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
Examination of the empathy scores of students enrolled in a faculty of dentistry
(Selcuk University, 2026) Beder, Melek; Yemenoğlu, Hatice; Şahiner, Gurbet Alev Öztaş
Background: To examine the empathy scores of undergraduate and postgraduate students studying at Atatürk University Faculty of Dentistry. Methods: A total of 465 undergraduate and postgraduate students enrolled in Atatürk University’s Faculty of Dentistry during the 2024-2025 academic year participated in the study. A questionnaire form was administered digitally to these students, including 11 questions addressing sociodemographic characteristics and the 20-question Jefferson Scale of Physician Empathy-Student Version (JSPE-S) to assess the students’ empathy scores. Results: The mean empathy score for all students was 83.90±13.67. Male students had significantly higher empathy scores than female students (p=0.001). In terms of maternal education, students with mothers with postgraduate education had significantly higher empathy scores than students with mothers with lower education levels (p=0.004). Conclusion: This study revealed that dental students and young professionals generally had high levels of empathy, but these levels varied depending on certain personal factors. Empathy training could enable students to communicate more effectively with patients.
A memory-dependent stochastic framework for photoacoustic interactions in poro-semiconductor media under extended Green–Naghdi and spatiotemporal nonlocal effects
(Elsevier, 2026) Sur, Abhik; Marin, Marin; Bhattacharyya, Argha Nath; Yaylacı, Murat; Das, Soumik
This study presents a stochastic framework for analyzing coupled photoacoustic thermo-hydro-mechanical interactions in a porous semiconductor medium, extending beyond conventional deterministic models by explicitly incorporating randomness, memory effects, and spatiotemporal nonlocality. Unlike classical approaches that assume idealized and noise-free conditions, the proposed formulation integrates stochastic boundary excitation through a Wiener process, enabling a more realistic representation of laser-induced thermal fluctuations. The constitutive relations are modeled using a Klein–Gordon-type nonlocal operator, incorporating intrinsic length- and time-scale parameters, while heat conduction is described within an extended Modified Green–Naghdi (MGN) framework that accounts for finite-speed propagation. Closed-form analytical solutions are obtained using normal-mode analysis, and numerical simulations are performed for poro-silicon to evaluate the impact of stochasticity on thermophysical fields. The results reveal that stochastic effects significantly amplify the near-surface thermal response, where the variance of temperature, Vθ(x,z,t), is observed to be approximately 70%–100% higher than the corresponding deterministic solution, indicating that stochasticity can nearly double the effective thermal fluctuations at the boundary. This discrepancy gradually diminishes with increasing depth, leading to convergence between stochastic and deterministic profiles. Additionally, acoustic pressure exhibits pronounced boundary-layer fluctuations before stabilizing within the medium. These findings demonstrate that incorporating stochastic effects is essential for accurately capturing boundary-dominated photoacoustic phenomena in semiconductor materials. The proposed model provides a unified and physically consistent framework that enhances predictive capability and is applicable to advanced technologies such as MEMS devices, photothermal imaging, laser-based material processing, and nanoscale semiconductor systems.
Plant-microbiome interactions are associated with enhanced salinity tolerance and methane emissions in rice
(Elsevier, 2026) Aycan, Murat; Fakhet, Dorra; Picazo, Pedro J.; Bodur, Seda; Nagano, Hirohiko; Asiloglu, Rasit; Mitsui, Toshiaki
Salinity is a severe environmental stressor that reduces crop performance, alters soil microbial communities, and influences greenhouse gas emissions such as methane (CH4). Climate change is expected to further increase salinity globally. Although plants have evolved physiological and molecular mechanisms to cope with salinity, the role of plant-microbiome interactions in salinity tolerance and their link to CH4 emissions remain poorly understood. Here, we investigated the interactions among plant salinity tolerance, rhizobiome, and CH4 emission under salinity stress. We used salt-tolerant and salt-sensitive rice genotypes grown in nutrient-poor paddy field soil and nutrient-rich commercial nursery soil under climate-controlled greenhouse conditions with salinity stress until harvesting. Salt-sensitive genotypes exhibited decreases in early biomass and gas exchange due to salinity stress under nutrient-rich nursery soil. However, salinity effects were mitigated by plant-microbiome interactions, which improved plant growth performance. Rhizosphere microbiome analysis revealed that Rhizobacteria, including Cyanobacteria, were associated with plant development and salinity tolerance. Salinity altered methanogenic archaeal communities, especially Methanobacteria and Methanocellia, with salt-tolerant genotypes releasing more CH4 during stress. Gas exchange and antioxidant enzyme activity were positively correlated with CH4 emissions, suggesting an association between improved physiological performance under salinity and microbial methanogenesis. Gene expression profiling revealed a significant upregulation of hormone- and ion-transport-related genes in paddy soil, which may be associated with stress tolerance, microbial activity, and CH4 emissions. This study proposes a mechanistic framework that links plant salinity tolerance, rhizosphere microbial dynamics, and methane production, illustrating how these interconnected processes shape plant performance and the environmental outcomes. These findings emphasize the necessity of balancing agricultural productivity with CH4 emissions and soil resilience under climate-induced stress.
