WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Novel Statistical Approaches for Survival Analysis of RNA-Sequencing Data(Bentham Science Publ Ltd, 2026) Cephe, Ahu; Karabulut, Erdem; Zararsız, Gözde Ertürk; Sezgin, Ahmet; Koçhan, NeclaIntroduction/Objective Accurate patient survival predictions are vital for effective cancer treatments. Precision medicine uses gene expression data to improve prognosis by considering genetic variability. Predicting survival in cancer patients using high-dimensional gene expression data, such as RNA-sequencing (RNA-seq), attracted much attention in recent years. However, the literature contains limited algorithms for survival modeling that account for the high dimensionality, heterogeneity, and correlated genes of RNA-seq data. This study aims to develop novel approaches for predicting survival and identifying biomarkers using RNA-seq data.Introduction/Objective Accurate patient survival predictions are vital for effective cancer treatments. Precision medicine uses gene expression data to improve prognosis by considering genetic variability. Predicting survival in cancer patients using high-dimensional gene expression data, such as RNA-sequencing (RNA-seq), attracted much attention in recent years. However, the literature contains limited algorithms for survival modeling that account for the high dimensionality, heterogeneity, and correlated genes of RNA-seq data. This study aims to develop novel approaches for predicting survival and identifying biomarkers using RNA-seq data.Methods Survival data of RNA-seq is first transformed into binary classification data using a stacking algorithm. Then, block-based priority-Lasso and IPF-Lasso algorithms are applied to the dataset, which includes two distinct types of variables. Additionally, sample weights obtained from the voom transformation are incorporated. Our approaches, named voomStackLasso, are tested on 12 real datasets from the TCGA database. We used Harrell's concordance index and the integrated Brier score to evaluate model performance, and the number of selected features to assess model sparsity.Results The results indicated that the voomStackLasso algorithms demonstrated comparable or superior performance compared to other existing survival algorithms. Furthermore, we have introduced an R package called MLSeqSurv, which allows for the utilization of both established survival algorithms from the literature and voomStackLasso algorithms for RNA-seq data.Conclusion This study introduces two new algorithms for the survival analysis of RNA-seq data. Additionally, this study has led to new research directions for applying both existing and newly developed classification algorithms to the survival analysis of RNA-seq data.Article Citation - WoS: 3Citation - Scopus: 4Rare Earth Elements in the Global Economy: Usage, Recovery, and the Quest for Supply Security – A Review(Springer Heidelberg, 2026) Top, Soner; Ayten, Asim Mustafa; Altiner, Mahmut; Demir, Idris; Kursunoglu, SaitOften described as the vitamins of modern industry, rare earth elements (REEs) are indispensable for the deployment of low-carbon and clean energy technologies. However, ensuring a secure and sustainable REE supply remains a major challenge due to the strong interdependence between application-driven demand, extraction and processing technologies, and the geopolitical concentration of resources. This review adopts an integrated analytical framework in which these three dimensions are treated as interconnected components shaping the resilience of global REE supply chains. First, the major application sectors of REEs are examined to clarify how emerging energy and advanced manufacturing technologies drive demand for specific elements and amplify their strategic importance. Second, extraction and processing technologies are reviewed in relation to both primary and secondary resources, highlighting how technological maturity, process selection, and material characteristics constrain or enable supply expansion. Finally, geopolitical and strategic aspects of the REE supply chain are analyzed to demonstrate how resource concentration, policy instruments, and international dependencies directly influence technological deployment and industrial competitiveness. By explicitly linking application-driven demand, technological pathways for extraction and processing, and geopolitical supply structures within a unified framework, this review provides a coherent understanding of the systemic challenges facing the REE sector and identifies key leverage points for improving the robustness and sustainability of REE supply chains in the context of the global clean energy transition.Article Sensitive Hybrid Plasmonic Refractive Index Sensor Based on Ag Cross-Grating Nanoantenna and Au Quantum Dot upon SiO2 Nanowire(IOP Publishing Ltd, 2026-04-03) Sanli, Atif Kerem; Kilic, Veli Tayfun; Tabaru, Timucin EmreThis study presents a distinctive hybrid plasmonic sensor architecture combining a silver (Ag) cross-shaped nanoantenna with a gold (Au) quantum dot (QD) for enhanced refractive index sensing applications. The structure consists of a silicon dioxide (SiO2) substrate and a cylindrically shaped SiO2 wire on it, topped with a silicon nitride (Si3N4) dielectric layer and an Ag cross grating, with an Au QD positioned at the center. Using free and open source 3D Finite-Difference Time-Domain (FDTD) simulations, exceptional electric field enhancement at the resonant wavelength of approximately 639-667 nm is demonstrated. The optimized structure achieves remarkable quality factors (Q-factors) exceeding 267 for