequency.Öğe An Analysis of How Economic and Monetary Policy Uncertainty Affect the Cryptocurrency Market(Sosyoekonomi Society, 2025) Kadooglu-Aydin, Gulden; Kaplan-Yildirim, Ruya; Munyas, TurgayThis study examines how Economic Policy Uncertainty (EPU) and Monetary Policy Uncertainty (MPU) affect the returns often different cryptoassets using Quantile Regression (QR) and Robust Least Squares (RLS) methods. Quantile regression allows a nuanced examination of how these uncertainties affect returns at different levels under market conditions. Using monthly data from January 1, 2018, to June 1, 2024, the analysis shows that MPU has a negative impact on cryptoasset returns under normal and bull market conditions. However, this effect diminishes during bear market periods. Conversely, EPU has a significant negative impact only during bull markets. These results suggest that market conditions critically shape the sensitivity of cryptoassets to uncertainty, with such effects amplified during bull market periods.Öğe Assessment of phenolic composition, sugars, and antioxidant capacity in Turkish fig (Ficus carica L.) cultivars(Tubitak Scientific & Technological Research Council Turkey, 2025) Zahid, Ghassan; Kelebek, Hasim; Kuden, Ayzin; Shimira, Flavien; Kacar, Yildiz AkaFig fruits (Ficus carica L.) have significant health benefits. T & uuml;rkiye is the leading fig producer in the world. Despite their diversity and rich medicinal properties, the biochemical fingerprints and nutritional quality of local figs are poorly understood. This study aimed to analyze the peels and pulps of eight Turkish figs with varying colors for their total phenolic composition, sugars, and antioxidant capacity. Thirty-one phenolic compounds (PCs) were detected using HPLC-MS/MS. The dark-purple 01-1N-58 genotype had the highest amount of colored PCs in fruit peels and pulps (151.25 and 31.57 mg/100 g dw, respectively). Likewise, the maximum quantity of colorless PCs was found in the peels of the same genotype (1063.91 mg GAE/100 g dw). The highest antioxidant capacity was also observed in the 01-1N-58 genotype. Cyanidin-3-O-rutinoside and chlorogenic acid were the dominant PCs in the peels and pulps. This study showed that the fig fruit peels, especially with darker colors, had a greater total quantity of bioactive compounds than pulp. High variability was observed among the studied cultivars and genotypes, which is crucial to help fig breeding researchers, consumers, and the food industry to select fig varieties with the most health benefits.Öğe Morphometric effectiveness of calcium hydroxylapatite application in zygomatic and malar area on correction of nasolabial folds(Lippincott Williams & Wilkins, 2025) Kabakci, Ayse Gul; Gursel, Amira Tandirovic; Aydin, Baris; Eren, Dilek; Bozkir, Memduha GulhalThis study aims to investigate the indirect effects of calcium hydroxylapatite (CaHA) injections in the zygomatic and malar regions on the healing of nasolabial folds (NLFs). Given the anatomical complexity and proximity of the nasolabial area, selecting appropriate techniques for CaHA applications is crucial to prevent potential complications. The study is designed to contribute insights into the safety and efficacy of injections, aiming to enhance patient outcomes and minimize risks in aesthetic applications. This retrospective single-center study analyzed the effectiveness of CaHA injections in the zygomatic and malar regions for correcting NLFs in 51 female participants aged between 30 and 55. Images from clinical archives were used, taken before the application and 6 months after the application. The primary outcomes were evaluated using Gabor filter analysis, Global Aesthetic Improvement Scale, and Wrinkle Severity Rating Scale, complemented by morphometric measurements using Image J 1.52a software. Measurements before and 6 months after the application revealed significant improvements in NLF length: from 2.59 +/- 0.64 cm to 2.24 +/- 0.53 cm on the right side and from 2.76 +/- 0.81 cm to 2.59 +/- 0.61 cm on the left side. This corresponds to an improvement of 13.51 % and 6.16%, respectively. Evaluations using the Wrinkle Severity Rating Scale, Global Aesthetic Improvement Scale scores, and Gabor filter analysis also demonstrated positive NLF depth post-treatment changes. The results of our study indicate that CaHA injections in the zygomatic and malar regions lead to an indirect improvement in NLFs. Furthermore, our study provides standardized quantitative methods that can be used to assess the effectiveness of treatments in the nasolabial area. These analyses offer reliable tools for evaluating aesthetic procedures and provide valuable contributions to clinical practice.Öğe Effects of Rice Husk Ash Particles on Tribological Properties of Bronze Matrix Composite Brake Pads(International Institute for the Science of Sintering (IISS), 2025) Sugozu, Ilker; Kus, Husamettin; Avcu, AdemThe objective of this study was to examine and compare the physical, mechanical, and tribological properties of hybrid bronze metal matrix composite brake pads reinforced with fly ash and rice husk ash (RHA). To this end, metal matrix brake pad samples with various ratios of rice husk were prepared by hot pressing method. Density, hardness, friction coefficient, friction stability, and specific wear rate values were ascertained for the produced samples. