Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12514/3596

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A Methodological Approach To the Investigation of Regional Variations in Artuqid Islamic Architecture
(Nilay Ozsavas Ulucay, 2025) Kutlu, İzzettin; 08.02. Department of Architecture / Mimarlık Bölümü; 08. Faculty of Engineering and Architecture / Mühendislik Mimarlık Fakültesi; 01. Mardin Artuklu University / Mardin Artuklu Üniversitesi
Anatolia is a geographical area characterized by various architectural styles from different civilizations and offers a rich historical and cultural heritage in terms of Islamic architecture. This study aims to examine the spatial features of the Harput, Silvan, and K & imath;z & imath;ltepe Great Mosques built during the Artuqid period and determine the effects of regional differences on the architectural features. The study discusses the historical and architectural characteristics of mosques and adopts a method of analysis based on Kevin Lynch's urban images of paths, edges, districts, nodes, and landmarks. With this method, the plan diagrams, spatial organizations, and facades of the mosques were typologically compared, and their relationships with regional variations were examined. The results reveal that the mihrab dome and the harim plan scheme are significant in the key design decisions in the spatial configuration of the three mosques. However, different architectural approaches, such as the porticoes and interior walls, were developed depending on regional requirements and functions. The study emphasizes the importance of these mosques in Islamic history and provides a framework for examining the relationship between the monumental structures and urban images by using the proposed methodology.
The Mediating Role of Self-Esteem in the Relationship Between Nursing Students’ Self-Efficacy in Paediatric Medication Administration and Their Self-Confidence Levels in Clinical Decision-Making
(BioMed Central Ltd, 2025) Butun, A.; Özbay, H.; Ersü, N.F.
Background: Preventing medication errors and ensuring safe medication application for students to enhance their self-efficacy are important for patient safety. Improving self-efficacy and self-confidence and teaching strategies for managing the anxiety of nursing students during medication administration to children are crucial in paediatric clinical practises. Aim: The primary aim of this study was to evaluate nursing students’ medication administration self-efficacy in children, self-confidence anxiety, and self-esteem in clinical decision-making. The second aim was to reveal the mediating role of self-esteem in the relationship between nursing students’ self-efficacy in medication administration in children and self-confidence and anxiety levels in clinical decision-making. Methods: This study employed a cross-sectional survey research design. A total of 317 nursing students participated in the study. The data were collected between 16/09/2024 and 30/09/2024 via face-to-face survey technique. The data were collected using Student Introduction Form, Medication Administration Self-Efficacy Scale in Children for Nursing Students, Nursing Anxiety and Self-Confidence with Clinical Decision-Making Scale, and Rosenberg Self-Esteem Scale Short Form. Results: Nursing students reported low self-efficacy (45.53 ± 15.85) and self-confidence (62.61 ± 30.16) in paediatric medication administration, along with moderate anxiety levels (89.20 ± 41.99). However, self-esteem levels were high (1.91 ± 0.52). Self-esteem was found to partially mediate the relationship between self-efficacy and self-confidence but did not significantly mediate the relationship between self-efficacy and anxiety. Among the participants, 39.4% stated that they did not make a mistake in calculating the medication dose in children. 69.1% of participants reported a need for training in the preparation and administration of paediatric medications. Conclusion: The results suggest that interventions to improve self-esteem could enhance nursing students’ self-confidence in clinical decision-making, particularly in paediatric medication administration. Incorporating self-esteem-building activities and targeted training into nursing curricula is recommended to address low self-efficacy and moderate anxiety levels. These results have important implications for nursing education, suggesting that such interventions could reduce medication errors and improve patient safety. Future research should explore the long-term impact of these interventions on clinical performance and patient outcomes. Clinical trial number: Not applicable. © The Author(s) 2025.
Assessment of the Usage of Innovative Integrated Photogrammetry Method in Structural Behavior Analysis: the Case of Mardin Melik Mahmut Mosque
(Association for Computing Machinery, 2025) Kutlu, I.; Soyluk, A.