biological media, representing among the highest reported values for plasmonic sensing structures. Unlike conventional red-shift sensors, our design exhibits a distinctive blue-shift sensing behavior arising from hybrid plasmonic mode coupling, achieving sensitivities ranging from 190 to 344 nm RIU-1 for various analytes, including water, blood, PDMS, body fat, ethanol, and glass. The ultrasharp resonances (FWHM similar to 2.3 nm) combined with intense field enhancement make this design highly suitable for biosensing applications.Article Follow-up of Health-Related Physical Fitness Elements in Mild Intellectual Disability for Three Years: A Sex Comparison(PeerJ Inc., 2026-03-04) Bozdağ, Berkan; Sönmez, Hüseyin Gazi; Prieto-González, Pablo; Karahan, Mustafa; Canli, Umut; Ergin, Murat; Koçak, Çalık VeliChildren with mild intellectual disability (MID) have significant limitations in both intellectual functioning and cognitive, social, and motor skill behaviors. Understanding the development of physical fitness in boys and girls with MID, and identifying sex-related differences can help devise interventional programs to improve physical fitness in these groups. The aim of this study was to compare sex differences in the time-dependent changes in health-related physical fitness components in individuals with MID. A longitudinal design was employed over three years. A total of 111 individuals with MID (46 girls and 65 boys) aged between 10 and 14 years (mean age 11.97 +/- 1.39 years) participated in the study. The physical fitness levels of the participants were assessed using the Brockport Physical Fitness Test (BPFT) battery. The tests included body composition (body height, body mass, and body mass index), aerobic endurance (15 m Progressive Aerobic Cardiovascular Endurance Run (PACER) test), and musculoskeletal function (dominant handgrip strength, back-saver sit-and-reach, and trunk lift). The results revealed that, over time, the longitudinal developmental trajectories for body mass, body height, aerobic endurance, and dominant handgrip strength were more favorable for boys. However, the longitudinal development curves for body mass index (BMI), trunk lift, and flexibility were similar for both boys and girls. The findings of this study provide valuable evidence for developing targeted physical activity programs for individuals with MID, and demonstrate the need for programs aimed at increasing aerobic endurance and muscle strength in girls with MID.Article An Adaptation Mechanism of Model Reference Adaptive System Based on Variable Structure Control for Online Parameter Estimation of IPMSM(Wiley, 2026-01) Tekgun, Burak; Barut, Murat; Ates, ErtugrulThis study introduces stator currents-based model reference adaptive system (MRAS) estimators that employ variable structured control (VSC) in the adaptation mechanism to enable the online estimation of stator resistance and permanent magnet (PM) flux in interior permanent magnet synchronous motors (IPMSMs). These MRAS estimators estimate stator resistance and PM flux by analysing the error between the stator currents measured as the reference model and the stator currents generated by the adaptive model. The performance of the proposed estimators is assessed through simulation studies. Furthermore, the proposed approach is compared to a conventional MRAS employing a fixed-gain proportional-integral (PI) controller. Simulation results and error analyses indicate that the VSC-based MRAS algorithms outperform traditional PI-based MRAS in terms of accuracy and reliability. Additionally, the proposed method eliminates the reliance on a fixed-gain PI controller, a common component in conventional MRAS systems.Article Citation - WoS: 2Citation - Scopus: 2Depositional 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: 1Citation - Scopus: 1An Ultra-Low Fabric Capacitive Glove for Real-Time Motion Tracking and Human–computer Interaction(Institute of Physics, 2025-11-04) Başıbüyük, Y.; Mutluç, M.N.; Şavur, Ö.; İçöz, K.This study presents the development of a wearable glove system that integrates ultra-low-cost, fabric-based capacitive sensors for motion detection and human–computer interaction. The system combines touch and bend sensors fabricated from commercially available silver-coated fabric and silicone acrylic tape, enabling real-time tracking of finger movements via measurable capacitance changes. The glove translates physical gestures into digital commands, facilitating intuitive control in virtual environments. Experimental evaluation demonstrated stable operation across a wide pressure range (10–200 g, equivalent to 1.25–25 kPa), with an unnormalized sensitivity of ∼0.00504 pF g−1 (∼0.0040 pF kPa−1), corresponding to a normalized sensitivity of ∼0.0067 kPa−1 when referenced to the baseline capacitance (C<inf>0</inf> ≈ 6 pF). The device exhibited high repeatability over 4000 loading cycles, and minimal signal variation (coefficient of variation, CV < 0.005). Integration with a Unity-based interface enabled low-latency gesture tracking in real time. Each sensor was fabricated for less than $0.05 using simple, scalable methods, without nanomaterials or cleanroom processing. Owing to its affordability, fabrication simplicity, and mechanical robustness, the proposed glove system provides a practical and scalable platform for wearable motion tracking, with strong potential in rehabilitation, assistive technologies, and interactive systems. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.Article Citation - WoS: 27Citation - Scopus: 32miRcorrNet: 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.