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) were employed to analyses the microstructure and wear surface. Results indicated that with the increase in rice husk ratio, the hardness value increased, whereas the density decreased. Furthermore, an augmentation in the friction coefficient values was attained by increasing the ratio of rice husk. The highest friction coefficient among all the samples produced was determined in the RHA-8 sample, with a value of 0.462. However, the lowest specific wear value was obtained in the RHA-6 sample, with 4.33 x 10-6 cm3/Nm. The coefficient of friction values obtained from all the samples produced were measured to be in the range of 0.3-0.6, which is the desired range for use as a brake pad material in automotive applications. This study demonstrated that RHA, an agricultural byproduct, may be utilized effectively in brake pads, thereby reducing production costs and enhancing the performance of the pads.Öğe Municipal solid waste to biomass energy in Türkiye: A life cycle assessment approach for circular economy integration(Pergamon-Elsevier Science Ltd, 2025) Tokmakci, Muhammet; Ozdil, N. Filiz (Tumen); Bilgili, MehmetThis study assesses the potential of biomass energy derived from municipal solid waste (MSW) in T & uuml;rkiye, focusing on its contribution to the national energy portfolio and the circular economy. T & uuml;rkiye, facing increasing energy demand and environmental challenges, has a growing need to diversify its energy sources. By utilizing MSW, the country can simultaneously address waste management issues and generate renewable energy. The analysis, based on data from 2010 to 2020, reveals that T & uuml;rkiye's theoretical biomass potential from MSW was approximately 31,789 kt, with an electricity generation potential of 379,698 GWh, representing 7.81 % of the country's electricity demand. This study uses a Life Cycle Assessment (LCA) approach to evaluate the environmental impacts of different WtE technologies, including pyrolysis, gasification, and anaerobic digestion. The LCA results show that adopting these technologies could significantly reduce greenhouse gas emissions, particularly carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Furthermore, regional analysis highlights the Marmara region as having the highest biomass energy potential, contributing over 35 % of T & uuml;rkiye's total MSW production. Projections for 2030 suggest that T & uuml;rkiye's annual waste generation could exceed 35 million tons, offering even greater potential for biomass energy production. In addition, this study compares T & uuml;rkiye's WtE potential with that of other countries, particularly in the European Union, and suggests that by adopting similar technologies and policy frameworks, T & uuml;rkiye can enhance its energy independence and meet its renewable energy targets. The results underscore the importance of integrating MSW-derived biomass energy into T & uuml;rkiye's national energy strategy, contributing to a sustainable and circular economy model.Öğe Mechanical behavior and fracture analysis of the cylindrical component of type-III high-pressure composite tanks(Wiley, 2025) Avcu, Adem; Seyedzavvar, Mirsadegh; Boga, Cem; Choupani, NaghdaliThis study presents a broad investigation of the mechanical properties and fracture behavior of a type-III high-pressure composite tank, with an emphasis on the cylindrical section, which is critical for ensuring the safety and reliability of pressure vessels in various applications. The experimental methods included split disk tensile (SDT), curved compact tension (CCT), and pipe ring notched bending (PRNB) tests, which were used to evaluate the hoop tensile strength, fracture toughness, and critical internal pressure of the cylindrical section under different loading conditions. Finite element analysis was used to complement the experimental findings and predict the failure behavior of this section. The SDT test was performed on samples taken from the cylindrical portion of the pressure tank, and its strength and modulus of elasticity were determined. Using CCT and PRNB tests, the fracture toughness of the studied tank materials was found to be 36.90 and 35.73 MPa root m, respectively. The small difference between these results confirmed the reliability of the tests in determining fracture toughness. Analysis of critical internal pressure versus crack length in the cylindrical section emphasized the importance of crack detection and management for safe operation. Overall, this study provides valuable insights into the mechanical behavior and fracture characteristics of the cylindrical part of high-pressure composite tanks, which can contribute to their design and performance for enhanced safety and reliability in various industrial applications.Highlights Determining the mechanical properties of the composite tank with the SDT test. Characterizing the fracture toughness with CCT and PRNB tests. FE analysis of fracture behavior of high-pressure composite tank. Providing valuable insights to increase safety and reliability.