Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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A Comparative Study of Existing and Current On-Site Documentation of Anatolian Seljuk Kümbets
(Elsevier Ltd, 2025) Güzelci, O.Z.; Türel, A.; 01. Abdullah Gül University
During the Anatolian Seljuk period (1077–1307), monumental tombs known as kümbets emerged as a distinct architectural typology in present-day Türkiye. 2D drawings of these structures, produced since the early 20th century, contain inconsistencies that necessitate verification and accurate documentation. This study digitally documents Anatolian Seljuk kümbets in 3D to generate updated 2D sections reflecting their current condition and compares these with previously published drawings. The methodology includes collecting available 2D sections, digitally documenting kümbets through field studies, generating new 2D sections from 3D models, and systematically comparing these datasets. Two image-based metrics are employed in the comparison: the Exact Pixel Match Ratio (EPMR), which evaluates pixel-level alignment, and the Structural Similarity Index Measure (SSIM), a standard indicator for visual similarity. The results provide a comparative framework for assessing previous drawings and present a verified, up-to-date dataset of kümbet sections for future research. © 2025 Elsevier B.V., All rights reserved.
Shooting a Water Slug into an Air Column with and without Vent
(American Society of Mechanical Engineers (ASME), 2025) Bozkuş, Z.; Tijsseling, A.S.; Dinçer, A.E.; van de Ven, F.; 01. Abdullah Gül University
Compressed air is used to shoot a single water slug into an upward sloping pipe with elbow and orifice at its upper end. The experiment concerns a 12 m long pipe of 0.1 m diameter connected to a 0.5 m3 air vessel. The 10 to 50 kg heavy slugs are initially at rest in the lower part of the system. Because the upper end is closed by a flange with orifice, the water slug is expected not to hit the upstream elbow. It causes - like a piston - a fast compression of the air column ahead of it. Sometimes the slug bounces back and forth, which results in a pressure oscillation of serious amplitude. Numerical simulations based on an elementary mathematical model are normally used to interpret the pressure measurements, not all of which are fully understood. Lessons learned are summarised, and suggestions for improved experiments and enhanced simulations are given. The research is of importance, for example, for steam lines where liquid condensates may collect in lower parts after power failure. Start-up of the system will then lead to rapid slug acceleration and potentially damaging impact on elbows, orifices, and machinery. © 2025 Elsevier B.V., All rights reserved.
Drug Repositioning via Entity Transformation in Biomedical Knowledge Systems
(Springer Science and Business Media Deutschland GmbH, 2025) Erkantarci, B.; Bakal, G.; 01. Abdullah Gül University
The drug discovery process for known diseases is crucial in bioinformatics, given the extensive clinical trials, regulatory approvals, and high costs. Computational in silico methods are essential to mitigate these challenges, as they help identify promising drug candidates, thereby reducing the time and cost associated with drug discovery. An effective strategy in this domain is drug repositioning, where existing drugs, already approved for one disease, are repurposed for treating another. This approach is advantageous as it leverages the established safety profiles of existing drugs, avoiding toxic effects on human metabolism. In this effort, we employed a translational entity embedding-based neural network model to advance drug repositioning efforts. We utilize the Semantic Medline Database (SemMedDB) as the primary source of biomedical entity relationships for model training. The model is validated using repoDB, a gold standard dataset for drug repositioning. Technically, the model will learn to minimize the vector distance between related entities. This distance will serve as the basis for predicting potential drug-disease pairs in drug repositioning, offering a novel computational method to expedite the drug discovery process. © 2025 Elsevier B.V., All rights reserved.
Space-Time Geography
(Edward Elgar Publishing Ltd., 2025) Östh, J.; Türk, U.; 01. Abdullah Gül University
This is a definition of space-time geography in the Thematic Encyclopedia of Regional Science. This thematic Encyclopedia explores the multifaceted world of regional science, presenting a systematic and coherent overview of its central topics. It highlights the interdisciplinary nature of the field, examining the wide range of concepts, theories, methods and models that shape spatial-oriented approaches to the social sciences. Contributions from expert scholars delve into key aspects of regional science, from urban poverty and natural resource management to smart cities and AI. Highly accessible entries cover the definition, history, theoretical background, and applications of each topic, as well as avenues for future research. © 2025 Elsevier B.V., All rights reserved.
