WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Depositional Model, Cyclicity, and Hydrocarbon Potential of the Eocene Sakesar Carbonate Ramp, Salt Range, Pakistan(Springer, 2026-02-02) Shah, Syed Bilawal Ali; Shah, Syed Haider AliThe Sakesar Formation in the Salt Range, Pakistan, represents a well-developed Eocene carbonate ramp deposited along the southern Tethyan margin. This study integrates petrographic analysis, palynofacies evaluation, organic geochemical measurements and sequence stratigraphic interpretation to characterise the depositional environments, diagenetic evolution, and petroleum system potential of the formation. Six microfacies (MF1-MF6) were identified through thin-section petrography ranging from high-energy shoal grainstones to low-energy lagoonal marls. Quantitative palynofacies analysis shows energy dependent trends in organic matter composition, with shoal facies dominated by opaque phytoclasts and lagoonal facies enriched in amorphous organic matter (AOM). Organic geochemical measurements including Total Organic Carbon (TOC), Hydrogen Index (HI), Oxygen Index (OI), and Rock-Eval pyrolysis parameters, combined with vitrinite reflectance (Ro) data, indicate that lagoonal marl-micrite facies (MF6) contain Type II kerogen with the highest TOC values (2.80%), elevated HI (293 mg hydrocarbons per gram TOC), and peak oil-window maturity (0.72% Ro). These attributes identify MF6 as the primary oil-prone source rock. Mid-ramp wackestones and packstones (MF3-MF4) possess moderate generative potential and serve as internal seals or baffles, whereas high-energy shoal facies (MF1-MF2) show favourable reservoir characteristics but limited source potential. Sequence-stratigraphic analysis demonstrates that maximum flooding surfaces (MFS) frequently coincide with organic-rich MF6 intervals, producing predictable vertical stacking of source, seal, and reservoir units at parasequence scale. The integrated petrographic, palynofacies, and geochemical framework confirms the dual role of the Sakesar Formation as both a reservoir and a source-seal interval, with metre-scale cyclicity enhancing hydrocarbon charge and trapping efficiency. These findings refine the depositional and petroleum system model of the Sakesar carbonate ramp and provide valuable predictive analogues for Eocene carbonate exploration within the Himalayan foreland basin and related Tethyan settings.Article Boundaries of Belonging: the Spatial and Social Logic of Being Yilli People in Kayseri(Sage Publications Inc, 2025-11-26) Mus Ozmen, Nihan; Asiliskender, Burak; Ozmen, ZehniThis study explores the spatial, social, and cultural dynamics of being yilli, a deeply rooted local identity in Kayseri, Turkey. Drawing on ethnographic fieldwork, oral histories, and spatial analysis, it examines how the yilli people negotiate urban transformation through selective adaptations to modernization while maintaining traditional social boundaries. The research shows that the yilli do not passively resist change but actively reinterpret modernization to reinforce status, kinship, and symbolic belonging. Spatial relocation and investment patterns reflect economic strategies and efforts to preserve cultural distinction amid urban expansion. The findings demonstrate that urban transformation in Kayseri is both a material and cultural process, shaped by layered histories of memory, hierarchy, and social imagination. Through the case of the yilli, the study contributes to broader debates in urban sociology and cultural geography, offering insights into how culture-centered societies adapt to and reshape modernization processes.Article Citation - WoS: 26Citation - Scopus: 31miRcorrNet: Machine Learning-Based Integration of miRNA and mRNA Expression Profiles, Combined with Feature Grouping and Ranking(PeerJ Inc., 2021-05-19) Yousef, M.; Göy, G.; Mitra, R.; Eischen, C.M.; Jabeer, A.; Bakir-Güngör, B.A better understanding of disease development and progression mechanisms at the molecular level is critical both for the diagnosis of a disease and for the development of therapeutic approaches. The advancements in high throughput technologies allowed to generate mRNA and microRNA (miRNA) expression profiles; and the integrative analysis of these profiles allowed to uncover the functional effects of RNA expression in complex diseases, such