Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Editorial Preface(Birkhauser, 2019) Inam, I.; Büyükaşık, E.Article Citation - Scopus: 1A Cinematic Narration of Urban Segregation Through Migration in Turkey: an Analysis of the Film Block-C Directed by Zeki Demirkubuz(Intellect Ltd., 2025) Aydin, M.F.; Erdoğdu Erkarslan, Özlem; Erkarslan, Ö.; Erkarslan, ÖnderMetropolitan life is always one of the major concerns of modernity as well as the set for the cinematic art. The critical gaze of cinema throws a light on how cities provide various social and architectural contexts for diversified groups as an indispensable part of the scenario. This study delves into the portrayal of metropolitan life in Zeki Demirkubuz’s 1994 film C Blok (Block-C) through the intertwined concepts of spatial alienation, urban segregation and urban migration. Situated within the context of 1990s Istanbul, the film serves as a microcosm for exploring the social and architectural landscape of Turkish modernity. It scrutinizes the interactions between diverse social classes residing in a suburban apartment complex, offering critical insights into how western-style modernization has shaped urban spaces and individual experiences. In this context, the theoretical foundation of this research encompasses the advent of western-style modernization in Turkey, its permeation into societal realms, and the concept of spatial alienation at the social stratum. Moreover, adopting a critical thinking perspective, this study probes the notions of home and house, elucidating their implications for individuality within the framework of spatial alienation. © 2025 Intellect Ltd.Article Integrating QSAR Analysis and Machine Learning To Explore the Antidiabetic Potential of Natural Compounds(AMG Transcend Association, 2025) Sincar, B.; Yalcin, D.; Bayraktar, O.This study explores the antidiabetic potential of 72 natural compounds using molecular descriptors and QSAR modeling combined with machine learning techniques. The dataset includes 11 experimentally obtained compounds and 61 from the literature, characterized by their IC50 values indicating 50% inhibition of α-glucosidase enzyme activity. Molecular descriptors were generated using ChemAxon’s MarvinSketch and PADEL software, narrowing down over 3000 descriptors to 23 relevant features. Statistical analysis revealed significant multicollinearity among variables, necessitating the application of non-linear machine learning models, namely Random Forest and Gradient Boosting. These models demonstrated predictive capabilities with R² values of 0.7751 and 0.8066, respectively, and highlighted molecular weight and the number of heteroatoms in ring structures as critical features influencing IC50 values. Despite the dataset's variability and limited size, the study underscores the potential of integrating QSAR and machine learning approaches to effectively predict the antidiabetic activity of natural compounds. The findings provide valuable insights for advancing computational methods in drug discovery. © 2025 by the authors.Article Citation - WoS: 3Citation - Scopus: 3Nonlocal Static Modeling of Laminated Composite Shells Using Peridynamic Differential Operator in a Higher-Order Shear Deformation Framework(Elsevier Ltd, 2025) Bab, Yonca; Dorduncu, Mehmet; Kutlu, Akif; Markert, BerndThis study investigates the flexural behaviour of the laminated composite shells in the framework of Higher-Order Shear Deformation Theory (HSDT) and Peridynamic Differential Operator (PDDO), namely PD-HSDT, for the first time. Laminated composite shell structures are widely used in aerospace, automotive, and marine industries due to their high strength-to-weight ratio and design flexibility. Therefore, understanding their mechanical behavior under various loading conditions is crucial for ensuring structural reliability and performance optimization. However, such structures may possess complex curvatures and highly heterogenous laminate stackings, leading to inaccurate numerical stress analyses. The HSDT successfully captures displacement and stress distributions as well as cross-sectional warping through higher-order functions exist in the kinematics. Moreover, the PDDO represents the local derivatives in their nonlocal form, making it well-suited for problems involving higher-order derivatives and discontinuities. The governing equations and boundary conditions of the HSDT are solved by using the PDDO to accurately achieve the stress and displacement fields in the laminated composite shells. The robustness of the PD-HSDT is established by considering various loading and boundary conditions. The proposed approach demonstrates high accuracy in stress and displacement predictions when validated against reference solutions available in existing literature. This indicates strong potential for extending the methodology to more complex loading scenarios and damage mechanisms in future studies.Article Citation - Scopus: 1Recent Advances in