Spatial Interdependencies
(Edward Elgar Publishing Ltd., 2025) Türk, U.; Östh, J.; 01. Abdullah Gül University
This is a definition of spatial interdependencies in the Thematic Encyclopedia of Regional Science. This thematic Encyclopedia explores the multifaceted world of regional science, presenting a systematic and coherent overview of its central topics. It highlights the interdisciplinary nature of the field, examining the wide range of concepts, theories, methods and models that shape spatial-oriented approaches to the social sciences. Contributions from expert scholars delve into key aspects of regional science, from urban poverty and natural resource management to smart cities and AI. Highly accessible entries cover the definition, history, theoretical background, and applications of each topic, as well as avenues for future research. © 2025 Elsevier B.V., All rights reserved.
Citation - Scopus: 1
Quantum Computing at a Glance
(Elsevier, 2025) Golec, M.; Hatay, E.S.; Gill, S.S.; Mao, Y.; Buyya, R.; 01. Abdullah Gül University
Quantum computing’s current capacity to efficiently tackle complex problems exceeds that of traditional methods, as demonstrated by its use in optimization and artificial intelligence. This chapter explains the concept of quantum computing, along with its differences from traditional computing. It further provides an overview of the fundamental elements of quantum computing, such as qubits, superposition, entanglement, and decoherence. Moreover, it discusses broadly quantum algorithms, quantum gates, quantum key distribution, quantum software tools, and quantum computing applications. It aims to highlight quantum computing’s revolutionary potential for solving complex problems and revolutionizing several fields. © 2025 Elsevier B.V., All rights reserved.
Citation - Scopus: 2
Top Research Priorities in Quantum Computing
(Elsevier, 2025) Hatay, E.S.; Golec, M.; Nguyen, H.T.; Gill, S.S.; Patros, P.; Xu, M.; Buyya, R.; 01. Abdullah Gül University
Quantum computing is poised to revolutionize computational performance and capabilities, offering unprecedented efficiency in solving complex problems that surpasses classical approaches. This potential is particularly evident in fields such as optimization and artificial intelligence. This chapter delves into critical priority areas in quantum computing, including the development and application of quantum software tools. We place a strong emphasis on reimagining the use of quantum computing for modeling and simulation, sensing, and secure communication. Furthermore, we explore current trends like quantum communications for 6G networks, quantum cloud and serverless computing, scalable qubit arrays, and the pursuit of robust and reliable quantum systems. Lastly, we address emerging research areas and the open challenges ahead, encompassing advancements in foundational theory, education, ethical and societal considerations, and pathways to commercialization. © 2025 Elsevier B.V., All rights reserved.
Stimuli-Responsive and Self-Assembled Sericin Materials for Various Applications
(Elsevier, 2025) Arabaci, N.; Demirbas, A.; Dadi, S.; Dogan, F.; Öçsoy, I.; 01. Abdullah Gül University
The silkworm cocoon's structural integrity is maintained by sericin, which acts as a sticky binding layer that envelops the fibroin fibers, effectively holding them together. In the silk industry, sericin is removed from the structure of fibroin during the degumming process in order to provide the silk's whiteness, softness, and smoothness and also to make it dyeable. Sericin, which is separated from the fibroin of the cocoon by the degumming process in the textile industry in the production of silk fabric, is discarded as waste material. This waste helps cell attachment, proliferation, and differentiation in sericin-based materials, owing to its biocompatibility, biodegradability, and bioactivity features. Due to all these specific features, sericin protein is involved in the production of various biomaterials such as films, hydrogels, scaffolds, conduits, fibers, and devices used in tissue engineering and regenerative medicine. © 2025 Elsevier B.V., All rights reserved.