as cancer. Several researches attempt to integrate miRNA and mRNA expression profiles using statistical methods such as Pearson correlation, and then combine it with enrichment analysis. In this study, we developed a novel tool called miRcorrNet, which performs machine learning-based integration to analyze miRNA and mRNA gene expression profiles. miRcorrNet groups mRNAs based on their correlation to miRNA expression levels and hence it generates groups of target genes associated with each miRNA. Then, these groups are subject to a rank function for classification. We have evaluated our tool using miRNA and mRNA expression profiling data downloaded from The Cancer Genome Atlas (TCGA), and performed comparative evaluation with existing tools. In our experiments we show that miRcorrNet performs as good as other tools in terms of accuracy (reaching more than 95% AUC value). Additionally, miRcorrNet includes ranking steps to separate two classes, namely case and control, which is not available in other tools. We have also evaluated the performance of miRcorrNet using a completely independent dataset. Moreover, we conducted a comprehensive literature search to explore the biological functions of the identified miRNAs. We have validated our significantly identified miRNA groups against known databases, which yielded about 90% accuracy. Our results suggest that miRcorrNet is able to accurately prioritize pan-cancer regulating high-confidence miRNAs. miRcorrNet tool and all other supplementary files are available at https://github.com/ malikyousef/miRcorrNet. © 2021 Elsevier B.V., All rights reserved.Article Citation - WoS: 2Citation - Scopus: 7Triple Positive Solutions for M-Point Boundary-Value Problems of Dynamic Equations on Time Scales With P-Laplacian(Texas State Univ, 2015) Dogan, AbdulkadirIn this article we study the existence of positive solutions for m-point dynamic equation on time scales with p-Laplacian. We prove that the boundary-value problem has at least three positive solutions by applying the five functionals fixed-point theorem. An example demonstrates the main results.Article Citation - WoS: 2Citation - Scopus: 2Transparent Colloidal Crystals With Structural Colours(Frontiers Media S.A., 2022-03-07) Erdem, Talha; O'Neill, Thomas; Zupkauskas, Mykolas; Caciagli, Alessio; Xu, Peicheng; Lan, Yang; Eiser, Erika; O’Neill, ThomasSpatially ordered arrangements of spherical colloids are known to exhibit structural colours. The intensity and brilliance of these structural colours typically improve with colloidal monodispersity, low concentrations of point and line defects and with increasing refractive index contrast between the colloids and the embedding medium. Here we show that suspensions of charge stabilised, fluorinated latex particles with low refractive-index contrast to their aqueous background form Wigner crystals with FCC symmetry for volume fractions between 13 and 40%. In reflection they exhibit both strong, almost angle-independent structural colours and sharp, more brilliant Bragg peaks despite the particle polydispersity and bimodal distribution. Simultaneously, these suspensions appear transparent in transmission. Furthermore, binary AB, A(2)B and A(13)B type mixtures of these fluorinated and similarly sized polystyrene particles appeared predominantly white but with clear Bragg peaks indicating a CsCl-like BCC structure and more complex crystals. We characterised the suspensions using a combination of reflectivity measurements and small-angle x-ray scattering, complemented by reflectivity modelling.Article Topological Feature Generation for Link Prediction in Biological Networks(PeerJ Inc, 2023-05-09) Temiz, Mustafa; Bakir-Gungor, Burcu; Sahan, Pinar Guner; Coskun, Mustafa; Güner Şahan, PınarGraph or network embedding is a powerful method for extracting missing or potential information from interactions between nodes in biological networks. Graph embedding methods learn representations of nodes and interactions in a graph with low-dimensional vectors, which facilitates research to predict potential interactions in networks. However, most graph embedding methods suffer from high computational costs in the form of high computational complexity of the embedding methods and learning times of the classifier, as well as the high dimensionality of complex biological