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Citation - WoS: 1
Citation - Scopus: 1
3-State Protein Secondary Structure Prediction Based on Scope Classes
(Inst Tecnologia Parana, 2021) Atasever, Sema; Azginoglu, Nuh; Erbay, Hasan; Aydin, Zafer
Improving the accuracy of protein secondary structure prediction has been an important task in bioinformatics since it is not only the starting point in obtaining tertiary structure in hierarchical modeling but also enhances sequence analysis and sequence-structure threading to help determine structure and function. Herein we present a model based on DSPRED classifier, a hybrid method composed of dynamic Bayesian networks and a support vector machine to predict 3-state secondary structure information of proteins. We used the SCOPe (Structural Classification of Proteins-extended) database to train and test the model. The results show that DSPRED reached a Q(3) accuracy rate of 82.36% when trained and tested using proteins from all SCOPe classes. We compared our method with the popular PSI PRED on the SCOPe test datasets and found that our method outperformed PSI PRED.
Citation - WoS: 6
Citation - Scopus: 6
3-Sulfopropyl Methacrylate Based Cryogels as Potential Tissue Engineering Scaffolds
(Taylor & Francis Ltd, 2020) Durukan, Adile Yuruk; Isoglu, Ismail Alper
In this study, we developed cryogels containing 3-sulfopropyl methacrylate (SPMA) and 4-vinyl pyridine (4-VP) as a potential scaffold for tissue engineering applications. Cryogels with varying monomer ratios were synthesised by chemical cross-linking under cryogelation conditions. Effect of initiators and cross-linker amount (0.025-0.15 g MBA; 0.012-0.05 g APS; 2.5-12.5 mu l TEMED) and also freezing temperature (-20 and -80oC) were investigated, and the conditions were optimised according to the morphological structures examined by SEM. The functional groups of the materials were characterised by FT-IR. Compression test and swelling were applied to investigate mechanical properties and water absorption ability, respectively. As a preliminary study, selected materials were tested for cell cytotoxicity with MTT. According to our results, the ionic and biocompatible cryogels prepared in this study possessing a highly porous and interconnective structure with good mechanical characteristics and swelling properties can be suitable as tissue scaffolds for many applications.
3D Sampling of K-Space With Non-Cartesian Trajectories in MR Imaging
(Gazi Univ, Fac Engineering Architecture, 2025) Dundar, Mehmet Sait; Gumus, Kazim Z.; Yilmaz, Bulent
This study presents an innovative approach to 3D k-space sampling in MR imaging using non-Cartesian concentric shell trajectories. The method involves 32 concentric shells of varying radii, allowing for rapid data acquisition through undersampling techniques. Simulations using IDEA software demonstrate that this approach can fill the k-space in less than one second, a significant time reduction compared to traditional FLASH sequences that can take 3-4 minutes. The concentric shell model enhances imaging efficiency by minimizing artifacts and ensuring uniform k-space filling, leading to higher resolution and faster scans. This technique shows promise for clinical applications, particularly in dynamic imaging scenarios such as acute stroke and pediatric radiology, where speed and precision are critical. As illustrated in Figure A, the concentric shell trajectories enable uniform k-space filling, significantly reducing scan times and improving image quality. These results are based on the simulations conducted with IDEA software.
3Mont: A Multi-Omics Integrative Tool for Breast Cancer Subtype Stratification
(Public Library Science, 2025) Unlu Yazici, Miray; Marron, J. S.; Bakir-Gungor, Burcu; Zou, Fei; Yousef, Malik
Breast Cancer (BRCA) is a heterogeneous disease, and it is one of the most prevalent cancer types among women. Developing effective treatment strategies that address diverse types of BRCA is crucial. Notably, among different BRCA molecular sub-types, Hormone Receptor negative (HR-) BRCA cases, especially Basal-like BRCA sub-types, lack estrogen and progesterone hormone receptors and they exhibit a higher tumor growth rate compared to HR+ cases. Improving survival time and predicting prognosis for distinct molecular profiles is substantial. In this study, we propose a novel approach called 3-Multi-Omics Network and Integration Tool (3Mont), which integrates various -omics data by applying a grouping function, detecting pro-groups, and assigning scores to each pro-group using Feature importance scoring (FIS) component. Following that, machine learning (ML) models are constructed based on the prominent pro-groups, which enable the extraction of promising biomarkers for distinguishing BRCA sub-types. Our tool allows users to analyze the collective behavior of features in each pro-group (biological groups) utilizing ML algorithms. In addition, by constructing the pro-groups and equalizing the feature numbers in each pro-group using the FIS component, this process achieves a significant 20% speedup over the 3Mint tool. Contrary to conventional methods, 3Mont generates networks that illustrate the interplay of the prominent biomarkers of different -omics data. Accordingly, exploring the concerted actions of features in pro-groups facilitates understanding the dynamics of the biomarkers within the generated networks and developing effective strategies for better cancer sub-type stratification. The 3Mont tool, along with all supporting materials, can be found at https://github.com/malikyousef/3Mont.git.
