Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Kamiloğlu, Aybike(6)
- Kutlu, Naciye(6)
- Ecem Bayram, Nesrin(5)
- Bayram, Ozkan(4)
- Bayram, Sinan(4)
- Igman, Erdal(4)
- Teber, Ahmet(4)
- Tutkun, Cansu(4)
- Dertli, Enes(3)
- Elbir Abca, Tuğba(3)
- Gerçek, Yusuf Can(3)
- Guleryuz, Didem(3)
- Simsek, Onder(3)
- Çolak, Murat(3)
- İspirli, Hümeyra(3)
- Abdioglu, Murat(2)
- Ari-Arat, Ceren(2)
- Can, Zehra(2)
- Ekincioğlu, Yavuz(2)
- Eryılmaz Türkkan, Gökçen(2)
- Güven, Ebru Mazlum(2)
- Güven, Onurhan(2)
- Hasar, Ugur Cem(2)
- Hırca, Tuğçe(2)
- Kara, Yakup(2)
- Kolaylı, Sevgi(2)
- Kotaman, Hüseyin(2)
- Kızıl, Hamit Emre(2)
- Niazkar, Majid(2)
- Sarac, Mehmet Fahri(2)
- Sayan, Enes(2)
- Yaman, Havva(2)
- Yetişensoy, Okan(2)
- Yılmaz, Özlem(2)
- Çakiroğlu, Ünal(2)
- Abdolahpour Salari, Maryam(1)
- Adiyaman, Gokhan(1)
- Afzali, Seied Hosein(1)
- Akaras, Nurhan(1)
- Akgun, Nurullah(1)
Yayınlar
- MakaleAçık Erişim2026Scopus SJRQ2The Effect of Data Types’ on the Performance of Machine Learning Algorithms for Cryptocurrency Prediction
Tanrikulu, Hulusi Mehmet; Pabuccu, Hakan
Forecasting cryptocurrencies as a financial issue is crucial as it provides investors with possible financial benefits. A slight improvement in forecasting performance can lead to increased profitability; Therefore, obtaining a realistic forecast is very important for investors. Bitcoin, frequently mentioned in recent due to its volatility and chaotic behavior, has become an investment tool, especially during and after the COVID-19 pandemic. In this study, selected ML techniques were investigated for predicting cryptocurrency movements by using technical indicator-based data sets and measuring the applicability of the techniques to cryptocurrencies that do not have sufficient historical data. In order to measure the effect of data size, Bitcoin’s last 1 year and 7 years of data were used. Following the related literature, Google trends and the number of tweets were used as input features, in addition to the most commonly used twelve technical indicators. Random Forest, K-Nearest Neighbors, Extreme Gradient Boosting (XGBoost-XGB), Support Vector Machine (SVM), Naive Bayes (NB), Artificial Neural Networks (ANN), and Long-Short-Term Memory (LSTM) network were optimized for best results. Accuracy, F1, and area under the ROC curve values were used to compare the model performance. For continuous data, ANN and SVM performed the best with the highest accuracy and outperformed the other ML models for complete and reduced sets. LSTM reached the best accuracy for trend data, but SVM, NB, and XGB models showed similar performance. The research shows that some indicators significantly affect prediction performance, and the data discretization process also improved the model’s accuracy. While the number of samples affects the results of many ML models, correctly optimized and fine-tuned models may also give excellent results even with less data.
