Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Optimizing Inhibitor Injection in Geothermal Wells With Electrical Submersible Pump(Elsevier Ltd, 2025) Aydin, H.; Tezel, S.I.; Erol, S.Electrical submersible pump (ESP) is a reliable artificial lift method to extend productive lifespan of geothermal wells. In the geothermal industry a common practice involves installing ESPs below the well's flashing depth. This placement approach aims to mitigate the risk of mineral precipitation, which can occur when hot geothermal fluids transition to a two-phase state (liquid and vapor) as pressure decreases. Positioning the pump below the flashing depth also prevents pump's underloading and gas cavitation. The inhibitor injection line usually integrated around the ESP string and installed downstream of the ESP motor. However, this standard practice introduces a challenge regarding inhibitor performance. While this placement ensures effective distribution of inhibitors throughout the production flow, the extended travel time from the surface to the point of application at the ESP can diminish inhibitor effectiveness due to continuous exposure to high temperatures throughout the wellbore. This study proposes relocating the inhibitor injection point within the production tubing closer to the flashing depth. This reduces inhibitor travel time from 108 min to 48 min and has the potential to significantly improve inhibitor effectiveness. Consequently, the implementation of capillary tubing is anticipated to yield annual cost savings per wellbore of approximately USD 10,000, coupled with the mitigation of mineral deposits within the studied well equipped with ESP. To evaluate this approach, a wellbore simulation tool and PHREEQC were employed to dynamically model the pressure and temperature profiles alongside the geochemical evolution of the produced fluids in the wellbore. This modeling approach offers significant value by potentially enabling the optimization of inhibitor usage and reducing the length of required inhibitor injection line. © 2024 Elsevier LtdArticle Citation - WoS: 4Citation - Scopus: 5Diffusion-Based Data Augmentation Methodology for Improved Performance in Ocular Disease Diagnosis Using Retinography Images(Springer Heidelberg, 2024) Aktas, Burak; Ates, Doga Deniz; Duzyel, Okan; Gumus, AbdurrahmanDeep learning models, integral components of contemporary technological landscapes, exhibit enhanced learning capabilities with larger datasets. Traditional data augmentation techniques, while effective in generating new data, have limitations, especially in fields like ocular disease diagnosis. In response, alternative augmentation approaches, including the utilization of generative AI, have emerged. In our study, we employed a diffusion-based model (Stable Diffusion) to synthesize data by faithfully recreating crucial vascular structures in the retina, vital for detecting eye diseases by using the Ocular Disease Intelligent Recognition dataset. Our goal was to augment retinography images for ocular disease diagnosis using diffusion-based models, optimizing the outputs of the fine-tuned Stable Diffusion model, and ensuring the generated data closely resembles real-world scenarios. This strategic approach resulted in improved performance in classification models and augmentation outperformed traditional methods, exhibiting high precision rates ranging from 85% to 76.2% and recall values of 86%, and 75% for 5 classes. Beyond performance enhancement, we demonstrated that the inclusion of synthetic data, coupled with data reduction using the t-SNE method, effectively addressed dataset imbalance. As a result of synthetic data addition, notable increases of 3.4% in the precision metric and 12.8% in the recall metric were observed in the 7-class case. Strategically synthesizing data addressed underrepresented classes, creating a balanced dataset for comprehensive model learning. Surpassing performance improvements, this approach underscores synthetic data's ability to overcome the limitations of traditional methods, particularly in sensitive medical domains like ocular disease diagnosis, ensuring accurate classification. The codes of the study will be shared on GitHub in a way that benefits everyone interested: https://github.com/miralab-ai/generative-data-augmentation.Article Citation - WoS: 4Citation - Scopus: 4Vo<sub>2</Sub>-based Dynamic Coding Metamaterials for Terahertz Wavefront Engineering(Springer, 2025) Akyurek, Bora; Noori, Aileen; Demirhan, Yasemin; Ozyuzer, Lutfi; Guven, Kaan; Altan, Hakan; Aygun, GulnurDigital coding metasurfaces (DCMS) offer a promising alternative to conventional metasurface designs for achieving common functionalities by controlling the phase of reflected or transmitted electromagnetic waves. Their simple unit cell designs allow for scalability across the THz spectrum and facilitate large-area fabrication. The true potential of DCMS lies in dynamical coding, which enables real-time reconfigurability through a tuning and/or switching mechanism. In this study, metasurfaces that achieve 1-bit dynamic coding of unit cells via thermally induced metal-insulator transition of VO2 layers are designed and fabricated. We investigate experimentally the beam splitting functionality at certain frequencies in the 0.50-0.75 THz range reflected from the stripe- and checkerboard patterned metasurface samples, and demonstrate the switching of this functionality under thermal illumination.Article Citation - WoS: 5Citation - Scopus: 5Multiorgan-On for Cancer Drug