MAU GCRIS Standard Database (Mardin Artuklu University)
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Dini Milliyetçiliğin Müphemliği: Kavramsal Bir Berraklaştırma Girişimi
No full textMilliyetçilik çalışmalarında uzun süre ihmal edilen milliyetçilik ile kutsal inançlar ara- sındaki ilişki, günümüzde devletlerin, devlet dışı aktörlerin ve siyasi liderlerin dinin duy- gusal repertuarına sıkça başvurmasıyla birlikte belirginlik kazanmıştır. Bununla birlikte, dini milliyetçiliğe ilişkin literatür kavramsal ve kuramsal düzeyde henüz yeterince olgun- laşmamıştır. Bu çalışma, kavramın içerdiği belirsizlikleri ele alarak, bu sorunu aşmak amacıyla üçlü bir kategori önerisinde bulunmaktadır. İlk kategoride, dinin etnik kimlikle özdeşleşmesi ve zamanla etnikleşmesi incelenirken; ikincide, dinin milli ideallerle bütün- leşerek ulusal birliğin pekişmesindeki rolüne ışık tutulmaktadır. Üçüncü kategori ise, dini kimliğin medeniyet düzeyinde sınır inşası işlevine odaklanmaktadır. Çalışma, seküler ve dini milliyetçilik arasındaki karmaşık etkileşimlerin hibrit modeller ortaya çıkardığını ve sekülerleşme ile dindarlaşma süreçlerinin esnek, bağlama duyarlı ve yeniden üretilebilir olduğunu savunmaktadır
Synthesis, Characterization of a Novel Nickel-Organo Supported Magnetic Nanocatalysts (Fe3O4@SiO2@Tris@Ni): Effective Hydrogen Generation From Sodium Borohydride
No full textEnergy demand and environmental problems are increasing day by day as global threats. The burning of fossil fuels has harmful effects on ecological systems. Global threats related to energy can be eliminated by environmentally friendly, cost-effective, and renewable resources. Hydrogen is among the sustainable and renewable energy sources due to being the most common element on earth, non-toxic reaction products and having high calorific value. It was the first time nickel-organo-silica supported magnetic nanocatalysts (MNCs) were synthesised in this study. These synthesized MNCs were characterized in detail. Then, these MNCs were used to produce hydrogen from sodium borohydride in high efficiency. The saturation magnetization value and average particle size of the Fe3O4@SiO2@Tris@Ni MNCs have been measured as 33.27 emu/g and 10.26 nm, respectively. The Fe3O4@SiO2@Tris@Ni MNCs were used for the first time in hydrogen generation in this study. The hydrogen generation by sodium borohydride (NaBH4) methanolysis/ethylene glycolysis of the catalyst has been carried out at 298 K using 0.75 % NaBH4, 75 mg nanocatalyst, and 20 mL methanol/ethylene glycol. The amount of hydrogen produced in the methanol/ethylene glycol processes has been measured as 2167 mL H2/g NaBH4. The highest hydrogen generation rate has been obtained using 0.75 % NaBH4, 75 mg catalyst, and 20 mL ethylene glycol, and this value was calculated as 1067 mL H2/(min & sdot;gcat). The reusability performance of the catalyst was determined to have a decrease of 25.86 % after the fifth cycle compared to the initial use. According to these results, the catalyst is a promising material with advantages such as high efficiency in hydrogen generation and the possibility of repeated use.[MAU. BAP.24.SHMYO.039]This study was funded by the project with the grant number MAU. BAP.24.SHMYO.039
Analysis of Adaptation Processes and Anxiety Levels of University Students Staying with Earthquake Survivor Families in State Dormitories
No full textBackground This study aimed to examine the adaptation processes and anxiety levels of university students living with earthquake survivor families placed in state dormitories after recent major earthquakes. Materials and Methods A descriptive, cross-sectional quantitative study was conducted in a state dormitory between May and August 2023. A total of 108 students participated using the snowball sampling method. Data were collected through a Descriptive Characteristics Form and the Beck Anxiety Scale. Statistical analyses included descriptive statistics and linear regression using SPSS 25.0. Results Among the participants, 49% reported increased frequency of contact with their families after the earthquake. Sharing the same dormitory space with earthquake-affected families led to limited personal space for 56%, emotional impact for 51%, and benefits such as emotional support for 56%. Additionally, 45% noted changes in their attitudes, 46% in their social lives, and 56% in their social responsibility awareness. Regression analysis showed that sharing the same environment with families explained 33.7% of the variance in Beck anxiety scores. A significant positive relationship was found between cohabitation with families and anxiety levels (B=0.337, p Conclusions The findings indicate that post-earthquake family cohabitation significantly affects students' psychological and social well-being. Living in close proximity to affected family members increases anxiety levels. Providing psychological support services for students is crucial to reduce anxiety and facilitate post-disaster recovery and adaptation