The integration of photogrammetric modeling with the finite element method has emerged as a valuable approach in the practical analysis and determination of structural behavior. Photogrammetry, a technique that utilizes the analysis and processing of photographs to create 3D models of real-world objects, offers a powerful tool for capturing accurate geometric data. On the other hand, the finite element method provides a numerical framework for the mathematical modeling and analysis of complex structural systems. This article presents a methodology that integrates these two modeling techniques by comparing their performance with integrated and classical models. Classical modeling is a technique performed in a finite element software and has been applied for many years. Accordingly, this study aims to reveal the limitations of photogrammetry, develop solutions to these limitations, and provide integrated model generation. The material definitions and load assignments were kept consistent across both modeling techniques for observing the differences in analysis. The study used SAP2000, and modal analysis was conducted to analyze the behavior and to compare the geometrical properties of the models independent of region and time. The obtained results reveal a high level of similarity, with the natural vibration periods of the models demonstrating 98%, the stress values exhibiting 90%, and deformation values 90% similarity, a result of the dynamic loads applied in the X-Y direction. Consequently, this study highlights the potential for further improvement in the integrated model generation process by identifying the advantages and disadvantages of each modeling technique. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Efficient Removal of Ciprofloxacin From Water Using High-Surface Activated Carbon Derived From Rice Husks: Adsorption Isotherms, Kinetics, and Thermodynamic Evaluation
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Demirdağ, E.; Demirel, M.F.; Benek, V.; Doğru, E.; Önal, Y.; Alkan, M.H.; Alacabey, İ.
Activated carbon is widely recognized as an effective material for removing pollutants, especially pharmaceutical residues, from water. In this study, high-surface-area activated carbon derived from rice husks (RHAC) was synthesized via KOH activation and used for the adsorption of ciprofloxacin, a widely used fluoroquinolone antibiotic. Its adsorption behavior was systematically investigated through batch experiments varying the pH, adsorbent dosage, contact time, initial concentration, and temperature. The RHAC exhibited a high surface area of 1539.7 m2/g and achieved a maximum adsorption capacity of 398.4 mg·g−1. The Freundlich isotherm best describes its adsorption equilibrium, suggesting multilayer adsorption on a heterogeneous surface. Kinetic modeling revealed that the adsorption process followed a pseudo second-order model (R2 = 0.9981), indicating chemisorption as the rate-limiting mechanism. Thermodynamic parameters (ΔH° = 6.61 kJ/mol, ΔG° < 0) confirmed that the process was endothermic and spontaneous. These findings demonstrate that RHAC is a highly efficient, low-cost, and sustainable adsorbent for removing ciprofloxacin from aqueous environments. © 2025 by the authors.
Design, Synthesis, Characterization, and Surface Texture Investigation of a Novel Nickel-Supported Magnetic Nanocatalyst (Hierarchical Layered) for Efficient Hydrogen Production (Hydrolysis/Alcoholysis)
(Elsevier B.V., 2025) UMAZ, A.; ECE, M.Ş.
In this study, Fe3O4@TROMETHAMINE-Ni magnetic nanocatalysts (MNCs) were synthesized for the first time. Various characterization techniques, including fourier transform infrared spectroscopy (FTIR), x-ray diffractometer (XRD), scanning electron microscopy (SEM), pulsed sample magnetometer, electron paramagnetic resonance (EPR), and surface area measurement (BET), have been used to elucidate the structure and morphology of Fe3O4@TROMETHAMINE-Ni MNCs. The average particle size, surface area, and saturation magnetization value of Fe3O4@TROMETHAMINE-Ni MNCs have been measured as 7.97 nm, 60.11 m2/g, and 43.49 emu/g, respectively. The Fe3O4@TROMETHAMINE-Ni MNCs were determined to be superparamagnetic. EPR analysis was used to calculate the g-factor values before and after sodium borohydride (NaBH4) hydrolysis of Fe3O4@TROMETHAMINE-Ni MNCs, which were found to be 4.81 and 4.95, respectively. This value indicates that the electrons surrounding the oxygen vacancies formed on the catalyst surface can enhance transport efficiency and improve catalytic activity. It was optimized by many parameters in hydrogen production with hydrolysis/alcoholysis of NaBH4 using Fe3O4@TROMETHAMINE-Ni MNCs. For hydrogen production by NaBH4 hydrolysis of Fe3O4@TROMETHAMINE-Ni MNCs, it has been carried out using 265 mM NaBH4, 75 mg Fe3O4@TROMETHAMINE-Ni MNCs, and 20 mL of pure water/methanol at room temperature. The amount of hydrogen produced under optimum conditions has been measured as 1533 mL/min·gcat. It was determined that the reusability performance of Fe3O4@TROMETHAMINE-Ni MNCs showed a minor decrease of 8.42 % compared to the initial usage after the sixth cycle. These results show that Fe3O4@TROMETHAMINE-Ni MNCs are a promising material with advantages such as high efficiency in hydrogen production and the ability to be used repeatedly. © 2025 Elsevier B.V.
