WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
Browse
334 results
Search Results
Article GenShare: A Blockchain-Based Genomic Data Sharing Platform(Association for Computing Machinery, 2026-01-27) Dedeturk, B.A.; Soran, A.; Bakir-Güngör, B.Every day, hundreds of gigabytes of data are produced due to the exponential growth of next-generation sequencing and omics technologies. By combining omics data with other data types, such as electronic health record data, panomics research is actively attempting to uncover novel and potentially useful biomarkers. For the effective analysis of high-throughput-derived omics data, it is imperative to establish robust and reliable platforms that prioritize ethical considerations while effectively managing privacy, ownership concerns, and the responsible sharing of data. The GenShare model was proposed to provide an efficient platform that fits these needs. GenShare is a hybrid platform that utilizes blockchain technology. Paillier’s homomorphic encryption scheme in tandem with Intel Software Guard Extension (SGX) serves to enable the sharing of genomic data, execution of count queries, and statistical analysis of genomic data while preserving privacy and avoiding compromise of sensitive information. The objective of this paradigm is to confront security and privacy concerns through the integration of homomorphic encryption and SGX, addressing additional challenges associated with Hyperledger Fabric and Ethereum. In pursuit of this objective, the implementation of the system involved establishing the Hyperledger Fabric network, with various workloads employed to assess the network’s efficiency. Consequently, it was hypothesized that the new GenShare model would enhance the data collection and dissemination cycle and serve as a proficient platform catering to the needs of its users. © 2026 Copyright held by the owner/author(s).Article Citation - WoS: 1Citation - Scopus: 1Photoluminescent Carbon Dots for Sensitive and Selective Cu2+ Ion Detection(Institute of Physics, 2026-01-07) Sahin-Tiras, K.; Karabel Ocal, S.; Mutlugün, E.; Sahin Tiras, KevserGreen-emitting carbon dots (CDs) were synthesized via a solvent-free, vacuum-assisted method using citric acid and urea. The CDs exhibited strong photoluminescence and served as selective, sensitive probes for Cu2+ detection in water, with a detection limit of 26 nM. Among the tested metal ions, Cu2+ induced the most significant PL quenching. Time-resolved photoluminescence measurements of the CDs in the presence of Cu2+ ions revealed a minimal change in lifetime, despite a significant decrease in PL intensity, along with unchanged UV-vis absorption, indicating a mixed quenching mechanism. The sensor’s applicability was confirmed in raisin extract and tea infusion, showing notable PL suppression. With their simplicity, selectivity, and sensitivity, these CDs offer promising potential as nanosensors for detecting Cu2+ in environmental and real-world analytical settings. © 2026 The Author(s). Published by IOP Publishing Ltd.Article CRISPR/Cas9-mediated Metabolic Engineering of Endophytic Pseudomonas Loganensis Sp. Nov. for the Production of Nutritionally Valuable Carotenoids(American Chemical Society, 2026-01-02) Arslansoy, N.; Karaman, M.Z.; Fidan, O.Carotenoids with significant nutritional and antioxidant properties have been widely utilized in the food, feed, pharmaceutical, and cosmetic industries. They improve the nutritional value of foodstuffs and have been used as natural food colorants. However, their current supply chain is mainly dependent on extraction from plants and chemical synthesis, both of which have bottlenecks, including environmental concerns, toxicity, and allergenicity. To address global demand for sustainable and environmentally friendly production of nutrients, we engineered the endophytic Pseudomonas loganensis sp. nov. as a niche microbial chassis for nutritionally valuable carotenoid production. Using CRISPR-Cas9, we knocked out key carotenogenic genes to construct strains capable of producing zeaxanthin, lycopene, and β-carotene. Additionally, an overexpression plasmid was introduced to produce astaxanthin. HPLC analysis confirmed the successful production of four target carotenoids. The culture conditions and media compositions were optimized using response surface methodology, resulting in a ∼5-fold increase in the titers of zeaxanthin (13.4 mg/L), lycopene (9.67 mg/L), and β-carotene (23.53 mg/L), and a ∼12-fold increase in astaxanthin titer (1 mg/L) compared to LB medium without optimization. Our