Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Gul, Muhammet(102)
- Güler, Ömer(69)
- Akkurt, Nevzat(68)
- Tekin, H.O.(52)
- ALMisned, Ghada(49)
- Yucesan, Melih(49)
- Celik, Erkan(45)
- Zengin, Gokhan(40)
- Serdar, Osman(39)
- Kocabaş, Mehmet(37)
- Aslan, Naim(31)
- Baskonus, Haci Mehmet(31)
- Bulut, Hasan(31)
- Mete, Suleyman(31)
- Paksoy, Mehmet Yavuz(30)
- Kök, Mediha(27)
- Ince, Muharrem(26)
- Yildirim, Ozal(26)
- Özkul, İskender(26)
- Sulaiman, Tukur Abdulkadir(25)
- Topal, Murat(25)
- Guler, Omer(24)
- Serin, Faruk(23)
- Benzer, Fulya(22)
- Erten, Fusun(22)
- Alataş, Mevlüt(21)
- Güler, Seval Hale(21)
- Baykal, Duygu Sen(20)
- Taşgın, Yahya(20)
- Kutlu, Banu(19)
- Onat, Onur(19)
- Sahin, Kazim(19)
- Tanyol, Mehtap(19)
- Torğut, Gülben(19)
- Yildirim, Numan(19)
- Kahraman, Gökhan(18)
- Orhan, Cemal(18)
- Say, Yakup(18)
- Susam, Selim Orhun(18)
- Utku, Anıl(18)
Yayınlar
- MakaleAçık Erişim2026Scopus SJRQ2Design and Characterization of Y2O3/Pr2O3–Enriched Inconel-718 Alloys for Nuclear Applications
Albayrak, Muhammet Gökhan; Güler, Ömer; Güler, Seval Hale; Evin, Ertan; ALMisned, Ghada; Sen Baykal, Duygu; Alkarrani, Hessa; Susoy, Gulfem; Kilic, Gokhan; Tekin, Hüseyin Ozan
This study explores the physical, structural, and radiation shielding enhancements in Inconel 718 superalloys reinforced with 1 wt% Y2O3 and varying Pr2O3 contents from 0 to 10 wt%, respectively. X-ray diffraction analysis confirmed preservation of the face-centered cubic structure, with increasing Pr2O3 inducing peak broadening and partial amorphization. The scanning electron microscopy/energy-dispersive X-ray spectroscopy results verified the homogeneous dispersion of oxides without agglomeration. Gamma-ray shielding parameters, including the mass attenuation coefficient (MAC), half-value layer, and effective atomic number, significantly improved with higher Pr2O3 content, particularly at low to mid photon energies. The 718Y-10PO sample exhibited the lowest transmission factors and the highest MAC values across all the tested energies. Buildup factors decreased in the Pr-rich samples, confirming reduced photon scattering. Notably, the fast neutron removal cross section for 718Y-10PO as 0.15521 cm−1 exceeded the benchmark materials like graphite and B4C. These findings establish the 718Y-10PO alloy as a promising candidate for advanced nuclear shielding applications, combining structural integrity with promising gamma and neutron attenuation capabilities.
- MakaleYalnız künye2026Scopus SJRQ2Synthesis, structural characterization, and radiation interaction behaviour of (ErSmGdYPr)2Hf2O7 high-entropy oxide powder: A preliminary investigation for potential applications in nuclear environments
Güler, Ömer; Güler, Seval Hale; Özkul, İskender; ALMisned, Ghada; Baykal, Duygu Sen; Tekin, Huseyin Ozan
This study represents an initial investigation toward exploring the multifunctional potential of the (ErSmGdYPr)2Hf2O7 high-entropy oxide as a thermal barrier coating (TBC) material in radiation environments. Therefore, the evaluated parameters should be considered as a preliminary step rather than a complete representation of the material’s overall performance in such complex applications. In this context, (ErSmGdYPr)₂Hf2O7 powders were synthesized through high-energy ball milling of commercial rare-earth oxide precursors followed by calcination at different temperatures. Structural evolution during synthesis was investigated using X-ray diffraction, scanning electron microscopy with energy-dispersive spectroscopy, and thermal analysis techniques. The results confirmed the formation of a defective fluorite-type high-entropy oxide structure after calcination at elevated temperatures, accompanied by homogeneous elemental distribution and stable ceramic microstructures. In addition to structural characterization, the radiation interaction behaviour of the synthesized material was evaluated through gamma-ray attenuation parameters and fast neutron removal cross-section analysis. The obtained results indicate that the presence of multiple rare-earth elements provides favorable interaction characteristics with both photons and fast neutrons. These findings highlight the potential of this high-entropy oxide as a precursor for multifunctional coating materials. However, it should be noted that this work represents a preliminary powder-level investigation, and further research on actual coating deposition and thermal testing is required to validate its service performance.