Öğe Recombinant Expression of L-methioninase from Brevibacterium linens and Evaluation of its Anticarcinogenic Properties against MiaPaCa-2 Cells(Bentham Science Publ Ltd, 2025) Ipek, Semih Latif; Alkis, Meryem Damla Ozdemir; Tulek, Ahmet; Gokturk, DilekIntroduction This study aimed to investigate the anti-carcinogenic effects of recombinant L-methioninase (rBlmet) on the pancreatic cancer cell line MiaPaCa-2.Methods In this study, rBlmet was initially cloned, expressed, and purified. To increase enzyme activity, the His-tags on the enzyme were removed using thrombin. rBlmet was then applied to MiaPaCa-2 cells, and the cell viability of MiaPaCa-2 cells was evaluated by neutral red assay after rBlmet treatment. The combined effect of etoposide with rBlmet against MiaPaCa-2 cells was also evaluated for 12 and 24 hours using a neutral red assay. Furthermore, cell morphology was evaluated by Giemsa and DAPI/F-actin staining methods. Survivin and caspase-3 gene expression levels were measured by RT-qPCR.Results and Discussion The specific activity of the enzyme increased after His-tag elimination to 5.62 mu mol/mg per minute. rBlmet showed a significant cytotoxic effect on the MiaPaCa-2 cell line. The IC50 value (24 h) of rBlmet for MiaPaCa-2 cells was 3.02 U/mL. In addition, rBlmet increased the cytotoxic effect of etoposide on the MiaPaCa-2 cell line, while it showed less effect on HaCat, which is a normal human cell line. Furthermore, rBlmet increased caspase-3 expression and downregulated survivin gene expression in MiaPaCa-2 cell lines.It successfully inhibited the growth of Mia-PaCa-2 cells by exploiting exogenous methionine amino acid in the growth medium. This study revealed promising results. However, further studies are needed on additional pancreatic cancer cell lines and in vivo models.Conclusion Based on these findings, it can be concluded that rBlmet not only has great potential to treat pancreatic cancer in the future but can also be used as an adjuvant to enhance the effectiveness ofchemotherapeutic agents like etoposide.Öğe Finite Mixture Model-Based Analysis of Yarn Quality Parameters(MDPI, 2025) Karakas, Esra; Koyuncu, Melik; Ukelge, Mulayim OngunThis study investigates the applicability of finite mixture models (FMMs) for accurately modeling yarn quality parameters in 28/1 Ne ring-spun polyester/viscose yarns, focusing on both yarn imperfections and mechanical properties. The research addresses the need for advanced statistical modeling techniques to better capture the inherent heterogeneity in textile production data. To this end, the Poisson mixture model is employed to represent count-based defects, such as thin places, thick places, and neps, while the gamma mixture model is used to model continuous variables, such as tenacity and elongation. Model parameters are estimated using the expectation-maximization (EM) algorithm, and model selection is guided by the Akaike and Bayesian information criteria (AIC and BIC). The results reveal that thin places are optimally modeled using a two-component Poisson mixture distribution, whereas thick places and neps require three components to reflect their variability. Similarly, a two-component gamma mixture distribution best describes the distributions of tenacity and elongation. These findings highlight the robustness of FMMs in capturing complex distributional patterns in yarn data, demonstrating their potential in enhancing quality assessment and control processes in the textile industry.Öğe Financing or taxation? Assessing the effectiveness of carbon emissions reduction programs(Elsevier, 2025) Can, Ufuk; Can, Zeynep GizemCarbon emissions are of significant concern, as they pose a growing threat to the integrity of ecological systems. This paper investigates the effectiveness of consumption-based carbon emissions reduction programs. We use an innovative quantile panel regression methodology as well as a comprehensive preliminary analysis and robustness analysis with a sample of 38 member countries of the Organization for Economic Cooperation and Development (OECD). Our empirical findings demonstrate that output and foreign trade have a significant impact on carbon emissions, thus supporting the trade-extended environmental Kuznets curve. Furthermore, environmental taxes and green finance play a pivotal role in mitigating carbon emissions, and the latter emerges as a particularly effective policy instrument. The sector-and product-specific determination of environmental taxes, coupled with the strategic channeling of green finance to clean and renewable energy sources and production processes, will catalyze advancements in environmental sustainability.