Citation - WoS: 12
Citation - Scopus: 14
4D-QSAR Investigation and Pharmacophore Identification of Pyrrolo[2,1-C][1,4]Benzodiazepines Using Electron Conformational-Genetic Algorithm Method
(Taylor & Francis Ltd, 2016) Ozalp, A.; Yavuz, S. C.; Sabanci, N.; Copur, F.; Kokbudak, Z.; Saripinar, E.
In this paper, we present the results of pharmacophore identification and bioactivity prediction for pyrrolo[2,1-c][1,4]benzodiazepine derivatives using the electron conformational-genetic algorithm (EC-GA) method as 4D-QSAR analysis. Using the data obtained from quantum chemical calculations at PM3/HF level, the electron conformational matrices of congruity (ECMC) were constructed by EMRE software. The ECMC of the lowest energy conformer of the compound with the highest activity was chosen as the template and compared with the ECMCs of the lowest energy conformer of the other compounds within given tolerances to reveal the electron conformational submatrix of activity (ECSA, i.e. pharmacophore) by ECSP software. A descriptor pool was generated taking into account the obtained pharmacophore. To predict the theoretical activity and select the best subset of variables affecting bioactivities, the nonlinear least square regression method and genetic algorithm were performed. For four types of activity including the GI(50), TGI, LC50 and IC50 of the pyrrolo[2,1-c][1,4] benzodiazepine series, the r(train)(2), r(test)(2) and q(2) values were 0.858, 0.810, 0.771; 0.853, 0.848, 0.787; 0.703, 0.787, 0.600; and 0.776, 0.722, 0.687, respectively.
Citation - WoS: 2
Citation - Scopus: 1
94.8 Km-Range Direct Detection Fiber Optic Distributed Acoustic Sensor
(Optica Publishing Group (Formerly OSA), 2019) Uyar, F.; Onat, T.; Unal, C.; Kartaloǧlu, T.; Ozdur, I.; Özbay, E.
This work demonstrates an ultra-long range direct detection fiber optic distributed acoustic sensor which can detect vibrations at a distance of 94.8 km with 10 m resolution along the sensing fiber. © 2023 Elsevier B.V., All rights reserved.
Citation - WoS: 2
Citation - Scopus: 3
94.8 Km-Range Direct Detection Fiber Optic Distributed Acoustic Sensor
(Institute of Electrical and Electronics Engineers Inc., 2019) Uyar, Faruk; Onat, Talha; Unal, Canberk; Kartaloǧlu, Tolga; Ozdur, Ibrahim T.; Özbay, Ekmel
This work demonstrates an ultra-long range direct detection fiber optic distributed acoustic sensor which can detect vibrations at a distance of 94.8 km with 10 m resolution along the sensing fiber. © 2019 Elsevier B.V., All rights reserved.
A Comprehensive Analysis of Acoustic Emission Signals To Distinguish the Different Damage Types for Fiber-Reinforced Polymers: A Review
(Wiley, 2025) Yilmaz, Cagatay
Fiber-reinforced polymers (FRP) attract the attention of key industries, such as aerospace, wind energy, and automotive, as they can reduce the weight of structural components without compromising their mechanical properties. Due to FRP's anisotropic and non-homogeneous structure, their failure under different loading conditions and the corresponding failure mechanisms must be investigated. One method that progressively monitors the failure of FRP underload is Acoustic Emission (AE). AE can register the elastic stress waves in the form of digitized waveforms, released by the discontinuous events that occur in the FRP under load. These discontinuities can be clustered and identified as transverse cracking, fiber/matrix interface debonding, delamination, and fiber failure by analyzing the AE waveforms. Recently, numerous clustering approaches using machine learning algorithms, along with the varying features of AE waveforms, have been developed and are being used. These algorithms include supervised and unsupervised clustering, deep learning algorithms, and neural network methods, among others. While supervised algorithms require a training dataset to classify AE signals, unsupervised algorithms can perform clustering without training datasets. Deep learning and neural network algorithms can train themselves to cluster data, but they may require a significant amount of computer power when the dataset is large. This review paper provides comprehensive information on the clustering algorithm, along with the AE wave features, the range of features for different damage types, and the type of reinforcer.