- MakaleYalnız künye2026Scopus SJRQ2Phytoremediation of elements in municipal wastewater treatment plant effluent by Lemna gibba L.: a full-scale study
Topal, Murat; Öbek, Erdal; Çelik, Erdal; Arslan Topal, E. Işıl
In this study, capacity of naturally growing Lemna gibba L. in removing elements (B, As, Al, Ca, Ba, Co, Fe, Cu, K, Cr, Li, Mo, Ni, Mn, Na, Mg, Sb, P, Si, Pb, Se, Ti, Zn, V, and Sr) from the effluent of secondary clarifier of a municipal wastewater treatment plant (MWWTP) was determined week by week (W1, W2, W3, and W4) and analyzed as a whole using statistical models. To determine the removal contribution of Lemna gibba L. to the MWWTP effluent, secondary clarifier without Lemna gibba L. was used as a control. The aim here is to determine the contribution of Lemna gibba L. to MWWTP’s removal efficiency. Trace elemental quantification was conducted via validated ICP-MS following microwave-assisted acid digestion. In this context, according to the analysis results, the removal efficiency of Lemna gibba L. for Al was highest at 89.66% over the weeks. Furthermore, treatment efficiencies above 50% were achieved for Co (57.86–60.61%), Sb (64.25–67.35%), and Ti (63.27–66.21%). Based on statistical analyses, PCA (principal component analysis)) and HCA (hierarchical cluster analysis) models explained 85% of the total variance. As a result, this study demonstrated that Lemna gibba L. removes elements from MWWTP effluent, contributing to the removal efficiency of the secondary clarifier and clearly showing its potential use in phytoremediation.
- MakaleYalnız künye2026Scopus SJRQ1From trash to technology: Ai-driven waste classification with hybrid CNN-transformer approach for sustainable recycling
Utku, Anil
The increasing amount of waste globally requires more efficient recycling processes and increases the importance of intelligent, automatic classification systems. Since traditional waste separation methods are time-consuming and have high error rates, artificial intelligence-based solutions have great potential in this area. In this study, the effectiveness of deep learning-based waste classification models was investigated, and nine different waste types were classified using DenseNet121, EfficientNetB0, ResNet50, ViT, DenseNet121-ViT, EfficientNetB0-ViT, ResNet50-ViT. Experimental results show that hybrid CNN-ViT models achieved the highest accuracy rates. Mainly, the EfficientNetB0-ViT model exhibited the best performance with a 95% accuracy rate and made a balanced classification for all waste types. The model can optimize recycling processes by ensuring the correct separation of wastes and contribute to environmental sustainability by reducing misclassification. Artificial intelligence-supported waste management systems offer an effective solution in critical areas such as reducing greenhouse gas emissions, saving energy, and supporting environmentally friendly urban planning. The findings of this study reveal that deep learning-based artificial intelligence models are an important tool for sustainable environmental management.
