Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article A New Discrete Differential Evolution Algorithm Coupled With Simulation–optimization Model for Groundwater Management Problems(Springer Science and Business Media Deutschland GmbH, 2024) Şahin, O.G.; Gurarslan, G.; Gündüz, O.Discrete differential evolution (DDE) is a promising algorithm specifically developed to solve discrete problems. In this study, we aim to apply DDE to groundwater management problems and to compare its performance and discrete space search capabilities with the well-known genetic algorithm (GA) techniques. Local search process was used to enhance the performance of GA algorithm. Metaheuristic algorithms are used for finding location of wells as a hybrid optimization procedure. Two examples from the groundwater management literature were selected to test the performance of the algorithm. The main novelty and objective of this study lie in the comparison of the discrete space search capabilities of the mentioned metaheuristics algorithms using the groundwater management problems. In the first test example, discrete space search performances of algorithms are 15% and 93% for GA and DDE, respectively. In the second test example, DDE exhibited a significantly higher test results (77%) compared to GA (1%). The analysis revealed that GA often prematurely converged and was insufficient to produce the optimum result. DDE reaches the solution considerably faster than the other algorithms. The results showed the superior performance of DDE in the discrete space. As the problem becomes more discrete, the performance of the DDE algorithm in finding the optimum solution increases considerably. Thus, it can be revealed that DDE can also be applied to a wider range of water resource management problems as an effective discrete optimization algorithm. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.Article Citation - WoS: 2Citation - Scopus: 2Fabrication of Bioactive Helix Aspersa Extract-Loaded Chitosan-Based Bilayer Wound Dressings for Skin Tissue Regeneration(Amer Chemical Soc, 2024) Perpelek, Merve; Tıhmınlıoğlu, Funda; Tamburaci, Sedef; Karakasli, Ahmet; Tihminlioglu, FundaIn recent years, there has been a notable shift toward exploring plant and animal extracts for the fabrication of tissue engineering structures that seamlessly integrate with the human body, providing both biological compatibility and physical reinforcement. In this particular investigation, we synthesized bilayer wound dressings by incorporating snail (Helix aspersa) secretions, comprising mucus and slime, into chitosan matrices via lyophilization and electrospinning methodologies. A nanofiber layer was integrated on top of the porous structure to mimic the epidermal layer for keratinocyte activity as well as acting as an antibacterial barrier against possible infection, whereas a porous structure was designed to mimic the dermal microenvironment for fibroblast activity. Comprehensive assessments encompassing physical characterization, antimicrobial efficacy, in vitro bioactivity, and wound healing potential were conducted on these bilayer dressings. Our findings revealed that the mucus and slime extract loading significantly altered the morphology in terms of nanofiber diameter and average pore size. Snail extracts loaded on a nanofiber layer of bilayer dressings showed slight antimicrobial activity against Staphylococcus epidermidis and Escherichia coli. An in vitro release study of slime extract loaded in the nanofiber layer indicated that both groups 1 and 2 showed a burst release up to 6 h, and a sustained release was observed up to 96 h for group 1, whereas slime extract release from group 2 continued up to 72 h. In vitro bioactivity assays unveiled the favorable impact of mucus and slime extracts on NIH/3T3 fibroblast and HS2 keratinocyte cell attachment, proliferation, and glycosaminoglycan synthesis. Furthermore, our investigations utilizing the in vitro scratch assay showcased the proliferative and migratory effects of mucus and slime extracts on skin cells. Collectively, our results underscore the promising prospects of bioactive snail secretion-loaded chitosan constructs for facilitating skin regeneration and advancing wound healing therapies.Article Citation - WoS: 1Citation - Scopus: 1Chemical Composition Optimization and Isothermal Transformation of Δ-Transformation Plasticity Steel for the Third-Generation Advanced High-Strength Steel Grade(Wiley-v C H verlag Gmbh, 2024) Okur, Onur; Davut, Kemal; Palumbo, Gianfranco; Nalcaci, Burak; Guglielmi, Pasquale; Yalcin, Mustafa Alp; Erdogan, MehmetA new low-manganese transformation-induced plasticity steel is designed with optimized nickel content to achieve superior strength and ductility while minimizing the use of expensive nickel. The steel is optimized using JMatPro software, then cast, and hot rolled. To assess the effect of intercritical annealing on austenite (martensite at room temperature) volume fraction and carbon content, hot-rolled steel samples quenched from different annealing temperatures (680-1100 degrees C) are used. Additionally, hot-rolled steel coupons are intercritically annealed at about 50% austenite formation temperature (740 degrees C) and then subjected to isothermal treatments at 300-425 degrees C for varying times (10-90 min). After optimizing these treatments to maximize retained austenite (RA), tensile specimens are heat-treated first at 740 degrees C and then isothermally at 325 degrees C. Thermodynamic calculations suggest that aluminum combined with silicon may lead to the delta ferrite formation, and even minimal nickel content can stabilize a considerable amount of austenite. In the experimental studies, it is shown that lower-temperature bainitic holding enhances austenite stability by enriching the carbon content. Optimized two-stage heat treatments yield up to 25.8% RA, with a tensile strength of 867.2 MPa and elongation of 40.6%, achieving a strength-elongation product of 35.2 GPax%, surpassing the third-generation advanced high-strength steel grades minimum requirement of 30 GPax%.