Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Gul, Muhammet(74)
- Akkurt, Nevzat(39)
- Celik, Erkan(35)
- Serdar, Osman(35)
- Güler, Ömer(33)
- Kutlu, Banu(32)
- Paksoy, Mehmet Yavuz(32)
- Yucesan, Melih(31)
- Tekin, H.O.(30)
- Yildirim, Numan(30)
- Yildirim, Nuran Cikcikoglu(30)
- ALMisned, Ghada(28)
- Mete, Suleyman(26)
- Danabas, Durali(20)
- Ince, Muharrem(20)
- Serin, Faruk(20)
- Ates, Mehmet(19)
- Can, Erkan(19)
- Onat, Onur(18)
- Benzer, Fulya(17)
- Kocabaş, Mehmet(17)
- Tanyol, Mehtap(17)
- Kizak, Volkan(16)
- Alataş, Mevlüt(15)
- Aydin, Rahmi(15)
- Kahraman, Gökhan(15)
- Kilic, G.(15)
- Polat, Alper(15)
- Susam, Selim Orhun(15)
- Xu, Qian(15)
- Aslan, Naim(14)
- Guler, Omer(14)
- Gürler, Nedim(14)
- Karatay, Gülnaz(14)
- Utku, Anıl(14)
- Yildirim, N. C.(14)
- Özkul, İskender(14)
- Demirol, Ferhat(13)
- Erguven, Gokhan Onder(13)
- Firat, Erhan(13)
Yayınlar
- MakaleYayıncıda açık erişim2026Scopus SJRQ1Geoeconomic dependency in selected rare-earth metals and compounds: A product-level trade network analysis
Ateş, Erdem
This study examines trade concentration, network structure, and China-centered import dependency in three selected rare-earth metal and compound categories (HS 280530, HS 284610, and HS 284690) over 2012–2024. Using bilateral trade data from the CEPII BACI database, the analysis combines concentration ratios and the Herfindahl–Hirschman Index with bilateral trade-flow networks, centrality measures, cosine-similarity networks, and country-level China Import Dependency Ratios (CID). The results reveal substantial product-level heterogeneity. Trade concentration and network structure evolve differently across the three categories, while changes in similarity-network density, community structure, and modularity are particularly pronounced for HS 284690. Trade shares and network centrality do not always move in parallel, indicating that market concentration and structural network position capture distinct dimensions of trade organization. Country-level dependency analysis further shows increasing reliance on China across all three product categories: both mean CID and the share of importing countries sourcing at least 50% of their imports from China increase between 2012 and 2024. Overall, the findings demonstrate the value of integrating concentration, network, and dependency measures to identify product-specific patterns of geoeconomic exposure in selected rare-earth metals and compounds.
- MakaleYalnız künye2026Scopus SJRQ1Innovative solutions for aquaculture: detecting fish diseases with hybrid deep learning model and explainable artificial intelligence
Utku, Anıl; Barut, Abdulkadir; Alofaysan, Hind
Early identification of fish diseases is critical to maintain aquaculture and minimize its financial burden. In the diagnosis of diseases, time is critical and scientists’ experience is imperative, which makes the artificial intelligence-based models necessary. It is intended by this study to integrate deep learning with explainable artificial intelligence methods to establish an artificial intelligence-powered framework for early detection of disease in fish. In this study, we developed a hybrid artificial intelligence system designed to detect diseases in freshwater fish by analyzing skin images. The primary objectives of the system are to minimize economic losses, prevent further disease spread, and ultimately increase aquaculture productivity. For this purpose, we used a dataset consisting of images from seven different disease categories, with 250 images in each class. A new hybrid model, Residual Network-50–Vision Transformer, was developed by integrating the strengths of Residual Network-50 and Vision Transformer architectures to improve classification accuracy. The proposed model was subjected to rigorous comparison with established architectures, including Visual Geometry Group 16, Mobile Convolutional Neural Network Version 2, Efficient Neural Network–Baseline Model B0, standalone Vision Transformer, and the original Residual Network-50. The results demonstrated that Residual Network-50–Vision Transformer outperformed the model, achieving an impressive 99.14% accuracy rate. Furthermore, the study employed local interpretable model-independent explanations to explain which image features most significantly influence the model’s classification decisions, thereby enhancing the interpretability and confidence in the model’s output. The application of such advanced image processing models in combination with explainable AI techniques demonstrates significant potential to support sustainable aquaculture by reducing disease outbreaks and associated financial losses.