Developing a Label Propagation Approach for Cancer Subtype Classification Problem
(TUBITAK, 2022) Güner, P.; Bakir-Güngör, B.; Coşkun, M.; 02. 04. Bilgisayar Mühendisliği; 01. Abdullah Gül University; 02. Mühendislik Fakültesi
Cancer is a disease in which abnormal cells grow uncontrollably and invade other tissues. Several types of cancer have various subtypes with different clinical and biological implications. Based on these differences, treatment methods need to be customized. The identification of distinct cancer subtypes is an important problem in bioinformatics, since it can guide future precision medicine applications. In order to design targeted treatments, bioinformatics methods attempt to discover common molecular pathology of different cancer subtypes. Along this line, several computational methods have been proposed to discover cancer subtypes or to stratify cancer into informative subtypes. However, existing works do not consider the sparseness of data (genes having low degrees) and result in an ill-conditioned solution. To address this shortcoming, in this paper, we propose an alternative unsupervised method to stratify cancer patients into subtypes using applied numerical algebra techniques. More specifically, we applied a label propagation-based approach to stratify somatic mutation profiles of colon, head and neck, uterine, bladder, and breast tumors. We evaluated the performance of our method by comparing it to the baseline methods. Extensive experiments demonstrate that our approach highly renders tumor classification tasks by largely outperforming the state-of-the-art unsupervised and supervised approaches. © 2022 Elsevier B.V., All rights reserved.
Citation - Scopus: 3
Chaos in PID Controlled Nonlinear Systems
(Korean Institute of Electrical Engineers, 2015) Ablay, G.; 01. Abdullah Gül University
Controlling nonlinear systems with linear feedback control methods can lead to chaotic behaviors. Order increase in system dynamics due to integral control and control parameter variations in PID controlled nonlinear systems are studied for possible chaos regions in the closed-loop system dynamics. The Lur’e form of the feedback systems are analyzed with Routh’s stability criterion and describing function analysis for chaos prediction. Several novel chaotic systems are generated from second-order nonlinear systems including the simplest continuous-time chaotic system. Analytical and numerical results are provided to verify the existence of the chaotic dynamics. © 2021 Elsevier B.V., All rights reserved.
Editors' Introduction: Fall 2025
(Cambridge Univ Press, 2025) Dincer, Evren M.; Yukseker, Deniz; Kolluoglu, Biray; 06. İnsan ve Toplum Bilimleri Fakültesi; 01. Abdullah Gül University; 06.03. Sosyoloji
An Extension of Lucas's Theorem
(indian Nat Sci Acad, 2025) Cinkir, Zubeyir; Ozturkalan, Aysegul; 01. Abdullah Gül University; 02.02. Endüstri Mühendisliği; 02. Mühendislik Fakültesi
We give elementary proofs of some congruence criteria to compute binomial coefficients modulo a prime number. These criteria are analogues to the symmetry property of binomial coefficients. We give extended version of Lucas's Theorem by using those criteria. We give applications of these criteria by describing a method to derive identities and congruences involving sums of binomial coefficients.
Fuzzy Logic-Enhanced PMC Index for Assessing Policies for Decarbonization in Higher Education: Evidence from a Public University
(MDPI, 2025) Fidan, Fatma Sener; 01. Abdullah Gül University; 02.02. Endüstri Mühendisliği; 02. Mühendislik Fakültesi
Higher education institutions play a critical role in the transition to a low-carbon future due to their research capacity and societal influence. Accordingly, the calculation of greenhouse gas (GHG) emissions and the prioritization of mitigation strategies are of particular importance. In this study, a comprehensive campus-level GHG inventory was prepared for a public university in T & uuml;rkiye in alignment with the ISO 14064-1:2018 standard, and mitigation strategies were evaluated. To prioritize these strategies, both the classical Policy Modeling Consistency (PMC) index and, for the first time in the literature, a fuzzy extension of the PMC model was applied. The results reveal that the total GHG emissions for 2023 amounted to 4888.63 tCO2e (1.19 tCO2e per capita), with the largest shares originating from investments (31%) and purchased electricity (28.38%). While the classical PMC identified only two high-priority actions, the fuzzy PMC reduced score dispersion, resolved ranking ties, and expanded the number of high-priority actions to seven. The top strategies include awareness programs, energy-efficiency measures, virtual meeting practices, advanced electricity monitoring, and improved data management systems. By comparing the classical and fuzzy approaches, the study demonstrates that integrating fuzzy logic enhances the transparency, reproducibility, and robustness of strategy prioritization, thereby offering a practical roadmap for campus decarbonization and sustainability policy in higher education institutions.
