Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Erratum Erratum to “Plasma Proteomic Markers of Interleukin-1β Pathway Associated With Incident Age-Related Macular Degeneration in Persons with AIDS” [Ophthalmol Sci. 2025;5:100794] (Ophthalmology Science (2025) 5(5), (S2666914525000922), (10.1016/J.xops.2025.100794))(Elsevier Inc., 2026) Hunt, P.W.; Olshen, A.B.; Murad, N.; Ambayec, G.C.; Sezgin, E.; Schneider, M.F.; Jabs, D.A.The publisher of this journal would like to note an error in the article “Plasma Proteomic Markers of Interleukin-1β Pathway Associated with Incident Age-Related Macular Degeneration in Persons with AIDS.” An earlier version of Figure 1 was inadvertently published instead of the final revised figure. The correct figure appears below.[Figure presented] © 2025 American Academy of OphthalmologyArticle 3D Magnetic Nanocomposite Aerogel (3D-MANCA) for Humidity Sensing and Dye Adsorption Applications(Institute of Physics, 2026) Shah, N.; Tetik, H.; Lin, D.Introducing magnetic properties to aerogels not only opens new application areas but also enhances their performance in various applications. Herein, we report a novel 3D magnetic agar nanocomposite aerogel (3D-MANCA) with outstanding characteristics such as high porosity, magnetic property, rapid swelling behavior, and a unique stimuli-driven electrical conductivity. Agar and nanocellulose mixture were selected as the matrix material, while magnetic Fe<inf>3</inf>O<inf>4</inf> nanoparticles, CuO nanoparticles, and graphene nanopowder were incorporated as functional additives. 3D-MANCA obtained after a uni-directional freeze casting process exhibited a highly-ordered microporosity. It showed excellent magnetic properties and methylene-blue adsorption capability and a great performance as humidity sensor. © 2026 The Author(s). Published on behalf of The Electrochemical Society by IOP Publishing Limited.Article Improved Colorectal Gland Segmentation in Histopathology Images with Adaptive Resizer-Enhanced U-Net Models(Springer Science and Business Media Deutschland GmbH, 2026) Fidan, E.; Gumus, A.Utilizing low-resolution images for computer vision tasks such as classification and segmentation can sometimes hinder the model’s ability to accurately learn essential features. While using high-resolution images and designing compatible models might seem like viable solutions, they are not always feasible due to energy efficiency and graphical computation constraints. Downsizing images for model training and application is an effective approach for improving computational efficiency and optimizing model performance.The bilinear resizing method, commonly employed for this purpose, inherently causes information loss due to its numerical approach, which relies solely on the four nearest pixel values to compute each target pixel. This limitation becomes more pronounced with high-resolution images, where the down sampling process intensifies the loss of critical information. However, recent advancements have introduced adaptive resizer modules, which dynamically adjust image dimensions to better preserve essential features before processing by deep learning models. In this study, an adaptive resizer-based segmentation framework is proposed for the gland segmentation task, which is crucial for accurate disease diagnosis, particularly in cancer analysis. Three distinct encoder-decoder architecture segmentation models are assessed for image segmentation using the Colorectal Adenocarcinoma Gland (CRAG) gland segmentation database. Each architecture was tested separately, employing six different backbone encoders that were pretrained on the ImageNet dataset. The comparative analysis showed that the adaptive resizer improved segmentation performance, increasing the Intersection over Union (IoU) metric by an average of 5.6%. This enhancement raised the lowest IoU from 62% to 70% and the highest to 78%. The code is available on GitHub at https://github.com/miralab-ai/adaptive-resizer-segmentation. © The Author(s) 2026.Conference Object Material Optimisation for Future Double Skin Façade System Design(Institute of Physics, 2025) Unluturk, M.S.; Kazanasmaz, Z.T.; Ekici, B.; Göksal Özbalta, T.G.Façades have a significant impact on energy consumption in interiors. Designers aimed to reduce energy consumption by developing different façade systems. Double Skin Façade (DSF) aims to increase thermal and ventilation performance in the interior. The depth of the cavity gap between the two façade layers with air inside may adversely affect indoor daylight performance. In addition, studies in the literature indicate that this façade system shows optimum performance in cold climates. With the right design decisions, the DSF system can provide optimum performance in hot climates. In building designs with DSF systems in these climate zones, daylight and energy simulations can make the right design decisions. However, the climate crisis (CC) is increasing air temperatures and sunshine hours in hot and arid climate zones. Simulations are based on current climate data, and the recommendations obtained may not show optimum performance in the future. The study aims