AtıfScopus1WoS1OpenAlex3
İncele - MakaleYalnız künye2026Scopus SJRQ2Optimization of native plant selection for phytomining of strategic/critical raw materials using Artificial Bee Colony algorithm
Arslan Topal, E. Işıl; Topal, Murat; Çelik, Erdal; Öbek, Erdal
This study investigates the potential of native plant species (NPs) as secondary sources for strategic/critical raw materials (SCRMs) through phytomining, aiming to identify the most efficient accumulator for sustainable element recovery. To achieve high-precision results, the Artificial Bee Colony (ABC) algorithm, a robust meta-heuristic optimization technique inspired by the foraging behavior of honeybees, was utilized to minimize the error between experimental data and predicted models to optimize the accumulation of key elements including cobalt (Co), strontium (Sr), antimony (Sb), vanadium (V), phosphorus (P), lanthanum (La), magnesium (Mg), titanium (Ti), aluminum (Al), and scandium (Sc). The research focused on three NP species—Musk thistle (MT), curly dock (CD), and Juncus (JS)—collected from a geothermal hot spring area. Methodological validation was performed through comparative statistical analysis and the calculation of bioconcentration factor (BCF) and translocation factor (TF) to assess phytoremediation efficiency. The ABC optimization results revealed that MT exhibited the most significant accumulation capacity, particularly for Mg, reaching a peak concentration of 3,910 mg/kgdw in the leaves. The concentration range (lowest to highest value) was between 0.01 (for La) and 3,910 mg/kgdw for the studied plants. Principal component analysis (PCA) corroborated these findings, explaining cumulative variances of 80.4% (MT), 89.4% (CD), and 76.4% (JS). The innovation of this study lies in the application of the ABC algorithm to the field of phytomining, which offers a more dynamic and flexible alternative to traditional regression-based models. The primary advantage of this proposed method is its superior global search capability and ability to handle multi-elemental interactions with high predictive accuracy. However, a potential disadvantage remains the computational complexity and the requirement for fine-tuning control parameters to ensure consistent convergence. Overall, MT is identified as a highly promising candidate for the phytomining of SCRMs, with Mg emerging as the most effectively accumulated element under the optimized ABC model.
- MakaleYalnız künye2026Scopus SJRQ2Compositional control of structural, magnetic, and gamma-ray attenuation properties in rare-earth substituted Ho-based double perovskite oxides synthesized via mechanical alloying and oxidation
Özkul, İskender; Kalay, Ece; Güler, Seval Hale; Karaduman, Oktay; Şimşek, Telem; Bülbül, Zeynel Abidin; Aksu Canbay, Canan; Sen Baykal, Duygu; ALMisned, Ghada; Tekin, H.O.
Rare-earth substitution provides a route for tailoring the structural, magnetic, and gamma-ray attenuation behaviour of Ho-based Co-Mn double perovskites; however, the combined effects of rare-earth ionic size, magnetic character, and substitution level remain insufficiently understood. In this study, Ho1.5La0.5CoMnO6, Ho1.2Er0.8CoMnO6, Ho1.3Sm0.7CoMnO6, and Ho2CoMnO6 were synthesized through a two-step route involving mechanical alloying to obtain precursor powders, followed by annealing at 1000 °C in air to promote oxidation and double-perovskite phase formation. Their structural, thermal, surface-chemical, magnetic, and gamma-ray attenuation properties were examined by X-ray diffraction, thermal analysis, X-ray photoelectron spectroscopy, SEM-EDS, vibrating-sample magnetometry, and theoretical shielding calculations based on half-value layer (HVL) and transmission factor (TF) parameters. The XRD patterns were consistent with predominantly monoclinic P21/n type double-perovskite structures, while weak additional reflections suggested possible minor secondary phases. SEM-EDS showed homogeneous elemental distributions, and XPS analysis indicated Co2+ dominated and mixed Mn-valence characteristics in the spectra where reliable component analysis was possible. All compositions exhibited a low-temperature ferromagnetic-like field response but did not reach magnetic saturation at 3 T. Ho2CoMnO6 and Ho1.3Sm0.7CoMnO6 showed the highest field-dependent magnetization values at 10 K, whereas Ho1.2Er0.8CoMnO6 displayed the lowest response. The theoretical gamma-ray attenuation calculations showed clear composition-dependent differences. At 0.662 MeV, the HVL values were 1.0650, 0.9972, 1.0438, and 0.9967 cm for Ho1.5La0.5CoMnO6, Ho1.2Er0.8CoMnO6, Ho1.3Sm0.7CoMnO6, and Ho2CoMnO6, respectively. At the same photon energy and a thickness of 1.0 cm, the corresponding TF values were 0.0896, 0.0858, 0.0882, and 0.0860. Thus, Ho1.2Er0.8CoMnO6 and Ho2CoMnO6 exhibited the lowest HVL and TF values among the investigated compositions. The shielding calculations identified Ho1.2Er0.8CoMnO6 and Ho2CoMnO6 as the most effective attenuators, with lower HVL and TF values across the investigated energy range. These results show that rare-earth substitution enables compositional tuning of magnetic and theoretical gamma-ray attenuation behaviour, with the observed trends reflecting the combined influence of rare-earth ionic size, magnetic character, substitution level, and valence-state complexity.
