WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Influence of Innovative Thawing Approaches on the Thermal and Chemical Structure Changes of Frozen Beef Liver(Springer, 2026) Avsar, Nazlican; Uzuner, SibelFreezing effectively preserves meat quality, but the formation of ice crystals during the process can impact tenderness and functionality. Thawing is a critical step, as it can lead to physicochemical changes-such as protein oxidation and further ice crystal growth-that may reduce product quality and consumer appeal. Therefore, the thawing method plays a key role in determining the final quality of frozen meat. This study evaluated the physicochemical and structural characteristics of beef liver frozen at - 18 +/- 2 degrees C for 20 h and thawed using three methods: water immersion thawing (WIT), ultrasonic bath thawing (UBT), and air fryer thawing (AFT). No significant differences in drip loss were observed among the UBT, AFT, and WIT samples (p > 0.05). Color measurements (L*, a*, b*) were significantly higher in raw liver than in AFT and UBT samples (p < 0.05). Compared to raw liver and the WIT method, AF and UB thawing lowered the denaturation temperature, indicating reduced thermal stability. The lowest metmyoglobin (MetMb) content was found in the UBT sample (36.57 +/- 0.87%), followed by the AFT sample (41.71 +/- 1.29%), suggesting better pigment preservation with UB thawing. Highlights circle AF and UB thawing methods resulted in a lower denaturation temperature. circle UBT showed the lowest MetMb content, helping to minimize oxidation. circle UBT caused less damage to protein chains and better preserved structural stability. circle UBT preserved desirable aroma characteristics more effectively.Article Liposomal Encapsulation of a Synthetic Bromophenol for Antitumor Efficacy and Apoptotic Activity in Cancer Cells(Springer, 2026) Oztanrikulu, Bercem Dilan; Ozdemir, Ekrem; Avci, Bahri; Goksu, Suleyman; Bayrakceken, Handan Uguz; Askin, HakanA novel synthetic bromophenol (BP), inspired by marine-derived natural bromophenols, was evaluated for its antitumor activity and for the enhancement of its in vitro performance through liposomal encapsulation (LipoBP). Etoposide was used as a reference in characterization, release, and loading studies. PEGylated liposomes were employed to improve BP's solubility, bioavailability, and therapeutic potential. The cytotoxicity, apoptosis, and gene expression effects of free BP and LipoBP were assessed in A549 (lung) and MCF-7 (breast) cancer cell lines. WST-8 assays showed that encapsulation significantly increased BP's cytotoxic activity, particularly in A549 cells, while flow cytometry and Annexin V-FITC/PI analyses indicated more pronounced apoptotic induction by LipoBP compared with free BP. qRT-PCR analyses revealed upregulation of proapoptotic genes (BAX, CASP6, CASP3 and CASP9) and downregulation of antiapoptotic/survival genes (BCL-XL, IQSEC2) in both cell lines, indicating activation of intrinsic apoptotic pathways. Plain liposomes exhibited minimal cytotoxicity, confirming their biocompatibility. Liposomal bromophenol, which we have introduced to the literature for the first time, is expected to be a promising nanocarrier system that could be effective in cancer treatment by improving the therapeutic index of new drug candidates such as marine bromophenols.Article Fluid-CO2 Injection in a Hypersaline Volcanic Systems: A Reactive Transport and Experimental Evaluation with Application to the Tuzla Geothermal Field, Turkiye(Springer, 2026) Tonkul, Serhat; Erol, Selcuk; Baba, Alper; Regenspurg, SimonaThis study evaluates the CO2 sequestration capability of the Tuzla Geothermal Field (TGF) in northwest T & uuml;rkiye under reservoir conditions (200 degrees C and 4.4 MPa). While ongoing studies at TGF have investigated CO2 co-injection primarily for geothermal heat extraction, the present study focuses on the associated potential for long-term CO2 storage. To this end, CO2-brine-rock interactions were examined through batch reactor experiments and reaction path modeling using the PhreeqC geochemical tool. The experiments revealed complex dissolution/precipitation reactions that altered reservoir properties, with mineralogical analyses (XRD, XRF, SEM, and EDS) showing the formation of secondary phases such as calcite, kaolinite, and Ca-rich aluminosilicates. These results indicate that the Tuzla reservoir rocks provide sufficient divalent cations to support mineral trapping under reservoir conditions. Overall, our findings highlight that, in addition to its promise for heat extraction, CO2 co-injection at TGF offers an opportunity for permanent geological storage, thereby strengthening the dual benefits of this approach.Correction Automating Software Size Measurement From Python Code Using Language Models (Vol 33, 19, 