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Modeling Soil Temperature with Fuzzy Logic and Supervised Learning Methods
No full textSoil temperature is a critical environmental factor that affects plant development, physiological processes, and overall productivity. This study compares two modeling approaches for predicting soil temperature at various depths: (i) fuzzy logic-based systems, including the Mamdani fuzzy inference system (MFIS) and the adaptive neuro-fuzzy inference system (ANFIS); (ii) supervised machine learning algorithms, such as multilayer perceptron (MLP), support vector regression (SVR), random forest (RF), extreme gradient boosting (XGB), and k-nearest neighbors (KNN), along with multiple Linear regression (MLR) as a statistical benchmark. Soil temperature data were collected from Tokat, Türkiye, between 2016 and 2024 at depths of 5, 10, 20, 50, and 100 cm. The dataset was split into training (2016–2021) and testing (2022–2024) periods. Performance was evaluated using the root mean square error (RMSE), the mean absolute error (MAE), and the coefficient of determination (R2). The ANFIS achieved the best prediction accuracy (MAE = 1.46 °C, RMSE = 1.89 °C, R2 = 0.95), followed by RF, XGB, MLP, KNN, SVR, MLR, and MFIS. This study underscores the potential of integrating machine learning and fuzzy logic techniques for more accurate soil temperature modeling, contributing to precision agriculture and better resource management.https://doi.org/10.3390/app15116319https://doaj.org/article/2e4b9ecd05484052ad057ca7971fe20
Gas Flow Sensing with a Piezoresistive Silicon Nanowire-Based MEMS Force Sensor
No full texthttps://doi.org/10.1109/mems61431.2025.1091765
Hydroelastic analysis of partially or totally immersed Mindlin plates with a hybrid isogeometric-based approach
No full textIn this study, the dynamic characteristics of a cantilevered Mindlin plate, partially or totally in contact with fluid on both sides, are examined using the proposed hybrid isogeometric finite element – boundary element framework. The interaction problem is divided into two parts through the implementation of the linear hydroelasticity theory, allowing for the independent treatment of structural and fluid problems. In the structural part of the analysis, the thick plate is modeled as first-order shear deformable by adopting Reissner–Mindlin plate theory, with the material assumed to be homogeneous and isotropic. The resulting eigenvalue problem is then solved by the isogeometric finite element method (IGAFEM). In the second part of the analysis, assuming the fluid is ideal and incorporating the in vacuo dynamic characteristics as boundary conditions, fluid-structure interaction effects are determined by the isogeometric boundary element method (IGABEM) in terms of generalized added mass coefficients. Subsequently, parametric studies for various plate thicknesses and submergence depths are conducted. The analysis reveals that wet natural frequencies differ noticeably from their in vacuo counterparts due to the presence of the free surface of the fluid. In addition, the effect of the radiated free surface waves from the vibrating structure are included into the mathematical model by imposing linearized free surface condition, through the frequency-dependent added mass and hydrodynamic damping effects of the fluid. The numerical accuracy of the proposed approach is verified against the commercial finite element software ANSYS, showing favourable agreement in the predicted natural frequencies and corresponding mode shapes.https://doi.org/10.1177/10812865241309300https://hdl.handle.net/11697/26065
Generating Landslide Archive Inventories Using Web Scraping and NLP Techniques for Türkiye
No full text<title>Abstract</title> <p>Landslides are among the most frequent natural hazards that cause significant loss of life and serious economic damage worldwide. Although many inventories have been created using different approaches to understand landslide events, these are rarely updated automatically or in real time. Traditional approaches are laborious processes due to the time and intensive labor requirements, and are limited in terms of timeliness due to reporting delays. To address these challenges, we developed an automated approach that integrates web scraping, natural language processing (NLP), and geocoding techniques using digital media news sources in Türkiye to create a landslide archive inventory. Our algorithm verified 1727 of the 3051 news articles it captured between 1997 and 2024 as landslides and identified a total of 478 fatalities in 212 deadly incidents. 66.5% of the landslides captured on the web were located at the neighborhood/village level, providing substantial spatial accuracy. This location accuracy has also enabled risk estimation at the neighborhood/village level. Comparison with the manual national inventory shows moderate agreement, with F1 scores ranging from 0.434 to 0.552 in ± 1 and ± 7 daytime windows. The automated method not only captures spatial and temporal patterns of landslides but also extracts key attributes such as location, number of fatalities, and triggering factors (i.e., natural and anthropogenic). Our study demonstrates the potential of web-based automated approaches to complement traditional landslide inventories by providing near-real-time and verifiable data. Finally, we suggest adopting common reporting standards for natural hazard digital newspapers so that this approach can spread globally.</p>https://doi.org/10.21203/rs.3.rs-7463555/v
Improving rPET/PBT Bead Foam Structure via Chain Extender Modification and Blend Variance