Political Views as a Lens: Examining the Impact of Socioeconomic Status on Perceived Human Rights Practices Through Life Satisfaction
No full textCevik, Orhan/0000-0002-1519-4376; Aslan, Yavuz/0000-0002-6692-5247;This study aims to examine the relationships between socioeconomic status (SES), life satisfaction, and perceived human rights practices (PHRP) within the framework of Bandura's social cognitive theory, which emphasizes the interaction of personal, environmental, and behavioral factors in shaping perceptions and behaviors. By integrating this perspective, the study provides a novel understanding of how socioeconomic factors and well-being influence human rights perceptions. In addition, a revalidation study of the Human Rights in the Context of Generational Rights Scale was conducted. The research was designed as a quantitative and cross-sectional study. A total of 791 adults living in different cities in T & uuml;rkiye were reached online in June 2022. The data collection tools were a demographic information form, the revalidated version of Human Rights in the Context of Generational Rights Scale, and the Life Satisfaction Scale. The collected data were analysed using IBM's SPSS v.26 and SPSS Amos v.24 and Hayes' Process Macro plug-in v.4.2. It was found that SES has a direct negative effect on PHRP and an indirect positive effect through life satisfaction. In addition, political opinion was found to have a moderating effect on the relationship between SES and PHRP in terms of government and opposition. These findings suggest that perceptions of human rights are influenced not only by structural socioeconomic conditions but also by subjective well-being and political affiliations. This highlights the importance of considering psychological and ideological factors in discussions on human rights perceptions, providing implications for policymakers and scholars examining social inequalities and governance
Inclusive Leadership's Impact on Career Sustainability: Understanding the Mediating Role of Thriving at Work in Humanitarian Organizations
No full textThis study examines the influence of Inclusive Leadership (IL) on Thriving at Work (TW) and Career Sustainability (CS), with a particular focus on the mediating role of thriving in Humanitarian Organizations (HOs). Drawing on Self-Determination Theory (SDT), the Job Demands-Resources (JD-R) model, and Social Information Processing Theory (SIPT), the research presents IL as a contextual resource that encourages psychological safety, fairness, and openness. By fostering these conditions, IL strengthens employees' vitality and capacity for learning, enabling them to remain adaptable and maintain their careers in demanding environments. Survey data were collected from 264 employees working in both international and local humanitarian organizations, and structural equation modeling (SEM) was applied to test the proposed framework. The results indicate that IL has a positive effect on TW, and that thriving partially mediates the link between IL and CS. This demonstrates the crucial role of thriving in converting Inclusive Leadership behaviors into long-term career outcomes. Theoretically, the study advances leadership and career research by integrating IL, thriving, and sustainability into a unified framework. Practically, it suggests that humanitarian organizations should prioritize leadership development and foster supportive environments that build resilience, promote continuous learning, and enhance employee well-being
Determination of Suitable Sowing Date of Safflower in Diyarbakır Conditions
No full textSafflower (Carthamus tinctorius L.) oil is widely used both as a cooking oil and in industrial applications and is tolerant to adverse weather conditions such as cold, drought and salinity. This study was conducted to determine the most suitable sowing date and safflower variety for the conditions in Diyarbakır, Türkiye, during the 2009-2010, 2010-2011 and 2011-2012 growing seasons. The experiment followed a randomized complete block design with split plots and four replications, using two safflower varieties: Remzibey-05 and Dinçer. Seeds were planted on the trial field of GAP UTAEM (GAP Internatiolan Agricultural Research and Training Center). The results showed that the highest seed yields were obtained from the Remzibey-05 variety sown on 15 December (2766 kg ha-1) and 15 November (2755 kg ha-1), and from the Dinçer variety sown on 1 December (2677 kg ha-1). The lowest yield was recorded for the variety Remzibey-05 sown on 15 April (1005 kg ha-1). Besides, the highest crude oil yield was obtained in Dinçer cultivar with in 1st December 831 kg ha-1 and the lowest was obtained from Dinçer variety in 15th April sowing date with 332 kg ha-1. Based on the results, sowing dates between 15 November and 15 December are recommended for optimal safflower production under Diyarbakır condition
Cytotoxic and Antimicrobial Analysis of Biosynthesized Selenium Nanoparticles From Solanum Tuberosum Peels
