Recep Tayyip Erdoğan Üniversitesi Kurumsal Akademik Arşivi
DSpace@RTEÜ, Recep Tayyip Erdoğan Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
High-resolution DIC analysis of in situ strain and crack propagation in coated AZ31 magnesium alloys under mechanical loading
(Springer Nature, 2025) Yavuzyeğit, Berzah; Karali, Katerina; Davis, Sarah; Morrison, Benjamin; Karabal, Süleyman; Balandiz, Kemal; Blunn, Gordon
Biodegradable magnesium (Mg) alloys are promising for various biomedical applications but their susceptibility to corrosion poses significant challenges. This study systematically examines the microstructural integrity and failure mechanisms of electrochemically deposited phosphate- and fluorine-rich coatings on AZ31 Mg alloy subjected to three-point bending (3 PB) in both non-corrosive and physiological (HBSS) environments. High-resolution digital image correlation (HR-DIC) combined with scanning electron microscopy (SEM) enables in situ visualization and quantitative analysis of crack initiation, evolution, and propagation within the coatings. Our findings reveal that thinner (5 µm) coatings are prone to forming dense networks of fine cracks, while thicker (15 µm) coatings display fewer but wider cracks, with both morphologies strongly governed by localized shear strain. Importantly, cross-sectional analyses after load-holding demonstrate that, while surface cracks initially remain confined within the coating, cracks generated under higher mechanical loading can propagate through the entire coating thickness. These through-thickness cracks create direct pathways for corrosive fluids to access the underlying alloy, serving as initiation sites for stress corrosion cracking within the substrate. Furthermore, our results indicate that fluoride in the coating mitigates rapid corrosion. Overall, the study reveals that coating failure and the formation of through-thickness cracks play a critical role in facilitating localized corrosion and crack initiation within the alloy under combined mechanical and corrosive environments.
Impacts of agritech on sustainable agriculture in Sub-Saharan Africa: a quantile regression approach towards SDG 2.4
(BioMed Central Ltd, 2025) Kantoğlu, Barış; Çabaş, Meral; Erdem, Azad; Pilatin, Abdulmuttalip; Barut, Abdulkadir; Radulescu, Magdalena
Agricultural greenhouse gas emissions on the planet threaten both food security and climate change. The United Nations is calling for food security and sustainable agriculture to end hunger by 2030. Sustainable Development Goal 2.4 addresses resilient agricultural practices to combat climate change and produce sustainable food. Resilient agricultural practices are only possible with agricultural technologies (AgriTech) that will create a digital transformation in agriculture. AgriTech can meet the increasing food demand by increasing production efficiency while increasing resource efficiency by combating problems such as climate change and water scarcity. The aim of this study is to examine the impacts of AgriTech usage on sustainable agriculture in Sub-Saharan African (SSA) countries. The analyses were conducted using panel data from 20 SSA countries between 2000 and 2022. In this study, MMQR (Method of Moments Quantile Regression) provided consistent results across quantiles in variable interactions, while GMM (Generalized Method of Moments) and KRLS (Kernel Regularized Least Squares Method) approaches were used to ensure consistency of results. The findings confirm that AgriTech (ATECH) and agricultural value added (AGRW) contribute significantly to sustainable agriculture in SSA countries. The coefficients of ATECH and AGRW variables are negative and statistically significant in all quantiles. This shows that when AgriTech use and agricultural value added increase in SSA, emissions from agriculture decrease and the environment improves. However, agricultural credits (ACRD) are insufficient to reduce agricultural emissions. Furthermore, agricultural workers (AEMP) and internet use (INT) help reduce agricultural emissions up to the 60th and 50th quantiles, while this effect disappears at higher quantile levels. These results emphasize the importance of integrating green procurement and green production technologies supported by green credits into agricultural production in order to achieve sustainable agricultural development goals in SSA. Policies that facilitate farmers’ access to agricultural green credits should be adopted in SSA societies. Infrastructure works that will increase farmers’ access to the internet should be increased. Awareness of agricultural workers on green production and sustainability should be provided to agricultural workers. Highlights. The results show that agricultural technologies, agricultural growth, agricultural labor, and internet use reduce agricultural emissions in SSAcountries, while credit use increases agricultural emissions. AgriTech use (ATECH) and agricultural value-added (AGRW) have statistically significant negative coefficients in all quantiles, indicating that increasing AgriTech and value-added reduce agricultural greenhouse gas emissions. The potential of AgriTech to reduce emissions is higher in low-emission quantiles (10–30%), while the effect is relatively weaker in high-emission quantiles. Agricultural credits (ACRD) only provide environmental improvements in the low-emission quantile (25%) and are insufficient to reduce emissions in high quantiles. Agricultural labor (AEMP) and internet use (INT) significantly reduced emissions at 10–50% quantiles, while this effect disappeared at higher quantiles. Farmers’ success in reducing emissions is directly dependent on their internet access. Panel instantaneous momentum quantile regression (MMQR) was preferred to capture heterogeneous interactions, and the robustness of the results was confirmed with the GMM and KRLS approaches.