Comparison of the Gonadoprotective Functions of Nigella Sativa Oil, Metformin and Vitamin E on Streptozotocin-Induced Diabetic Testis
(Edizioni Minerva Medica, 2025) Kaya, S.; Seker, U.; Ozmen, M.F.; Ayaz, H.; Erdogan, G.; Nergiz, Y.
BACKGROUND: Changes in blood glucose levels in DM cause many complications. We aimed to make a detailed comparison study on the protective effects of Nigella sativa oil, metformin, and vitamin E on the histopathologic effects of diabetes on the male reproductive system. METHODS: In the experiment, 30 rats were divided equally into 5 groups: Control, DM, DM+NS, DM+M and DM+E. To induce diabetes in the experimental groups, a one-time injection of 45 mg/kg Streptozotocin was administered. Rats with blood glucose levels above 250 mg/dl were included in the experiment. The experiment period lasted 8 weeks. Weekly body weight of the rats, reproductive organ weights at the end of the experiment, spermatologic data, immunohistochemical staining, TUNEL assay staining and morphometric evaluation were performed. RESULTS: According to Johnsen Biopsy Score and Seminiferous Tubule diameter data, the DM+NS group had similar results to the control group, indicating that Nigella sativa oil preserved the seminiferous tubule diameter structure better than vitamin E and metformin. There were head, neck and tail defects in the diabetes group. Based on the results of the applications carried out to evaluate apoptosis and proliferation in testicular tissue, it can be concluded that the treated diabetic groups, especially the Nigella sativa oil, improved the structure of spermatogenic tubules and also reduced the number of apoptotic cells, as shown by the results of the TUNEL test (P<0.05). CONCLUSIONS: We think that Nigella sativa oil is more effective on the mechanism of diabetes than other active substances and regulates metabolic changes and may be an effective therapeutic agent for diabetes treatment. © 2024 EDIZIONI MINERVA MEDICA.
Digital Perspectives of Sumela Monastery in the Interaction of Cultural Heritage and Technology
(EUM - Edizioni Universita di Macerata, 2025) Kutlu, İ.; Bekar, İ.
The rapid development of technology has a significant impact on the preservation and accessibility of cultural heritage. This study aimed to investigate the impact of technology on historical buildings through digital perspectives of Sumela Monastery in Trabzon (Turkey). The study consists of 4 stages: data collection, field study, photogrammetric modelling and evaluation process. A digital model of the Sumela Monastery was built, the place of digital documentation processes in conservation criteria was revealed, and the monastery model was introduced to a wide audience through the Sketchfab platform. Furthermore, sections from different programs that this digital model can be imported were presented. These digital perspectives provide new possibilities for the documentation, preservation and interactive exploration of heritage. This paper emphasises the role of technology in the field of cultural heritage and discusses the importance of the digitisation of the Sumela Monastery. © 2010 eum edizioni università di macerata Registrazione al Roc n. 735551 del 14/12/2010.
Characterising Acute and Chronic Care Needs: Insights From the Global Burden of Disease Study 2019
(Nature Research, 2025) Zuniga, Y.M.H.; Zumla, A.; Zuhlke, L.J.; Zoladl, M.; Ziaeian, B.; Zhong, C.; Gallus, S.
Chronic care manages long-term, progressive conditions, while acute care addresses short-term conditions. Chronic conditions increasingly strain health systems, which are often unprepared for these demands. This study examines the burden of conditions requiring acute versus chronic care, including sequelae. Conditions and sequelae from the Global Burden of Diseases Study 2019 were classified into acute or chronic care categories. Data were analysed by age, sex, and socio-demographic index, presenting total numbers and contributions to burden metrics such as Disability-Adjusted Life Years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost (YLL). Approximately 68% of DALYs were attributed to chronic care, while 27% were due to acute care. Chronic care needs increased with age, representing 86% of YLDs and 71% of YLLs, and accounting for 93% of YLDs from sequelae. These findings highlight that chronic care needs far exceed acute care needs globally, necessitating health systems to adapt accordingly. © The Author(s) 2025.
Development of an LSU rRNA-Targeted qPCR Assay and Transcriptional Profiling of Defense-Related Genes To Elucidate Barley Resistance To Bipolaris Sorokiniana
(Academic Press, 2025) Alkan, M.; Bozoğlu, T.; Yeken, M.; Yeken, M.Z.; Emiralioğlu, O.; Tekin, F.; Özer, G.