Hydrogel-Based 3D Disease Modeling and Drug Screening Platforms(2025) Bilginer-Kartal, R.; Çoban, B.; Yildirim-Semerci, Ö.; Arslan-Yildiz, A.Three-dimensional (3D) disease modeling and drug screening systems have become important in tissue engineering, drug screening, and development. The newly developed systems support cell and extracellular matrix (ECM) interactions, which are necessary for the formation of the tissue or an accurate model of a disease. Hydrogels are favorable biomaterials due to their properties: biocompatibility, high swelling capacity, tunable viscosity, mechanical properties, and their ability to biomimic the structure and function of ECM. They have been used to model various diseases such as tumors, cancer diseases, neurodegenerative diseases, cardiac diseases, and cardiovascular diseases. Additive manufacturing approaches, such as 3D printing/bioprinting, stereolithography (SLA), selective laser sintering (SLS), and fused deposition modeling (FDM), enable the design of scaffolds with high precision; thus, increasing the accuracy of the disease models. In addition, the aforementioned methodologies improve the design of the hydrogel-based scaffolds, which resemble the complicated structure and intricate microenvironment of tissues or tumors, further advancing the development of therapeutic agents and strategies. Thus, 3D hydrogel-based disease models fabricated through additive manufacturing approaches provide an enhanced 3D microenvironment that empowers personalized medicine toward targeted therapeutics, in accordance with 3D drug screening platforms. © 2025. The Author(s), under exclusive license to Springer Nature Switzerland AG.Article Citation - Scopus: 2Digital Sensing Technologies in Cancer Care: a New Era in Early Detection and Personalized Diagnosis(Elsevier Ltd, 2025) Yucel, M.; Önder, A.; Kurt, T.; Keles, B.; Beyaz, M.; Karadağ, Y.; Yildiz, U.H.Digital sensor platforms are systems that integrate sensors with digital technology, which revolutionize data collection, processing, and transmission for enabling real-time, high-precision and automated diagnostics. These platforms often serve as the backbone of modern monitoring systems, enabling real-time data acquisition and analysis for a wide range of applications. Recent advancements in digital sensor platforms have paved the way for transformative innovations in cancer diagnosis. These cutting-edge technologies offer unprecedented opportunities to facilitate early detection, improve diagnostic accuracy, and personalize treatment methods. This review explores the landscape of digital sensor platforms in the context of cancer diagnosis, providing an overview of their principles, functionalities, and clinical applications. The review further illustrates that biosensors, lab-on-a-chip (LOC) devices and wearable sensors have leveraged on nanotechnology, biorecognition materials and artificial intelligence (AI) for revolutionizing cancer diagnosis. It consolidates the recent advances in digital sensor platforms for cancer diagnosis and the associated critical challenges, such as regulatory concerns, standardization, and ethical considerations. Further, the review summarizes the feasibility for the integration of digital sensor platforms with routine clinical practices for the development of efficient cancer diagnosis and treatment methods. © 2025 The AuthorsConference Object Pen Holder Design for a Handwriting Education Assistance Robot(Springer Science and Business Media B.V., 2025) Güler, O.; Özdemir, Ekrem; Özdemir, E.; Dede, Mehmet İsmet Can; Balkan, M.A.; Öztürk, Ç.; Dede, M.İ.C.The aim of this work is to contribute to quality education by developing a robot system that can assist in handwriting education. The effects of educational robots on learning motivation and performance enhancement have been proven by various studies. In this context, the handwriting assistive robot aims to ease the work of teachers by enabling students to learn how to write more easily and to provide a platform where students can learn on their own. This robot can contribute to the spread of quality education by supporting equal educational opportunities, especially in disadvantaged areas and in cases where the number of teachers is insufficient. The robot supports three different operation modes: Active Mode, Assistive Mode, and Passive Mode. In this study, the pen holder design of this robot is presented. The final design is suitable for both right- and left-handed users, does not require an additional sensor, and the writing ergonomics is increased by keeping the contact point of the pen with the paper at a constant point independent of the holding style. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Book Part Controlled Release Kinetics(Springer Berlin Heidelberg, 2016) Altinkaya, S.A.Book Part Controlled Release Dose(Springer Berlin Heidelberg, 2016) Altinkaya, S.A.Book Part Controlled Release by Membrane(Springer Berlin Heidelberg, 2016) Altinkaya, S.A.