- MakaleAçık Erişim2026Scopus SJRQ1Biochemical effects and theoretical study of a metformin in the carp (Cyprinus carpio) fry
İSPİR, Ünal; Tüzün, Burak; KIRICI, Muammer; Poustforoosh, Alireza; YONAR, Muhammet Enis; YONAR, Serpil MİŞE; ŞEKER, Engin
Pharmaceutical chemicals are frequently detected in wastewater, and metformin, an oral hypoglycemic agent, is among the most common. In this study, the effects of metformin on biochemical (total protein, glycogen, lipid) and antioxidant (malondialdehyde (MDA), glutathione (GSH), glutathione S-transferase (GST), catalase (CAT)) parameters were investigated in carp ( Cyprinus carpio ) fry. Fish were exposed to 40 and 80 µg/L metformin for 96 h, 14 and 21 days. No mortalities occurred in any group. At 80 µg/L for 21 days, total protein activity and lipid levels significantly decreased. Glycogen activity showed no significant differences compared to controls. Antioxidant parameters measured spectrophotometrically revealed that MDA levels, CAT and GST activities decreased with time but increased with dose, while GSH levels rose with time yet decreased with dose. Overall, significant time- and dose-dependent effects ( p < 0.05) were observed. In silico analyses were also performed. The activity of metformin against antioxidant proteins was evaluated, and molecular dynamics simulations confirmed strong interactions with the most active protein. ADME/T analysis provided pharmacokinetic insights, and Gaussian-based quantum chemical calculations (EHOMO, ELUMO, ΔE, dipole, etc.) characterized electronic and structural properties. These combined results indicate that metformin alters key biochemical pathways in carp fry and has significant reactivity toward antioxidant proteins. Findings suggest potential ecotoxicological risks in aquatic systems and relevance to pharmacological profiling.
AtıfScopus1OpenAlex1
İncele - MakaleAçık Erişim2026Scopus SJRQ2Impact of probiotics and β-glucan on the detoxification and gastrointestinal bioaccessibility of aflatoxin B1 in a cereal-based fermented beverage (boza)
Macit, Arife; Sevim, Sumeyra; Sancak, Banu; Kizil, Mevlude
The aim of this study was to investigate the effects of Lactobacillus leichmannii as a probiotic bacteria, Saccharomyces boulardii as a yeast, and β-glucan as a prebiotic on the binding ability of aflatoxin B1 (AFB1) and its bioaccessibility in a cereal-based fermented beverage. For this purpose, nine study groups with their combinations were formed. The amount of unbound AFB1 was determined by high performance liquid chromatography (HPLC) after incubation and during the stomach, small intestine, and colon stages using an in vitro digestion model. After incubation, the highest percentage of AFB1 binding (27.79%) was obtained with S. boulardii. The lowest bioaccessibility was observed with L. leichmannii + S. boulardii at the stomach stage (41%), L. leichmannii + β-glucan at the small intestine stage (52%), and L. leichmannii + S. boulardii + β-glucan at the colon stage (35%). These findings suggest that probiotics and prebiotics reduce aflatoxin bioaccessibility, thereby limiting gastrointestinal absorption.
- MakaleAçık Erişim2026Scopus SJRQ1Multi-Task NILM with Anomaly Detection Using a Hybrid CNN–BilSTM–Transformer Model
Gunay, Mihriban; Demir, Yakup; Zhilevski, Marin
Non-Intrusive Load Monitoring (NILM) enables estimation of the energy use of individual appliances in smart buildings from a single aggregate meter. In practice, however, this task is not straightforward. Signals from different appliances can overlap, and the measured data may also include distortions such as spikes, drops, and noise. To address these issues, this study presents a multi-task triple-hybrid deep learning framework that handles appliance classification and anomaly detection together. The model brings together 1D-CNN, BiLSTM, and Transformer Attention so that local patterns, temporal dependencies, and wider contextual information can be learned within the same structure. It also uses a dual-output design to classify appliance categories and detect anomaly types simultaneously. Experiments were carried out on Building 1 of the UK-DALE dataset with four appliances: kettle, microwave, washer dryer, and fridge freezer. For the anomaly task, synthetic disturbances were added to segmented signal windows and grouped as normal, spike, drop, and noise. To check how well the proposed framework handled different scenarios, it was tested on both the UK-DALE and REDD datasets. Looking at the main UK-DALE results, the model correctly identified appliances 99.48% of the time and spotted anomalies with 98.80% accuracy. A secondary test on the REDD dataset yielded an 86.44% classification score. This proves the architecture can adjust to completely new power grid environments without losing its edge. On top of that, when pitted against standard benchmark models like Seq2Point, this triple-hybrid design clearly does a better job of mapping out complex signal changes. As a result, it yields much stronger anomaly detection metrics.
