Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Identification of Turkish Extra Virgin Olive Oils Produced in Different Regions With Volatile Compounds(Innovhub SSI-Area SSOG, 2025) Sevim, Didar; Koseoglu, Oya; Ertan, Hasan; Ozdemir, Durmun; Ulan, MehmetThis study aims to characterize the composition of the volatile compounds in Turkish extra virgin olive oils (EVOOs) produced from three cultivars-Ayvalik, Gemlik, and Memecik-harvested in the South Marmara, South Aegean, and North Aegean regions during the 2014/15 and 2015/16 crop seasons. A total of 135 EVOO samples were obtained using industrial-scale 2-phase and 3-phase extraction systems. These samples were then analyzed using solid-phase microextraction (SPME) coupled with gas chromatography (GC). Among the twelve volatiles identified, trans-2-hexen-1-ol and cis-2-penten-1-ol exhibited the highest levels of abundance across all samples and seasons. Subsequently, 1-penten-3-one, hexanal, and cis-3-hexenyl acetate were identified, and it was determined that these contribute to the green and fruity sensory profile of high-quality olive oil. Two- and three-factor analyses of variance (ANOVA) revealed that volatile concentrations were significantly influenced by variety, harvest season, and extraction system. It is significant that 1-penten-3-one was found to be significantly influenced by both season and variety (p < 0.05), while 1-penten-3-ol exhibited a multifactorial dependency, with significant two-way interactions (season x variety, season x system, variety x system). Furthermore, PLS-DA-based classification successfully distinguished samples according to olive variety, indicating that volatile profiles could serve as reliable markers for authenticity and geographic origin. These findings underscore the potential of using volatile compounds as quality indicators and for geographic labelling in the olive oil industry.Article Geothermal Resources of Azerbaijan: A Comprehensive GIS-Based Remapping and Temperature Assessment Review(State Oil Company of Azerbaijan Republic, Oil Gas Scientific Research Project Institute, 2025) Isgandarov, S. M.; Uzelli, T. T.; Mukhtarov, A. N.; Baba, A. S.Azerbaijan has considerable geothermal energy potential. The resources are concentrated in regions such as the Absheron Peninsula, the Greater and Lesser Caucasus, the Kur Basin, and the Pre-Caspian-Guba region. Although the country does not have active volcanoes and geysers, geothermal energy can be extracted from deep wells, abandoned hydrocarbon fields, and natural hot springs. This study analyzes and maps Azerbaijan's geothermal resources using a Geographic Information System (GIS) to assess their potential for power generation and direct use. The main results show that wells such as Jarly-3 field thermal fluids with temperatures of up to 96 degrees C. Other promising sites include Daridagh in Nakhchivan and the Shikh field in Absheron, where geothermal water with a temperature of 68 degrees C. GIS-based interpolation techniques, including Kriging and Empirical Bayesian Kriging were applied to model the subsurface temperature distributions and identify regions with the highest geothermal potential. The study analyzed data from over 500 hot springs and geothermal wells to determine temperature variations at different depths. The results indicate that Azerbaijan's geothermal resources could support applications ranging from electricity generation to heating, agriculture, and industrial processes. Developing these resources could diversify Azerbaijan's energy sector and reduce dependence on fossil fuels. This study highlights the need for further exploration, improved drilling technologies, and investment in geothermal infrastructure to unlock the full potential of Azerbaijan's geothermal reserves.Article Improving Doppler Radar Performance through Optically-Reconfigurable Unequal Power Division with Semi-Analytical Approach(Taylor & Francis Ltd, 2025) Karatay, Anil; Atac, Enes; Dinleyici, Mehmet Salih; Yaman, FatihThe improvement of the signal-to-noise ratio (SNR) of Doppler radar systems, enabling the detection of targets at greater ranges even with limited power, has been a longstanding focus of research. However, while key limitations such as low target reflectivity and environmental interference are often addressed, the impact of efficient use of the input power remains an overlooked, yet crucial factor in overall sensitivity. Additionally, the power allocation needs to be examined from an analytical perspective for further enhancement. In this study, we present a novel measurement approach, utilizing both semi-analytical analysis and experimental methods, to improve the performance of a dual-antenna CW Doppler radar through the use of an optically reconfigurable unequal microwave power divider which provides well-directed power utilization. Comprehensive grid searches, supported by an analytical approach and considering various loss and noise scenarios, demonstrate the capability of the proposed reconfiguration method. In the Doppler radar experiments where the