Spot blotch, caused by Bipolaris sorokiniana, severely limits global barley production. This study characterized five isolates from Bolu, Türkiye, and screened 95 barley cultivars for resistance to the most aggressive isolate (B_BS01) using a 1–9 disease severity scale. Cultivars Gazda, Dara, Hilal, Nonius, and Bravo exhibited the highest resistance (Disease severity index: 35.00 %–36.67 %), forming a statistically distinct group. A quantitative PCR assay targeting the LSU rRNA locus of B. sorokiniana was developed, detecting pathogen DNA down to 0.1 pg with high specificity. This assay quantified starkly different colonization dynamics: pathogen DNA was effectively suppressed in resistant cultivars (Dara, Gazda), while it proliferated rapidly in susceptible ones (Meriç, Bülbül), resulting in up to 15-fold higher pathogen loads by 4 days post-inoculation. Temporal expression profiling of defense-related genes (PR1, PR2, PR3, PR5, PR10, CSD, LOX, PAL) was conducted in Dara and Meriç. Notably, PR1 and PR10 were more strongly induced in Meriç (17.06- and 10.56-fold at 72 h post-inoculation), whereas PR3 was preferentially upregulated in Dara. PR5 and LOX were downregulated in both cultivars; CSD showed moderate induction, and PR2 remained relatively stable. The combination of a sensitive qPCR assay and gene expression profiling provides robust tools for resistance screening and supports targeted breeding for spot blotch resistance in barley. © 2025 Elsevier Ltd
Estimation of CO2 Emissions From Vehicles Using Machine Learning and Multi-Model Investigation
(Polska Akademia Nauk, 2025) Mungan, M.S.; Arpa, O.
This study presents a comprehensive analysis of the prediction of carbon dioxide emissions from vehicles using machine learning-based regression models. Linear regression, lasso regression, k-nearest neighbor regression, random forest, and CatBoostRegressor algorithms are systematically evaluated using a dataset of vehicle specifications and emissions data. Hyper-parameter optimization was performed using a grid search method and the performance of the models was measured using mean squared error, root mean squared error, mean absolute error, and R-squared metrics. CatBoostRegressor stood out for its high predictive accuracy, while random forest and k-nearest neighbor models also produced notable results, while linear models failed to model complex data relationships. Correlation analysis showed that engine displacement, number of cylinders, and fuel consumption were strongly correlated (0.92–0.99) with carbon dioxide emissions. The comparison with the literature showed that the study was characterized by its multi-model approach, rigorous data pre-processing, and systematic optimization. However, the geographical limitation of the dataset and the lack of dynamic variables such as driving conditions restrict its generalizability. In the future, explainable artificial intelligence methods and larger datasets may overcome these limitations. By highlighting the applicability of CatBoostRegressor, this study strengthens the contribution of machine learning to environmental sustainability policy and provides methodological innovation in the literature. © 2025 The Author(s).
A Hybrid Machine Learning Approach for Predicting Power Transformer Failures Using Internet of Things-Based Monitoring and Explainable Artificial Intelligence
(Institute of Electrical and Electronics Engineers Inc., 2025) Aslan, Emrah; Özüpak, Y.; Alpsalaz, F.; Elbarbary, Z.M.S.; 08.01. Department of Computer Engineering / Bilgisayar Mühendisliği Bölümü; 08. Faculty of Engineering and Architecture / Mühendislik Mimarlık Fakültesi; 01. Mardin Artuklu University / Mardin Artuklu Üniversitesi
Power 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. © 2013 IEEE.
Citation - Scopus: 4
Bioactive Components, Antioxidant Capacity, and Antimicrobial Activity of Berberis Crataegina Fruit
(Elsevier B.V., 2024) Ercan, L.
