Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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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 Seismic Risk Prioritization of Stone Masonry Building Stock in Urla Peninsula Based on Rapid Assessment Techniques(Turkish Chamber of Civil Engineers, 2026) Karavin, Y.S.; Akdag, N.; Demir, U.This study aims to investigate seismic risk of stone masonry buildings in the Urla Peninsula, a region of historical and architectural significance within İzmir, Türkiye. A total of 100 stone masonry buildings were surveyed and documented with a focus on their architectural characteristics, including construction techniques, material types, structural configurations, and age. Data on the properties of all surveyed buildings are provided in an open-access database. Based on the survey, multiple rapid seismic performance assessment methods were applied to evaluate the vulnerability of these structures. These included: i) FEMA P-154 Rapid Visual Screening, ii) Provisions for the Seismic Risk Evaluation of Existing Buildings under Urban Renewal Law (RBTE-2019), iii) Seismic Vulnerability Index for Vernacular Architecture (SVIVA), and iv) the Masonry Quality Index (MQI). The comparative use of different methods is intended to investigate the relative influence of parameters shaping the seismic performance of the masonry building stock rather than to align their scores. The outcomes of this research are expected to contribute to the current risk mitigation efforts for stone masonry buildings in İzmir, thereby supporting regional seismic resilience planning. © 2026, Turkish Chamber of Civil Engineers. All rights reserved.Article Determining Area Affected by Corona in Lung Computed Tomography Images by Three-Phase Level Set and Shearlet Transform(Wolters Kluwer Medknow Publications, 2025) Aghazadeh, Nasser; Noras, Parisa; Moghaddasighamchi, SevdaBackground:The COVID-19 pandemic has created a critical global situation, causing widespread challenges and numerous fatalities due to severe respiratory complications. Since lung involvement is a key factor in COVID-19 diagnosis and treatment, accurate identification of infected regions in lung images is essential.Methods:We propose a multiphase segmentation method based on the level set framework to determine lunginvolved areas. The shearlet transform, a high-precision directional multiresolution transform, is employed to guide the gradient flow in the level set formulation. Additionally, the phase stretch transform (PST) is applied to enhance the contrast between infected and healthy regions, improving convergence speed during segmentation.Results:The proposed algorithm was tested on 500 lung images. The method accurately identified infected areas, enabling precise calculation of the percentage of lung involvement. The use of the shearlet transform also allowed clear delineation of ground-glass opacity boundaries.Conclusion:The proposed multiphase level set method, enhanced with shearlet and phase stretch transforms, effectively segments COVID-19-infected lung regions. This approach improves segmentation accuracy and computational efficiency, offering a reliable tool for quantitative lung involvement assessment.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 Citation - WoS: 1Citation - Scopus: 1Two Key Substitutions in the Chromophore Environment of mKate2 Produce an Enhanced FusionRed-Like Red Fluorescent Protein(Russian Federation Agency Science & innovation, 2025) Ruchkin, D. A.; Gavrikov, A. S.; Kolesov, D., V; Gorokhovatsky, A. Yu.; Chepurnykh, T., V; Mishin, A. S.; Bogdanov, A. M.Red fluorescent proteins (RFPs) are often probes of choice for living tissue microscopy and whole-body imaging. When choosing a specific RFP variant, the priority may be given to the fluorescence brightness, maturation rate, monomericity, excitation/emission wavelengths, and low toxicity, which are rarely combined in an optimal way in a single protein. If additional requirements such as prolonged fluorescence lifetime and/or blinking ability are applied, the available repertoire of probes could dramatically narrow. Since the entire diversity of conventional single-component RFPs belongs to just a few phylogenetic lines (DsRed-, eqFP578-and eqFP611-derived being the major ones), it is not unexpected that their advantageous properties are split between close homologs. In such cases, a systematic mutagenetic analysis focusing on variant-specific amino acid residues can shed light on the origins of the distinctness between related RFPs and may aid in consolidating their strengths in new RFP variants. For instance, the protein FusionRed, despite being efficient in fluorescence labeling thanks to its good monomericity and low cytotoxicity, has undergone considerable loss in fluorescence brightness/lifetime compared to the parental mKate2. In this contribution, we describe a fast-maturing monomeric RFP designed semi-rationally based on the mKate2 and FusionRed templates that outperforms both its parents in terms of molecular brightness, has extended fluorescence lifetime, and displays a spontaneous blinking pattern that is promising for nanoscopy use.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 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.Article Decision-Support Approaches for Sustainable Water Resource Management in Northwest Algeria(Polish Society of Ecological Engineering – PTIE, 2025) Meskine, Ahmed; Cherif, El Amine; Zerouali, Bilel; Ouadja, Abid; Santos, Celso Augusto Guimaraes; Bailek, Nadjem; Baba, AlperThis study investigates water resource management in the Wilaya of Mostaganem, northwest Algeria, using the water evaluation and planning (WEAP) decision support tool in combination with the analytic hierarchy process (AHP). As water scarcity becomes increasingly critical due to population growth, agricultural demands, and climate variability, effective management strategies are essential. This research employs WEAP to simulate various water demand and supply scenarios, assessing the impacts of irrigation efficiency, industrial development, and climate conditions on water availability. Under the ASI scenario, unsatisfied water demand may reach 4.3 hm3 per year by 2027. However, improving irrigation efficiency could reduce this by up to 50% compared to the reference scenario. Seasonal variations reveal deficits reaching 3.2 hm3 per month during the summer months of July through October. Additionally, the study highlights that a significant increase in water demand, exceeding 80 hm3 by 2060, can be mitigated through improved water supply initiatives, such as constructing new dams. The integration of AHP enables the prioritization of management strategies based on stakeholder preferences, demonstrating that adapting to climate change can stabilize demand below 50 million cubic meters. This integrated approach provides valuable insights for policymakers and stakeholders in developing sustainable water resource strategies that address the challenges faced by the Mostaganem region.Editorial Editorial: Advancing Biotechnology in Turkiye: a Dedication To All Women(Springer, 2025) Cadirci, Bilge Hilal; Buyukkileci, Ali Oguz; Binay, BarisArticle Investigation of the Effect of the Cutting Parameters on Cutting Forces and Tool Wear in the Stack Drilling of a Carbon Fibre-Reinforced Thermoplastic Matrix Composite and Aa7075(Univ Zagreb Fac Mechanical Engineering & Naval Architecture, 2025) Coskun, Ali; Etyemez, Ayhan; Ay, Mustafa; Kurt, Mustafa; Katmer, Sukran; Seker, Ulvi; Nohuz, MineThis study investigate the stack drillability of unidirectional (UD) carbon fibre reinforced thermoplastic matrix PAEK/CF composite and AA7075 plate utilised in aerospace. The effects of the cutting parameters on cutting forces during the drilling process of thermoplastic matrix composites and aluminium materials were experimentally analysed. Drilling operations were carried out on a CNC Vertical Machining Centre under dry-cutting conditions. For three different drill types, three different cutting speeds, and feed rate combinations, a total of 810 holes were drilled in a full factorial experimental design with 30 replicates for each combination. The damage on the hole surfaces on the drilled composite was identified with an optical microscope. The numerical data were obtained in the composite testing laboratory and analysed using Minitab (R) 21.1 statistical software and transformed into graphs. The most suitable drill type and cutting parameters were determined for the drillability of composite with thermoplastic matrix and aluminium (AA7075) plates when stacked.