2026)(Springer, 2025) Tenekeci, Samet; Unlu, Huseyin; Gul, Bedir Arda; Keles, Damla; Kucuk, Murat; Demirors, OnurArticle Reflection on Designing: Metacognitive Interventions to Enhance Metacognitive Awareness, Motivation, and Performance in Design Learning(Springer, 2025) Yazici, Gizem; Dogan, FehmiDesign education involves ill-defined problem-solving that demands both creativity and self-regulation. While metacognitive awareness significantly enhances learning outcomes and motivation, there is limited empirical evidence on how to systematically foster this skill in design studios. This study aims to investigate whether metacognitive interventions increase architecture students' metacognitive awareness levels, academic goal orientations, and design course success. In a quasi-experimental design, 84 third-year architecture students were divided into experimental (n = 58) and control (n = 26) groups. Pre-post-test data were collected using the MAI and AGOQ scales. Three structured interventions were implemented in the experimental group over six weeks. In the students who received the interventions, significant increases were observed in metacognitive awareness, mastery-performance goal orientation, and design course grades. In students with high awareness, mastery orientation, metacognitive awareness, and design course grades increased significantly, while in students with low awareness, metacognitive awareness and performance orientation increased. Pretest MAI and AGOQ scores accounted for 72.8% of the variance in grades, with MAI showing the strongest positive influence. Learning and proving orientations were moderately and positively correlated to grades, while avoidance orientation showed a moderate negative correlation. Metacognitive interventions enhance learning outcomes in design education by supporting metacognition and motivation.Correction Citation - WoS: 11Measurement of Jet Multiplicity Distributions in T(t)over-Bar Production in pp Collisions at √s = 7 TeV (Vol 74, 3014, 2014)(Springer, 2015) Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Woods, N.Article Citation - WoS: 15Search for Supersymmetry in pp Collisions at √s=7 TeV in Events With a Single Lepton, Jets, and Missing Transverse Momentum(Springer, 2013) Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Aguilo, E.; Swanson, J.Results are reported from a search for new physics processes in events containing a single isolated high-transverse-momentum lepton (electron or muon), energetic jets, and large missing transverse momentum. The analysis is based on a 4.98 fb(-1) sample of proton-proton collisions at a center-of-mass energy of 7 TeV, obtained with the CMS detector at the LHC. Three separate background estimation methods, each relying primarily on control samples in the data, are applied to a range of signal regions, providing complementary approaches for estimating the background yields. The observed yields are consistent with the predicted standard model backgrounds. The results are interpreted in terms of limits on the parameter space for the constrained minimal supersymmetric extension of the standard model, as well as on cross sections for simplified models, which provide a generic description of the production and decay of new particles in specific, topology based final states.Article Citation - WoS: 6Citation - Scopus: 7Physics-Based Machine Learning for Modeling of Laminated Composite Plates Based on Refined Zigzag Theory(Springer, 2025) Ermis, Merve; Dorduncu, Mehmet; Aydogan, GokayPhysics-based machine learning techniques have recently gained prominence for their ability to model complex material and structural behavior, particularly in laminated composite structures. This study introduces an innovative approach, being the first to employ physics-informed neural networks (PINNs) in conjunction with refined zigzag theory (RZT) for the stress analysis of laminated composite plates. A multi-objective loss function integrates governing partial differential equations (PDEs) and boundary conditions, embedding physical principles into the analysis. Using multiple fully connected artificial neural networks, called feedforward deep neural networks, tailored to handle PDEs, PINNs are trained using automatic differentiation. This training process minimizes a loss function that incorporates the PDEs governing the underlying physical laws. RZT, particularly suitable for the stress analysis of thick and moderately thick plates, simplifies the formulation by using only seven kinematic variables, eliminating the need for shear correction factors. The capability of the proposed method is validated through several benchmark cases in stress analysis, including 3D elasticity solutions, analytical solutions, and experimental results from a three-point bending test based on displacement measurements reported in