Forecasting the Consumer Price Index in Turkiye Using Machine Learning Models: A Comparative Analysis
(Gazi Univ, 2025) Nalici, Mehmet Eren; Soylemez, Ismet; Unlu, Ramazan; 01. Abdullah Gül University; 02.02. Endüstri Mühendisliği; 02. Mühendislik Fakültesi; 07. Fen Bilimleri Enstitüsü; 07.03. Endüstri Mühendisliği Anabilim Dalı
This study utilizes machine learning models to forecast Turkiye's Consumer Price Index (CPI), thereby addressing a critical gap in inflation prediction methodologies. The central research problem involves the forecasting of CPI in a volatile economic environment, which is essential for informed policymaking. The primary objective of this study is to evaluate the performance of three machine learning models, such as Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM), in forecasting CPI over periods ranging from one to six months, utilizing data from 2012 to 2024. The study's unique contribution lies in the application of the "SelectKBest" method, which identifies the most relevant indices, thereby enhancing the efficiency of the models. An ensemble method, Averaging Voting, is also employed to combine the strengths of these models, producing more accurate and robust predictions. The findings indicate that while the RF model consistently generates the most accurate forecasts across all shifts, the SVM model demonstrates a particular strength in the domain of short-term predictions. The ensemble model demonstrates a substantial performance improvement, with a R2 value of 0.962 for one-month ahead of estimates and 0.956 for five-month forecasts. This combined approach has been shown to outperform individual models, offering a more reliable framework for CPI forecasting. The findings offer valuable insights for economic policymakers, enabling more precise and stable inflation predictions in Turkiye.
Green Synthesis and Characterization of Zinc Oxide Nanoparticles via Thyme for Biomedical Applications: Effect of Plant Extract Concentration and Drying Method
(Springer, 2025) Karakaya, Humeyra; Kizilates, Burcu; Erdem, Ilker; 02.07. Malzeme Bilimi ve Nanoteknoloji Mühendisliği; 01. Abdullah Gül University; 02. Mühendislik Fakültesi
Green synthesis of nano particles using plant extracts is sustainable, cost-effective, and eco-friendly. However, the synthesis parameters are still being investigated. In this study, zinc oxide nanoparticles (ZnO NPs) were prepared via thyme extract (green synthesis) and the effect of synthesis parameters were investigated. Samples with different concentrations of thyme plant extract (PE) (10, 16 & 24% (v/v) PE / Zn salt solution) were prepared and two different drying methods (freeze-drying (FD) and oven-drying (OD)) were performed. XRD results showed the hexagonal crystalline ZnO were formed with considerable crystallinity (70.8-75.1%) without further heat treatment (calcination). The crystallite sizes of ZnO NPs were determined to be in the range of 11.9-14.8 nm. The ZnO NPs prepared via PE concentration of 16% (v/v) and freeze-drying was with the finest crystallite size (11.9 nm) and considerable crystallinity (72.9%). ZnO NPs prepared via FD method were found to have smaller particle sizes, thus providing a higher surface-to-volume ratio. DLS (dynamic light scattering) analysis was used for determining the particle size distribution (PSD) and surface charge of ZnO NPs at acidic, neutral and basic pH values. The antibacterial characteristics of ZnO NPs were determined against Gram (+) and (-) bacteria. The ZnO NPs with the finest microstructure (16% PE (v/v), FD) had the highest antibacterial activity. The green synthesized ZnO NPs prepared in this study may be promising candidates for various applications including biomaterials and biomedical applications with their fine microstructure and considerable antibacterial activity.
