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
Analysis of the changes in microstructure, mechanical, and contact properties of multi-pass friction stir processed dp800 steel
(Techno-Press, 2025) Aktarer, Semih Mahmut; Küçükömeroğlu, Tevfik; Sekban, Dursun Murat; Yaylacı, Ecren Uzun; Yaylacı, Murat; Özdemir, Mehmet Emin Ö.; Mirzaloglu, İrem
In this study, the friction stir process (FSP), which can be successfully applied to plate-type materials, was applied to DP800 steel in a varying number of passes (1, 2, and 3 passes), and the effects of the FSP on the microstructure, hardness, and strength values of the steel were examined. In addition, the changes in the strength values after the FSP were transferred to the finite element (FEM) and artificial neural network (ANN) based contact problem models, and the changes in the contact stress and areas were determined comparatively. As a result of the examinations, it was determined that there were significant reductions in grain sizes in the microstructure compared to the pre-processed material at all pass numbers after FSP. As a result, the hardness and strength values of the steel increased after FSP. FEM and ANN analyses revealed that maximum contact stress values increased after FSP due to higher strength, while contact area values decreased proportionally.
Foreign in two homelands: Racism, return migration, and Turkish-German history
(SAGE Publications Inc., 2025) Bilici, İlhan
Michelle Lynn Kahn's “Foreign in Two Homelands: Racism, Return Migration and Turkish–German History,” supported by the German Historical Institute, is a meticulous, influential, and comprehensive study of migration, racism, and the historiography of transnational identity in modern Europe.
Forest load capacity and carbon emissions in the world's largest forest nations: An EKC-based assessment for sustainable management
(John Wiley and Sons Inc, 2025) Pata, Uğur Korkut; Baykut, Ender; Göksu, Serkan
The 2030 Sustainable Development Goals (SDGs) emphasize the crucial role of forests in regulating the global climate. This study investigates the relationship between the forest load capacity factor (F-LCF), which measures the biocapacity of a country's forests relative to human demand, alongside per capita income, urbanization, and CO2 emissions. A panel of the 10 largest forest nations from 1992 to 2021 is analyzed using a cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model, and the Environmental Kuznets Curve (EKC) hypothesis (an inverted-U trajectory of environmental impacts as income grows) is tested by comparing short- and long-term income elasticities. The EKC pattern is confirmed for the whole sample and for Russia, Brazil, Canada, the United States, and Australia, but not for China, India, Indonesia, Peru, and the Democratic Republic of Congo. The results show that higher F-LCF levels reduce CO2 emissions, while rising GDP and urbanization amplify them. These findings underscore the importance of sustainable forest management for achieving the climate target (SDG-13) and protecting terrestrial ecosystems (SDG-15) and call for tailored policies that reflect the forest dynamics of individual countries.
Metal organic framework based humidity sensing: stability, performance, and IoT integration
(Elsevier, 2025) Akram, Waseem; Iqbal, Shahzad; Abbas, Zahir; Mansoor, Shiekh; Shah, Imran; Ullah, Asad; Kim, Woo Young
The incorporation of IoT technology with advanced sensing materials is converting smart agriculture by allowing precise control over environmental conditions and optimizing resource utilization for advanced agricultural productivity. This study examines the potential of metal-organic frameworks (MOFs) for soil moisture detection in plants, focusing on their application in IoT-enabled smart agriculture systems. Two MOFs, synthesized with nickel acetate and zinc acetate, were evaluated for their humidity-sensing capabilities. The nickel acetate-based MOF had a highly porous, rod-shaped morphology with homogeneous dendrites and high capacitance, in contrast to the Zn-MOF, which exhibited clustering and reduced effective humidity collecting sites, as confirmed by Raman and XRD investigations and SEM images. Ni-MOF outperformed Zn-MOF with a 7.5 times increase in capacitance between 10 % and 90 % relative humidity and a minimal hysteresis of 3.5 % at 70 % relative humidity. Additionally, Ni-MOF demonstrated exceptional response and recovery times of 1.6 s and 0.3 s, respectively. These attributes underscore Ni-MOF's suitability for reliable and efficient soil moisture sensing in agricultural applications. By integrating Ni-MOF sensors into wireless sensor networks and IoT frameworks, this research highlights their potential to fuse field-based sensor data with proximal sensing platforms, contributing to enhanced decision-making and optimization of agricultural operations.
Evaluation of parotid tumors using systemic inflammation markers and diffusion-weighted magnetic resonance images
(Taylor and Francis Ltd., 2025) Kılıçtaş, Ahmet Ufuk; Erdivanlı, Özlem Çelebi; Birinci, Mehmet; Beyazal Çeliker, Fatma; Terzi, Suat; Çeliker, Metin; Coşkun, Zerrin Özergin; Dursun, Engin
Background: Preoperative differentiation between benign and malignant parotid gland tumors is challenging. Apparent Diffusion Coefficient (ADC) from Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) and systemic inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have emerged as non-invasive diagnostic tools. Aims/Objectives: To evaluate the diagnostic utility of ADC, NLR, and PLR individually and in combination for distingushing benign from malignant parotid tumors and for differentiating major histopathological subtypes. Material and Methods: This retrospective study included 138 patients with histopathologically confirmed parotid tumors. ADC values were obtained from DW-MRI, and NLR and PLR were calculated from preoperative CBC. A decision tree model incorporating age, gender, ADC, PLR, and NLR was developed, and diagnostic performance was assessed using ROC analysis. Results: Complete data was available for for 108 patients. The decision tree achieved an AUC of 0.837 for malignancy prediction, with age and PLR as key predictors. Excluding ADC did not impact model performance (AUC=0.837; p=1.0). While ADC alone did not differentiate malignancy, it was effective for subtype classification: AUC=0.891 for Warthin tumor vs pleomorphic adenoma, and 0.771 for pleomorphic adenoma vs mucoepidermoid carcinoma. Conclusions and Significance: Systemic inflammation markers enhance malignancy prediction, whereas ADC contributes meaningfully to histological subtype differentiation.