Pharmacokinetics-Pharmacodynamics (pk-Pd) Modeling and Simulations(Springer/plenum Publishers, 2025) Mohammed, Abdurehman Eshete; Kurucaovali, Filiz; Okvur, Devrim PesenCancer is one of the most common and fatal diseases worldwide and kills millions of people every year. Cancer drug resistance, lack of efficacy, and safety are significant problems in cancer patients. A multiorgan-on-a-chip (MOC) device consisting of breast and liver compartments was designed with AutoCAD software. The MOC molds were printed by a Formlabs Form 2 3D printer. MDA-MB-231, HepG2, and MCF-10 A cells were used for the MOC experiments. The cell lines were cultured at 37 degrees C with 5% CO2, and cell viability was assessed via Alamar blue dye to generate pharmacodynamics (PD) data. Drug concentrations from the cell culture media were analyzed via Agilent 1260 Infinity II HPLC with a Waters Symmetry C18 column and used to generate pharmacokinetics (PK) data. The PK and PD data were modeled and simulated by Monolix and Simulix software, respectively. The safety and efficacy of drug dosing regimens were compared, and the best dosing regimens were selected. This research designed and fabricated a unique MOC consisting of liver and breast compartments that overcomes the need for sealing or assembling. It was used for PK-PD modeling and simulations, and its functionality was proven experimentally. The new MOC will be helpful in preclinical trials to evaluate the efficacy and safety of drugs.Article Evaluation of Partially Reduced Keratins Extracted From Wool Fibers as a Hydrogel Forming Biomaterial(inst Tecnologia Parana, 2024) Yalcin, Damla; Top, AybenIn this study, it was aimed to prepare low-cost hydrogel from reduced keratin. Keratin proteins were obtained from Merino wool via three extraction methods. In the first method, keratins were reduced using sodium sulfide. In the second method, keratins extracted with the first method were precipitated with HCl. Urea, EDTA, and sodium sulfide were used in the third method. Extraction yields of method 1, method 2, and method 3 were determined as 44 +/- 2, 27 +/- 1, and 42 +/- 2 %, respectively. For all extraction methods, the average value of the free thiol amounts was obtained as 0.06 +/- 0.02 mmol SH/g keratin. A considerable portion of the highly polydisperse keratins was separated between similar to 40 kDa and similar to 60 kDa in the SDS-PAGE gel, and this fraction corresponds to alpha-keratin proteins with low sulfur content. A strong band at similar to 1654 +/- 1 cm(-1) detected in the FTIR spectra of the keratins confirms mainly alpha-helical secondary structure. The self- standing hydrogel was obtained upon incubating 15 wt. % keratin solution at 37 degrees C. Storage modulus and loss modulus of the hydrogel were determined as 1.3 +/- 0.08 kPa and 0.1 +/- 0.015 kPa, respectively. The keratin hydrogel is not cytotoxic to L929 mouse fibroblast cells, suggesting that this affordable hydrogel can be applied as a drug delivery/encapsulation system and in wound healing.Review Citation - WoS: 13Citation - Scopus: 18Review of Cell Level Battery (calendar and Cycling) Aging Models: Electric Vehicles(Mdpi, 2024) Yarimca, Gulsah; Cetkin, ErdalElectrochemical battery cells have been a focus of attention due to their numerous advantages in distinct applications recently, such as electric vehicles. A limiting factor for adaptation by the industry is related to the aging of batteries over time. Characteristics of battery aging vary depending on many factors such as battery type, electrochemical reactions, and operation conditions. Aging could be considered in two sections according to its type: calendar and cycling. We examine the stress factors affecting these two types of aging in detail under subheadings and review the battery aging literature with a comprehensive approach. This article presents a review of empirical and semi-empirical modeling techniques and aging studies, focusing on the trends observed between different studies and highlighting the limitations and challenges of the various models.Article Citation - WoS: 2Citation - Scopus: 3Development of Mg-Alginate Based Self Disassociative Bio-Ink for Magnetic Bio-Patterning of 3d Tumor Models(Wiley-v C H verlag Gmbh, 2024) Coban, Basak; Baskurt, Mehmet; Sahin, Hasan; Arslan-Yildiz, AhuAlginate forms a hydrogel via physical cross-linking with divalent cations. In literature, Ca2+ is mostly utilized due to strong interactions but additional procedures are required to disassociate Ca-alginate hydrogels. On the other hand, Mg-alginate hydrogels disassociate spontaneously, which might benefit certain applications. This study introduces Mg-alginate as the main component of a bio-ink for the first time to obtain 3D tumor models by magnetic bio-patterning technique. The bio-ink contains magnetic nanoparticles (MNPs) for magnetic manipulation, Mg-alginate hydrogel as a sacrificial material, and cells. The applicability of the methodology is tested for the formation of 3D tumor models using HeLa, SaOS-2, and SH-SY5Y cells. Long-term cultures are examined by Live/dead and MTT analysis and revealed high cell viability. Subsequently, Collagen and F-actin expressions are observed successfully in 3D tumor models. Finally, the anti-cancer drug Doxorubicin (DOX) effect is investigated on 3D tumor models, and IC50 values is calculated to assess the drug response. As a result, significantly higher drug resistance is observed for bio-patterned 3D tumor models up to tenfold compared to 2D control. Overall, Mg-alginate