pendulum and servo motor were used as targets, an SNR increase of 3.04 and 2.11 dB in the radar signal was observed with the proposed method, respectively. This noticeable improvement in the SNR of the time-frequency plots indicates an enhancement in the measurement performance. The unequal power allocation enabled continuous detection of target motion with minimal signal loss, lowering the minimum detectable power level by more than 2 dB compared to the equal power division case. The experimental results show that integrating an optically reconfigurable microwave power divider into the Doppler radar system increases precision in velocity measurements.Article A Comparative Study on Experimental and FEA-Based Simulation of Dry Sliding Wear Behavior of Boronized AISI 304 Stainless Steel at Elevated Temperatures(Pleiades Publishing Ltd, 2025) Gok, Mustafa Sabri; Kucuk, Yilmaz; Khosravi, Farshid; Gunen, Ali; Karakas, Mustafa Serdar; Guden, MustafaIn this study, the influence of boronizing on the high-temperature wear behavior of AISI 304 was examined experimentally and with FEA simulation. Boronizing, conducted at 950 degrees C for 3 h using the powder-pack boronizing technique, showed an approximately 7-fold increase in hardness compared to untreated sample. Boride layer characterization was performed using XRD, SEM, and EDS line analyses. Wear tests were performed at ambient temperatures of 25, 250, and 500 degrees C. While the wear rates of the untreated sample increased dramatically with increasing temperature, those of the boronized samples were significantly limited. FEA simulation using the Johnson-Cook fracture model demonstrated a high degree of consistency with the experimental wear profiles and this alignment enables reliable wear predictions. The oxide layer formation was observed on the worn surface of boronized samples during the tests at elevated temperatures, resulting in less plastic deformation.Article Geographical Classification and Characterization of Turkish Gemlik Virgin Olive Oils From Two Locations (Salihli - Manisa and Gemlik - Bursa) Based on Their Glyceridic Profiles(Innovhub SSI - Stazioni Sperimentali per l'Industria, 2025) Diraman, Harun; Ozdemir, DurmusThe Gemlik olive cultivar (which is grown for its fruit and oil, also known as the Trilya or Tirilye olive) is the major domestic cultivar of the Marmara region and originated in Bursa province on the Gulf of Gemlik. It has also been cultivated widely for over twenty years in other olive growing regions in Turkey and is the source of speculative claims by the domestic sector about the properties of its oil. In this study, VOO samples produced from Gemlik olive cultivar grown over two crop years in the two main locations (Salihli-Manisa n=10 and Gemlik -Bursa n=14) and reference samples from the Olive Research Institute-Borova/Izmir (n=2) were analysed using the common and approved capillary GC (Fatty Acid Composition-FA) and HPLC (Triacylglycerol Profile-TAG) methods. All data from both methods were classified with the most popular chemometrics methods (Principal Component Analysis, PCA and Hierarchical Cluster Analysis, HCA). The results of the glyceridic data from the PCA indicated that the changes of cumulative percentage were the reason for variance levels (based on PC1 and PC2) in VOO samples of between 61.75 and 77.93% for all data over the two crop years. According to the PCA biplot analysis for the two crop years, some major-minor compounds and calculated parameters from FAs and TAGs data played an effective role in the geographical characterisation and classification of Gemlik VOO from two different locations, Manisa and Bursa. Consequently, the FA and TAG profiles could be promising in determining the correct geographical classification of monocultivar Gemlik VOOs.Article The Infinitude of the Primes and Some Coloring Theorems(Taylor & Francis inc, 2025) Adibelli, Azem Berivan; Goral, HaydarWe first prove the infinitude of the primes via a special case of Rado's theorem whose proof is based on the infinite Ramsey theorem. In the proof, we use the colorings of the positive integers introduced by Levent Alpoge [1] and Andrew Granville [2]. Finally, using Rado's theorem for integral domains, we will give another proof for the infinitude of nonassociated prime elements in any unique factorization domain R with a few units.Article Machine Learning in Flow Boiling: Predicting Bubble Lift-Off Diameter Despite Data Limitations(Yildiz Technical University, 2025) Tabrizi, Atta Heydarpour; Mohammadpourfard, Mousa; Mohammadpourfard, MostafaThis study concentrates on applying machine learning techniques to flow boiling in order to predict the bubble lift-off diameter. This prediction is critical because the diameter plays a key role in understanding boiling dynamics and calculating heat transfer rates. Additionally, accurately predicting this diameter is essential for optimizing thermal systems and enhancing energy efficiency. By evaluating the performance of three different machine learning algorithms: M5 tree, multilinear regression, and