Evaluating the Effects of Design and Manufacturing Parameters on Friction at the Surrogate Skin-3D Textile Interface
(Sage Publications Ltd, 2025) Temel-Cicek, Mevra; Cicek, Umur I.; Lloyd, Alex B.; Johnson, Andrew A.; 01. Abdullah Gül University
Additive manufacturing (AM) is increasingly employed in the development of 3D-printed wearables, including medical wrist supports, textiles, and protective garments. While the general tribological behavior of 3D-printed components has been widely studied, limited research has focused on the friction behavior of 3D-printed wearables when in contact with human skin, which is a crucial factor for improving wearer comfort by minimizing local skin friction. This study, therefore, investigates the influence of material type, manufacturing technology, and print parameters of 3D-printed textiles on frictional behavior against skin. Specimens were fabricated using three AM technologies: material extrusion (MEX), vat photopolymerization (VATP), and powder bed fusion (PBF). Each technology employed various materials and print parameters, specifically layer thickness (ranging from 0.05 to 0.3 mm) and print orientations (horizontal and vertical). Friction was measured using a custom-built handheld device at the interface between 3D-printed specimens and two surrogate skin models: lorica (representing the dorsal forearm) and silicone (representing the chest). The results revealed that friction was significantly influenced by both layer thickness and print orientation. For MEX specimens, acrylonitrile butadiene styrene, acrylonitrile styrene acrylate, and polycarbonate showed the highest friction, while for VATP, durable resin resulted in the highest friction coefficient. In contrast, PBF specimens exhibited very similar frictional behavior. Regarding layer thickness, higher values consistently resulted in the highest friction coefficients, regardless of manufacturing method or material type. These findings provide valuable insights for designers and engineers seeking to optimize the comfort of 3D-printed wearables, guiding the selection of suitable AM processes and parameters for products intended for direct skin contact.
Sustainable Stabilization of Peat Soil with Hybrid Geopolymer Jet Grout Columns
(Springer Int Publ A.G., 2025) Yalcin, Hakan; Erol, Aykut; Kaya, Zulkuf; Cadir, Cenk Cuma; Uncuoglu, Erdal; Akin, Muge K.; 01. Abdullah Gül University; 02.03. İnşaat Mühendisliği; 02. Mühendislik Fakültesi
Peat soils present severe challenges in geotechnical engineering due to their low shear strength, high water content, and aggressive chemical environments such as sulfate exposure. While cement-based jet grouting (JG) is widely used, it entails high carbon emissions and energy consumption. Hybrid geopolymer jet grout columns (HGJGCs) are presented in this work as a viable and sustainable alternative. Unlike conventional geopolymer studies that rely on pre-cured molds later exposed to aggressive environments, this research simulates realistic field conditions by injecting fresh geopolymer directly into sulfate-rich peat, where early-age durability and strength are critical. To address early strength limitations commonly seen in aggressive situations, a tiny amount of cement was added to the fly ash/GGBFS-based combination. Crucially, there is no need for high heat because the mechanism cures at room temperature. Physical model testing, laboratory-scale jet grouting, and performance comparisons with conventional JGCs were all carried out. Results show that HGJGCs increased the bearing capacity of peat by 5.5 times, improved compressive strength (5.3-5.7 MPa), and reduced settlement more effectively than JGCs. Additionally, CO2 emissions were reduced by 25.14% due to lower binder-related emissions and energy demand. This work shows that hybrid geopolymer systems are a viable, low-carbon substitute for peat stabilization because they can function well in real-world, chemically demanding situations.