Research highlighting the benefits of plants provides possibilities for their application as food preservatives and in complementary medicine. The fruits of the wild shrub species Berberis crataegina, which humans eat, were examined in this study. The objective has been to ascertain the fruit's bioactive constituents, including minerals, phenolic compounds, fatty acids, and volatile components, in addition to its antioxidant and antibacterial properties. The antioxidant capacity of B. crataegina fruit was investigated in vitro by DPPH, DMPD, ABTS, FRAP, CUPRAC, and Total antioxidant methods. Additionally, the disk diffusion technique was used to assess its antibacterial impact on fungus and bacteria. It was determined that the fruit of B. crataegina is rich in Ca (27399 ppm), K (9634 ppm) Mg (5052 ppm), and Fe (470 ppm), contains essential oils such as alpha-linolenic acid (37%), and oleic acid (14%). Strong antioxidant qualities were demonstrated by B. crataegina, particularly in the ABTS and CUPRAC assays. In addition to 47 volatile compounds consisting mostly of aldehydes, fatty acids, and terpenes, 52 phenolic compounds were detected, including chlorogenic acid, rutin hydrate, and procyanidin B2. It also showed antimicrobial properties on S. aureus, P. aeruginosa, and K. pneumoniae. © 2024 Elsevier Ltd
Muscular Strength and Endurance Adaptations To Functional Resistance Training in Young Elite Field Hockey Players
(Frontiers Media Sa, 2025) Gurkan, Alper Cenk; Eraslan, Meric; Aydin, Serhat; Altug, Tolga; Turkmen, Mustafa; Soyler, Mehmet; Kucuk, Hamza
Background: Functional strength training (FST) has gained considerable attention due to its potential in enhancing muscle strength, endurance, and body composition, especially among athletes. The purpose of this study was to assess the effects of a 12-week FST program on performance outcomes such as muscle strength, muscular endurance, and body composition in elite male field hockey players. Methods: The study involved 28 male athletes from the T & uuml;rkiye Hockey Federation Super League, with a mean age of 27.54 +/- 1.34 years and an average athletic experience of 7.62 +/- 0.48 years. The mean height of participants was 180.28 +/- 4.54 cm, and their mean weight was 75.59 +/- 3.08 kg. Participants were randomly divided into two groups: the experimental group (n = 14) and the control group (n = 14). Pre-intervention assessments were conducted to evaluate muscle strength (Leg Extension, Leg Curl, Bench Press, Pushdown), muscular endurance (30-s Sit-up and Push-up tests), and body composition [Body Mass Index (BMI) and Body Fat Percentage (BFP)]. The experimental group participated in the FST program three times per week for 12 weeks, while the control group maintained their usual training regimen. Post-test evaluations were performed using the same testing protocols. Statistical Analysis: Data were analyzed using two-way repeated measures ANOVA to assess the interaction effects of group and time (pre-test vs post-test). Partial eta squared (eta(2)) values were used to report effect sizes, and statistical significance was set at p < 0.05. Data analysis was carried out using SPSS 22.0 software. Normality was assessed through the Shapiro-Wilk test, and data distribution was further examined through skewness-kurtosis values, histograms, box plots, and Q-Q plots. Paired sample t-tests were performed for pairwise comparisons, with Cohen's d used to determine the effect sizes. The classification for effect sizes followed Hopkins' (2002) guidelines: small (>= 0.01), moderate (>= 0.06), and large (>= 0.14). Results: Significant group x time interaction effects were found for all measured variables (p < 0.05). The experimental group showed greater improvements in body composition, muscle strength, and muscular endurance compared to the control group. Specifically, the experimental group experienced a significant reduction in BMI (pre-test: 21.17 +/- 0.64 kg/m(2), post-test: 19.84 +/- 0.85 kg/m(2), p < 0.001) and BFP (pre-test: 15.36% +/- 0.62%, post-test: 12.13% +/- 0.47%, p < 0.001), while the control group showed minimal changes in these variables. Muscle strength improvements in the experimental group were significant for Leg Extension (pre-test: 83.93 +/- 4.87 kg, post-test: 66.07 +/- 4.01 kg, p = 0.003), Leg Curl (pre-test: 99.29 +/- 7.81 kg, post-test: 118.21 +/- 5.04 kg, p < 0.001), and Bench Press (pre-test: 66.43 +/- 6.91 kg, post-test: 87.14 +/- 4.69 kg, p < 0.001). In contrast, the control group did not show significant improvements in these tests. Muscular endurance was also superior in the experimental group for both the 30-s Sit-up (pre-test: 19.21 +/- 0.97, post-test: 23.36 +/- 1.28, p < 0.001) and Push-up (pre-test: 24.66 +/- 2.53, post-test: 27.04 +/- 0.81, p < 0.001) tests. Effect sizes (Cohen's d) indicated moderate to large effects for all measured variables, with d values ranging from 0.46 to 1.14 for strength and endurance improvements. Conclusion: The findings of this study demonstrate that a 12-week FST program significantly improves muscle strength, endurance, and body composition in elite male field hockey players. These results suggest that incorporating FST into athletic training regimens may optimize performance and enhance overall physical fitness in athletes.