hydrogel is successfully used to form bio-patterned 3D tumor models, and the applicability of the model is shown effectively, especially as a drug screening platform.Article An Information Retrieval-Based Regression Test Selection Technique(Springer International Publishing, 2023) Erşahin, B.; Erşahin, M.Regression testing (RT) is the crucial part of the software testing process. It is applied after a bug fix or a change in the functionality of the codebase. The main goal is to ensure that the modified software has the desired outcome and does not cause adverse effects in other parts of the software. RT may be costly depending on the test’s quantity and complexity. Therefore, regression test selection (RTS) can be introduced to minimize these costs. RTS runs only the test cases related to the modified parts of the software. Currently, various RTS studies focus on compiled languages such as Java, C/C++, and C#, and they mostly rely on direct code dependency between tests and the system under test. In this study, we have introduced a new RTS tool called Smartest to reduce the number of selected integration tests. Former RTS tools were focused mainly on unit tests according to dependencies of modified source files. Smartest is the first RTS tool that works for software written in JavaScript and can select integration tests written in natural language by the quality assurance team. Smartest is tested on three commercial projects and observed that it picks 13% of all test cases on average. Experiments show that Smartest minimizes the selected integration tests on RTS processes, although it does not use file-level code dependency. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.Article Citation - WoS: 2Citation - Scopus: 2The Unlimited Joy, 'once You Start You Can't Stop': Masculinity in Domestic Technology Commercials in Turkey(Taylor & Francis Ltd, 2024) Karaosmanoglu, Defne; Ata, Leyla Bektas; Emgin, BaharRecently, studies have begun examining men's interaction with domestic space to explore changing forms of masculinity and domesticity, arguing that housework has become a leisure activity for men, with domestic technologies serving as tools (toys) for them to engage with. In this article, we explore how men in Turkish television commercials of domestic technologies are portrayed and how these portrayals construct and reconstruct discourses of domesticity and masculinity. We aim to understand men's relationship with masculinity, home and domestic work in these commercials. Alongside leisure and fun, we explore the construction of discourses of masculinity and domesticity through specific themes such as the naughty scientist, the self-seeking purchaser, and the flirtatious chef. We argue that seeing more men on screen does not democratise domesticity since the equal share of workload at home is still far from being realised even in these portrayals. We also argue that domesticity is aestheticized with the participation of men and technology. Finally, women are used as instruments by men in reconstructing their masculinity through heterosexuality.Article Citation - WoS: 4Citation - Scopus: 4Identification of Volatile Biomarkers in Exhaled Breath by Polythiophene Solid Phase Microextraction Fiber for Disease Diagnosis Using Gc-Ms(Elsevier, 2024) Pelit, Fusun; Goksel, Ozlem; Dizdas, Tugberk Nail; Arin, Aycan; Ozgur, Su; Erbas, Ilknur; Pelit, LeventThe diagnosis of diseases through monitoring of volatile organic compounds (VOCs) in exhaled breath (EB) holds great potential for clinical applications. However, a standardized method for VOC analysis in EB yet to be proposed. The present study presents an untargeted method for screening and identifying potential volatile biomarkers in EB by a lab-made solid phase microextraction (SPME) fiber. A polythiophene-based SPME fiber was produced by an electrochemical method and VOC sampling was performed under dynamic and controlled conditions. Following the sampling step, the adsorbed VOCs on the SPME fiber were analyzed using gas chromatography-mass spectrometry (GC-MS). The VOCs in EB were screened by the MS detector in selected ion monitoring (SIM) mode within the mass/charge (m/z) range of 13-94 values. Potential biomarkers among all detected VOCs in each subject's EB sample were identified through machine learning algorithms, employing a comparative analysis of distinctive retention times (RT) and peak areas between the lung cancer (LC) and control groups in two stages. In the initial stage of the study, the areas of all peaks observed in the SIM-GC-MS chromatograms of 25 LC and 51 control group subjects were integrated, and the resulting retention times and peak areas were recorded for subsequent analysis to identify potential biomarkers. A total of 1.346 distinct compounds were detected among the 76 subjects in this step, and statistical analysis using the LightGBM algorithm revealed the potential biomarkers for LC diagnosis. The PTh-SPME fibre successfully identified four novel cancer biomarkers in breath matrix: 4-heptenal, 4-methyl-1-octene, 1,2,3,4-tetrahydro-5,8-dimethyl-1-octylnaphthalene and tetrahydro-2-(2,5-undecadiynyloxy)-2H-pyran. In the second step of the study, the efficacy of the top ten selected biomarkers was evaluated in a cohort of 166 subjects, including 70 individuals with LC and 96 in the control group. The model achieved accuracy, area under the curve (AUC), and F Score values of 0.818, 0.816, and 0.817, respectively. The test model correctly predicted 27 out of 33 subjects between LC and control groups.