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
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.
A Potential Hemostatic Chitosan/Gelatin Cryogel Impregnated with Verbascum Thapsus Leaf Extract for Noncompressible Hemorrhage Management
(IOP Publishing Ltd, 2025) Uzuner, Hacernur; Yuruk, Adile; Isoglu, Ismail Alper
In this study, we prepared a series of chitosan/gelatin (CS/GEL) cryogels containing Verbascum thapsus (V. thapsus) leaf extract and identified a lead formulation for noncompressible hemorrhage (NCH). Cryogels with average pore diameters ranging from 225 to 478 mu m were fabricated through cryogelation at various CS/GEL ratios. C15 was chosen as the base scaffold due to its homogeneous pore distribution, with a pore size coefficient of variation (CV) of approximately 0.22. Extract loading was 1%, 5%, 10%, and 20% w/v. Functional porosity was reported by the relative accessible void index (RAVI). In PBS, the values relative to neat C15 were 1.00, 0.27, 0.20, 0.13, and 0.09 for concentrations of 0%, 1%, 5%, 10%, and 20% w/v, respectively. In citrated blood, the series was 1.00, 0.29, 0.12, 0.14, and 0.09. After loading, equilibrium swelling decreased and the compressive modulus increased, consistent with partial pore filling in a fixed network. The cryogels maintained an interconnected macroporous network and showed swelling from 300% to 3600% in blood and PBS. Antibacterial activity reached 89% inhibition, and cell viability remained above 80%. Hemolysis was low and within acceptance limits. Clotting improved in whole blood as the blood clotting index decreased from 11.9 to 6.5, and the clotting time was approximately 6 min. The 5% w/v group provided the optimal balance of clotting, antibacterial effects, and biocompatibility. This study presents a novel hemostatic CS/GEL cryogel containing V. thapsus leaf extract that holds strong potential for future applications in NCH management.
Citation - WoS: 3
Citation - Scopus: 3
Ab Initio Simulation of Amorphous BC3
(Elsevier, 2020) Durandurdu, Murat
We report the structural and electrical properties of an amorphous BC3 model based on ab initio molecular dynamics simulations. The amorphous network is achieved from the melt and has a layer-like structure consisting of mainly hexagonal (six membered) rings as in the crystal. However, the distribution of boron atoms in the noncrystalline configuration appears to differ significantly from that of boron atoms in the crystal. The network is a solid solution and has randomly distributed nanosized graphene-like domains at each layer. Boron atoms have a tendency to form more overcoordinated defects involving with boron-boron homopolar bond(s). The mean coordination of boron and carbon atoms is 3.2 and 3.0, respectively. Interestingly the amorphous configuration is found to have a slightly higher density and bulk modulus than the crystal, which are attributed to the existence of overcoordinated units in the amorphous state. Based on the localization of the band tail states, noncrystalline BC3 is speculated to be a semiconducting material.
Citation - WoS: 2
Citation - Scopus: 1
Ab Initio Study of Boron-Rich Amorphous Boron Carbides
(Wiley, 2023) Yildiz, Tevhide Ayca; Durandurdu, Murat
Amorphous boron carbide compositions having high B contents (BxC1-x, 0.50 <= x <= 0.95) are systematically created by way of ab initio molecular dynamics calculations, and their structural, electrical, and mechanical characteristics are inclusively investigated. The coordination number of both B and C atoms increases progressively with increasing B/C ratio and more close-packed materials having pentagonal pyramid motifs form. An amorphous diamond-like local arrangement is found to be dominant up to 65% B content, and beyond this content, a mixed state of amorphous diamond- and B-like structures is perceived in the models because sp(3) hybridization around C atoms is still leading one for all compositions. The pentagonal pyramid motifs around C atoms are anticipated to appear beyond 65% content. The intericosahedral linear C-B-C chains do not form in any model. All amorphous boron carbides are semiconducting materials. The mechanical properties gradually increase with increasing B concentration, and some amorphous compositions are proposed to be hard materials on the basis of their Vickers hardness estimation.