results indicate the potential of endophytic bacteria as a microbial chassis for carotenoid bioproduction, underscoring the potential of synthetic biology to contribute to global efforts toward nutritional security and sustainable food systems. © 2026 The Authors. Published by American Chemical SocietyErratum Correction to “Multifaceted Effects of the Dielectric Component within Plasmon-Assisted Light-Emitting Structures”(American Chemical Society, 2025-12-17) Kulakovich, O.; Muravitskaya, A.; Ramanenka, A.; Efimova, T.; Krukov, V.; Mutlugün, E.; Gaponenko, S.In the original version of the article, the affiliation of Hilmi Volkan Demir needs following correction. The first affiliation of the author “Department of Electrical-Electronics Engineering, Abdullah Gul University, Kayseri 38080, Turkey” should be replaced by the affiliation “UNAM – Institute of Materials Science and Nanotechnology and The National Nanotechnology Research Center and Department of Electrical and Electronics Engineering, Department of Physics, Bilkent University, Ankara 06800, Turkey”. Therefore, the correct affiliations for H.V.D. are “UNAM – Institute of Materials Science and Nanotechnology and The National Nanotechnology Research Center and Department of Electrical and Electronics Engineering, Department of Physics, Bilkent University, Ankara 06800, Turkey; LUMINOUS! Center of Excellence for Semiconductor Lighting and Displays, School of Electrical and Electronic Engineering, School of Physical and Mathematical Sciences, School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore”. © 2025 American Chemical SocietyArticle Colloidal Photodetectors Based on Engineered Multishelled InP Based Quantum Dots(Institute of Physics, 2026-01-08) Akrema; Erol, E.; Savaş, M.; Yazici, A.; Erdem, T.; Mutlugün, E.; Faruk Yazıcı, AhmetIn this work, we present a straightforward and cost-effective approach to synthesize multi-shell InP/ZnSe/ZnSeS/ZnS quantum dots (QDs) that show promising potential for use in photodetectors. By carefully layering ZnSe, ZnSeS, and ZnS shells around an InP core, we were able to enhance the stability and optical performance of the QDs, achieving a narrow emission peak of 45 nm and a high photoluminescence quantum yield of 55%. These QDs were then integrated into simple photodetector devices, which possessed impressive sensitivity and detection capabilities. Specifically, our devices achieved a peak responsivity of 0.54 A W−1 and a detectivity of 2.22 × 1011 Jones at 400 nm with a 5 V bias. This study highlights the potential of InP-based QDs as a safer and more sustainable alternative to traditional QDs that contain toxic heavy metals, offering a viable path forward for developing high-performance optoelectronic devices. Our findings suggest that these InP/ZnSe/ZnSeS/ZnS QDs could be a key material for the next generation of high-performance optoelectronic devices, especially in applications that require highly sensitive and stable photodetectors. © 2026 The Author(s). Published by IOP Publishing Ltd.Conference Object Shooting a Water Slug Into an Air Column with and without Vent(Amer Soc Mechanical Engineers, 2025-07-20) Bozkus, Zafer; Dincer, Ali Ersin; Tijsseling, Arris S.; van de Ven, FonsCompressed 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.Conference Object Clean Energy Production and Decarbonization of Energy Sector With Floating Photovoltaic Systems(Institute of Physics, 2025-11-01) Bajc, T.; Ozgun, F.; Koca, K.; Karipoğlu, F.Floating photovoltaic systems (FPVS) offer several advantages over traditional land-based PV systems, which has contributed to a growing global interest in their deployment. Since the energy yields are strongly dependent on location and tilt angle of FPVS, this research focuses on the clean energy production and decarbonization potential of FPVS in Serbia and Türkiye for different water bodies, such are natural and artificial lakes and dams. The research is performed for the most appropriate lakes and dams, having in mind importance of the location, energy yields potential, distance from the electricity grid and main roads, environmental impact, water depth and land type quality. Tilt angles are analyzed in a range from 5 to 40°, and the optimal angle is depicted for selected locations. The highest energy yields for Türkiye were obtained for 30° tilt angle, while for Serbia it was 36°. The results showed that possible clean energy production in both countries reaches 15345 kWh of energy in total, while the yearly carbon emissions reduction for all selected locations