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İncele - MakaleYalnız künye2026Scopus SJRQ1Development and Validation of AI Acceptance Scale (AI-AS) for Learners in Higher Education
Kayalı, Bünyami; Yavuz, Mehmet; Üstün, Ayşin Gaye; Uçar, Hasan; Erdoğdu, Erdem; Bozkurt, Aras
The use of artificial intelligence (AI) applications in educational activities is increasing day by day. This situation highlights the need for valid and reliable measurement tools to determine students' levels of acceptance of this technology. This study aims to develop a standard measurement tool to determine students' levels of acceptance of AI. To this end, the systematic scale development steps proposed by DeVellis and Thorpe (2021) were followed. Exploratory factor analysis conducted with 560 participant responses and confirmatory factor analysis conducted with 950 participant responses resulted in a 26-item, 5-factor structure. The factors included in the scale were listed as "usability", "ease of use", "intention and attitude", "facilitating conditions" and "trust and data privacy". The findings revealed that the scale had high internal consistency and exhibited satisfactory model fit indices. The results indicate that the scale is a valid and reliable measurement tool for determining students' levels of AI acceptance. The study offers practical implications for researchers and practitioners and highlights directions for future work on AI adoption in higher education environments.
- MakaleAçık Erişim2026Scopus SJRQ2Production of Gamma-Aminobutyric Acid by Levilactobacillus brevis AK19B: Strain Characterization and Process Optimization Using Box–Behnken Design
Memiş, Habibe; Kamiloğlu, Aybike
Levilactobacillus brevis AK19B strain demonstrated promising probiotic potential as a hydrophilic lactic acid bacterium with valuable phytase activity. It also exhibited strong antioxidant properties and maintained viability in bile salt-rich environments, suggesting robustness in gastrointestinal conditions. To maximize gamma-aminobutyric acid (GABA) production, a Box–Behnken design was applied to assess the effects of monosodium glutamate (MSG) concentration, NaCl concentration, pH, and temperature. The results showed that these factors significantly influenced GABA synthesis, with their interactions well-modeled by a quadratic response surface. Optimal conditions were identified as pH 5.136, MSG concentration of 297 mM, temperature at 26 °C, and NaCl concentration of 2.82%, under which the predicted GABA production reached 43.85 mg/mL. These findings highlight AK19B as a promising candidate for functional food applications and industrial GABA biosynthesis.
- MakaleYalnız künye2026Scopus SJRQ2Effect of Erbium Addition to A380 Aluminum Alloy on Mechanical and Microstructural Properties
Gültekin, Çağrı; Çolak, Murat; Tabak, Yasemin; Şensoy, Abdullah Tahir
There are many studies on improving the properties of aluminum alloys, but the addition of rare earth elements occupies a particularly important place among them. In this study, the effect of erbium (Er) addition on the microstructure and mechanical properties of A380 aluminum casting alloy was systematically investigated. A series of alloys with varying Er contents (0.03%, 0.05% and 0.1 wt.%) was fabricated using the conventional casting method. The addition of Er led to significant grain refinement, primarily due to the formation of Al3Er intermetallic particles, which acted as potent nucleation sites during solidification. Optical microscopy and SEM analyses confirmed the morphological transformation of the eutectic silicon phase into a finer and more fibrous structure. Mechanical testing revealed that the alloy containing 0.1 wt.% Er exhibited the highest ultimate tensile strength (236 MPa), elongation (4.56%), and hardness (87.6 HB), indicating an optimal balance between strength and ductility. The improvement is attributed to both microstructural refinement and dispersion strengthening mechanisms. These results suggest that controlled Er addition can be an effective strategy for enhancing the performance of cast Al–Si alloys, making them promising candidates for demanding structural applications in the automotive and aerospace industries.
AtıfScopus3WoS1İncele - MakaleAçık Erişim2026Scopus SJRQ2Microstructural Evolution of Vanadium-Modified A380 Aluminum Alloy under Different Solidification Conditions
Çolak, Murat; Avci, Ömer; Demir, Muhammet Emin
Quality requirements for aluminum alloys are continuously increasing with technological advancements, driving the need for improved alloy design and casting control. Alloying additions and solidification conditions play a decisive role in determining the microstructural characteristics of cast aluminum alloys. In this study, a commercial A380 aluminum alloy was modified with vanadium (V) additions of 0.03, 0.06, and 0.1 wt.% and cast in step permanent molds with section thicknesses ranging from 5 to 30 mm, enabling a systematic investigation of different solidification conditions. Melting, liquid metal treatment, metallographic preparation, SEM/EDS analysis, density measurements, and solidification modeling were employed. The results demonstrate that vanadium addition and solidification time jointly govern the morphology and distribution of eutectic silicon and intermetallic phases. Under the investigated casting conditions, a V addition of 0.06 wt.% resulted in the most homogeneous microstructure, while higher V content led to the formation of coarser intermetallic phases, particularly at longer solidification times. These findings emphasize the importance of considering the combined effects of alloying and solidification parameters when optimizing the microstructure of A380 aluminum castings for industrial applications.