AtıfScopus3OpenAlex2
İncele - MakaleYalnız künye2026Scopus SJRQ3New national and regional bryophyte records, 86
Wilbraham, J.; Abdirasulov, F.; Aguirre, J.; Alataş, M.; Álvaro Alba, W.R.; Aslan Ergenekon, Z.; Aswathy Raj, K.; Ayhan, E.; Batan, N.; Bednarek-Ochyra, H.
- MakaleYalnız künye2026Scopus SJRQ3Impact of ZnF2 and PbF2 on the radiation attenuation performance of the fluoride-based bismuth borate glass system
Aşkın, A.
Among the various types of glasses, fluoride-based glasses stand out due to their chemical and mechanical stability, low refractive indices, low phonon energies, and low transition temperatures. In this study, key radiation shielding parameters, including the mass attenuation coefficient (µm), half-value thickness (HVL), mean free path (MFP), transmission fraction (T), effective atomic number (Zeff), exposure build-up factors (EBF) and fast neutron removal cross-section (∑R), of the newly developed fluoride-based glass system, xZnF2—(25-x)PbF2—25Bi2O3—49.8B2O3—0.2Cr2O3 (where x is between 0, and 25 mol%), were evaluated. The data was gathered through Monte Carlo simulations, utilizing the Geant4 framework for a germanium detector and the PHY-X/PSD software. The parameters were assessed for gamma-ray energies ranging from 0.284 to 1.33 MeV across all glass samples. The results clearly show that the presence of PbF2 significantly enhances radiation shielding, owing to the high atomic number (Z) of lead. The highest µm and Zeff values were found to be highest and MFP, HVL, and T values were found to be lowest for the glass sample with the highest PbF2 content. Furthermore, the ∑R values of the glasses were observed to decrease as the PbF2 content reduced, highlighting the importance of high-Z elements in neutron absorption. Therefore, gamma and neutron shielding abilities of the studied glasses improve with the addition of PbF2 into the glass structure and glass system containing 25% mole PbF2 exhibits superior gamma and neutron shielding performance compared to shielding concrete.
AtıfScopus1WoS1İncele - MakaleYalnız künye2026Scopus SJRQ2A Bernstein polynomial estimation of the moment generating function
Susam, Selim Orhun
We study Bernstein polynomial smoothing for nonparametric estimation of the moment generating function (MGF) of a distribution supported on (Formula presented.). We prove strong consistency of the Bernstein-smoothed MGF estimator and show that, when the smoothing degree m grows sufficiently fast, it shares the same (Formula presented.) asymptotic normal distribution as the empirical MGF estimator, with variance (Formula presented.). A second-order bias–variance expansion reveals that Bernstein smoothing yields a bias of order (Formula presented.) and a variance-reduction term of order (Formula presented.). This leads to the optimal smoothing rate (Formula presented.) for pointwise mean squared error (MSE) minimization. Simulation results confirm that the Bernstein estimator is especially effective in challenging boundary-dominated settings, notably for U-shaped beta models and for larger positive t values. Overall, Bernstein polynomial smoothing provides a simple, theoretically justified, and practically effective tool for nonparametric MGF estimation on compact supports.
- MakaleYalnız künye2026Scopus SJRQ1Impact of hybrid Er2O3 and B4C additions on structural characteristics and experimental gamma-ray transmission behavior of Ni–Co–Fe–Cr–Mo high-entropy alloys
Özkul, İskender; Güler, Ömer; Durmus, Hasan; Camgoz, Berkay; ALMisned, G.; Yaprak, Gunseli; Tekin, H.O.
