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Re-evaluation of excavation class limits for underground excavations based on new data
No full textMany researchers have proposed empirical excavatability classifications to easily and quickly assess rock masses. These classifications mostly apply to surface excavations, while those for underground excavations are limited. Updating the classifications proposed for underground excavations based on new data is important in terms of eliminating the deficiencies in this regard. This study determined the engineering properties (RMR, Q, GSI), rock material strengths, and in-situ excavation classes of 16 underground rock masses. The new data were compared with excavation classifications from various researchers and empirical classes. The study found that empirical classifications for surface conditions are not applicable for underground. Excavation is more challenging in underground conditions due to stress from overburden. While excavation classes align for good to very good rock masses in both conditions, there is no perfect match for medium, weak, and very weak rock masses for underground. The study suggests that for underground excavation classes (blasting, hammer&blasting, hammer, and digging), both RMR89 and Q values should be used together to differentiate between classes. When using GSI for classification, the Is(50) value of the rock material should also be considered. The σcm parameter is the most critical in evaluating rock mass excavatability. © The Author(s) 2025.2-s2.0-1050227065864128622
[Mutluluğa Giden Yolda Yaşam Doyumu ve Öznel Zindelik: Bir Yapısal Eşitlik Modeli Uygulaması]
No full textThis study aims to examine the relationships between happiness, life satisfaction, and subjective vitality among student-athletes. Conducted using a correlational survey design, the research included a total of 400 students (149 female and 251 male; Mean age = 21.31 ± 2.32) enrolled in sports sciences programs across three different universities. The data collection tools utilized were the “Subjective Happiness Scale (SHS),” the “Subjective Vitality Scale (SVS),” and the “Life Satisfaction Scale (LSS).” The suitability of the data for analysis was assessed based on skewness and kurtosis values. Data analysis was performed using IBM AMOS V25 software (Chicago, USA), and the relationships between happiness, life satisfaction, and subjective vitality were tested through Structural Equation Modeling (SEM). According to the results of the structural equation model, the path coefficients between vitality, life satisfaction, and happiness were found to be significant. In this context, life satisfaction explains 44% of subjective happiness, while subjective vitality accounts for 54% of. Based on this, it can be suggested that increasing individuals' levels of life satisfaction and subjective vitality may also enhance their levels of happiness. © 2025, Ataturk Universitesi. All rights reserved
Research of Peganum harmala: Phytochemical Content, Mineral Profile, Antioxidant, Antidiabetic, Anticholinergic Properties, and Molecular Docking
No full textPeganum harmala is a significant medicinal, aromatic plant used in traditional medicine and the subject of many studies. In this study, the phytochemical compound and mineral profile of the plant's ethanol extract were identified quantitatively. Antioxidant properties were determined by total phenolic and flavonoid content, FRAP, DPPH, CUPRAC, ABTS, metal chelating, and phosphomolybdenum assays. Antidiabetic, anticholinergic, and skin care properties were specified by the inhibition of tyrosinase, α-glucosidase, α-amylase, butyrylcholinesterase (BChE), and acetylcholinesterase (AChE) enzymes, respectively. In addition, binding interactions of major phytochemicals with all enzymes were investigated by molecular docking studies. The phytochemical compound of the extract contained significant bioactive components such as acacetin, gentisic acid, p-coumaric acid, quinic acid, rutin, apigenin, and chrysin, while the mineral profile was rich in salt elements. AChE, BChE, tyrosinase, α-amylase, and α-glycosidase enzyme inhibitor results were determined as 2.99 mg GALAE/g, 4.14 mg GALAE/g, 35.8 mg KAE/g, 2.76 mmol ACAE/g, and 1.20 mmol ACAE/g, respectively. As a result, it was identified that it had antioxidant properties and strongly inhibited all enzymes except tyrosinase. The docking scores of major bioactive phytochemicals were found to be high. The best binding pose was obtained by docking acacetin into the active site of AChE (PDB: 4EY7), BChE (PDB: 4BDS), α-glucosidase (PDB: 3WY1), α-amylase (PDB: 6GXV) and tyrosinase (PDB: 2Y9X) receptors. Docking score values were calculated as −10.4, −9.2, −8.8, −7.8, and −7.4 kcal/mol, respectively. Thus, it was revealed that P. harmala has an important potential in drug research and treatment of some diseases. © 2025 Wiley-VHCA AG, Zurich, Switzerland.3996030
Combined innovative trend analysis methods for seasonal trend testing
No full textWhile holistic trend identification is essential, it does not consider the periodic, e.g., monthly, trend characteristics needed to identify seasonal trend behavior. Furthermore, identifying seasonal trends can help manage or regulate water resources systems and irrigation and agricultural operations. In this study, the innovative trend significance test (ITST), the revised ITST, and the Wilcoxon signed-rank test, which are non-parametric methods, are proposed as alternative seasonal trend tests by combining them with the innovative polygon trend analysis (IPTA), which provides visual and linguistic examinations of seasonal behaviors. Groundwater level data from the Chilgrove House (United Kingdom), flow data from the Danube River Basin (Romania), precipitation and temperature data from Türkiye were used to compare the proposed methods with the seasonal Mann-Kendall (SMK) method. For temperature and groundwater level data, all methods showed an increasing trend at different confidence intervals, but for other data, trends emerged according to the characteristics of the methods. So, some of the proposed methods are more rigid than the SMK in trend detection, while others are more sensitive. In addition to the advantage of its applications to seasonal trend behaviors, the proposed significance tests are combined with the IPTA method and comparable alternative methods to the SMK. So, seasons with a clear increase or decrease can be seen visually in the proposed combined methods contrary to the SMK method. Thus, both seasonal trend behaviors and inter-seasonal transitions can be examined graphically, and seasonal significance testing can be applied. According to the characteristics of these combined methods, they can be used not only for seasonal trend tests, just like the SMK method, but also for regional trend tests using stations data instead of seasons. © 2024 Elsevier B.V
