Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Comparative Optimization of Hot Water and Citric Acid Extraction Methods for Sericin Recovery From Silk Cocoons: In Vitro Antioxidant and Antidiabetic Activities(Springer, 2026) Sincar, Bahar; Ozdemir, Feyza; Bicakci, Beyza Tutku; Erdem, Cansu; Yalcin, Dilek; Alamri, Abdulhakeem S.; Bayraktar, OguzSilk sericin, a hydrophilic protein derived from Bombyx mori cocoons, has attracted increasing interest due to its antioxidant, moisturizing, and enzyme-inhibitory properties. Efficient extraction is essential to preserve its biofunctional potential. In this study, sericin was extracted using hot water and 1.25% (w/v) citric acid using autoclave-based heating to achieve pressurized conditions above 100 degrees C. A Box-Behnken Response Surface Methodology (RSM) was applied to systematically evaluate the effects of extraction parameters (temperature and time) and to optimize five key response variables: yield, purity, molecular weight and polydispersity index (PDI), total antioxidant capacity (ABTS), and alpha-glucosidase inhibition activity. The results revealed that higher temperatures (125 degrees C) produced the maximum sericin yield, while moderate conditions (115 degrees C for 45 min) ensured better preservation of antioxidant and antidiabetic activities. Hot acid extraction resulted in significantly enhanced purity and enzymatic inhibition compared to hot water extraction. Sericin fractions above 7 kDa exhibited the strongest bioactivity, as reflected by lower IC50 values in both ABTS and alpha-glucosidase inhibition assays. The optimized hot water citric acid-based method yielded 24.00% sericin with 100.00% purity and an IC50 of 0.67 mg/mL for alpha-glucosidase inhibition. This study compares hot water and hot acid autoclave extractions using Box-Behnken design and evaluates their effects on sericin yield, purity, and bioactivities. Citric acid-based extraction produced higher purity and stronger alpha-glucosidase inhibition, while hot water extraction preserved antioxidant potential more effectively. These findings support the use of citric acid as an eco-friendly and scalable extraction agent and highlight the potential of sericin in biomedical and nutraceutical applications.Article A Novel ORC-PEM Integrated System for Sustainable Hydrogen Production from Low-Grade Waste Heat in Oil Refineries(Elsevier, 2025) Nazerifard, Reza; Mohammadpourfard, Mousa; Zarghami, RezaThis study presents an integrated multi-generation system for sustainable hydrogen production by harnessing low-grade waste heat from the overhead stream of the NHT unit's stripper column in an oil refinery. The proposed system integrates an ORC with a PEM electrolyzer, forming a novel energy solution that efficiently converts waste heat into clean hydrogen through electricity generation. A detailed model of the proposed system is developed, enabling a comprehensive assessment of its performance from thermodynamic, economic, and environmental viewpoints. At the same time, key operational parameters are optimized using the RSM-BBD method to minimize the hydrogen production cost, thereby enhancing the system's economic viability and practical implementation. The results demonstrated that the system achieves a yearly hydrogen production of 304.53 tons under optimized conditions, for 2.36 $/kg. The integrated system's overall energy and exergy efficiencies are calculated at 8.62 % and 33.43 %, respectively, demonstrating its high thermodynamic performance. Additionally, the system mitigates 3047 tons of CO2 annually by displacing conventional hydrogen production methods.Article Citation - WoS: 4Citation - Scopus: 4Optimization of Resource-Aware Parallel and Distributed Computing: a Review(Springer, 2025) Czarnul, Pawel; Antal, Marcel; Baniata, Hamza; Griebler, Dalvan; Kertesz, Attila; Kessler, Christoph W.; Rakic, GordanaThis paper presents a review of state-of-the-art solutions concerning the optimization of computing in the field of parallel and distributed systems. Firstly, we contribute by identifying resources and quality metrics in this context including servers, network interconnects, storage systems, computational devices as well as execution time/performance, energy, security, and error vulnerability, respectively. We subsequently identify commonly used problem formulations and algorithms for integer linear programming, greedy algorithms, dynamic programming, genetic algorithms, particle swarm optimization, ant colony optimization, game theory, and reinforcement learning. Afterward, we characterize frequently considered optimization problems by stating these terms in domains such as data centers, cloud, fog, blockchain, high performance, and volunteer computing. Based on the extensive analysis, we identify how particular resources and corresponding quality metrics are considered in these domains and which problem formulations are used for which system types, either parallel or distributed environments. This allows us to formulate open research problems and challenges in this field and analyze research interest in problem formulations/domains in recent years.Article Citation - WoS: 1Citation - Scopus: 1Effect of Soil Water Content Changes on the Behavior of Buildings Equipped With Single and Double Tuned Mass Dampers Subjected To Earthquakes(Springer Science and Business Media Deutschland GmbH, 2025) Roozbahan, M.; Turan, G.Tuned mass dampers (TMDs) are one of the structural control systems that have been frequently used in the last century. A TMD is designed according to the properties of the main system. In building applications, the substructure’s soil affects the response of buildings, especially in soft-type soils. Therefore, the soil properties should be included in the analysis and design of tuned mass dampers. However, the soil properties are not always identical and vary due to different factor changes such as soil water content changes. Unlike previous research, which typically assumes constant soil properties, this study incorporates the impact of soil water content changes, a key factor that can significantly alter soil behavior. This study aims to evaluate the effectiveness