Öğe Interpretable Energy Forecasting: Comparative Analysis of Voting Regression and NODE Models for Electricity Power Consumption Prediction(IEEE, 2025) Asal, BurcakAccurate electricity power consumption estimation is vital for efficient energy management, demand-side response strategies and grid optimization. This study explores ensemble based machine learning-based and deep learning approaches for electricity power consumption prediction across three distinct zones by using a Voting Regression model including Linear Regression, Random Forest and K-Nearest Neighbors (KNN) and NODE (Neural Oblivious Decision Ensembles) model. Quantitative and qualitative experimental results show that Voting Regression model outperforms NODE model in overall and additionally, SHAP (SHapley Additive exPlanations) technique is applied on the Voting Regression model to analyze and explain the feature contributions and effects for the model prediction. Consequently, this study provides a reliable, explainable and data-driven framework for optimizing electricity power distribution and electricity consumption planning.Öğe TurkSentGraphExp: an inherent graph aware explainability framework from pre-trained LLM for Turkish sentiment analysis(PeerJ Inc, 2025) Kilic, Yasir; Tulu, Cagatay NeftaliSentiment classification is a widely studied problem in natural language processing (NLP) that focuses on identifying the sentiment expressed in text and categorizing it into predefined classes, such as positive, negative, or neutral. As sentiment classification solutions are increasingly integrated into real-world applications, such as analyzing customer feedback in business reviews (e.g., hotel reviews) or monitoring public sentiment on social media, the importance of both their accuracy and explainability has become widely acknowledged. In the Turkish language, this problem becomes more challenging due to the complex agglutinative structure of the language. Many solutions have been proposed in the literature to solve this problem. However, it is observed that the solutions are generally based on black-box models. Therefore the explainability requirement of such artificial intelligence (AI) models has become as important as the accuracy of the model. This has further increased the importance of studies based on the explainability of the AI model's decision. Although most existing studies prefer to explain the model decision in terms of the importance of a single feature/token, this does not provide full explainability due to the complex lexical and semantic relations in the texts. To fill these gaps in the Turkish NLP literature, in this article, we propose a graph-aware explainability solution for Turkish sentiment analysis named TurkSentGraphExp. The solution provides both classification and explainability for sentiment classification of Turkish texts by considering the semantic structure of suffixes, accommodating the agglutinative nature of Turkish, and capturing complex relationships through graph representations. Unlike traditional black-box learning models, this framework leverages an inherent graph representation learning (GRL) model to introduce rational phrase-level explainability. We conduct several experiments to quantify the effectiveness of this framework. The experimental results indicate that the proposed model achieves a 10 to 40% improvement in explainability compared to state-of-the-art methods across varying sparsity levels, further highlighting its effectiveness and robustness. Moreover, the experimental results, supported by a case study, reveal that the semantic relationships arising from affixes in Turkish texts can be identified as part of the model's decision-making process, demonstrating the proposed solution's ability to effectively capture the agglutinative structure of Turkish.Öğe Advancing wound healing: controlled release of tannic acid via epitope imprinted antimicrobial spongy cover material(Springer, 2025) Tuna, Busra; Arisoy, Piril; Oktay Basegmez, Hatice Imge; Pesint, Gozde BaydemirThe increasing resistance of microorganisms to conventional antibiotics calls for alternative antimicrobial strategies. This study introduces a novel approach to acute wound healing by incorporating epitope-imprinted spongy cover materials with antimicrobial properties, using Tannic acid (TA) as the active agent within biocompatible cryogels imprinted with gallic acid. The spongy materials were synthesized and characterized through Fourier Transform Infrared Spectroscopy (FTIR), swelling tests, and Scanning Electron Microscopy (SEM) to assess their structural and physicochemical properties. The antimicrobial efficacy of the cryogels, loaded with 1.5, 3, 5 mg/mL of TA concentrations, was tested against Staphylococcus aureus and Escherichia coli, common pathogens in wound infections. The highest inhibition zone was determined to be 15 mm for S. aureus and 12 mm for E. coli. Maximum TA adsorption was 210.27 mg/g for eMIP and 24.74 mg/g for NIP. Cumulative release studies revealed the highest release rate occurred within the first 2 h. TA release kinetics indicated a non-Fickian diffusion mechanism. Additionally, the biocompatibility and potential cytotoxicity of the spongy materials, including TA-loaded variants, were assessed using the MTT assay on cultured cells. The results confirmed that the spongy materials are non-toxic and do not inhibit cell proliferation, supporting their suitability for acute wound healing. This study demonstrates that TA-loaded epitope-imprinted Poly(2-hydroxyethyl methacrylate) (pHEMA)-based spongy materials possess antimicrobial properties, making them potential candidates for wound and burn dressing applications.