random forest, we aimed to assess their effectiveness in providing reliable predictions even with limited experimental data. This research is essential as it demonstrates the potential of machine learning to enhance predictive accuracy in scenarios where obtaining extensive datasets is challenging. Our findings show that these machine-learning techniques are effective for accurate predictions. The results show that the coefficient of determination ranged from 0.64 to 0.94, indicating how well the models fit the data. The root mean square error was between 0.009 and 0.02, and the mean absolute error ranged from 0.0004 to 0.02. Based on the findings, it can be inferred that the machine learning algorithms used in this study are reliable for predicting bubble lift-off diameter. This reliability also extends to other experimental parameters, suggesting that these techniques can be effectively applied in various contexts with limited data. This study demonstrates the potential of machine learning to predict experimental parameters and advances previous research by identifying key factors that influence bubble lift-off diameter. © 2025 Elsevier B.V., All rights reserved.Article Byzantine Wall Paintings in the Archaeological Sites of Aigai, Olympos, and Anaia (Turkey): Techniques and Material Characteristics(Routledge Journals, Taylor & Francis Ltd, 2025) Şerifaki, K.; Böke, H.The aim of this study is to determine the material characteristics of the paint layers and techniques of paintings executed in Late Roman and Byzantine churches located in the archaeological sites of Aigai, Olympos, and Anaia (Turkey) in order to select compatible materials prior to conservation treatments of the paintings and to establish the technical aspects of the paintings in relation to coeval Western examples. In this context, the execution technique, microchemical characteristics, stratigraphy of paintings, and mineralogical and chemical composition of the pigments were determined by polarized light microscopy (PLM), scanning electron microscopy coupled with X-ray energy dispersive spectroscopy (SEM-EDX), and Fourier transform infrared spectroscopy (FTIR). The analysis results indicated that wall paintings were executed by fresco, secco or fresco-secco techniques on a thin plaster layer that is composed of pure lime, straw, fine marble, brick, and sand aggregates. The ground layers of the paintings are composed of kaolin, calcite, and carbon black. The color compositions of the paintings were obtained by applying successive layers of paint on the ground layers. The pigments used in the paintings are mainly iron oxides for the red and yellow, green earth in celadonite and glauconite forms for greens, and lapis lazuli and Egyptian blue for blues. The present study demonstrates that the techniques and materials employed in the execution of wall paintings in Byzantine churches in Western Anatolia are analogous to those utilized in the Balkans, Crete, and Cyprus, with the exception of the presence of a clay-based ground. © The International Institute for Conservation of Historic and Artistic Works 2025.Article Citation - WoS: 1Citation - Scopus: 1Microporous Carbon Spheres for the Enrichment of Lead From Water Samples With Determination by Microsample Injection System - Flame Atomic Absorption Spectrometry (MIS-FAAS)(Taylor & Francis inc, 2025) Njjar, Muath; Ugan, Muhammet; Akturk, Ezgi Zekiye; Pelech, Iwona; Staciwa, Piotr; Akdogan, AbdullahMicroporous carbon spheres (MCSs) are advanced materials known for their high surface area, well-developed pore structure, low density, and rapid molecular diffusion, making them highly effective in solid-phase extraction (SPE) and other applications. In this study, MCSs synthesized from previously reported resorcinol-formaldehyde resin were employed as an adsorbent for the extraction and preconcentration of Pb(II) ions. The material was comprehensively characterized to confirm its suitability for adsorption applications. The adsorption and desorption behavior of MCSs toward lead ions was systematically examined under optimized conditions, including pH, eluent volume, eluent type, eluent concentration, and sample volume. Microinjection microsample injection system-flame atomic absorption spectrometry (MIS-FAAS) was used for the determination of lead ions. Experimental results from batch experiments showed that the MCSs exhibited a maximum adsorption capacity of 37.31 mg g-1. Under optimal conditions (pH 8.0, 1.0 mL of 0.1 M HNO3 eluent, and 10 mg of adsorbent), a preconcentration factor of 100 was achieved, with recovery values exceeding 90%. The method exhibited a limit of detection (LOD) of 0.73 mu g L-1. The developed method was successfully applied to real water samples, including tap water, entering industrial wastewater, and exiting industrial wastewater, confirming its potential for use in environmental monitoring and contamination control.Editorial Editorial: Advancing Biotechnology in Turkiye: a Dedication To All Women(Springer, 2025) Cadirci, Bilge Hilal; Buyukkileci, Ali Oguz; Binay, Baris