Boncuklu Tarla: Production and Social Dynamics of a Middle PPNB Knapped Stone Workshop (Mardin/Türkiye)
(Routledge Journals, Taylor & Francis Ltd, 2025) Kodaş, Ergül; Kodas, Ergul; 02.03. Department of Archaeology / Arkeoloji Bölümü; 02. Faculty of Letters / Edebiyat Fakültesi; 01. Mardin Artuklu University / Mardin Artuklu Üniversitesi
Boncuklu Tarla, located about 2 kilometres west of the Tigris River, is one of the few sites continuously occupied throughout the entire Pre-Pottery Neolithic Period. This site offers key insights into the evolving techniques and typologies of knapped stone tool production during the Neolithisation process. In 2017, excavations revealed a knapped stone workshop on the floor of a domestic structure, dated to the Middle PPNB. A total of 2,067 artefacts-including cores, flakes, debris, and unprocessed raw material-were found in situ, stacked together. Of these, 1,564 pieces are flint and 503 are obsidian. The finds are especially significant for understanding the use of pressure flaking techniques. Detailed typological and technological analyses, supported by experimental studies, have helped reconstruct all stages of the cha & icirc;ne op & eacute;ratoire in this production context. The Boncuklu Tarla assemblage contributes important data on Neolithic craft specialization and the organization of lithic production within domestic spaces.
Boiler Efficiency and Performance Optimization in District Heating and Cooling Systems With Machine Learning Models
(Taylor & Francis Ltd, 2025) Aslan, Emrah; Oezuepak, Yildirim; Alpsalaz, Feyyaz; 08.01. Department of Computer Engineering / Bilgisayar Mühendisliği Bölümü; 08. Faculty of Engineering and Architecture / Mühendislik Mimarlık Fakültesi; 01. Mardin Artuklu University / Mardin Artuklu Üniversitesi
This study focuses on the detection and analysis of boiler efficiency degradation in District Heating and Cooling (DHC) substations. The research presents an innovative approach to optimize boiler efficiency under different scenarios. Although DHC systems provide both heating and cooling services, this study focuses specifically on heating substations. In this context, various machine learning algorithms have been applied to effectively detect boiler efficiency degradation, and hyper-parameter adjustments have been performed using Bayesian optimization to improve the performance of the models. As a result of the analyses, the Gradient Boosting Regressor model showed significantly higher performance compared to other machine learning algorithms. The model successfully predicted the decline in boiler efficiency with an accuracy of 97.8%, and the Matthews Correlation Coefficient (MCC) value was recorded as 0.952. These results show that Gradient Boosting Regressor based approaches provide an effective solution for fault detection and diagnosis in district heating systems. In conclusion, this study provides both theoretical and practical contributions to the optimization of boiler efficiency, fault detection and diagnosis in DHC systems. The solutions offered by the study have the potential to increase the reliability and efficiency of the systems.
Pulsed Electric Fields-Driven Enhancement of Tomato Seed Quality and Resilience: Improving Germination, Stress Tolerance, and Microbial Disinfection
(MDPI, 2025) Akdemir Evrendilek, Gulsun; Yalcin, Bahar
Featured Application This study highlights the potential of pulsed electric field (PEF) technology as an innovative, non-thermal seed treatment method to improve tomato seed quality. By enhancing the germination performance, increasing the tolerance to abiotic stress, and reducing microbial contamination, the PEF treatment offers a sustainable and efficient approach for seed priming in commercial agriculture and seed processing industries.Abstract Seed quality is vital for agricultural productivity, as it directly influences the crop yield and resilience to environmental stressors. This study evaluated the effectiveness of a pulsed electric field (PEF) treatment in enhancing the tomato (Solanum lycopersicum) seed quality, seedling growth, and microbial safety. Tomato seeds were treated with PEFs at energy levels ranging from 1.07 to 17.28 J, and several parameters were assessed, including the germination rate, normal seedling development, tolerance to cold and salinity stress, electrical conductivity, and microbial inactivation. The highest germination rate (72.81%) was observed at 15.36 J on the seventh day of germination, whereas the highest normal seedling rate (94.62%) was recorded at 17.28 J (p <= 0.05). The germination under cold stress (5 days at 24 degrees C) was highest, with a 46.67% germination observed at both 1.92 and 10.88 J. PEF-treated seeds exposed to 100 and 200 mM of NaCl exhibited significantly improved germination compared to the controls (p <= 0.05). The electrical conductivity (EC) was more influenced by the incubation time than by the PEF intensity, as the EC of all samples showed a significant increase from 4 to 8 h. The samples treated with 17.28 J exhibited the highest germination rates under salt stress, reaching 62.00 +/- 0.90% and 50.00 +/- 0.60% under 100 mM and 200 mM of NaCl, respectively (p <= 0.05). The initial mean counts of the total mesophilic aerobic bacteria and the total mold and yeast-4.00 +/- 0.03 and 3.06 +/- 0.03 log cfu/g, respectively-were reduced to undetectable levels by the application of 17.28 J, with higher energy levels yielding greater inactivation. These findings demonstrate that the PEF is a promising technique for enhancing seed quality, promoting seedling vigor, and reducing microbial contamination, supporting its application in sustainable agriculture.