This study examines how Er2O3 and B4C additions affect the structural, microstructural, mechanical, and gamma-ray attenuation behaviour of Ni–Co–Fe–Cr–Mo high-entropy alloy composites. Five samples, labelled S0–S4, were produced by vacuum arc melting with different single and combined reinforcement contents. Thermodynamic calculations showed that the metallic matrix meets the general conditions expected for solid-solution HEA formation. XRD results indicated that an FCC-based matrix remained dominant in all samples. Reflections related to Er2O3 were identified in the Er2O3-containing compositions, while several weak secondary reflections could not be assigned with certainty because of their low intensity and peak overlap. SEM-EDS analysis confirmed the presence of Er-, O-, B-, and C-containing regions and also revealed local compositional variations within the microstructure. The reinforcement additions produced a clear increase in microhardness, with the highest value of 693 ± 51 HV0.5 obtained for the hybrid-reinforced S3 sample. Gamma-ray attenuation was measured at 276, 302, 356, and 383 keV using a high-purity germanium (HPGe) detector under narrow-beam condition. S4 showed the lowest nominal transmission factor at most energies at its actual sample thickness. However, after correcting for thickness using the Beer-Lambert relationship, S2 generally showed the highest nominal linear attenuation coefficient, while S4 gave closely comparable values at several energies. Some of the differences between samples were within the propagated counting uncertainties and were therefore interpreted with caution. Overall, the results show that the composition giving the highest hardness does not necessarily provide the strongest thickness-normalized gamma-ray attenuation. The attenuation behaviour is influenced by several factors, including reinforcement composition, sample thickness, density, phase distribution, microstructural heterogeneity, and measurement uncertainty. These findings highlight the need to optimize reinforced HEA composites according to the specific mechanical and radiation-related property being targeted.
- BildiriYalnız künye2026Scopus SJRQ4Residual-Based Evaluation of Basin and Basin Edge Effects in Türkiye: Implications for Regional Site Amplification Modeling
İçen, Abdullah; Ilki, A.; Goksu, C.; Cinar, T.; Erdik, M.
This study investigates basin, basin edge and complex topography effects in ground motion records using residuals from empirical ground motion models, to better understand regional site amplification patterns in Türkiye. Using data from the updated Strong Motion Database of Türkiye (SMD-TR) strong-motion database, we compute residuals using site amplification function and analyze their spatial distribution across regions. The clustering technique, Gaussian Mixture Models (GMM), is employed to identify regions with coherent residual patterns, primarily to capture regional site effects. After regionalization, peak amplifications within the VS30 range of 400–550 m/s are examined for potential associations with sedimentary basins or basin edge effects. The results reveal systematic amplification anomalies within the VS30 range of 400–550 m/s that are not fully captured by conventional site proxies such as VS30. Notably, residuals consistently cluster along basin edges and within deep valley regions, indicating the influence of complex three-dimensional and topographic amplification mechanisms. These observations underscore the limitations of current site characterization approaches and motivate further refinement of site response models, particularly for partially non-ergodic applications in seismic hazard analysis. This study focuses on residual-based evaluations to identify potential basin, basin-edge, and topographic effects that warrant more detailed investigation.
- MakaleYayıncıda açık erişim2026Scopus SJRQ1Experimental study of an alternative precast concrete beam–column connection with embedded steel block detail
Baltaci, Alihan; Sunca, Fezayil; Şahi̇n, Muhammed Cihat; Şen, Doğa; Keçeci̇, Bedirhan; Polat, Alper; Altunişik, Ahmet Can
Precast systems have gained increasing popularity due to their advantages in construction speed, cost efficiency, and quality control. However, past earthquakes have revealed that beam–column connections are often the most vulnerable regions in precast structures, making their seismic performance a critical area of investigation. This study investigates the cyclic behavior of two full-scale precast specimens with different beam–column connection configurations: a code-compliant, Moment-Resisting Emulative-Welded Connection detail (MRCON) and an alternative Embedded Steel Block Connection detail (ESBCON). Both specimens were tested under quasi-static reversed cyclic loading to evaluate their hysteretic response, energy dissipation, stiffness degradation, residual displacements, and modal characteristics. The results demonstrate that while MRCON provided higher initial stiffness and energy dissipation, it experienced severe localized damage and rapid structural deterioration at larger drift ratios. In contrast, the embedded steel block in ESBCON successfully distributed the damage across a wider joint region, leading to a more gradual stiffness reduction and slightly lower residual displacements. Although the overall structural efficiency of ESBCON was partially hindered by the slippage of the steel block, it achieved a competitive level of moment transfer capacity compared to the conventional welded connection detail, highlighting its potential as a damage-distributing alternative once slip-mitigating modifications (surface roughening to enhance bond and embedding within the column) are implemented.