Citation - WoS: 6
Citation - Scopus: 6
Absorption Enhancement by Semi-Cylindrical Structures for an Organic Solar Cell Application
(Optical Soc Amer, 2020) Hah, Dooyoung
Organic solar cells are attractive for various applications with their flexibility and low-cost manufacturability. In order to increase their attractiveness in practice, it is essential to improve their energy conversion efficiency. In this work, semi-cylindrical-shell-shaped structures are proposed as one of the approaches, aiming at absorption enhancement in an organic solar cell. Poly(3-hexylthiophene-2,5-diyl) blended with indene-C60 bisadduct (P3HT:ICBA) is considered as the active layer. Light coupling to the guided modes and a geometrical advantage are attributed to this absorption enhancement. Finite-difference time-domain methods and finite element analysis are used to examine the absorption spectra for two types of devices, i.e., a debossed type and an embossed type. It is shown that absorption enhancement increases as the radius of the cylinder increases, but reaches a saturation at about 4-mu m radius. The average absorption enhancement with an active layer thickness of 200 nm and radius of 4 mu m, and for incidence angles between 0 degrees and 70 degrees, is found as 51%-52% for TE-polarized input and as 30%-33% for TM-polarized input when compared to a flat structure. Another merit of the proposed structures is that the range of incidence angles where the integrated absorption is at the level of the normal incidence is significantly broadened, reaching 70 degrees-80 degrees. This feature can be highly useful especially when organic solar cells are to be placed around a round object. The study results also exhibit that the proposed devices bear broadband absorption characteristics. (C) 2020 Optical Society of America
Citation - WoS: 2
Citation - Scopus: 2
Accelerated Artificial Bee Colony Optimization for Cost-Sensitive Neural Networks in Multi-Class Problems
(Wiley, 2025) Hacilar, Hilal; Dedeturk, Bilge Kagan; Ozmen, Mihrimah; Celik, Mehlika Eraslan; Gungor, Vehbi Cagri
Metaheuristics are advanced problem-solving techniques that develop efficient algorithms to address complex challenges, while neural networks are algorithms inspired by the structure and function of the human brain. Combining these approaches enables the resolution of complex optimization problems that traditional methods struggle to solve. This study presents a novel approach integrating the ABC algorithm with ANNs for weight optimization. The method is further enhanced by vectorization and parallelization techniques on both CPU and GPU to improve computational efficiency. Additionally, this study introduces a cost-sensitive fitness function tailored for multi-class classification to optimize results by considering relationships between target class levels. It validates these advancements in two critical applications: network intrusion detection and earthquake damage estimation. Notably, this study makes a significant contribution to earthquake damage assessment by leveraging machine learning algorithms and metaheuristics to enhance predictive models and decision-making in disaster response. By addressing the dynamic nature of earthquake damage, this research fills a critical gap in existing models and broadens the understanding of how machine learning and metaheuristics can improve disaster response strategies. In both domains, the ABC-ANN implementation yields promising results, particularly in earthquake damage estimation, where the cost-sensitive approach demonstrates satisfactory outcomes in macro-F1 and accuracy. The best results for macro-F1, weighted-F1, and overall accuracy provides best results with the UNSW-NB15 and earthquake datasets, showing values of 64%, 72%, 68%, and 60%, 80%, and 79%, respectively. Comparative performance evaluations reveal that the proposed parallel ABC-ANN model, incorporating the novel cost-sensitive fitness function and enhanced by vectorization and parallelization techniques, significantly reduces training time and outperforms state-of-the-art methods in terms of macro-F1 and accuracy in both network intrusion detection and earthquake damage estimation.
Achieving Extreme Solubility and Green Solvent-Processed Organic Field-Effect Transistors: A Viable Asymmetric Functionalization of [1]Benzothieno[3,2-B][1]Benzothiophenes
(American Chemical Society, 2025) Yıldız, T.A.; Deneme, İ.; Usta, H.