AtıfOpenAlex1İncele - MakaleAçık Erişim2026Scopus SJRQ1Affective States of Academics: The Dissolving Fantasy of the ‘Good Academy’
Gülçiçek, Demet; Erdoğan, Emine
Drawing on the affective trajectories of academics in social science and humanities departments, this article asks how they imagine a ‘good academy’ and how they navigate the tension between that imagination and the demands of contemporary university regulations. Based on sixteen in-depth interviews with early-career researchers in Ankara, Turkey, it traces how academics narrate their affective relationship with the academy. Bringing together Berlant's conceptualisation of cruel optimism and Ngai's analysis of low-key affective states such as ugly feelings, the article shows that the attachment to the good academy is narrated as something that obstructs flourishing due to the institutional demands in higher education. This in-betweenness is analysed in relation to loosening attachment to the academy that is produced by a mood of irritation.
- MakaleAçık Erişim2026Scopus SJRQ1A Metric-Driven Evaluation Framework for Remaining Useful Life Prognosis with Quantified Uncertainty
Vashishtha, Govind; Chauhan, Sumika; Ertarğın, Merve
This paper introduces a novel metric-driven evaluation framework for Remaining Useful Life (RUL) prognosis in rotating machinery, featuring robust uncertainty quantification. Accurate RUL prediction is vital for optimizing maintenance and preventing failures, but existing methods often struggle with complex nonlinear degradation or lack reliable uncertainty estimates. Our proposed framework integrates a probabilistic Deep State Space Model (DSSM) with a variational inference approach to model complex, non-linear degradation trends and inherent aleatoric uncertainty. A key innovation is the use of the Slime Mold Algorithm (SMA) for efficient hyperparameter optimization, ensuring maximum accuracy. Furthermore, an online adaptation mechanism, governed by a heuristic reinforcement learning agent, allows the model to continuously update its knowledge and adapt to concept drift in real-time. Experimental validation on the IMS bearing dataset demonstrates superior RUL prediction accuracy, evidenced by the lowest Root Mean Square Error (RMSE) of 8.1829 cycles, and a PICP of 0.59416. This dual capability makes the framework highly suitable for real-world predictive maintenance, enhancing safety and reliability.
- MakaleYalnız künye2026Scopus SJRQ3Green revolution in nanotechnology: phytogenic CuO nanoparticles for biomedical and pharmaceutical applications
Ceylan, Yusuf; Korkmaz, Nesrin; Kaçan, Fatma N.; Aydin, Ali; Korkmaz, Şengül A.; Yildirim, Ebru Ş.
Copper oxide nanoparticles (CuO NPs) were synthesized using a green approach with Vitis vinifera L. extract, a plant rich in secondary metabolites that act as natural reducing agents. The obtained CuO NPs were characterized by XRD, EDX, and STEM analyses. FT-IR analysis revealed the presence of functional groups originating from plant biomolecules and confirmed the formation of Cu–O bonds, indicating the successful synthesis and stabilization of CuO NPs. XRD confirmed distinctive CuO diffraction peaks at 32.38°, 35.35°, 38.61°, 40.75°, 48.79°, 51.90°, 57.66°, 61.38°, 65.94°, and 75.12°. STEM imaging showed predominantly spherical, well-dispersed nanoparticles with an average size of 23–38 nm. Antibacterial analysis revealed a minimum inhibitory concentration (MIC) of 4 µg mL−1 against Escherichia coli ATCC 25922. In anticancer assays, the CuO NPs demonstrated notable cytotoxicity at both low concentrations and even at levels below the control group in A549, Calu-1, and Saos-2 cancer cell lines, highlighting their strong biomedical potential.