- MakaleYalnız künye2026Scopus SJRQ1Exploring the photocatalytic potential of NbTiZrW-based high-entropy alloys with Hf/Mo/Ta additions: Influence of alloying elements on their structural and photocatalytic performance
Zakir, O.; Guler, O.; Idouhli, R.; Aklalouch, M.; Dikici, B.; Khadiri, M.E.; Abouelfida, A.; Selen, V.; Şimşek, T.
In this study, the photocatalytic performance of NbTiZrW-based high-entropy alloys (HEAs) with Hf, Mo, and Ta additions was investigated. The alloys were synthesized by mechanical alloying for 120 h under a high-purity Ar atmosphere to prevent oxidation. The photocatalytic activity of the samples was evaluated based on the degradation of methylene blue (MB) under UV irradiation. Structural and chemical characterizations were performed using energy-dispersive spectroscopy (EDS), X-ray diffraction (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The results showed that MB removal by adsorption reached 22.96 % for NbTiZrWHf, 21.90 % for NbTiZrWTa, and 47.01 % for NbTiZrWMo. The incorporation of Mo into the NbTiZrW alloy was found to enhance electrostatic interactions between MB molecules and the alloy surface. Upon UV irradiation, the degradation efficiency increased significantly, reaching 32.84 % for NbTiZrWHf, 82.02 % for NbTiZrWTa, and 46.13 % for NbTiZrWMo within 3 h. The improved performance of the NbTiZrWHf alloy was attributed to its low particle size, which provided a larger number of active sites for photocatalytic activity, as confirmed by SEM analysis.
AtıfScopus1OpenAlex1İncele - MakaleYalnız künye2026Scopus SJRQ2Comparative phytochemical characterization and bioactivity evaluation of hemp (Cannabis sativa L.) root extracts using green extraction technologies
Korkmaz, Nesrin; Yaman, Cennet; Güçlü, Ebru; Doğan, Üzeyir; İmamoğlu, Rızvan; Aslan korkmaz, Şengül
This study investigates the largely untapped therapeutic potential of industrial hemp (Cannabis sativa L.) roots, which are usually discarded as agricultural byproducts. The phytochemical composition and biological activities of extracts obtained using Soxhlet, ultrasound-assisted extraction (UAE), and supercritical CO₂ (SC-CO₂) techniques were comparatively evaluated. Compounds were characterized using FTIR, GC–MS, LC–MS, and ICP-MS. SC-CO₂ extraction yielded the most chemically diverse profile, particularly enriched in fatty acids and triterpenoids. In vitro assays demonstrated that SC-CO₂ and Soxhlet extracts significantly promoted fibroblast migration and reduced inflammatory responses compared to UAE extracts. Gene and protein expression analyses further supported these bioactivities. In conclusion, this study highlights the phytopharmaceutical potential of hemp root extracts obtained using alternative extraction techniques, including supercritical CO₂ extraction. While SC-CO₂ extraction enabled the recovery of a chemically diverse extract, the present study focuses on comparative phytochemical and bioactivity outcomes rather than a quantitative assessment of environmental sustainability. The findings support further investigation of hemp roots, currently treated as an underutilized biomass, for potential applications in natural product research.