Bosniak classification of renal cysts using large language models: a comparative study
(Springer Heidelberg, 2025) Hacıbey, İbrahim; Kaba, Esat
Background: The Bosniak classification system is widely used to assess malignancy risk in renal cystic lesions, yet inter-observer variability poses significant challenges. Large language models (LLMs) may offer a standardized approach to classification when provided with textual descriptions, such as those found in radiology reports. Objective: This study evaluated the performance of five LLMs-GPT-4 (ChatGPT), Gemini, Copilot, Perplexity, and NotebookLM-in classifying renal cysts based on synthetic textual descriptions mimicking CT report content. Methods: A synthetic dataset of 100 diagnostic scenarios (20 cases per Bosniak category) was constructed using established radiological criteria. Each LLM was evaluated using zero-shot and few-shot prompting strategies, while NotebookLM employed retrieval-augmented generation (RAG). Performance metrics included accuracy, sensitivity, and specificity. Statistical significance was assessed using McNemar's and chi-squared tests. Results: GPT-4 achieved the highest accuracy (87% zero-shot, 99% few-shot), followed by Copilot (81-86%), Gemini (55-69%), and Perplexity (43-69%). NotebookLM, tested only under RAG conditions, reached 87% accuracy. Few-shot learning significantly improved performance (p< 0.05). Classification of Bosniak IIF lesions remained challenging across models. Conclusion: When provided with well-structured textual descriptions, LLMs can accurately classify renal cysts. Few-shot prompting significantly enhances performance. However, persistent difficulties in classifying borderline lesions such as Bosniak IIF highlight the need for further refinement and real-world validation.
When words become voice: intermedial storytelling and identity in the Georgian folk tale master and pupil
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Öztürk, Gül Mükerrem
This article closely examines the Georgian folk tale Master and Pupil, focusing on the intermedial transformation of its sequential narrative structure as an instance of oral storytelling. The tale is analyzed within the broader discourses of performativity, voice, and narrative subjectivity through the lenses of performance theory, media formalism, and the Aarne-Thompson-Uther (ATU) classification system (Type 325). The study reveals a transition in the tale from silence to vocal authority; here, voice functions not only as a means of communication but also as a vehicle for resistance, transformation, and the negotiation of identity. Master and Pupil emerges, beyond a magical apprenticeship narrative, as a multilayered performance of disembodiment and symbolic transmission through an intermedial perspective; in this context, musicality and vocality operate as liminal forces. The pupil's acquisition of voice signifies both a narrative rupture and a restructuring of hierarchical relations. Furthermore, the article situates the tale within the broader matrix of the Georgian oral storytelling tradition, demonstrating how recurring motifs surrounding the transformation of voice reflect culturally embedded patterns of media convergence and embodied knowledge. By foregrounding the tale's intermedial dynamics, this study reframes folk tales as a fluid site of aesthetic, cultural, and epistemic negotiations.
Hedonic hunger and food cravings: understanding their role in premenstrual syndrome among nursing students
(Frontiers Media SA, 2025) Koçyiğit, Emine; Gümüşay, Mehtap; Demirel Özbek, Yağmur
Background: Premenstrual syndrome (PMS), characterized by physical, psychological, and behavioral symptoms occurring during the luteal phase of the menstrual cycle, affects more than 48% of women of reproductive age worldwide. The aim of the research is to examine the relationships between hedonic hunger, food cravings, and emotional eating in relation to PMS among Turkish female nursing students. Method: This cross-sectional and descriptive study was conducted on 207 female undergraduate nursing students. Data were obtained using survey and a face-to-face interview method. The questionnaire includes general information, anthropometric measurements, the Premenstrual Syndrome Scale (PMSS), the Power of Food Scale (PFS), the Food Craving Questionnaire-Trait (FCQ-T), and the Emotional Eater Questionnaire (EEQ). Data analysis was performed with IBM SPSS V26 software. Results: In total, 169 (81.6%) PMS (+) and 38 (18.4%) PMS (−) female students participated in the study. The mean age was 21.09 ± 2.41 years, and the mean body mass index was 23.3 ± 4.07 kg/m2. The PFS-Tr, FCQ-T and EEQ total scores was positively correlated with PMSS scores. The strongest predictor for hedonic hunger was food cravings, whereas hedonic hunger, PMS, and emotional eating were significant factors for food cravings. PMS was a problem experienced by most of the students. The results indicate that the presence of PMS is associated with increased hedonic hunger, food cravings, and emotional eating tendencies among university students. Conclusion: Raising awareness of PMS and conducting nutrition-related trainings for university students would help them get the knowledge and skills they need to manage its symptoms.