Interaction of Inula Viscosa (L.) Aiton with IBA1 via Rosmarinic Acid and Rutin: Insights from Computational Models and Biological Effects
(Wiley-VCH verlag GmbH, 2025) Aktas Pepe, Nihan; Acar, Busra; Ceylan Ekiz, Yagmur; Senol, Ayse Merve; Semiz, Gurkan; Sen, Alaattin; Celik Turgut, Gurbet; 04. Yaşam ve Doğa Bilimleri Fakültesi; 01. Abdullah Gül University; 04.02. Moleküler Biyoloji ve Genetik
Inula viscosa (L.) Aiton is a traditional medicinal plant extensively utilized in Mediterranean nations for the treatment of rheumatic pain, inflammatory disorders, diabetes, anemia, and cancer. This study further explored its anti-inflammatory mechanisms through the highest components, chlorogenic acid, rosmarinic acid, and rutin, on the expression of the ionized calcium-binding adapter molecule 1 (Iba1) on monocyte-derived macrophage-like cells. Iba1 is known to contribute pathogenesis of diverse inflammatory diseases. HPLC analysis identified 13 major phenolic compounds, with rosmarinic acid, chlorogenic acid, and rutin as major components. The aqueous extract of the plant and its major components exhibited dose-dependent antiproliferative activity on pTHP-1, RAW264.7, and PCS-201-012 cells. Immunofluorescence staining revealed a significant reduction in Iba1 protein expression, which is associated with inflammation, at the high dose of I. viscosa and rutin. Molecular docking studies indicated that rosmarinic acid and rutin had the strongest predicted interactions with Iba1, with docking scores of -12.403 and -12.301 kcal/mol and MM/GBSA binding energies of -64.47 and -84.20 kcal/mol, respectively. I. visoca and its major components were observed to significantly suppress iNOS activity in LPS-stimulated cells; these findings were also supported by RT-PCR results. Treatment with the high dose of I. viscosa resulted in 9.45% necrotic cells and caused cell cycle arrest in the S phase (59.2 +/- 5.23%). This suggests that it may potentially reduce the proliferation of activated macrophages. In the fibroblast migration assays, the relative wound closure rate was found to be significant 27.06 +/- 18.09% at the low dose of I. viscosa and 31.59 +/- 22.42% at the high dose of I. viscosa. Although the relatively low wound closure rate limits tissue repair, it may benefit chronic wounds and fibrosis by suppressing excessive cell proliferation and inflammation. These results suggest that I. viscosa is a promising natural source of bioactive compounds with potential applications in anti-inflammatory drug development.
A Comprehensive Review on the Extraction and Recovery of Lithium from Primary and Secondary Sources: Advances Toward Battery-Grade Materials
(Wiley, 2025) Top, Soner; Kursunoglu, Sait; Altiner, Mahmut; 01. Abdullah Gül University; 02.07. Malzeme Bilimi ve Nanoteknoloji Mühendisliği; 02. Mühendislik Fakültesi
Lithium-ion battery (LIB) technologies have become indispensable to modern energy systems, driving global demand for high-purity lithium compounds. This review focuses on lithium recovery and purification strategies for battery-grade lithium carbonate (Li2CO3) and lithium hydroxide (LiOH), addressing both primary sources (brines and minerals) and secondary sources (waste materials). Industrially established processes, such as evaporation-based brine treatment and conventional metallurgical methods, are discussed alongside emerging techniques, including membrane separation, solvent extraction, and CO2-assisted precipitation. Particular attention is given to lithium precipitation mechanisms, the behaviour of co-existing ions during extraction, and the specific quality requirements for cathode material synthesis. By evaluating process scalability, environmental impact, and product purity, this review provides a comprehensive understanding of current practices and future directions. Additionally, it highlights the growing importance of lithium in the context of accelerating electric vehicle (EV) adoption, underscoring the bright and expanding future of the lithium industry.
Enhanced Photoluminescence via Plasmonic Gold Nanoparticles and Improved Stability of Perovskite Nanocrystals in Macroporous (Polydimethylsiloxane) PDMS Matrices
(Springer, 2025) Ocal, Sema Karabel; Tiras, Kevser Sahin; Onses, M. Serdar; Mutlugun, Evren; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik Mühendisliği
In this work, we report a simple and cost-effective method for improving both the environmental stability and photoluminescence quantum efficiency (PLQY) of perovskite nanocrystals (PNCs). Through their embedding in a specially designed macroporous polydimethylsiloxane (MPDMS) matrix and incorporation of plasmonic gold nanoparticles (Au NPs), remarkable improvements are achieved. The resulting MPDMS@PNC composites are seen to retain near-unity quantum efficiency even after 24-h immersion in water and are observed to retain over 85% of the original efficiency even at 75 degrees C, displaying excellent thermal stability. More interestingly, by incorporating Au NPs and subjecting the material to mechanical pressure, the lifetime of the PNCs gets further increased. This is due to the more intimate spatial arrangement of Au NPs in the porous matrix, enhancing localized surface plasmon resonance (LSPR) coupling and thereby enhancing the photoluminescence (PL) of the PNCs. In general, this approach offers a scalable and robust route to designing stable, high-performance perovskite-based materials for next-generation optoelectronic applications.

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