Novel structural engineering strategies for solubilizing high-mobility semiconductors are critical, which enables green solvent processing for eco-friendly, sustainable device fabrication, and unique molecular properties. Here, we introduce a viable asymmetric functionalization approach, synthesizing monocarbonyl [1]benzothieno[3,2-b][1]benzothiophene molecules on a gram scale in two transition-metal-free steps. An unprecedented solubility of up to 176.0 mg·mL–1(at room temperature) is achieved, which is the highest reported to date for a high-performance organic semiconductor. The single-crystal structural analysis reveals a herringbone motif with multiple edge-to-face interactions and nonclassical hydrogen bonds involving the carbonyl unit. The asymmetric backbones adopt an antiparallel arrangement, enabling face-to-face π-π interactions. The mono(alkyl-aryl)carbonyl-BTBT compound, m-C6PhCO-BTBT enables formulations in varied green solvents, including acetone and ethanol, all achieving p-channel top-contact/bottom-gate OFETs in ambient conditions. Charge carrier mobilities of up to 1.87 cm2/V·s (μeff≈ 0.4 cm2/V·s; Ion/Ioff≈ 107–108) were achieved. To the best of our knowledge, this is one of the highest OFET performances achieved using a green solvent. Hansen solubility parameters (HSP) analysis, combined with Scatchard–Hildebrand regular solution theory and single-crystal packing analysis, elucidates this exceptional solubility and reveals unique relationships between molecular structure, interaction energy densities, cohesive energetics, and solute–solvent distances (Ra). An optimal solute–green solvent interaction distance in HSP space proves critical for green solvent-processed thin-film properties. This asymmetric functionalization approach, with demonstrated unique solubility insights, provides a foundation for designing green solvent-processable π-conjugated systems, potentially advancing innovation in sustainable (opto)electronics and bioelectronics. © 2025 Elsevier B.V., All rights reserved.
Citation - WoS: 1
Citation - Scopus: 1
Achieving High Optical Absorption in Thin Film Photovoltaic Devices via Nanopillar Arrays and Metal Nanoparticles
(Wiley-VCH Verlag GmbH, 2025) Tut, Turgut
In this study, crystalline silicon nanopillars has been employed as a hexagonal array photonic crystal structure with low optical reflection, augmented by silver metallic nanoparticles ranging from 10 to 50 nm in diameter in order to achieve high absorption in thin silicon films, a critical factor for applications in photovoltaic devices. Initially, it has been begun with an optimized structure in terms of pillar filling ratio, pillar height, and diameter, as established in the previous study. This allows to obtain a hexagonal array of nanopillars with a surface characterized by low optical reflection. To enhance the optical absorption within the bulk of the silicon thin film, the optical scattering properties of silver (Ag) metallic nanoparticles (MNPs) has been harnessed. The integration of silver metal nanoparticles into the photonic crystal hexagonal nanopillar array involved introducing a cavity into the silicon pillar. Placing Ag MNPs near the bottom of the cavity prevented the degradation of the photonic crystal's ability to maintain low reflection within the desired optical spectrum (between 400-1100 nm). Comparison between the nanopillar hexagonal array structure with Ag MNPs and the bare silicon substrate revealed a remarkable 104.76 percent increase in optical absorption for a 1-micron thick silicon bulk material. This triple hybrid structure exhibits tremendous potential in photovoltaic device applications, including solar cells and photodetectors, with the capacity to significantly enhance conversion efficiency.
Citation - WoS: 5
Citation - Scopus: 4
Active Subnetwork Ga: A Two Stage Genetic Algorithm Approach to Active Subnetwork Search
(Bentham Science Publ Ltd, 2017) Ozisik, Ozan; Bakir-Gungor, Burcu; Diri, Banu; Sezerman, Osman Ugur
Background: A group of interconnected genes in a protein-protein interaction network that contains most of the disease associated genes is called an active subnetwork. Active subnetwork search is an NP-hard problem. In the last decade, simulated annealing, greedy search, color coding, genetic algorithm, and mathematical programming based methods are proposed for this problem. Method: In this study, we employed a novel genetic algorithm method for active subnetwork search problem. We used active node list chromosome representation, branch swapping crossover operator, multicombination of branches in crossover, mutation on duplicate individuals, pruning, and two stage genetic algorithm approach. The proposed method is tested on simulated datasets and Wellcome Trust Case Control Consortium rheumatoid arthritis genome-wide association study dataset. Our results are compared with the results of a simple genetic algorithm implementation and the results of the simulated annealing method that is proposed by Ideker et al. in their seminal paper. Results and Conclusion: The comparative study demonstrates that our genetic algorithm approach outperforms the simple genetic algorithm implementation in all datasets and simulated annealing in all but one datasets in terms of obtained scores, although our method is slower. Functional enrichment results show that the presented approach can successfully extract high scoring subnetworks in simulated datasets and identify significant rheumatoid arthritis associated subnetworks in the real dataset. This method can be easily used on the datasets of other complex diseases to detect disease-related active subnetworks. Our implementation is freely available at https://www.ce.yildiz.edu.tr/personal/ozanoz/file/6611/ActSubGA.