of optimized single and double tuned mass dampers (DTMDs) in response reduction of buildings considering the changes in the water content of soil. In this study, a metaheuristic-based optimization method is programmed to optimize TMDs and DTMDs for low-, mid-, and high-rise buildings considering soil-structure interaction (SSI). The efficiency of the optimized tuned mass dampers on the response reduction of buildings due to changes in soil water content is evaluated. According to the investigated results of 14 near-field earthquake simulations, it is concluded that the efficiency of the TMDs is significantly affected by changes in soil water content. Moreover, according to the result, the DTMD efficiency is slightly better than the TMD-controlled structure. © Springer Nature Switzerland AG 2025.Article Phase Shift Optimization for Ris Enabled Pnc System With Multiple Antennas(Ieee-inst Electrical Electronics Engineers inc, 2024) Ilguy, Mert; Ozbek, Berna; Musavian, Leila; Mumtaz, ShahidReconfigurable intelligent surfaces (RIS) have been developed to exploit the stochastic characteristics of the propagation environment for next generation wireless systems. On the other hand, the integration of wireless physical network coding (PNC) and multiple antennas yields notable enhancements in system performance. This paper presents a multiuser system, employing RIS enabled PNC alongside multiple antennas to minimize both delay and error probability. Our aim is to establish reliable communication between the user pairs, which communicate through a base station (BS) via RIS. Therefore, the reflecting coefficients including both phases and amplitudes of the RIS are optimized by using the alternating direction method of multipliers (ADMM) algorithm for both single and multiple RIS cases. Extensive results are presented to compare the proposed algorithm with random phase shift, network coding (NC) and the search algorithm to illustrate its superiority.Article Citation - WoS: 27Citation - Scopus: 34Multi-Zone Optimisation of High-Rise Buildings Using Artificial Intelligence for Sustainable Metropolises. Part 2: Optimisation Problems, Algorithms, Results, and Method Validation(Pergamon-Elsevier Science LTD, 2021) Ekici, Berk; Kazanasmaz, Zehra Tuğçe; Turrin, Michela; Taşgetiren, M. Fatih; Sarıyıldız, I. SevilHigh-rise building optimisation is becoming increasingly relevant owing to global population growth and urbanisation trends. Previous studies have demonstrated the potential of high-rise optimisation but have been focused on the use of the parameters of single floors for the entire design; thus, the differences related to the impact of the dense surroundings are not taken into consideration. Part 1 of this study presents a multi-zone optimisation (MUZO) methodology and surrogate models (SMs), which provide a swift and accurate prediction for the entire building design; hence, the SMs can be used for optimisation processes. Owing to the high number of parameters involved in the design process, the optimisation task remains challenging. This paper presents how MUZO can cope with an enormous number of parameters to optimise the entire design of high-rise buildings using three algorithms with an adaptive penalty function. Two design scenarios are considered for quad-grid and diagrid shading devices, glazing type, and building-shape parameters using the setup, and the SMs developed in part 1. The optimisation part of the MUZO methodology reported satisfactory results for spatial daylight autonomy and annual sunlight exposure by meeting the Leadership in Energy and Environmental Design standards in 19 of 20 optimisation problems. To validate the impact of the methodology, optimised designs were compared with 8748 and 5832 typical quad-grid and diagrid scenarios, respectively, using the same design parameters for all floor levels. The findings indicate that the MUZO methodology provides significant improvements in the optimisation of high-rise buildings in dense urban areas.Article Citation - WoS: 38Citation - Scopus: 50Multi-Zone Optimisation of High-Rise Buildings Using Artificial Intelligence for Sustainable Metropolises. Part 1: Background, Methodology, Setup, and Machine Learning Results(Elsevier Ltd., 2021) Ekici, Berk; Kazanasmaz, Zehra Tuğçe; Turrin, Michela; Taşgetiren, M. Fatih; Sarıyıldız, I. SevilDesigning high-rise buildings is one of the complex tasks of architecture because it involves interdisciplinary performance aspects in the conceptual phase. The necessity for sustainable high-rise buildings has increased owing to the demand for metropolises based on population growth and urbanisation trends. Although artificial intelligence (AI) techniques support swift decision-making when addressing multiple performance aspects related to sustainable buildings, previous studies only examined single floors because modelling and optimising the entire building requires extensive computational time. However, different floor levels require various design decisions because of the performance variances between the ground and sky levels of high-rises in dense urban districts. This paper presents a multi-zone optimisation (MUZO) methodology to support decision-making for an entire high-rise building considering multiple floor levels and performance aspects. The proposed methodology includes parametric modelling and simulations of high-rise buildings, as well as machine learning and optimisation as AI methods. The specific setup focuses on the quad-grid and diagrid shading devices using two daylight metrics of LEED: spatial daylight autonomy and annual sunlight exposure. The parametric model generated samples to develop surrogate models using an artificial neural network. The results of 40 surrogate models indicated that the machine learning part of the MUZO methodology can report very high prediction accuracies for 31 models and high accuracies for six quad-grid and three diagrid models. The findings indicate that the MUZO can be an important part of designing high-rises in metropolises while predicting multiple performance aspects related to sustainable buildings during the conceptual design phase. © 2021 The Author(s)