- MakaleYalnız künye2026Scopus SJRQ1The Use of Iron-Cobalt Sulphide Electrodes Decorated with Silver Nanoparticles as a Sensitive and Selective Sensor for Nitrite Determination in Different Meat Products
Anlar Daldal, Pınar; Öztürk Doğan, Hülya; Cinar Topcu, Kübra
In this study, silver nanoparticle-decorated iron cobalt sulphide (Ag@FeCoS₂) nanostructures were synthesized on the surface of a pencil graphite electrode (PGE). The resulting modified electrode obtained was used to determine the nitrite content in four different meat products (pastırma, bologna-type sausage, heat-treated sucuk, and ham) sourced from the same brand and widely consumed in the Turkish market. The fabricated Ag@FeCoS₂ electrode demonstrated high performance in amperometric nitrite detection, with a linear detection range (0.1 to 2.5 mM), high sensitivity (1759 μA mmol/L), and a low detection limit (0.29 μmol/L). The nitrite results obtained by the electrochemical method showed recoveries ranging from 99.3% to 102.5% compared with the spectrophotometric method. In addition, the physicochemical properties of the meat products, including pH, moisture, protein, fat, and ash contents, were characterized as complementary information on the real food matrices analyzed. Statistically significant differences were observed among the investigated products for these parameters. Overall, the developed Ag@FeCoS₂/PGE sensor provides a practical, accurate, and reliable analytical approach for nitrite determination in processed meat products.
- MakaleYalnız künye2026Scopus SJRQ3An exergoeconomic analysis of a wastewater treatment plant: investigation and optimization of sludge drying—a case study
Dagci, O.; Tozlu, A.; Berber, A.
The primary parameters in wastewater treatment plant applications are pollutant removal in compliance with standards and energy costs. This study conducts exergy, exergoeconomic, and optimization analyses on the Konya Wastewater Treatment Plant to enhance its energy efficiency. All assessments of the plant were based on actual operational data. Numerical calculations were executed using Engineering Equation Solver software. Exergoeconomic analyses were performed using the Specific Cost Method, while optimization calculations employed the Net Present Value approach. Thermodynamic calculations revealed that the exergy efficiency of the biogas engine was 30.8%, which increased to 39.8% when integrated into a cogeneration system. The overall exergy efficiency of the plant was calculated to be 35.3%, which rose to 58.6% when stabilized sludge was utilized as fuel. During the optimization phase, various drying systems were evaluated, and a hybrid greenhouse-solar-panel drying system was identified as the optimal model. The analyses indicated that the total cost was minimized at the maximum dryness value (70%), suggesting that the greenhouse-type drying system could achieve regional conditions. Compared to thermal and solar energy systems, hybrid systems have been observed to offer significant advantages in first-year costs. Optimization studies reveal that hybrid systems provide 41% greater cost savings in initial investment and operational expenses compared to thermal systems, and 29% greater savings compared to solar energy systems. Meeting the system's energy demand with fossil fuels results in annual emissions of 76,850 tons of CO₂ and 1500 tons of harmful pollutants, equivalent to removing 19,000 cars from traffic or preserving 7300 hectares of forest. Significant soil and ecosystem degradation also occurs. The use of solar energy substantially reduces these environmental impacts, improving air quality and conserving natural resources.