No full textIn recent years, interest in the eco-friendly manufacturing of metal nanoparticles from plant extracts has surged. Nonetheless, no research has examined the combined antibacterial and anticancer properties of SeNPs synthesized with Solanum tuberosum (S. tuberosum) extract. This study involved the synthesis of selenium nanoparticles (ST-SeNPs) utilizing phytochemicals with reducing and capturing properties derived from the aqueous extract of S. tuberosum shell through a green synthesis approach. To determine the unique characteristics of ST-SeNPs nanoparticles, a variety of techniques were used, including scanning electron microscopy (SEM), zeta potential analysis, transmission electron microscopy (TEM), dynamic light scattering (DLS), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), UV-visible (UV-Vis) spectroscopy, and energy dispersive X-ray spectrometry (EDX). The optical characteristics of ST-SeNPs were validated using UV-Vis measurement, revealing the peak absorbance at 350 nm. FTIR examination verified the presence of functional groups on the surface of the produced ST-SeNPs nanoparticles. Upon examination of the SEM results, it was concluded that the synthesized SeNPs exhibited uniform distribution and possessed a round morphology. The anticancer efficacy of the produced nanoparticles on the A549 lung cancer cell line and OVCAR-3 ovarian cancer cell line after 24 and 48 hours of exposure was assessed using the MTT test. It was established that elevated concentration inhibited cell growth. The inhibitory efficacy of SeNPs against the proliferation of Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and Candida albicans (C. albicans) was assessed using the disk diffusion agar technique. The evaluated SeNPs exhibited antibacterial efficacy against bacterial and yeast cells. The results indicate that ST-SeNPs produced via green synthesis can serve as anticancer and antibacterial agents
Öğretmenlerin Yapay Zekâ Farkındalığı ile Bilgisayarca Düşünme Becerilerinin Çeşitli Değişkenler Açısından İncelenmesi
No full text21. yüzyıldaki teknolojik gelişmeler, öğretmenlerin yalnızca dijital araçları kullanmalarını değil, bu teknolojilere yönelik farkındalık kazanmaları ve düşünme becerileri geliştirmeleri gerektiğini ortaya koymaktadır. Bu doğrultuda, yapay zekâ teknolojilerinin eğitime entegrasyonu, öğretmenlerin bu sistemleri tanıma ve etkili biçimde kullanma becerilerini önemli hale getirmektedir. Bu beceriler arasında, bireylerin karşılaştıkları sorunları sistemli bir şekilde analiz etmelerini ve çözüm üretmelerini sağlayan bilgisayarca düşünme becerisi öne çıkmaktadır. Bu araştırmanın amacı, öğretmenlerin yapay zekâ farkındalık düzeyleri ile bilgisayarca düşünme becerileri arasındaki ilişkiyi çeşitli demografik değişkenler açısından incelemektir. Nicel araştırma yöntemiyle yürütülen bu çalışmanın çalışma grubunu, 2024-2025 güz döneminde gönüllü katılım esasına göre çevrimiçi ortamda ulaşılan 981 öğretmen oluşturmaktadır. Veriler, Demografik Bilgi Formu, Öğretmenler İçin Yapay Zekâ Farkındalık Ölçeği ve Bilgisayarca Düşünme Becerileri Ölçeği aracılığıyla toplanmıştır. Verilerin analizinde betimsel istatistikler, bağımsız örneklem ttesti, tek yönlü varyans analizi (ANOVA), Pearson korelasyon analizi ile birlikte Tukey ve Tamhane testleri kullanılmıştır. Bulgular, öğretmenlerin yapay zekâ farkındalık düzeylerinin ve bilgisayarca düşünme becerilerinin genel olarak orta düzeyde olduğunu ortaya koymuştur. Ayrıca, bazı demografik değişkenlere (cinsiyet, eğitim düzeyi, görev yapılan okul türü, hizmet içi eğitim alma ve yapay zekâ aracı deneyimleme durumu) göre öğretmenlerin yapay zekâ farkındalığı ve bilgisayarca düşünme becerilerinde anlamlı farklılıklar bulunmuştur. Yapay zekâ farkındalığı ile bilgisayarca düşünme becerileri arasında pozitif yönde anlamlı bir ilişki tespit edilmiştir. Elde edilen sonuçlar, öğretmenlerin teknolojik farkındalık düzeylerinin artırılmasının, 21.yy. becerilerinin geliştirilmesi açısından önemli katkılar sağlayabileceğini göstermektedir.In the 21st century, technological advancements have necessitated that teachers not only use digital tools, but also develop awareness of these technologies and enhance their thinking skills. In this context, the integration of artificial intelligence technologies into education has made it increasingly important for teachers to acquire the skills required to understand and use these systems effectively. Among these skills, computational thinking stands out, as it enables individuals to systematically analyze problems they encounter and generate appropriate solutions. The aim of this study is to investigate the relationship between teachers' levels of awareness of artificial intelligence and their computational thinking skills, while considering various demographic variables. This study employed a quantitative research design, and the sample consisted of 981 teachers who voluntarily participated via an online platform during the fall