to propose an educational building model with a DSF system that will provide optimum visual comfort for 50 years in the Mediterranean climate type (CSA). Meteonorm has created weather scenarios for Izmir for 2050 and 2080. Opossum and Galapagos carried out the optimisation process using this data. The study proposes models that will perform optimally in Izmir for 50 years. © Published under licence by IOP Publishing Ltd.Conference Object Design of Adaptive Shading Device with Rigid Origami Technique: Improving Outdoor Thermal Comfort on Pathways of University Campus(Institute of Physics, 2025) Dağlier, Y.; Ekici, B.; Korkmaz, K.Since urbanization emerged with consequences for the built environment, shadows have played a key role in outdoor comfort. In hot climates, shadow has become a vital element in public spaces as it significantly affects social interaction on various occasions, such as university campus areas. The current state of the art shows that the role of shadings in outdoor environments is crucial to increasing pedestrian comfort and supporting overall well-being. While trees and canopies are commonly used for shading, their applicability is sometimes limited in pedestrian pathways. For example, the Izmir Institute of Technology (IZTECH) campus copes with outdoor discomfort during the extremely hot summer days. Due to the changing environmental conditions, static shading devices offer effective shadows only at specific times. This creates a necessity to design shading devices that can rotate and fold to mitigate temperatures more effectively and increase outdoor thermal comfort. A parametric shading model was developed using Grasshopper and Kangaroo Physics®, and its effectiveness was analyzed using Building Performance Simulation (BPS) tools. The research integrates heuristic optimization techniques to enhance shading performance, including Galapagos (Genetic Algorithm) and Opossum (RBF-opt and CMA-ES). Results indicate that the proposed kinetic shading devices reduced the universal thermal climate index (UTCI) by approximately 20% during peak sunlight hours. These findings suggest that adaptive shading strategies efficiently improve outdoor thermal comfort in urban public spaces. © 2025 Published under licence by IOP Publishing Ltd.Conference Object Energy-Efficient Urban Design Proposal in Urban Heat Island Formation: The Case of CSA Climate(Institute of Physics, 2025) Unluturk, I.U.; Yavuz, E.; Unluturk, M.S.; Akgun, B.Nowadays, unplanned construction resulting from urban growth and population increase reduces the resilience of cities and their historical texture and increases the need for buildings for housing in cities. This situation, which increases the density/height of city buildings, increases the surface temperature and reduces the green tissue, causes urban heat island. In this study, the Dumlupinar neighbourhood of Balıkesir, which attracts attention with its historical texture and where new buildings are designed in certain parts today, will be discussed. First, the areas with traditional and new buildings in the region are modelled parametrically in the Rhino/Grasshopper interface, obtained and compared through Dragonfly software and an urban prototype is created. However, in the computational design algorithms to be performed, not only today's weather scenario but also the weather scenario of 2050 was used. Models were created to minimise the urban heat island in 2050 climate conditions. This urban prototype is a proposal for sustainable cities to be built in cities in CSA climate types (Mediterranean climate). This proposal will guide municipalities in designing energy-efficient and carbon-neutral cities using the urban model of the urban heat island effect. © 2025 Institute of Physics Publishing. All rights reserved.Article Brewing Property in Onedimensional City? Exploring Starbucks' Locational Strategies-Impacts in the Case of Izmir, Türkiye(University Cueca, 2026) Coskun, Yagmur Asci; Penpencioglu, MehmetThe article examines Starbucks'locational strategies and their impact on urban spaces, drawing on Rossi's concept of the "one-dimensional city." As global brands increasingly shape urban environments, three key effects emerge: rising property prices near stores, the concentration of locations in malls, transit hubs, and walkable areas, and alignment with urban landscapes standardized by major transportation infrastructure decisions. Similar to many cities in the Global South, Starbucks in & Idot;zmir functions both as a product and a driver of property-driven, rent-seeking urban development.Empirical evidence reveals that its locational strategies enhance accessibility, increase property values, and reshape the built environment. Through spatial analysis, the article examines Starbucks locations within a walkability and accessibility framework, highlighting their concentration in high-value districts with strong public transit connections.This research underscores how global brands reinforce socio-economic divides, transform urban spaces, and promote consumption-driven urbanization through their integration into global capitalism and real estate dynamics.Article A