AtıfScopus1OpenAlex1İncele - DüzeltmeAçık Erişim2025Scopus SJRQ1Correction to: Scientific habits of arguing minds: enhancing online argumentation to foster SHOM (Educational technology research and development, (2025), 10.1007/s11423-025-10474-1)
Çakiroğlu, Ünal; Güven, Onurhan; Yaman, Havva; Güven, Ebru Mazlum
Authors' affiliation were incorrect in the article as originally published and have been corrected.
- MakaleYayıncıda açık erişim2025Scopus SJRQ2Sustainable Optimization of Ohmic Heating–Assisted Extraction of Polyphenolics from Goji Berry (Lycium barbarum L.): LC–MS/MS Profiling and Blueness–Greenness Assessment
Kantar, Harun; Ecem Bayram, Nesrin
This study aimed to extract bioactive compounds from goji berry (Lycium barbarum L.) fruit using the ohmic heating–assisted extraction (OHAE) method and optimize the extraction conditions. In this context, firstly, the extraction conditions to be applied for the OHAE method were determined using the response surface method (RSM)-Box Behnken experimental design. During the study, temperature, holding time, and electrical field strength were determined as independent variables, while the total phenolic compound (TPC), total flavonoid compound (TFC), and antioxidant activity (DPPH) were selected as dependent variables. As a result of the optimization, the optimum conditions were determined to be 60 °C for the temperature, 60 min for the holding time, and 45 V/cm for the electrical field strength, and the composite desirability value of the model was 0.90. The highest experimental results for TPC, TFC, and DPPH were found to be 23.83 mg GAE/g, 7.33 mg QE/g, and 24.53 mg TE/g, respectively. In addition, the polyphenolic profiles of all extracts obtained under different process conditions were determined by LC–MS/MS, and rutin was the phenolic detected at the highest rate in the extracts. In addition, the blueness and greenness of the analytical method used in this study were evaluated using the BAGI and ComplexGAPI metrics, respectively. The results indicate that OHAE is an effective and sustainable method for extracting bioactive compounds from goji berries.
AtıfScopus5WoS5OpenAlex4İncele - MakaleAçık Erişim2025Scopus SJRQ2An Integrated In Vitro and In Silico Investigation of the Bioactive Properties of Wild Glycyrrhiza glabra var. glandulifera
Kızıl, Hamit Emre; Ulcay, Sibel; Ekincioğlu, Yavuz; Öğütçü, Hatice; Ağar, Güleray
This investigation examined methanol extracts obtained from the whole plant (encompassing all organs except roots), flowers, and fruits of wild Glycyrrhiza glabra var. glandulifera, a liquorice cultivar indigenous to the Cappadocia region of Türkiye, constituting the first comprehensive in vitro and in silico analysis of this species within the region. Anatomical identification revealed distinctive structural characteristics, including thick-walled epidermal cells in the stem, organized clusters of collenchyma cells, and well-defined sclerenchyma layers encompassing the vascular bundles. The petiole exhibited a characteristic heart-shaped morphology containing three vascular bundles, while foliar analysis demonstrated the presence of stomata on both adaxial and abaxial surfaces, accompanied by a bifacial mesophyll arrangement. The extracts demonstrated remarkable antimicrobial efficacy against both Gram-positive and Gram-negative bacteria, as well as various fungal species. Furthermore, significant cytotoxic activity was observed against non-small cell lung cancer (H460), with the whole plant extract exhibiting IC50 values of 117.8 µg/mL (24 h) and 105.6 µg/mL (48 h). Flower extracts demonstrated IC50 values of 116.8 µg/mL (24 h) and 112.7 µg/mL (48 h), while fruit extracts displayed superior potency with IC50 values of 104.4 µg/mL (24 h) and 63.09 µg/mL (48 h). Molecular docking analyses, conducted utilizing AutoDock Tools 1.5.6 and BIOVIA Discovery Studio Visualizer 4.5, revealed significant protein-ligand interactions, yielding optimal binding energy and inhibition constant values of -9.57 kcal/mol and 96.92 nM, respectively. The RMSD values were calculated based on structural variations between ligand-protein complexes during re-docking procedures. These findings underscore the substantial biological potential of Glycyrrhiza glabra var. glandulifera from Cappadocia, necessitating further comprehensive investigation.