AtıfOpenAlex1İncele - MakaleYalnız künye2026Scopus SJRQ1MILA: An Innovative Approach to Identifying AI-Generated Content Using BERT, CNN, and BiLSTM
Utku, Anil
AI ethical principles are essential in balancing the social impacts of rapidly developing technology today. The widespread use of AI technologies has heightened the need for ethical and legal regulations in this area. In this process, fundamental principles such as data privacy, accountability, transparency, and human oversight take center stage to enhance the reliability of artificial intelligence and foster social trust. Generative AI refers to machines producing text, images, audio, and video content. However, generative AI brings ethical discussions since it can produce original content. Detecting AI-generated content is becoming increasingly complex due to the ability of AI models to produce increasingly more fluent and meaningful texts. This study created a hybrid MILA model using BERT, CNN, and BiLSTM models to detect AI-generated content. MILA was compared in detail with SVM, XGBoost, CNN, LSTM, and BiLSTM using sentence-level and article-level datasets. Experiments demonstrated that MILA outperformed the compared models, achieving 94.34% accuracy at the sentence-level and 93.62% accuracy at the article-level.
AtıfOpenAlex1İncele - MakaleYalnız künye2026Scopus SJRQ2Comparative Analysis of Sequential Electrooxidation and Electrocoagulation Processes for Leachate Treatment
Ogedey, Aysenur; Oguz, Ensar
This study aims to improve the removal efficiency of chemical oxygen demand (COD), NH₃-N, and turbidity from Bingöl leachate through a sequential electrochemical process. This process includes electrooxidation (EO) with Ti/PdO-CoO anodes and stainless-steel cathodes, followed by electrocoagulation (EC) with aluminum anodes and stainless-steel cathodes. The sequential electrochemical process lasted 400 min, consisting of 360 min of EO followed by 40 min of EC process. At pH 5, COD and turbidity reached optimal removal efficiencies of 89% and 99.9%, respectively, while NH₃-N achieved 88.5% at pH 9.5. These results indicate that the sequential electrochemical process was most effective under these pH values for removing organic matter, nitrogen, and suspended solids. The sequential electrochemical process led to significant improvements in the removal efficiencies of COD, NH₃-N, and turbidity, with increases of 32.5%, 44%, and 6.9%, respectively, compared to the EO process. The sequential electrochemical process showed improvements of 9.5% in COD and NH₃-N removal, and 1.2% in turbidity removal, compared to the results of the EC process. The pseudo-first-order (PFO) reaction rates for the EO and EC processes were determined, resulting in high R2 values (0.98–0.99). Additionally, the total consumption cost of the EO process was higher than that of the EC process. After the sequential electrochemical process, the consumption cost increased from $13.586/kg COD to $24.332/kg COD as the current density increased from 15 mA/cm2 to 25 mA/cm2.
AtıfScopus1WoS1OpenAlex1İncele - MakaleYalnız künye2026Scopus SJRQ1Happiness and Psychological Well-Being Among Fathers of Young Children: Evidence From Tunceli, Turkey
Şen Montazerirad, Buket; Yeşiltepe, Akgün
Fatherhood significantly influences psychological well-being and happiness, yet fathers particularly of young children are underrepresented in research. This study examines the relationship between happiness and psychological well-being in this group. This study aims to explore the relationship between happiness and psychological well-being among fathers of children in early childhood. A descriptive-correlational study was conducted with data collected online using validated self-report questionnaires on demographic characteristics, happiness, and psychological well-being from 257 participants. A statistically significant, strong, and positive relationship was found between happiness and psychological well-being (r = 0.626, p = 0.000). Regression analysis revealed that happiness explained 39.2% of the variance in psychological well-being and was a significant predictor (R2 = 0.392). Each unit increase in psychological well-being was associated with a 0.794-unit increase in happiness (β = 0.794; p < 0.05). Fathers’ happiness is a key determinant of their psychological well-being and psychosocial interventions targeting fathers may enhance both paternal and child well-being.