Hybrid Deep Learning Model for Maize Leaf Disease Classification With Explainable AI
(Taylor & Francis Ltd, 2025) Aslan, Emrah; Alpsalaz, Feyyaz; Aslan, Emrah; Uzel, Hasan; 08.01. Department of Computer Engineering / Bilgisayar Mühendisliği Bölümü; 08. Faculty of Engineering and Architecture / Mühendislik Mimarlık Fakültesi; 01. Mardin Artuklu University / Mardin Artuklu Üniversitesi
This study presents a hybrid learning model that integrates MobileNetV2 and Vision Transformer (ViT) with a stacking model to classify maize leaf diseases, addressing the critical need for early detection to improve agricultural productivity and sustainability. Utilising the 'Corn or Maize Leaf Disease Dataset' from Kaggle, comprising 4,062 high-resolution images across five classes (Common Rust, Grey Leaf Spot, Healthy, Northern Leaf Blight, Not Maize Leaf), the model achieves an impressive accuracy of 96.73%. Transfer learning from ImageNet, coupled with data augmentation (rotation, flipping, scaling, brightness adjustment), enhances generalisation, while a 20% dropout rate mitigates overfitting. The key advantage of the hybrid model lies in its ability to combine the strengths of MobileNetV2's localised feature extraction and ViT's global context understanding, enhanced by the stacking model's ability to reduce the weaknesses of either model. Explainable AI techniques, including SHapley Additive exPlanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), and Grad-CAM, provide transparent insights into model decisions, fostering trust among agricultural stakeholders. Comparative analysis demonstrates the model's superiority over prior works, with F1-scores ranging from 0.9276 to 1.0000. Despite minor misclassifications due to visual similarities, the model offers a robust, interpretable solution for precision agriculture.
Nano-Enabled Biochar Modulate Arsenic Toxicity in Plants: a Step Towards Crop Safety and Health
(Springer Int Publ Ag, 2025) Eren, Abdullah; Baran, Mehmet Fırat; Eren, Abdullah; Afzal, Shadma; Alam, Pravej; Baran, Mehmet Firat; Hayat, Shamsul; Department of Medical Services and Techniques / Tıbbi Hizmetler ve Teknikleri Bölümü; 16.01. Department of Organic Agriculture / Organik Tarım Bölümü; 16. School of Vocational Higher School of Kızıltepe/ Kızıltepe Meslek Yüksekokulu; 21. Vocational School of Health Services / Sağlık Hizmetleri Meslek Yüksekokulu; 01. Mardin Artuklu University / Mardin Artuklu Üniversitesi
As global agricultural demands continue to rise amidst increasing environmental stressors, enhancing plant resilience has become a critical necessity. Heavy metals (HMs), especially arsenic (As), severely impact crop productivity and quality, threatening global food security and human health. Arsenic toxicity disrupts normal physiological, biochemical and molecular processes in food crops due to its eco-toxicological effects. Nano-enabled biochar (Nano-BC) has emerged as a promising soil amendment capable of mitigating As-induced oxidative stress in horticultural crops by modulating stress responses, enhancing detoxification pathways and improving plant resilience. This review comprehensively examines the interactions of Nano-BC with soil matrices and microbial communities, highlighting its dual role in influencing soil health and plant growth. While Nano-BC improves soil structure, increases nutrient retention and supports beneficial microbial populations, its potential long-term ecological impacts and interactions with native microbial communities require further evaluation. Furthermore, we discuss the mechanisms by which Nano-BC modulates As bioavailability, phyto-toxicity and detoxification pathways in horticultural crops. Advances in Nano-BC applications have demonstrated its potential in producing "pollution-safe" crops, yet challenges remain regarding its environmental fate and persistence. Future research should focus on optimizing Nano-BC formulations to enhance its efficiency while minimizing unintended ecological consequences. By integrating Nano-BC into sustainable agricultural practices, we can move closer to achieving food security, mitigating HM stress in crops and aligning with global sustainable development goals (SDGs).