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 Citation - WoS: 1Comparison of Cell-Penetrating and Fusogenic Tat-Ha2 Peptide Performance in Peptideplex, Multicomponent, and Conjugate Sirna Delivery Systems(Amer Chemical Soc, 2024) Uz, Metin; Bulmus, Volga; Altinkaya, Sacide AlsoyIn this study, the performance of the cell-penetrating and fusogenic peptide, TAT-HA2, which consists of a cell-permeable HIV trans-activator of transcription (TAT) protein transduction domain and a pH-responsive influenza A virus hemagglutinin protein (HA2) domain, was comparatively evaluated for the first time in peptideplex, multicomponent, and conjugate siRNA delivery systems. TAT-HA2 in all three systems protected siRNA from degradation, except in the conjugate system with a low Peptide/siRNA ratio. The synergistic effect of different peptide domains enhanced the transfection efficiency of multicomponent and conjugate systems compared to that of peptideplexes, which was attributed to the surface configuration of TAT-HA2 peptides depending on the nature of attachment. Particularly, the multicomponent system showed better cellular uptake and endosomal escape than the peptideplexes, resulting in enhanced siRNA delivery in the cytoplasm. In addition, the presence of cleavable disulfide bonds in multicomponent and conjugate systems promoted the effective siRNA delivery in the cytoplasm, resulting in improved gene silencing activity. The multicomponent system reduced the level of luciferase expression in SKOV3 cells to 45% (+/- 4). In contrast, the conjugate system and the commercially available siRNA transfection agent, Lipofectamine RNAiMax, caused luciferase suppression down to 55% (+/- 2) at a siRNA dose of 100 nM. For the same dose, the peptideplex system could only reduce the luciferase expression to 65% (+/- 5). None of the developed systems showed significant toxicity at any dose. Overall, the TAT-HA2 peptide is promising as a siRNA delivery vector; however, its performance depends on the nature of attachment and, as a result, its surface configuration on the developed delivery system.Article Regression Via Classification for Fingerprint Orientation Estimation(Ieee-inst Electrical Electronics Engineers inc, 2024) Erdogmus, NesliEstimating the direction in which the ridges and valleys of the fingerprint pattern are aligned often serves as a pivotal first step in fingerprint recognition systems. The ridge orientation map is a fundamental reference for subsequent processing stages, such as image enhancement, feature extraction, and matching. Therefore, its accuracy is essential to achieve high recognition rates. Ridge orientation estimation entails a regression problem since the task is to estimate an angle between 0 degrees and 180 degrees for each sub-region in the fingerprint image. However, the majority of the approaches in the literature pivot towards framing this regression task as a classification problem. This paper systematically analyzes the regression via classification methodology for fingerprint orientation estimation, exploring various discretization and encoding strategies. Specifically, we examine single and multiple discretization schemes designed to ensure that resulting bins maintain uniform length or uniform probability or are allocated randomly, paired with one-hot, ordinal, and cyclic encoding techniques. Our experiments are conducted on the FOE-TEST database from FVC-onGoing, the sole publicly available fingerprint orientation dataset. The findings highlight the efficacy of cyclic encoding over the one-hot encoding prevalent in prior research, while equal-length and equal-probability discretization strategies yield comparable results.Article Citation - WoS: 4Citation - Scopus: 3An Investigation of Rna Methylations With Biophysical Approaches in a Cervical Cancer Cell Model(Mdpi, 2024) Saglam, Buket; Akkus, Onur; Akcaoz-Alasar, Azime; Ceylan, Cagatay; Guler, Gunnur; Akgul, BunyaminRNA methylation adds a second layer of genetic information that dictates the post-transcriptional fate of RNAs. Although various methods exist that enable the analysis of RNA methylation in a site-specific or transcriptome-wide manner, whether biophysical approaches can be employed to such analyses is unexplored. In this study, Fourier-transform infrared (FT-IR) and circular dichroism (CD) spectroscopy are employed to examine the methylation status of both synthetic and cellular RNAs. The results show that FT-IR spectroscopy is perfectly capable of quantitatively distinguishing synthetic m(6)A-methylated RNAs from un-methylated ones. Subsequently, FT-IR spectroscopy is successfully employed to assess the changes in the extent of total RNA methylation upon the knockdown of the m(6)A writer, METTL3, in HeLa cells. In addition, the same approach is shown to accurately detect reduction in total RNA methylation upon the treatment of HeLa cells with tumor necrosis factor alpha (TNF-alpha). It is also demonstrated that m(1)A and m(6)A methylation induce quite a distinct secondary structure on RNAs, as evident from CD spectra. These results strongly suggest that both FT-IR and CD spectroscopy methods can be exploited to uncover biophysical properties impinged on RNAs by methyl moieties, providing a fast, convenient and cheap alternative to the existing methods.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: 1Citation - Scopus: 1Application of a Size Measurement Standard for Data Warehouse Projects(Wiley, 2024) Unlu, Hueseyin; Yueruem, Ozan Rasit; Yildiz, Ali; Demirors, OnurMethodologyIn this research, we conducted a case study to establish a foundation for size measurement and effort estimation in DWH projects. We first applied a productivity-based estimation approach using linear regression with the ISBSG repository to assist organizations without historical data. We then evaluated various machine learning algorithms to improve estimation accuracy. Finally, we tested a combined model that integrates both approaches for estimating effort in external projects.ResultsUsing the ISBSG dataset, linear regression models based on productivity achieved a Mean Magnitude of Relative Error (MMRE) of 0.285. Machine learning algorithms improved accuracy by 22.81%, reducing the MMRE to 0.220. The final model, applied to external projects, yielded MRE values between 0.010 and 0.245.ConclusionThe ISBSG repository is a valuable resource for effort estimation in DWH projects. Combining productivity-based estimation with machine learning enhances accuracy and predictive performance, making it a more reliable approach than traditional models.