Machine Learning Framework for Advanced Analytical Detection of CD36 Using Immunosensors Below Limit of Detection(Elsevier Ltd, 2026) Yeke, M.C.; Gelen, S.S.; Fil, H.; Yalcin, M.M.; Gumus, A.; Yazgan, I.; Odaci, D.We introduce a machine learning (ML)-based regression framework for quantitative electrochemical analysis, representing a paradigm shift from traditional univariate methods to a multivariate approach. Conventional analysis is constrained by reducing the entire signal to a single peak current feature to define a linear range and calculate a limit of detection (LOD). In contrast, our methodology treats the Differential Pulse Voltammetry (DPV) curve as time-series data, creating a high-dimensional fingerprint by systematically evaluating multiple data windows with varying widths around the main signal peak to identify the most informative segment. To validate this approach, a biosensor was developed by immobilizing Anti-CD36 antibodies on polydopamine-modified screen-printed carbon electrodes for the detection of CD36, a key protein in metabolism and immunity. Measurements were collected across 12 concentrations, including blank samples, spanning a range of 0 to 25 ng/mL. Following data augmentation, nine different regression models were evaluated, with the top-performing models achieving near-perfect prediction accuracy (R2>0.99) across this entire range. This high accuracy across the full concentration spectrum quantitatively demonstrates the method's ability to operate without relying on traditional concepts like linear range or LOD, enabling reliable detection at ultra-low levels. Furthermore, the immunosensor exhibited high selectivity against common interferents and excellent recovery in human serum. This methodology represents a significant advancement in analytical electrochemistry, providing a transferable approach for enhancing sensitivity in biomarker detection with potential applications in clinical diagnostics and biomedical research. The codes and dataset are made publicly available on GitHub to support further research: https://github.com/miralab-ai/biosensors-AI. © 2026 The Author(s)Article Energy Harvesting in High Altitude Platform Station Enabled Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2026) Tuylu, M.; Erdoǧan, E.High altitude platform station (HAPS) systems are becoming crucial facilitators for future wireless communication networks, enhancing connectivity across all vertical communication layers, including small Internet of Things (IoT) sensors and devices, terrestrial users, and aerial devices. In the context of the widely recognized vertical heterogeneous network (VHetNet) architecture, HAPS systems can provide service to both aerial and ground users. However, integrating HAPS systems as a core element in the VHetNet architecture presents a considerable energy challenge, marking a prominent constraint for their operation. Driven by this challenge, we introduce an energy harvesting (EH) strategy tailored for HAPS systems, enabling a HAPS system to gather energy from another HAPS system, which is not constrained by energy limitations. To assess the performance capabilities of the proposed model, we derive outage probability (OP), ergodic capacity (EC) and verify them by using Monte Carlo (MC) simulations. Moreover, we explore the system in terms of throughput. The findings reveal that harnessing full potential of EH stands as a viable approach to meet the energy demands of HAPS systems. © 2001-2012 IEEE.Conference Object Building-Level Circularity Assessment in Urban Regeneration: A Mediterranean Case Study(Institute of Physics, 2025) Aral, D.; Khadim, N.; Kayaçetin, N.C.; Durmus Arsan, Z.D.As the urgency to operate within planetary boundaries intensifies, adopting the circular economy (CE) in the built environment has become essential to mitigate environmental emissions, resource depletion, and waste generation. However, CE implementation at the building level remains fragmented in rapidly urbanizing lower-income countries. There is a pressing need for robust assessment to quantify the current level of circularity and identify context-specific opportunities for improvement. This study aims to evaluate the circularity potential of a residential building block in an urban regeneration project in Izmir, Türkiye, using the Whole Building Circularity Indicator (WBCI) applied to assess circularity across key lifecycle stages and system levels. The results indicate a WBCI score of 0.17 (on a scale of 1 fully circular to 0 fully linear) and a moderate flexibility of 0.70. This reflects a linear building profile driven by virgin materials, mass-intensive construction, limited adaptability, disassembly, and low end-of-life recovery potential. The structure layer presents the lowest system circularity score of 0.11. The study contributes to the literature on building circularity assessment by highlighting the critical role of the assessment framework in guiding the built environment toward more resource-efficient and sustainable outcomes in Mediterranean contexts, and offers practical insights to inform policy development. © Published under licence by IOP Publishing Ltd.