Cardiac Autonomic Control Reflects Sympathovagal Changes Associated With Withholding Urination
(Wiley, 2025) Alabdo, Ahmad; Oflazoglu, Basak; Kus, Mehmet Mustafa; Cakan, Pinar; Ugras, Seda; Yildiz, Sedat
IntroductionIncreased volume of the urinary bladder causes urge to urinate and constricts the sphincter by increasing the tonus of the sympathetic nervous system (SNS). Activity of the autonomic nervous system (or sympatho-vagal balance) can be assessed by heart rate variability (HRV). Current study aimed to test in healthy young male participants whether HRV technique reflects increased sympathovagal balance during bladder distention as revealed by strong urge to urinate.Materials and MethodsA total of young and apparently healthy 11 males agreed to participate to the current study. They were asked to provide 5-min continuous electrocardiogram (ECG) recordings in supine position for determination of HRV on two occasions, i.e. before and approximately for 3 1/2 hours after withholding urination. HRV parameters included heart rate (HR, per min), total power (TP, ms2), and standard deviation of RR intervals (SDNN, ms); percentage of successive RR intervals that were different >= 50 ms (pNN50), low frequency (LF) and high frequency (HF) bands and their normalized units (LFnu and HFnu, respectively) and their ratios (LF/HF). Half of the students provided samples on both occasions and those data were compared by paired t-test following log10 transformation.ResultsWithholding urination did not change HR (from 80.0 +/- 4.1 to 84.5 +/- 3.1 per min, p = 0.135) but decreased total power (from 2692 +/- 802 to 1605 +/- 357 ms2, p = 0.008), SDNN (from 50.4 +/- 5.8 to 38.7 +/- 3.8 ms, p = 0.007) and pNN50 (from 15.6 +/- 3.3 to 5.9 +/- 2.6%, p = 0.016) and increased LFnu (from 57.3 +/- 5.3 to 65.1 +/- 4.5, p = 0.029) and LF/HF ratio (from 1.77 +/- 0. 73 to 2.42 +/- 0.47, p = 0.047).ConclusionsIncreased LF/HF together with decreased SDNN and pNN50 suggest that HRV successfully reflects increased sympathetic tonus over the parasympathetic to help accommodate the urine in the bladder. Moreover, it seems that HRV can be used to assess sympathovagal changes non-invasively during voiding. Additionally, it appears that in all HRV measurements, participants should not have postponed their urination during recording.
Antidepressant-Like Effects of Ashwagandha (Withania Somnifera) on Chronic Unpredictable Mild Stress-Induced Depression in Adolescent Rats
(Springer, 2025) Gökdemir, Gül Şahika; Şeker, Uğur; Gökdemir, Mehmet Tahir; Baylan, Mukadder; Demirtas, Berjan; Gokdemir, Mehmet Tahir; Department of Internal Medical Sciences / Dahili Tıp Bilimleri Bölümü; Department of Basic Medical Sciences / Temel Tıp Bilimleri Bölümü; 10. Faculty of Medicine / Tıp Fakültesi; 01. Mardin Artuklu University / Mardin Artuklu Üniversitesi
RationaleAdolescent depression is often linked to biological changes associated with stress. However, new approaches and treatment strategies for early intervention and prevention of depression in children and adolescents are still limited. Ashwagandha is an Ayurvedic herb widely used in the management of anxiety and stress. However, there is no information in the current literature on its potential effect on adolescent depression.ObjectivesThis study aimed to investigate the effects of depression on proapoptotic proteins and neuroinflammation and the antidepressant effect of Ashwagandha on depression-like symptoms in adolescent rats exposed to the Chronic Unpredictable Mild Stress (CUMS) model.MethodsIn the study, CUMS model was used to induce depression in adolescent rats. Rats were treated with Ashwagandha or Sertraline. To evaluate the antidepressant effects, behavioral tests as well as biochemical and histological analyses were performed. Forced Swim Test (FST), Sucrose Test and Elevated Plus Maze Test were performed as behavioral tests. Brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) were measured by the ELISA method in the fronto-parietal cortex. Proapoptotic proteins (Bax and Caspase-3) and inflammatory markers (TNF-alpha and IL-1 beta), as well as glial fibrillary acidic protein (GFAP), were evaluated immunohistochemically in the fronto-parietal cortex.ResultsProapoptotic proteins (Bax and Caspase-3) and inflammatory markers (TNF-alpha and IL-1 beta) were increased in the CUMS group. BDNF and GFAP levels were decreased. Ashwagandha treatment was more effective than Sertraline in reducing the levels of these proteins and markers. Additionally, Ashwagandha prevented weight loss.ConclusionsAshwagandha showed antidepressant-like effects in adolescent rats, reducing apoptosis, inflammation, and neuroinflammation, suggesting potential for treating adolescent depression.

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