the literature. These results show consistent agreement with the referenced solutions, confirming the accuracy and reliability of the proposed method. Comprehensive evaluations are conducted to examine the effects of softcore presence, elastic foundation, various lamination schemes, and differing loading and boundary conditions on the stress distribution in laminated plates.Article Ggnn: Group-Guided Nearest Neighbors for Efficient Image Matching(Springer, 2025) Cine, Ersin; Bastanlar, Yalin; Ozuysal, MustafaThe widely adopted image matching approach remains dependent on exhaustive matching of local features across images. Existing methods aiming to improve efficiency either approximate nearest neighbor (NN) search, compromising accuracy, or apply filtering only after establishing tentative matches, which restricts potential efficiency gains. We challenge the assumption that exhaustive NN search is necessary by proposing a more efficient hierarchical approach that maintains matching accuracy without relying on full-scale NN search. Our key insight is that efficiently identifying sufficiently similar, geometrically meaningful feature matches-rather than the most similar but geometrically random ones-can improve or maintain performance at a lower computational cost. We propose a novel method, Group-Guided Nearest Neighbors (GGNN), which matches groups of features first and then matches individual features only within these matched groups. This hierarchical pipeline reduces the computational complexity of feature matching from \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta (n<^>2)$$\end{document} to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta (n \sqrt{n})$$\end{document}, significantly improving efficiency. Experimental results on homography estimation demonstrate that GGNN outperforms standard NN search while achieving performance comparable to state-of-the-art methods. Additionally, we formulate GGNN as a general framework, where conventional NN search is a special case with a single global feature group. This formulation provides a continuum of feature matching methods with varying computational costs, enabling automatic selection based on a given time budget.Article Citation - WoS: 3Citation - Scopus: 2Cradle-To Life Cycle Assessment of Heavy Machinery Manufacturing: a Case Study in Türkiye(Springer, 2025) Üçtuğ, F.G.; Ediger, V.Ş.; Küçüker, M.A.; Berk, İ.; İnan, A.; Moghadasi Fereidani, B.Purpose: Amidst accelerated industrialization and urbanization, the surge in heavy equipment production, crucial for construction, mining, industry, and transportation, necessitates a comprehensive examination of its environmental implications from a sustainability standpoint. This study aims to scrutinize the environmental impacts of manufacturing forklifts and semi-trailers in Türkiye, employing the life cycle assessment (LCA) methodology. Methods: The life cycle assessment (LCA) methodology is the foundational framework for evaluating the environmental impacts associated with forklift and semi-trailer manufacturing. A cradle-to-gate approach was employed. CCaLC2 software alongside the Ecoinvent 3.0 database and CML LCIA methodology was used. Results: The carbon footprint analysis reveals that the production of a single forklift and semi-trailer generates 10.8 tons CO2eq. and 24.9 tons CO2eq. of emissions, respectively. Considering the mass of the machinery, these figures translate to 2.8 ton CO2eq./ton machinery and 1.57 ton CO2eq/ton machinery for the forklift and semi-trailer, respectively. These results were found to be consistent with values reported for similar (but not identical) heavy machinery. Notably, the predominant share of environmental impact stems from raw material acquisition for both products, with subsequent contributions from various production stages. Steel utilization emerges as the primary contributor to all environmental impact categories, constituting an average contribution of 75%. Noteworthy exceptions include the acidification potential of forklift production, where the incorporation of the engine emerges as the primary hotspot with a significant 38% contribution. Conclusions: The findings present the environmental footprint associated with forklift and semi-trailer manufacturing, emphasizing the pivotal role of raw material acquisition, particularly steel utilization. Insights derived from this environmental impact assessment provide invaluable guidance for enhancing environmental sustainability. Decision-makers and industry stakeholders can leverage these conclusions to implement targeted measures, such as exploring alternative materials or refining production processes, to mitigate the environmental consequences of resource-intensive heavy equipment manufacturing, aligning with broader sustainability objectives. © The Author(s) 2025.