goes up to 10.76 tCO<inf>2</inf>/year in total. Since the legal framework for the application of FPVS is not established yet in observed countries, these results contribute to the future development of legislation in the field of FPVS and encourage the stakeholders to invest in clean energy production. © Published under licence by IOP Publishing Ltd.Conference Object Modular Floating Energy Islands With Green Hydrogen Integration: Design of a Small-Scale P2x Scheme(Institute of Physics, 2025-11-01) Akpolat, A.N.; Cundeva, S.; Todorovic, J.; Rexhepi, V.; Okhay, O.; Bakon, T.; Borg, R.P.The climate crisis and rising carbon emissions make the integration of renewable energy systems into electricity grids worldwide inevitable. In this context, modular floating energy islands (MFEI) provide innovative solutions for hybrid systems with high renewable energy penetration. This study explores the simultaneous use of various renewable resources, such as solar, wind, tidal, and wave energy, through small-scale MFEI structures that can be situated in seas and lakes. Thanks to their modular design, these systems offer benefits like scalability, portability, and ease of maintenance, allowing for flexible and adaptive developments in the energy infrastructure. As highlighted in recent literature (e.g., the North Sea Wind Power Hub and EU H2Ocean projects), offshore structures for green hydrogen production support energy storage and carbon-free fuel conversion within the Power-to-X (P2X) framework. This study evaluates the potential of photovoltaic (PV)-supported hydrogen production in MFEI structures through numerical analyses. The results emphasize the strategic role of these structures in enhancing energy security, coastal protection, and reducing carbon emissions by producing significant amounts of hydrogen. This hydrogen can be used for various purposes, including re-electrification, industrial applications, heating, and agriculture. Future research should focus on real-time data optimization, AI-supported system management, and integrated hydrogen consumption scenarios. © Published under licence by IOP Publishing Ltd.Conference Object Security Through Digital Twin-Based Intrusion Detection: A Swat Dataset Analysis(IEEE, 2023-10-18) Bozdal, MehmetDigital twin, as a virtual replica of physical entity, offer valuable insights into Industrial Control System (ICS) behavior and characteristics. Leveraging the convergence of digital twins and cybersecurity, this research explores its role in securing critical infrastructure, using the Secure Water Treatment (SWaT) system as a case study. Existing intrusion detection systems (IDS) for SWaT encounter challenges related to requiring huge amounts of a dataset for training, being unable to adopt high data dimensionality, and adaptability to emerging threats. To address these issues, a hybrid digital twin model is proposed, combining physics-based models and data-driven approaches. This model facilitates precise attack localization and explainable IDS outcomes. The method exhibits promising capabilities for enhancing critical infrastructure security and adapting to evolving cyber threats. Experimental results demonstrate the ability to detect eight out of nine attack types.Article High-Accuracy Identification of Durian Leaf Diseases: A Convolutional Neural Network Approach Validated with K-Fold Cross-Validation and Bayesian Optimization(Springer, 2025-11-18) Soylemez, Ismet; Nalici, Mehmet Eren; Unlu, RamazanTo address the economic losses caused by plant diseases in durian farming, this study presents an optimized deep learning model that diagnoses diseases from leaf images with high accuracy. The model's performance is maximized through Bayesian optimization and hyperparameter tuning, while its reliability is maximized through layered five-fold cross-validation. Training the convolutional neural network model on 2595 leaf images displaying six different states (five diseased and one healthy) resulted in an average test accuracy of 91.98%. This high, consistent success rate demonstrates the model's generalizability to different datasets without overfitting. While the 'Healthy' and 'Algal' classes were successfully detected with high F1-scores, there are difficulties distinguishing between the 'Blight' and 'Colletotrichum' classes due to visual similarities. This study establishes a new reference point for durian disease classification and makes a significant contribution to the development of reliable artificial intelligence-based diagnostic tools for precision agriculture.