- MakaleYalnız künye2026Scopus SJRQ1Exploring research themes in the Journal of Librarianship and Information Science: Insights from topic modelings
Aslan, Alper; Özyurt, Özcan
This study aims to explore research interests and trends in the journal by analyzing the entire publication history of the Journal of Library and Information Science (JoLIS) between 1969 and 2023 using Latent Dirichlet Allocation (LDA). A comprehensive topic modeling analysis was conducted on 1437 articles for which titles, abstracts and keywords were available. The research focuses on identifying key thematic shifts in the journal’s publications. The findings highlight that topics such as Information Literacy & Research and Librarian Roles & Skills are growing in importance, while traditional topics such as Cataloging & Classification are declining. The results reveal shifts in the focus of the LIS field, providing critical insights to guide future research. In particular, Information Literacy & Research emerges as a highly accelerating topic, reflecting the need for digital competencies in response to evolving information environments. Meanwhile, declining interest in Cataloging & Classification is in line with the automation of traditional library functions, shifting training priorities toward digital literacy and data management skills. By mapping the evolution of research priorities, this study serves as a valuable resource for LIS researchers and practitioners, helping them to align their work with future developments in the field.
AtıfScopus9WoS7OpenAlex11İncele - MakaleYalnız künye2026Scopus SJRQ4Smart logistics with a maturity assessment perspective
Göçmen Polat, Elifcan; Derse, Onur
The logistics sector is influenced by digitalisation and technological advancement in improving sustainability and efficiency. Logistics companies, which are highly capable of incorporating innovative technologies into their business flows, have made profound impacts, ultimately leading to a transformation in logistics services. In this context, this study presents the current and target maturity levels to make an international logistics company smarter and provides recommendations as an improvement road map for the logistics sector. Within the scope of this research, nine dimensions and 36 maturity items of the smart logistics (SL) concept are discussed to assess the maturity levels using the weighted maturity score calculation model (WMSC), in which evaluation of all maturity items using the capability maturity model (CMM) maturity levels and calculation of the criteria weights using fuzzy DEMATEL (F-DEMATEL) is integrated. Computational results show that warehouse management systems and material flow control systems have lower maturity levels. Thus, product picking by voice, integrating the warehouse management system, ensures real-time updates and data integration, reducing stockouts and overstock.
- MakaleYalnız künye2026Scopus SJRQ3The relationship between muscle strength and oxygenation and activities of daily living in adolescents and young adults with pulmonary arterial hypertension
Dik, Jan; Topcuoglu, Ceyhun; Vardar-Yagli, Naciye; Goksuluk, Merve Basol; Aypar, Ebru; Alehan, Dursun; Saglam, Melda
Pulmonary arterial hypertension leads to dyspnoea, fatigue, and oxygen desaturation, limiting activities of daily living and functional capacity. This study aimed to evaluate the impact of pulmonary arterial hypertension on activities of daily living performance, functional capacity, peripheral muscle strength, oxygen dynamics, and energy expenditure. Eighteen adolescents and young adults with pulmonary arterial hypertension (10 females, 8 males; age 9–30 years) and 15 healthy controls (10 males, 5 females; age 9–30 years) were included. Peripheral muscle strength was assessed using a handheld dynamometer, functional capacity via the 6-minute walk test, and muscle oxygenation through near-infrared spectroscopy. Lower-limb endurance was evaluated with the 1-minute sit-to-stand test and activities of daily living performance with the Glittre Activities of Daily Living test. Compared to controls, the pulmonary arterial hypertension group had significantly lower 6-minute walk test distance (441.9 m versus 636.9 m; p < 0.001), reduced sit-to-stand repetitions (28 versus 42.1; p < 0.001), weaker peripheral strength, and lower minimum muscle oxygen saturation (24.9% versus 51.8%; p < 0.001). Glittre Activities of Daily Living test duration was longer (143 s versus 105 s; p < 0.001), with greater oxygen desaturation (−13% versus −1%; p < 0.001), higher dyspnoea scores using modified Borg scale (5 versus 1; p < 0.001), and blunted heart rate response (ΔHR [change in heart rate]: 32 versus 64; p = 0.011). These findings demonstrate that pulmonary arterial hypertension significantly impairs both cardiopulmonary and peripheral muscle function. Protecting muscle health and improving functional capacity should be prioritised to enhance quality of life in this population.
- 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.
AtıfScopus1WoS1OpenAlex3İncele - 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.