AtıfScopus1WoS1OpenAlex1İncele - MakaleAçık Erişim2026Scopus SJRQ2Design of Fe–35Ni/PCL nanocomposites with coupled magnetic and shape memory properties
Kök, Mediha; Çirak, Z Deniz; Aydin, Handan; Coşkun, Meltem
In this study, poly(ϵ-caprolactone) (PCL)-based nanocomposite films reinforced with a Fe–35%Ni alloy, which possesses a low coefficient of thermal expansion and distinct magnetic properties, were produced. The composites were prepared using the solvent casting method, with the Fe–Ni alloy incorporated into the PCL matrix at different weight ratios (10%–50%). The structural, morphological, thermal, and magnetic properties of the resulting nanocomposites were comprehensively investigated using FTIR (Fourier transform infrared spectroscopy), XRD (X-ray diffraction), SEM (scanning electron microscopy/energy dispersive x-ray spectroscopy), differential scanning calorimetry, TGA (Thermogravimetric analysis) ve (vibrating sample Magnetometry). FTIR results indicated that the Fe–Ni addition does not form chemical bonds with the PCL matrix and that the composite structure is formed through physical interactions. XRD analyses confirmed that the semi-crystalline structure of PCL is preserved and that the Fe–Ni alloy exhibits a face-centered cubic (FCC) crystal structure. SEM images revealed that while a homogeneous distribution is achieved at low doping levels, partial agglomeration occurs at high levels. Thermal analyses showed that Fe–Ni particles increase the degree of crystallization through a nucleation effect and provide a significant increase in melting temperature and crystallinity values, particularly in the 10%–40% range. TGA results revealed that the thermal stability of the composites increased and their decomposition behavior became multi-stage. Magnetic measurements showed that the saturation magnetization increased significantly with increasing Fe–Ni content, and the composites acquired ferromagnetic character. Furthermore, it was determined that the developed composites exhibit distinct shape memory behavior and can return to their original form upon thermal stimulation. The findings indicate that Fe–35%Ni-doped PCL nanocomposites are a promising candidate for multifunctional applications due to their enhanced thermal, magnetic, and smart material properties.
- MakaleYalnız künye2026Scopus SJRQ1The Effect of Women’s Menstrual Attitudes and Hygiene Practices on Self-Care Behaviors
Yeyğel, Çiler; Yeşiltepe, Akgün
Objective: While menstrual attitudes and hygiene practices are often examined in the literature through informational, risk-based, and cultural lenses, studies that directly address their holistic relationship to self-care behaviors remain limited. This study aims to investigate the impact of women’s menstrual attitudes and hygiene practices on their self-care behaviors. Methods: This is a cross-sectional analytical study. The study was completed between 5 October 2024 and 23 January 2025, with 700 women aged 18–49 in their reproductive period. Data were collected using a Demographic Information Form, the Menstrual Attitude Questionnaire, and the Self-Care Inventory. Spearman’s correlation analysis, the Mann-Whitney U test, and the Kruskal-Wallis test were used for data analysis. To examine nonlinear relationships and multivariable interactions, a Random Forest regression analysis was performed. Results: A positive and statistically significant relationship was found between menstrual attitudes and overall self-care (r = 0.132, p < 0.001). MAQ scores did not differ significantly across variables (p > 0.05). However, SCI scores showed significant differences based on menstrual hygiene education status, type of underwear used during menstruation, hand hygiene practices, and frequency of menstrual material use (p < 0.05). According to the Random Forest regression model, menstrual attitudes were identified as the strongest predictor of self-care behaviors. Conclusions: The results of this study supported the positive influence of women’s menstrual attitudes and hygiene practices on their self-care behaviors. The relationships between self-care and parameters such as menstrual hygiene education, frequency and type of menstrual material use, and hand hygiene during menstruation were clearly demonstrated. Given the limited number of studies in this field, randomized controlled trials and meta-analyses with high levels of evidence are recommended to generalize these results.