No full textAbstract In this study, the influence of the chain extender (CE) and the blend ratio on the bead foam extrusion of rPET/PBT is investigated. The shape and density of the bead foams were analyzed during extrusion using a camera scanner while the morphology of the foam was investigated using scanning electron microscopy (SEM). Melt strength and thermal behavior were also investigated with Rheotens and differential scanning calorimetry (DSC), respectively. Both chain extender and blend ratio had pronounced effect on the foaming behavior. Significant improvements were observed up to 0.8 wt.-% CE in rPET50PBT50, which achieved an average cell size of 107 ± 17 μm and a density of 182 kg/m³, representing a weight reduction of 86.4% compared to the bulk material. In addition, rPET40PBT60 with 0.8 wt.-% CE gave an average cell size of 108 ± 23 μm and a foam density of 170 kg/m³, with a comparable cell size distribution. After CE modification, the melt strength of rPET-dominant blends obtained higher values but a strong decrease in elongation was observed. In contrast, the CE-modified rPET40PBT60 and rPET30PBT70 blends exhibited much higher elongation with a moderate increase in melt strength which resulted in better bead and foam morphologies. DSC analysis revealed lowest crystallization temperature in rPET50PBT50 with deviations shifting towards higher temperatures. All blends except rPET70PBT30 shows double melting peak formation, with higher rPET formulations also exhibiting cold crystallization. These findings provide crucial insight for development of rPET/PBT foams by controlling the blend and CE composition, which is critical for achieving temperature-resistant bead foams with improved structural integrity. Graphical Abstracthttps://doi.org/10.1007/s10924-024-03360-
Optimized Spirulina Fermentation with Lacticaseibacillus rhamnosus: Bioactive Properties and Pilot-Scale Validation
No full textSustainable bio-based products derived from fermentation are gaining increasing interest. The present study was designed to determine the interaction of Lacticaseibacillus rhamnosus 23.2 bacteria with spirulina in a 3 L glass bioreactor and the effect of aeration and agitation speed on the final product biomass and antioxidant capacity. The fermentation medium contained only glucose, an inorganic salt mixture, and spirulina powder. The estimated biomass and antioxidant activity were found to be 3.74 g/L and 84.72%, respectively, from the results of the optimization model. Scale-up was performed with the obtained optimization data, and three pilot-scale fermentations were carried out in a 30 L stainless steel bioreactor. As a result of pilot production, the obtained bioactive products were freeze-dried, and their antibacterial, antioxidant, total phenolic properties, and cytotoxic activity were investigated. The pilot production results showed that the increase in bacterial cell number was around 3–4 log after 24 h of fermentation. An inhibitory effect against pathogenic bacteria was observed. A strong radical scavenging effect was found in antioxidant analyses. Total phenolic substance content was 26.5 mg gallic acid equivalent (GAE) g−1, which was the highest level in this study. Cytotoxic activity showed that bioactive products had a cytotoxic effect against Caco-2 adenocarcinoma cells. This study emphasizes the potential of Arthrospira platensis biomass as a substrate for the production of lactic acid bacteria (LAB)-based bioproducts. It is thought that the results obtained from this study may position potential innovative strategies in the food, pharmaceutical, agriculture, and cosmetic industries.https://doi.org/10.3390/fermentation11050248https://doaj.org/article/9e9a4781f115426887dd03b544059e5chttps://avesis.yildiz.edu.tr/publication/details/3a5f6e1c-72a2-4c9f-b967-56e4d1a35e8c/oa
Metacognitive Awareness and Critical Thinking Disposition of Pre-Service Teachers: A Structural Equation Modeling
No full textMetacognition supports pre-service teachers' critical thinking (CT) processes because higher levels of metacognitive awareness of pre-service teachers increase their disposition to CT. This research aims to examine pre-service teachers' metacognitive awareness in terms of self-, organizational, and judgmental dimensions, to measure their CT disposition in engagement, cognitive maturity, and innovativeness, and to qualify the relationship between metacognitive awareness and disposition to CT of pre-service teachers. In the quantitatively designed study, the “Metacognitive Awareness Scale” and the adapted version of the “Critical Thinking Disposition Scale” were conducted on 305 pre-service teachers studying in the faculty of education in different universities in Turkiye. According to the results of descriptive analyses, the overall level of the pre-service teachers’ self-perceived metacognitive awareness was found high; the organizational awareness of the pre-service teachers was at the highest level whereas their level of judgmental awareness was the lowest, and the overall level of their self-perceived disposition to CT was calculated as high. The results of structural equation modeling analyses indicated that as the level of metacognitive awareness of pre-service teachers increases, their disposition to CT increases. Self- and organizational awareness exerted no significant influence on engagement, cognitive maturity, or innovativeness, while judgmental awareness had a significant positive effect on engagement but not on cognitive maturity or innovativeness.https://doi.org/10.16986/hunefd.170593
Optimization of Cross-Derivatives for Ribbon-Based Multi-Sided Surfaces
No full textThis work investigates ribbon-based multi-sided surfaces that satisfy positional and cross-derivative constraints to ensure smooth transitions with adjacent tensor-product and multi-sided surfaces. The influence of cross-derivatives, crucial to surface quality, is studied within Kato’s transfinite surface interpolation instead of control point-based methods. To enhance surface quality, the surface is optimized using cost functions based on curvature metrics. Specifically, a Gaussian curvature-based cost function is also proposed in this work. An automated optimization procedure is introduced to determine rotation angles of cross-derivatives around normals and their magnitudes along curves in Kato’s interpolation scheme. Experimental results using both primitive (e.g., spherical) and realistic examples highlight the effectiveness of the proposed approach in improving surface quality.https://doi.org/10.2139/ssrn.5097071https://doi.org/10.1016/j.gmod.2025.101275https://doaj.org/article/a6babe1e19a0413fbf2e05af4633e416https://avesis.yildiz.edu.tr/publication/details/c03d781d-011c-4786-954f-31703183ffbc/oa
A Novel Video-Based Approach for Dynamic Structural Identification of Iron Tie-Rods Under Adverse Environmental Conditions
No full texthttps://doi.org/10.1080/15583058.2025.256862