networks. To address these challenges, in this study, we use the Chopper algorithm as an alternative approach to graph embedding, which accelerates the iterative processes and thus reduces the running time of the iterative algorithms for three different (nervous system, blood, heart) undirected protein-protein interaction (PPI) networks. Due to the high dimensionality of the matrix obtained after the embedding process, the data are transformed into a smaller representation by applying feature regularization techniques. We evaluated the performance of the proposed method by comparing it with state-of-the-art methods. Extensive experiments demonstrate that the proposed approach reduces the learning time of the classifier and performs better in link prediction. We have also shown that the proposed embedding method is faster than state-of-the-art methods on three different PPI datasets.Article Citation - WoS: 9Citation - Scopus: 13The Impact and Future of Artificial Intelligence in Medical Genetics and Molecular Medicine: An Ongoing Revolution(Springer Heidelberg, 2024-08) Ozcelik, Firat; Dundar, Mehmet Sait; Yildirim, A. Baki; Henehan, Gary; Vicente, Oscar; Sanchez-Alcazar, Jose A.; Dundar, MunisArtificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.Article Tapered Curved-Beam Hinges for Electret-Based Vibration Energy Harvesting Devices(IOP Publishing Ltd, 2024-12-01) Hah, DooyoungInterest in vibration energy harvesting have been growing recently for various applications. One of the major development goals for vibration energy harvesters has been improvement in energy conversion efficiency. To pursue that goal, one of the main approaches has been to broaden the spectra of harvesters. Employment of nonlinear springs, such as curved-beam hinges, has proven to be effective for that purpose. The main contribution of the current study is to introduce a lateral taper to the curved beam so as to further optimize the harvester performances. Via numerical analysis by using stochastic differential equations, the study shows that at 0.05g of vibration strength, tapered curved-beam hinges can result in higher electric power output than the non-tapered ones. Deformation-induced stress was taken into consideration as well, in reference to the fracture strength of the material (single-crystal silicon). At lower vibration strength (0.02g), spring nonlinearity becomes weaker, and as a result, the narrowest curved-beam hinge produces the highest output power. Overall, the current study demonstrates that tapering of the curved beam can be a useful addition in the vibration energy harvester design.Article Citation - WoS: 54Citation - Scopus: 61Synthesis, Cytotoxic and Antimicrobial Activities of Novel Cobalt and ZINC Complexes of Benzimidazole Derivatives(Elsevier Science SA, 2017-01) Apohan, Elif; Yilmaz, Ulku; Yilmaz, Ozgur; Serindag, Ayfer; Kucukbay, Hasan; Yesilada, Ozfer; Baran, YusufIn this study fourteen novel cobalt (II) or zinc (II) complexes of benzimidazoles were synthesized from the 1-(4-substitutedbenzyl)-1H-benzimidazoles and CoCl2.6H(2)O or ZnCl2. Cytotoxic activities of novel complexes were investigated against lung cancer cells (A549) and BEAS-2B. Three of the examined compounds (1, 4 and 5) showed high cytotoxic activity against A549. While the IC50 of the cisplatin was 2.56 pg/mL for A549 cells at 72 h, the IC50 values of compounds 1, 4 and 5 were 1.97, 1.87 and 1.9 mu g/mL, respectively. IC50 values of these compounds for BEAS-2B cells were higher than the IC50 values for A549. While the IC50 values for BEAS-2B cells were 59.8, 24.5 and 32.67 mu g/mL, respectively, the IC50 of the cisplatin was determined as 2.53 pgimL in the present work. Three of the compounds have also high antimicrobial activity against all the microorganisms used. (C) 2016 Elsevier B.V. All rights reserved.Article Square Root Computation in Finite Fields(Springer, 2024-03-12) Adiguzel-Goktas, Ebru; Ozdemir, EnverIn this paper, we present a review of three widely-used practical square root algorithms. We then describe a unifying framework where each of these well-known algorithms can be seen as a special case of it. The framework with singular curves offers a broad perspective to compare and further improve the existing methods in addition to offering a new avenue for square root computation algorithms in finite fields.