- MakaleAçık Erişim2026Scopus SJRQ1Evaluation and Classification of Emergency and Disaster Assembly Areas with ORESTE-Sort
Ozdemir, Umit; Mete, Suleyman; Gul, Muhammet
Emergency and Disaster Assembly Areas (EDAA) are designated safe zones where basic needs can be met until temporary shelters are established following natural or man-made disasters like floods, fires, earthquakes, explosions, or chemical incidents. Promptly relocating disaster victims to these areas is crucial for minimizing loss of life and facilitating effective search and rescue operations by maintaining an uninterrupted flow of information. To prepare for disasters like earthquakes, which cause significant material and emotional damage to large populations, sustainable disaster management must be ensured to evaluate site suitability, correct deficiencies, and avoid inappropriate locations. This study will examine the evaluation criteria for EDAAs established by the Tunceli Provincial Disaster and Emergency Management Authority (AFAD) in terms of area, structure, security, and accessibility, taking into account the region’s specific characteristics. Based on a literature review, eleven criteria have been proposed and ranked using the Besson mean ranking method. Areas have been classified into four categories (e.g., adequate, not suitable) using the optimistic, pessimistic, and comprise approaches of the Assignment Rule Driven by Attitudes (ARDA) and the ORESTE-Sort method. The examination of 19 EDAA provides two perspectives: an optimistic view that recommends classifying eleven areas as first class and using all areas as they are, and a pessimistic view that calls for urgent improvements in three areas and states that one area (EDAA 1) is deemed unsuitable due to its assignment to class (Formula presented.). It is also advised that the second area should not be used, despite being rated as class (Formula presented.), due to its proximity to the river and its slope characteristics. The study also performs a sensitivity analysis of the method and provides recommendations for future research.
AtıfScopus2WoS1İncele - MakaleAçık Erişim2026Scopus SJRQ1A smartphone-based vibration dataset for induction motor fault diagnosis under different speed and load conditions
Ertarğın, Merve; Orhan, Ahmet; Yıldırım, Özal; Chauhan, Sumika; Vashishtha, Govind
Induction motors are foundational components across industrial applications, valued for their inherent robustness, operational simplicity, and cost-efficiency. Maintaining their reliable function is paramount for a wide range of mechanical and electrical systems. However, they are prone to various mechanical and electrical faults, such as bearing defects, rotor issues, and voltage imbalances, which can significantly impair their performance and reliability. This study presents a novel vibration dataset for induction motor fault diagnosis, uniquely acquired using a smartphone-based inertial sensor rather than conventional industrial accelerometers. Vibration signals were recorded along three orthogonal axes (gx, gy, gz), alongside gravity-compensated acceleration components (guserx, gusery, guserz), enabling detailed analysis of both raw and gravity-free vibration characteristics. Data were collected under diverse conditions, including healthy operation and several fault types, across varying rotational speeds and load states. The dataset features long-duration vibration recordings sampled at 100 Hz, suitable for both time-domain analysis and window-based feature extraction. Its inclusion of multiple operating speeds and load conditions is ideal for studying the impact of operational variability on fault signatures. By leveraging low-cost and readily accessible smartphone sensors, this dataset supports practical and accessible vibration data acquisition for supporting the development, benchmarking, and validation of data-driven fault diagnosis methods. This resource is expected to significantly advance research in condition monitoring of induction motor, particularly for machine learning and signal processing applications using vibration data.
- MakaleYalnız künye2026Scopus SJRQ2Adsorption of Reactive Red 120 dye from aqueous solutions using sepiolite clay with a channel-structured morphology: Mechanism, kinetics, isotherm, and thermodynamic studies
Fırat, Tülay
The effective treatment of dye-containing wastewater remains a major environmental challenge due to the high stability and solubility of reactive dyes. In this study, the adsorption behavior of Reactive Red 120 (RR120), an anionic reactive azo dye, from aqueous solutions was investigated using natural sepiolite clay possessing a channel-structured morphology. Batch adsorption experiments were performed to evaluate the effects of contact time (1–200 min), initial dye concentration (50–500 mg L−1), adsorbent dosage (0.1–1.5 g), solution pH (2–10), and temperature (25–50°C). The adsorption equilibrium was reached within approximately 75 min. The Langmuir isotherm provided the best fit to the equilibrium data, yielding a maximum monolayer adsorption capacity of 168.4 mg g−1 at 298 K. Thermodynamic analysis revealed that the adsorption process was spontaneous and endothermic, with an activation energy of 32.41 kJ mol−1. Adsorption kinetics were analyzed using pseudo-first-order, pseudo-second-order, and intraparticle diffusion models, while equilibrium data were evaluated using Langmuir, Freundlich, and Temkin isotherm models. The kinetic data were best described by the pseudo-second-order model, while thermodynamic analysis revealed that the adsorption process was spontaneous and endothermic. FTIR and XRD analyses further supported the important role of the channel-structured framework of sepiolite in RR120 adsorption. Unlike many clay-based adsorbents that require chemical modification, natural sepiolite exhibited high adsorption performance due to its intrinsic fibrous morphology, nano-channel structure, and high surface area. These findings demonstrate that natural sepiolite is a promising, low-cost, and sustainable adsorbent for the treatment of dye-contaminated wastewater.