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İncele - MakaleYayıncıda açık erişim2025Scopus SJRQ1Scientific habits of arguing minds: enhancing online argumentation to foster SHOM
Çakiroğlu, Ünal; Güven, Onurhan; Yaman, Havva; Güven, Ebru Mazlum
This paper reports on a study aiming at examining whether online argumentation enhance the teacher candidates’ scientific habits of mind (SHOM). The study was carried out as a pre-experimental design including pre and post-test. Scientific Habits of Mind scale, interviews and written arguments were used as data collection tools. Google Classroom, sentence openers, prompt questions and videos were used to facilitate the online argumentation process. Five different SSIs were given as discussion and argumentation tasks for the participants who worked in online groups. The results indicated that, the SHOM scores of the teacher candidates were slightly decreased while the argumentation skills were significantly increased. In addition, there was a medium, positive correlation between the levels of scientific habits of mind and levels of argumentation skills. Participants’ perspectives also showed the contributions of virtual argumentation strategy implemented in this study. Sentence openers, prompt questions, videos and feedback were the prominent factors shaped the online argumentation process. We believe that the findings of this study would assist in future design and implementation of online tools for enhancing argumentation.
AtıfScopus1WoS2OpenAlex2İncele - MakaleAçık Erişim2025Scopus SJRQ2Investigation of the Structural and Corrosion Properties of Duplex Surface Treated AZ31 Magnesium Alloy
Durna, İdris; Çatar, Recep; Altun, Hikmet
The AZ31 alloy was first completely coated with pure aluminum in this study using the electric arc spray coating method. Then, considering the existing benefits of the micro-arc oxidation process (MAO), a ceramic oxide coating was formed by applying MAO to the Al-coated surface. Thus, a duplex coating was obtained on the base material. The structural properties of both the Al-coated samples and the duplex coatings obtained after the MAO process were investigated by scanning electron microscopy, energy-dispersive x-ray analysis (EDS), and x-ray diffraction devices. The electrochemical behavior of the coatings was carried out in a 3.5 wt.% NaCl solution. The samples were polarized from the potential value − 0.2 V below the corrosion potential to the maximum value of 2 V at a scanning rate of 1 mV/s, and potentiodynamic polarization curves were recorded. According to the electrochemical experiments, Al coatings and duplex coatings improved the corrosion resistance of AZ31 alloy. The corrosion current density values were 298.23 µA/cm2 for the base material, 0.415 µA/cm2 for the Al coating, and 0.014 µA/cm2 for the duplex coating, respectively. The best corrosion resistance among all samples was obtained in duplex-coated samples obtained by MAO. Due to their low corrosion resistance, magnesium alloys are restricted in many areas, especially aviation, automotive, and biomedical. Therefore, this study aimed to improve the corrosion resistance of AZ31 magnesium alloy.
- MakaleYalnız künye2025Scopus SJRQ1Exploring the transformative power of GenAI in education: an exploratory journey from social studies classes
Yetişensoy, Okan
The potential of GenAI in educational settings has attracted considerable attention, yet practical explorations of its use in K-12 classrooms are still scarce. This research aims to explore the role of GenAI models in social studies, focusing on their influence on learning-teaching processes and understanding of AI. While exploring the influence of GenAI on pedagogical aspects from the perspective of the teacher and students, this qualitative study also embraces AI as a cross-curricular theme and seeks to understand how GenAI-supported teaching activities shape students’ AI understanding. The study group of this research, conducted according to the basic qualitative research design, consisted of 21 middle school students studying in one class and a social studies teacher who implemented the practices. The primary data collection tool for the research was semi-structured interview forms. In the relevant research, a teaching framework supported by GenAI, combining “Teaching with AI” and “Teaching about AI” was developed. During the four-week process, the practitioner teacher covered the curricular outcomes using lesson plans designed in alignment with this framework. In the semi-structured interviews, students stated that engaging in activities supported by GenAI not only made the learning process more effective and interesting but also enhanced their understanding regarding AI. The teacher highlighted that GenAI models encouraged constructivist learning environments, ensured the active involvement of all students, including those in inclusive education, and contributed to AI learning through their engaging structure. Additionally, the teacher highlighted technology’s drawbacks, including encouraging dependence on convenience and potentially providing inaccurate information. The relevant findings of the study, serving as first observations, are expected to provide valuable insights for future research. At this point, it is recommended that further studies be conducted to explore the transformative potential of GenAI in education, especially by employing experimental designs. An additional suggestion, on the other hand, is to disseminate AI throughout the entire curriculum of all subjects within a specific educational level as a cross-curricular theme, as opposed to limiting its teaching to merely a singular, isolated subject area.