semester of the 2024–2025 academic year. Data were collected through a Demographic Information Form, the Artificial Intelligence Awareness Scale for Teachers, and the Computational Thinking Skills Scale. For data analysis, descriptive statistics, independent samples t-test, one-way analysis of variance (ANOVA), Pearson correlation analysis, as well as Tukey and Tamhane tests were used. The findings revealed that teachers' levels of awareness about artificial intelligence and computational thinking skills were generally moderate. The findings also indicated significant differences in teachers' artificial intelligence awareness and computational thinking skills based on certain demographic variables (gender, level of education, type of school, participation in in-service training, and experience with AI tools). A significant positive relationship was found between awareness of artificial intelligence and computational thinking skills. The results obtained suggest that increasing teachers' levels of technological awareness can make important contributions to the development of 21stcentury skills
A Hybrid Machine Learning Approach for Predicting Power Transformer Failures Using Internet of Things-Based Monitoring and Explainable Artificial Intelligence
No full textElbarbary, Zakaria/0000-0003-1750-9244; Alpsalaz, Feyyaz/0000-0002-7695-6426; Aslan, Emrah/0000-0002-0181-3658Power transformers are critical components in ensuring the continuous and stable operation of power systems. Failures in these units can lead to significant power outages and costly downtime. Existing maintenance strategies often fail to accurately predict such failures, highlighting the need for novel predictive approaches. This study aims to improve the reliability of power systems by predicting transformer failures through the integration of IoT technologies and advanced machine learning techniques. The proposed hybrid model combines the LightGBM algorithm with GridSearch optimization to achieve both high predictive accuracy and computational efficiency. In addition, the model enhances interpretability by incorporating SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) for transparent decision making. The study presents a detailed comparison of different classification algorithms and evaluates their performance using metrics such as accuracy, recall, and F1 score. The results show that the hybrid model outperforms other methods, achieving an accuracy of 99.91%. The SHAP and LIME analyses provide engineers and researchers with valuable insights by highlighting the most influential features in failure prediction. In addition, the model's ability to efficiently handle large data sets enhances its practicality in real-world power systems. By proposing an innovative approach to failure prediction, this research contributes to both the theoretical foundation and practical advancement of sustainable and reliable energy infrastructures.Deanship of Research and Graduate Studies at King Khalid University [RGP2/108/46]The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Small Research Project under grant number RGP2/108/46
Prognostic Value of Hemoglobin, Albumin, Lymphocyte, Platelet (HALP) Scores in Patients With Non-Valvular Atrial Fibrillation: Insights From the After-2 Study
No full textObjectives: The relationship between hemoglobin, albumin, lymphocyte, platelet (HALP) score, and various cancers and cardiovascular diseases has been tested previously. However, the relationship between HALP score and non-valvular atrial fibrillation (NVAF) has not been adequately tested. Therefore, our study aimed to investigate the relationship between HALP score and mortality in patients with NVAF. Methods: This study included 2,592 NVAF patients from 35 centers in Turkey. Patients were divided into two groups: those with HALP scores 58.96 (high HALP score group, 1,296 patients). The primary outcome measured was all-cause mortality. Results: The mean HALP score was 66 +/- 33. Patients in the low HALP score group had higher 1- and 5-year all-cause mortality rates (1-year: 12.9% vs. 5.4%, p < 0.001; 5-year: 38.5% vs. 20.2%, p < 0.001). Cox regression analysis identified the HALP score as an independent predictor of mortality (1-year: HR = 0.987, 95% CI = 0.981-0.992, p < 0.001; 5-year: HR = 0.990, 95% CI = 0.987-0.993, p < 0.001). ROC analysis determined a HALP score 52.3 predicted 1-year mortality with 62.9% sensitivity and 62% specificity (AUC = 0.680); a score of 55 predicted 5-year mortality with 60.3% sensitivity and 62.2% specificity (AUC = 0.657). Kaplan-Meier analysis revealed increasing mortality over time in the low HALP score group (log-rank tests, 1-year = 44.86, p < 0.001; 5-year = 108.54, p < 0.001). Conclusions: The HALP score is a simple, accessible measure, and our findings suggest that lower HALP scores are associated with increased 1-year and 5-year mortality in NVAF patients. This provides a reference for clinicians assessing risk in this vulnerable population