Influence of ECO coating thickness and microstructural defects on corrosion, corrosion fatigue, and stress corrosion cracking in biomedical Mg alloys
(Elsevier, 2026) Yavuzyeğit, Berzah; Karali, Katerina; Davis, Sarah; Balandiz, Kemal; Jones, Lauren; Smith, Nigel; Blunn, Gordon
Resorbable magnesium (Mg) alloys are attractive for orthopaedic and cardiovascular implants but can degrade rapidly in physiological electrolytes, and combined corrosion–mechanical loading may trigger premature failure. Electrochemical oxidation (ECO) coatings can reduce corrosion by forming a ceramic-like surface enriched with fluoride and phosphate species, yet their brittleness raises concerns regarding integrity under concurrent corrosion and loading. Here, we investigate how ECO coating thickness influences corrosion behaviour and mechanical response under physiologically relevant conditions. AZ31 and X0 alloys were coated with 5 μm and 15 μm ECO layers and tested under static and cyclic three-point bending (3PB) in Hank's balanced salt solution (HBSS). 3PB fatigue tests revealed that cracks in the alloy initiate at the tensile surface and are associated with coating defects such as pits and cracks in the coating, or localised Ca-P deposits. Under non-corroded conditions and after 1-week of corrosion, uncoated alloy rods demonstrated slightly higher fatigue resistance and delayed crack initiation compared to coated counterparts. After 3 weeks of immersion, only the coated rods retained load-bearing capacity, with the 15 μm coating showing the longest fatigue life. Under static sustained loading, all coatings reduced crack initiation under elastic stress, whereas the 15 μm coating suppressed through-thickness crack propagation under plastic loading and thereby prevented catastrophic stress corrosion cracking (SCC)-style failure over the test duration. Overall, ECO coatings do not universally eliminate corrosion–mechanical interactions; rather, their protective efficacy is strongly condition-dependent and increases for the thicker coating under the environment–load combination examined.
Citronella oil as a natural anesthetic alternative to 2-Phenoxyethanol in Danube sturgeon (Acipenser gueldenstaedtii): Artificial neural network (ANN) optimization and multilevel physiological assessment
(Elsevier, 2026) Minaz, Mert; Er, Akif; Ak, Kübra; Köse, Özay; Alparslan, Cem; Tuhan, Merve; Hoseini, Seyyed Morteza
This study aimed to optimize the induction and recovery performance of anesthesia in Danube sturgeon (Acipenser gueldenstaedtii) using citronella oil and 2-phenoxyethanol (2-PE), and to evaluate the hematological, biochemical, and histological responses that may occur after anesthesia. Concentrations of 300, 600, and 900 μL L−1 for citronella oil and 750, 1000, and 1500 μL L−1 for 2-PE were tested. An artificial neural network (ANN) based model was developed using the induction and recovery times. According to the model results, the most suitable candidate concentrations in terms of induction and recovery times were determined to be 550 μL L−1 for citronella oil and 1200 μL L−1 for 2-PE. In the hematological evaluation performed after anesthesia, all blood parameters were found to be significantly higher in the citronella group compared to the control group. In the 2-PE group, only platelet (PLT) levels showed a significant increase. In time-series biochemical analyses (0, 3, 6, and 9 h), it was determined that ALT levels were significantly affected by the anesthetic agent and time. In contrast, more limited changes were observed in AST, ALP, and total protein parameters. Histopathological examinations revealed no significant pathological findings in the gill tissue in either anesthetic application. However, the melanomacrophage centers observed in the liver tissue of the 2-PE group suggested a possible agent-related response at the hepatic level. In conclusion, the ANN approach enabled the determination of candidate optimum concentrations for both anesthetics. When hematological, biochemical, and histological findings are evaluated together, citronella oil appears to be a promising natural anesthetic for Danube sturgeon. It may also be a potential alternative to 2-phenoxyethanol. However, this finding needs to be supported by further validation studies.