AtıfScopus2WoS1OpenAlex2İncele - MakaleAçık Erişim2025Scopus SJRQ2Optimization of Phenolic Compound Extraction from Bee Products via Solvent Systems and PCA Integration
Birinci, Ceren; Kara, Yakup; Gıdık, Betül; Kolaylı, Sevgi; Can, Zehra
To achieve a highly selective and sensitive analysis of phenolic compounds in bee products (honey, bee bread, and propolis), a simultaneous quantification of 25 phenolic compounds was performed using high-performance liquid chromatography coupled with a diode array detector. In the study, various solvents were utilized to enhance the phenolic profile of bee products, including pH 2 and 7 ultra-pure water, diethyl ether, and ethyl acetate. These included non-liquid–liquid extraction, pH 2 with 10 mL of pure water and 20 mL of diethyl ether; pH 2 with 10 mL of pure water and 20 mL of ethyl acetate; pH 2 with 10 mL of pure water, 10 mL of diethyl ether, and 10 mL of ethyl acetate; and pH 7 with 10 mL of pure water, 10 mL of diethyl ether, and 10 mL of ethyl acetate. Additionally, the integration of phenolic compounds identified through the enrichment method was pursued using principal component analysis (PCA). The extraction yields and recovery rates of phenolic compounds can be significantly improved by combining and integrating different extraction techniques. Our results demonstrated that using different solvent combinations significantly improved both the yield and diversity of phenolic compounds extracted from the complex matrices of bee products.
AtıfScopus2WoS2OpenAlex1İncele - MakaleAçık Erişim2025Scopus SJRQ1Investigation of life satisfaction and spiritual well-being of living liver donors in Turkey
Gunes, Hüseyin; Bulbuloglu, Semra; Saritas, Serdar
Spiritual well-being may be among the most common feelings felt by living liver donors. The feeling that pushes an individual to good behavior may be spiritual well-being, and the feeling that emerges as a result of achieving goodness may be life satisfaction. In our study, we aimed to analyze the spiritual well-being and life satisfaction of living liver donors and to examine the relationship, if any, between spiritual well-being and life satisfaction. Our descriptive and cross-sectional study was conducted with 306 living liver donors (n = 306). In the data collection process, we used a personal information form, the Spiritual Well-Being Scale, and the Satisfaction with Life Scale. In data analysis, we utilized descriptive statistical methods, one-way analysis of variance. Of all living liver donors participating in this study, 37.3% were aged 41–50 years, 73.5% were female, and 53.9% donated their liver to their spouse or child. The predictor variable of spiritual well-being was found to account for approximately 29% of the total variance in the predicted variable of life satisfaction. There was a positive and strong correlation between spiritual well-being and life satisfaction of living liver donors (p < 0.05). Spiritual well-being and life satisfaction of living liver donors are positively affected by each other. In order to provide more psychosocial support to these heroes who disregard their own health and try to save others’ lives, it is best practice to support their spiritual well-being, increase their life satisfaction and develop awareness about these two values. No Level Assigned. This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/0026.