Determination of Mineral, Fatty Acid, and Soluble Carbohydrate Profiles of Green Algae Ulva rigida, Chaetomorpha linum, Codium fragile, Caulerpa prolifera and Caulerpa racemosa f. requienii Collected from Türkiye Coasts
No full textThe nutritional properties of five different green macroalgae including Ulva rigida, Chaetomorpha linum, Codium fragile, Caulerpa prolifera and Caulerpa racemosa f. requienii from Turkey were investigated. The chemical composition of green macroalgae was varied, with ash, crude fiber, protein, lipid and carbohydrate ranging from 40.71 to 52.82%, 12.02-17.56%, 4.40-26.19%, 0.57-3.85% and 4.58-42.28% in dry weight, respectively. The fatty acid contents of the algae were quite variable and palmitic acid (C16) was found to be the primary fatty acid for all the samples with a value of more than 49.61%. Palmitic acid was followed by oleic acid, which is a monounsaturated fatty acid. This study revealed that green algae are rich in important soluble carbohydrates such as myo-inositol and glucose, health promoting unsaturated fatty acids (mainly oleic acid) and essential macroelements such as potassium, magnesium and microelements such as iron, zinc and selenium. The results of the current study contribute to a better understanding of macroalgae and encourage their use in food-related applications. © 2025, Central Fisheries Research Institute. All rights reserved
A multi-stage fusion deep learning framework merging local patterns with attention-driven contextual dependencies for cancer detection
No full textCancer is a severe threat to public health. Early diagnosis of disease is critical, but the lack of experts in this field, the personal assessment process, the clinical workload, and the high level of similarity in disease classes make it difficult. In recent years, deep learning-based artificial intelligence models have shown promise, with the potential to increase diagnosis speed and accuracy. These models attract attention with their automatic learning and adaptation capabilities. In this study, the deep learning-based PADBSRNet model and the PADBSRNet-Vision Transformer (ViT) hybrid method are proposed for the detection of brain tumors and skin and lung cancers. PADBSRNet is a comprehensive deep neural network architecture that integrates separable and traditional convolution layers, multiple attention mechanisms, bidirectional recurrent neural networks, and cross-connections/multi-stage feature fusion strategies. This architecture offers significant advantages in terms of effectively extracting local-global, contextual features and accurately modeling long-term dependencies in image classification tasks. The second proposed approach developed a hybrid method that combines the advantages of the PADBSRNet model and the ViT model. Experimental analysis on medical datasets such as the Figshare Brain Tumor Dataset, IQ-OTH/NCCD Dataset, and Skin Cancer: Malignant vs. Benign Dataset has evaluated the proposed models' performances. According to the experimental results, the PADBSRNet model has shown successful performance with 95.24 %, 99.55 %, and 88.61 % accuracy rates, respectively. The experimental findings show that the proposed deep learning model can effectively learn the complex relationships and hidden patterns of cancer disease, thus producing applicable and effective results in cancer diagnosis.4005417
Development of analytical methods and method validation for the qualitative and quantitative determination of Carboxymethyl Cellulose (CMC) in yogurt and ayran
No full textThis study presents the development and validation of analytical methods for the qualitative and quantitative determination of Carboxymethyl Cellulose (CMC) in yogurt and ayran. The methods were evaluated for their detection limit (LOD), quantification limit (LOQ), and method detection limit (MDL) across multiple samples, demonstrating robust sensitivity with MDL and LOD values of 0.03% for both yogurt and ayran. Recovery studies showed high accuracy, with recovery rates between 98% and 100%, and consistent recovery within the acceptable range of 97–103%, reinforcing the methods' reliability. The quantitative analysis exhibited strong repeatability and reproducibility, with low relative standard deviations (RSDr and RSDR), confirming minimal intra-day and inter-day variability. The calibration curves for CMC analysis demonstrated excellent linearity with high coefficients of determination (R2 = 0.9985 for yogurt and 0.9951 for ayran), ensuring accurate quantification over a wide concentration range. Measurement uncertainty analysis further validated the methods' precision and accuracy, showing low relative uncertainties for trueness, repeatability, and reproducibility. Robustness evaluations indicated that the methods maintained consistent recovery rates despite variations in pH, heating time, and sample quantity, highlighting their reliability under different conditions. For qualitative analysis, the visual images method showed exceptional performance with perfect sensitivity and specificity, accurately identifying all positive and negative samples without any false positives or negatives. This high level of accuracy makes the visual images method a valuable tool for ensuring product safety and compliance with quality standards in the dairy industry. Overall, the validated analytical methods for CMC detection in yogurt and ayran demonstrated high precision, accuracy, and reliability, making them essential for quality control and regulatory compliance in dairy production. © 2024 Elsevier Lt
Development of the Disaster Risk Perception Scale: Evaluation of Its Impact on Disaster Preparedness
No full textObjectives: Developing a disaster risk perception scale is a critical component of Disaster Risk Management (DRM), enabling the assessment and evaluation of the reactions, behaviors, and risk culture characteristics of individuals living under disaster risk. The objective of this study is to develop a disaster risk perception scale and to assess its effect on disaster preparedness.