- BildiriYalnız künye2026LLM Based Software Test Scenario Generation System From Bug Descriptions
Gundem, Merve Yilmazer; Karakose, Mehmet
Large, user-interactive software systems require extensive software testing for safe deployment. Manually generated test cases by software testers require extensive time and effort, and their scope remains limited. In this study, a system based on LLM is proposed for automatic test cases and test steps generation from bug descriptions. In the proposed system, bug descriptions were first collected from the Defects4J Dataset. Keywords relevant to the bug scope were extracted from the descriptions. Structured automatic prompts were generated from the extracted keywords. The generated prompts were fed into the LLM as input, and software test cases appropriate for the bugs were generated. The method was evaluated on actual bug descriptions by comparing it to a general (baseline) prompt. Experimental results show that the lengths of the generated scenarios are similar, but the proposed method increases the keyword match rate with error descriptions to an average of 89 %. The findings reveal that keyword-driven prompts are effective in generating more reliable and error-specific test scenarios without requiring additional data.
- MakaleAçık Erişim2026Scopus SJRQ1The mediating role of problem solving in the relationship between emotional intelligence and mental well-being
Erdoğan, Ramazan; Özcan, Büşra; Kızar, Oktay; Kızılkoca, Mustafa; Çalışır, İrem Kaptangil; Bozkurt, Eyüp; Uğurlu, Fatih Mehmet; Tan, Suriye; Koçal, Meryem
Background: This study aims to examine the relationship between emotional intelligence and mental well-being among university students and to reveal the mediating role of problem-solving skills in this relationship. Methods: Of these students, 707 participated, and the Emotional Intelligence Trait Scale, the Warwick-Edinburgh Psychological Well-being Scale, and the Problem-Solving Inventory were used as data collection tools. The SPSS software was used for data analysis. Results: Emotional intelligence appears to have a significant effect on mental well-being, and emotional intelligence directly significantly predicts problem-solving skills, but mental well-being does not have a significant effect on problem-solving skills. Emotional intelligence appears to have a direct effect on problem-solving, and mental well-being mediates this effect. The explanatory power of the model is moderate in terms of the role of emotional intelligence in predicting mental well-being and more limited in terms of its role in predicting problem-solving skills. Conclusion: In conclusion, emotional intelligence strengthens individuals’ mental well-being and directly positively impacts their problem-solving skills. However, mental well-being does not play a mediating role in the problem-solving process. This suggests that the direct effect of emotional intelligence is primary in improving problem-solving skills, and mental well-being does not serve as a decisive mediating factor in this process. Therefore, interventions aimed at strengthening emotional intelligence can be effective both in enhancing individuals’ mental well-being and in directly supporting problem-solving skills.
- MakaleYalnız künye2026Scopus SJRQ3A new lectin from Amanita vaginata mushroom with potent anti-inflammatory activity
Seliman, Thoiba Mogahid Hussein; Ozsoy, Nurten; Altiparmak-Ulbegi, Gulsum; Alp-Kavlo, Hevidar; Arcan, Gulsah Gamze; Akev, Nuriye; Can, Ayse; Aksoy-Sagirli, Pinar
This study used 80% ammonium sulphate fractional precipitation, followed by affinity chromatography to purify a new lectin (AVL) from the crude extract of the Amanita vaginata mushroom. The purification procedure achieved a 20% yield, a specific activity of 5120 HU/mg protein, and a 16-fold increase in purity. SDS-PAGE analysis showed a single band of 45 kDa. We assessed AVL's anti-inflammatory effect by measuring levels of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), induced by lipopolysaccharide (LPS), in RAW 264.7 macrophages. Western blot analysis showed that iNOS and COX-2 protein levels were barely detectable in the control groups, but markedly elevated in the LPS-treated groups. However, AVL treatment significantly inhibited the expression of both iNOS and COX-2 in LPS-stimulated cells. This effect was dose-dependent. These findings suggest that AVL's anti-inflammatory effects are mediated through the suppression of iNOS and COX-2 expression.
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