AtıfScopus3WoS3OpenAlex3İncele - MakaleAçık Erişim2025Scopus SJRQ2The structural, optical, topographical, and H2 sensing characteristics of a Zn-doped Fe2O3 thin layer deposited via DC & RF magnetron co-sputtering method
Merhan Muğlu, Günay; Şenay, Volkan; Saritaş, Sevda; Abdolahpour Salari, Maryam; Kundakçi, Mutlu
In this study, a Zn-doped iron oxide layer was deposited onto a microscope slide using the magnetron co-sputtering technique with direct current (DC) and radio frequency (RF) sources. We comprehensively characterized the resulting Zn-doped Fe2O3 thin layer, employing techniques such as XRD, Raman spectroscopy, UV–VIS spectrophotometry, SEM, EDX, & AFM. XRD examination showed the nanocrystalline structure in the thin layer under investigation. Based on recorded absorption data, the band gap energy value calculation resulted in a value of 2.23 eV for the thin film. Raman spectroscopy identified peaks possessing Raman shifts from 100 to 1400 cm−1. SEM investigation illustrated a consistently uniform thin film surface characteristic throughout the substrate. Additionally, the AFM study disclosed a small RMS roughness value, indicative of an unrough surface for the Zn: Fe2O3 thin layer. The Fe2O3 thin film doped with Zn employing a 30 W DC voltage demonstrated effective hydrogen sensing capability at 300 °C, achieving notable response and recovery time. This work presents a novel application of Zn-doped Fe2O3 thin films as highly sensitive and stable hydrogen sensors, tailored for high-temperature environments. The unique combination of nanocrystalline structure and Zn doping optimizes the material’s electronic properties, enhancing its responsiveness to hydrogen gas. This approach offers a scalable, cost-effective pathway for developing advanced sensor technologies suited to environmental monitoring, industrial safety, and hazardous gas detection, making it a valuable addition to the field of gas-sensing materials.
AtıfScopus19WoS19OpenAlex11İncele - MakaleYalnız künye2025Scopus SJRQ3Numerical Investigation of EDS Maglev Systems in Terms of Performance and Cost for Different PMs-Aluminum Rail Arrangements
Mollahasanoglu, Hakki; Abdioglu, Murat; Ozturk, Ufuk Kemal; Okumus, Halil Ibrahim; Coskun, Elvan; Gencer, Ali
Permanent-magnet electro-dynamic suspension (PMs-EDS) maglev systems are shaping the future of modern transport by providing high-speed, energy-efficient, and sustainable transport solutions. In this study, numerical simulations were performed to determine the optimum geometrical parameters of aluminum rail and permanent magnet arrangements for EDS systems. For that, the aluminum rail and permanent magnet combinations were investigated, and then the same simulations were repeated by creating cavities in the aluminum rails for cost efficiency. The highest levitation-to-drag ratio (LDR) was achieved with magnet arrays having a fill factor of 0.4, 20 mm thick aluminum, and an aluminum rail width of 60 mm. Additionally, by creating cavities into the rails, it was calculated that approximately $2.44 million could be saved from the total cost of $17.34 million cost of the 1000 km double-strip aluminum rails, with negligible reduction in the LDR ratio. The findings of this study provide a sustainable and economical transport solution by increasing the cost effectiveness of PMs-EDS maglev systems. The results obtained may pave the way for the development of different types of applications of maglev technology and increase the potential for commercial use of maglev transport systems.