Citation - WoS: 15
Citation - Scopus: 20
Adaptive Fault Detection Scheme Using an Optimized Self-Healing Ensemble Machine Learning Algorithm
(China Electric Power Research inst, 2022) Yavuz, Levent; Soran, Ahmet; Onen, Ahmet; Li, Xiangjun; Muyeen, S. M.
This paper proposes a new cost-efficient, adaptive, and self-healing algorithm in real time that detects faults in a short period with high accuracy, even in the situations when it is difficult to detect. Rather than using traditional machine learning (ML) algorithms or hybrid signal processing techniques, a new framework based on an optimization enabled weighted ensemble method is developed that combines essential ML algorithms. In the proposed method, the system will select and compound appropriate ML algorithms based on Particle Swarm Optimization (PSO) weights. For this purpose, power system failures are simulated by using the PSCAD-Python co-simulation. One of the salient features of this study is that the proposed solution works on real-time raw data without using any pre-computational techniques or pre-stored information. Therefore, the proposed technique will be able to work on different systems, topologies, or data collections. The proposed fault detection technique is validated by using PSCAD-Python co-simulation on a modified and standard IEEE-14 and standard IEEE-39 bus considering network faults which are difficult to detect.
Adaptive Re-Use of Medieval Caravanserais in Central Anatolia
(Gangemi Editore S P A, 2019) Yoney, Nilufer Baturayolu; Asiliskender, Burak; Urfalioglu, Nur
Kayseri, located at the junction of two major trade routes from northeast to southwest and from southeast to northwest, has been a commercial center for at least 4,000 years. The 23,500 tablets found at the Assyrian trade colony in Kanesh-Karum dating around 2,000 BCE and located 20km from the modern city provide ample proof. The great number and relevant size of Medieval caravanserais around the city as well as commercial buildings at the center indicate that this importance continued. Some of these caravanserais are already in use, albeit with inadequate architectural preservation measures while others are abandoned and/or partially destroyed. Indeed, the preservation, restoration and adaptive re-use of Medieval buildings is a major problematic, bringing out issues and interventions related to lacunae and reintegration, liberation or clearance of additions, structural strengthening with traditional/contemporary technologies, partial reconstruction, consolidation, cleaning and conservation of original building materials, and preventive maintenance. This paper aims to consider the possible presentation and adaptive re-use of Seljukid caravanserais over and inventory of accessible and at least partially preserved examples, focusing on eight case studies from the late 12th and 13th centuries: Karatay Han (1240), Tuzhisar Sultan Han (1232-1236), Eshab-i Kehf Han (before 1235), Cirgalan Han, Saruhan, Agzikarahan (1231-1240), Alayhan and Oresin Han.
Citation - WoS: 1
Citation - Scopus: 1
Addressing the Modern Regimes of Urban Spectacle: Revisiting the Ottoman General Exhibition of 1863 in Istanbul
(Sage Publications inc, 2024) Tozoglu, Ahmet Erdem
One of the most spectacular events of the Ottoman experience of modernity was the inauguration of the Ottoman General Exposition in Istanbul in 1863. The ancient Hippodrome, which is one of the most prominent venues of the city and the setting of memorable celebrations and festivals for centuries, hosted the event and provided the visitors with the opportunity to become part of the modern regimes of gaze and spectacle. This article posits three observer roles to reveal the multilayered structure of urban spectacle in mid-century Istanbul, namely the sultanic gaze, spectacle of the ordinary citizens, and the mediated experience of the foreigner. To understand the particularities of each position, I utilize several visual and textual documents about the exhibition event. Though just a single case in Ottoman urban history, the exposition enables us to understand how the new manner of modern urban spectacle emerged during a spectacular public event in Istanbul.

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