Methods: A pilot study was conducted with 359 participants, followed by a main study involving 786 participants. All participants resided in Giresun and Elazig, Turkey, the regions recently affected by earthquakes, floods, and landslides.
Results: A reliable and valid disaster risk perception scale with 25 items and 5 dimensions (exposure/impact, probability, uncontrollable, worry/fear, and vulnerability) was developed. The disaster risk perception of the participants differed significantly according to their educational level, income level, city of residence, and disaster education. As per the multiple regression analysis, the exposure/impact and worry/fear variables had positive and significant effects on disaster preparedness.
Conclusions: For future studies, it is recommended to implement the disaster risk perception scale across diverse disaster types to assess and evaluate the outcomes effectively.3996587
Optimizing Visibility of Historical Structures Using Modified Weighted Differential Evolution: Insights from the Kromni Valley, Gümüşhane, Türkiye
No full textIt is very important for historical structures to see each other in order to reveal the historical and cultural identity of a region. Historical structures in the Kromni Valley of Gümüşhane, located near the Sümela Monastery, served as places of worship, communication, trade, and social activity centers during their period of active use. This study analyses the spatial relationships of 38 historic buildings, including churches, chapels and castles, whose 3D models are created by in-situ measurements and point clouds obtained by unmanned aerial vehicles, using a 3D viewshed analysis using geographic information systems and remote sensing data. The research introduces a modified weighted differential evolution-based viewshed analysis (mWDE-WS) to enhance the visibility of these structures. In order to assess the applicability of the proposed method, a statistical comparison was conducted between four different Differential Evolution (DE) algorithms (standard DE, LSHADE, CobiDE, JADE and WDE) and the mWDE. The Wilcoxon signed-rank test indicates that mWDE is a more effective solution than alternative methods for addressing the relevant real-world issues. The study also integrates drainage network analysis to assess flood risks and the relationship between cultural structures and water flow. Findings show that historical structures in the region were built not randomly but within a rational approach and 64% of the study area is visible from structures and 2% of the area is visible from ten or more structures. mWDE-WS analysis revealed that the visible area could increase by 20% to 84.37% if the historic structures were placed in optimal locations. In addition, the historical structures were built away from 3rd order streams to minimize flood risk and humidity, demonstrating the community's awareness of the local topography and hydrology. © Author(s) 2025
Yığma taş minarelerin doğal frekanslarının sıcaklık ve neme bağlı değişimleri
No full textIt is very important to distinguish the reason of change in natural frequencies of structures either caused by a possible damage or environmental conditions as temperature and humidity. In this study, the changes in the dynamic properties of masonry minarets under environmental effects such as temperature and humidity were investigated. The Minarets of İskenderpaşa, Hacı Kasım and Tavanlı Mosques in Trabzon were monitored by ambient vibration test method, the relationship between natural frequencies and temperature and humidity was tried to be determined. For this purpose, the natural frequencies of these minarets were measured at certain intervals under different temperature and humidity conditions over a period of approximately six months. The vibration measurement system which was developed by our research team was used in the measurements. From the data collected by these measurements, the variation intervals of the natural frequencies (the smallest and the highest values), the percentages of change and their relations with temperature and humidity were revealed. This relationship was determined by using linear-nonlinear simple and multiple regression analyses. From the study, it was found that the natural frequencies change under environmental effects such as temperature and humidity, and this rate of change was approximately 7%. © 2025 Gazi Universitesi. All rights reserved