AtıfScopus4WoS5OpenAlex5İncele - MakaleAçık Erişim2025Scopus SJRQ2Liquorilactobacillus hordei SK6 and Liquorilactobacillus mali SK26 from Traditional Water Kefir Produce Dextrans with Technological Roles
Edis, Kader Korkmaz; İspirli, Hümeyra; Yilmaz, Mustafa Tahsin; Dertli, Enes
The significance of exopolysaccharides (EPS) in various applications has garnered increasing attention. In this study, two bacteria, Liquorilactobacillus hordei SK6 and Liquorilactobacillus mali SK26, isolated from traditional water kefir grains, produced 8.89 g/L and 7.2 g/L of homopolymeric glucan, respectively. NMR analysis revealed that both glucans were dextrans composed of (1 → 6)-linked α-d-glucose units, with (1 → 3)-linked α-d-glucose units serving as branching points, accounting for 5.3 ± 0.2% in dextran SK6 and 2.7 ± 0.15% in SK26. FTIR and XRD analyses further confirmed the amorphous nature of the dextrans, although dextran SK6 exhibited micro-arranged structures. Thermal characterization using TGA and DSC showed degradation temperatures of 298.5 °C for dextran SK6 and 282.1 °C for dextran SK26. Clear differences in morphological properties were observed using AFM and SEM. These findings provide valuable insights into dextran-producing strains and their potential applications in various industries.
AtıfScopus3WoS2OpenAlex4İncele - MakaleAçık Erişim2025Scopus SJRQ1A Meta-Analysis of Self-Management Interventions in Teaching Daily Living Skills to Autistic Individuals
Aydin, Orhan; Sulu, Mehmet D.; Ari-Arat, Ceren
The current study aimed to conduct a systematic review and meta-analysis of self-management interventions for teaching daily living skills to autistic individuals. This study accessed the corresponding studies by doing a search in six databases. 14 articles and one dissertation met the inclusion criteria. The included studies were first analyzed descriptively and coded according to quality indicators using What Works Clearinghouse (WWC) standards. Second, the effect sizes of the included studies were calculated using two different effect size measures (i.e., Tau-U and performance-criteria-based effect size values [PCES]). Third, these analyses were also conducted for generalization and maintenance data. Of 15 studies included in this review, nine met the WWC standards with and without reservations. Tau-U analyses were conducted for 14 studies, whereas PCES values were calculated for only eight studies with mastery criteria. The findings indicated that the self-management interventions had a.93 CI95 (.80, 1) overall effect size for Tau-U with a very large effect. On the other hand, the overall effect size for the PCES values indicated a moderate effect with.99. The weighted effect sizes in generalization and maintenance phases were very large for Tau-U; however, moderate to high effects for PCES. Although self-management interventions showed diversity, one of the domains of daily living skills (i.e., community living skills) has not been studied in the field. Notably, among the studies in our review, the last ones are from 2019. Detailed findings from descriptive analyses and two different effect size calculations are discussed, and recommendations for future studies are given.
AtıfScopus5WoS3OpenAlex9İncele - MakaleYalnız künye2025Scopus SJRQ1Extraction of Bioactive Compounds from Celery Root Peels Using an Ultrasound-Assisted Method with Choline Chloride–Based Deep Eutectic Solvents
Kamiloğlu, Aybike; Kutlu, Naciye; Elbir Abca, Tuğba; Yılmaz, Özlem
The concepts of sustainable and green technology have come to the forefront due to problems such as increasing environmental pollution, depletion of resources, and uncontrolled increases in industrialization. Green chemistry aims to reduce or completely eliminate pollution in the environment. In this study, both the ultrasonic method, which is a form of green technology, and deep eutectic solvents, which are among green solvents, were used, and a perspective on creating economic value from a waste product (celery root peel) is presented. In this context, phytochemical compounds (total flavonoid content and antioxidant activities) were obtained from celery root peels by ultrasonic-assisted extraction using 10 different choline chloride–based deep eutectic solvents, and the results were compared with methanol, an organic solvent. As a result, according to the total flavonoid content, the most effective deep eutectic solvent was choline chloride to sucrose, while according to the antioxidant activity value, choline chloride to lactic acid was found to be effective. For all of the analyzed bioactive compounds, higher or equal yields were obtained with all deep eutectic solvent extracts compared to methanol, and deep eutectic solvents could be alternatives to organic solvents (such as methanol) that may have toxic effects on humans or the environment.
AtıfScopus9WoS9OpenAlex10İncele