Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Dimensionality Effects in Anisotropic Single Layers TiSe5 and TiTe5: a Comparative Study of 2D Sheets and 1D Nanochains(IOP Publishing Ltd, 2026) Can Dogan, Kadir; Kutay Tamdogan, Omer; Bozkurt, Yagmur; Cetin, Zebih; Yagmurcukardes, MehmetIn this study, we present a comprehensive first-principles investigation of the structural, vibrational, and electronic properties of titanium pentachalcogenide structures in both two-dimensional (2D) and one-dimensional (1D) nanochain (NC) forms. Total energy and geometry optimizations reveal that the 2D TiX5 (X = Se, Te) structures exhibit in-plane anisotropy arising from the trigonal prismatic TiX3 units interconnected via the chalcogenide chains. Phonon band dispersions and elastic tensor elements confirm the dynamical and mechanical stability of the 2D layers, respectively. Electronically, while TiTe5 is a metal, TiSe5 possesses direct band gap semiconducting behavior. In addition, free-standing 1D NC counterparts, which are sub-units of the 2D structures, are investigated by means of their stability. Three stable 1D NCs, namely TiTe5-NC, TiSe7-NC, and TiTe7-NC, are found to be composed of edge-sharing TiX6-like units with either five- or seven-fold coordination. The dynamically stable 1D NCs are shown to be semiconductors with relatively larger band gaps as compared to 2D layers. Predicted Raman spectra reveal clear signatures of vibrational mode evaluations as a result of quantum confinement from the 2D layer to the 1D NC. Moreover, finite-temperature ab-initio quantum molecular dynamics simulations at 300 K confirm the thermal stability of both the 2D TiX5 layers and 1D NC derivatives, showing that the Ti-based systems retain their structural integrity under ambient conditions and are feasible candidates for experimental synthesis. Our findings highlight the formation of stable semiconducting 1D NCs of Ti-pentachalcogenides from their 2D counterparts.Article Developing Gold Nanoparticles Decorated With Carbon-Dots for Multiplexed Cellular Imaging(IOP Publishing Ltd, 2025) Kavuranpala, Tugce; Saydullaeva, Iroda; Ozcelik, SerdarThis study focuses on developing a novel hybrid nanomaterial composed of gold nanoparticle decorated with carbon dots, termed AuNP@C-dot, as a versatile platform for multiplexed imaging. Structural and spectral characterizations confirmed the successful conjugation of C-dots to AuNPs via covalent bonding, as evidenced by FTIR, X-ray photoelectron spectra, HRTEM analyses, and UV-Vis and fluorescence spectroscopies. The fluorescence intensities of C-dots are doubled through the conjugation to the AuNPs. The conjugation of fluorescent C-dots to plasmon-resonant AuNPs enables simultaneous multicellular imaging by taking advantage of the fluorescent signaling of C-dots and the scattering signaling of AuNPs. In vitro studies using human lung cell lines (A549 and BEAS-2B) confirmed the multiplexed imaging and revealed efficient cellular uptake and subcellular localization of AuNP@C-dots, including nuclear translocation, which is critical for radiotherapy and photodynamic therapy. Cell viability assessments utilizing a colorimetric assay for measuring cell metabolic activity and a colony formation assay demonstrated good biocompatibility of AuNP@C-dots at relevant concentrations. It can be envisioned that the AuNP@C-dot hybrid system may improve the detection and monitoring of cell health and disease due to its dual-modal imaging capability. Furthermore, they could be used for supervising controlled release of therapeutic agents, tailored for enhanced treatment efficacy. This study demonstrates the potential of C-dot-conjugated AuNPs as a multifunctional tool with inherent control mechanisms for the next-generation cellular analysis, drug administration, and diagnostic strategies.Article Vision-Language Model Approach for Few-Shot Learning of Attention Deficit Hyperactivity Disorder Using EEG Connectivity-Based Featured Images(IOP Publishing Ltd, 2025) Catal, Mehmet Sergen; Gumus, Abdurrahman; Karabiber Cura, Ozlem; Aydin, Ocan; Zubeyir Unlu, MehmetTraditional medical diagnosis approaches have predominantly relied on single-modality analysis, limiting clinicians to interpreting isolated data streams such as images or time series. The integration of vision language models (VLMs) into neurophysiological analysis represents a paradigm shift toward multimodal diagnostic frameworks, enabling clinicians to interact with diagnosis models through diverse modalities including text, audio, visual inputs, etc. This multimodal interaction capability extends beyond conventional label-based classification, offering clinicians flexibility in diagnostic reasoning and decision-making processes. Building on this foundation, this study explores the application of VLMs to electroencephalography (EEG)-based attention deficit hyperactivity disorder (ADHD) classification, addressing a gap in neurophysiological diagnostics. The proposed framework applies VLM-based few-shot ADHD classification by converting raw EEG data into EEG connectivity-based featured images compatible with contrastive language-image pre-training's (CLIP) image encoder. The adaptor-based CLIP approach (Tip-Adapter and Tip-Adapter-F) for few-shot learning improves CLIP's zero-shot classification performance, achieving 78.73% accuracy with 1-shot and 98.30% accuracy with 128-shot using the RN50x16 backbone. Experiments investigate prompt engineering effects, backbone architectures of CLIP, patient-based classification, and combinations of EEG connectivity features. Comparative analysis is performed with two datasets to evaluate the approach between different data sources. Through the adaptation of pre-trained VLMs to neurophysiological data, this technique demonstrates the potential for multimodal diagnostic frameworks that enable flexible clinician-model interactions beyond conventional label-based classification systems. The approach achieves effective ADHD classification with minimal training data while establishing foundations for applying VLMs in clinical neuroscience, where diverse modality interactions through text, visual, and audio inputs can enhance diagnostic workflows. The code is publicly available on GitHub to facilitate further research in the field: https://github.com/miralab-ai/vlm-few-shot-eeg.Article Citation - WoS: 23Citation - Scopus: 26Fish scale containing alginate dialdehyde-gelatin bioink for bone tissue engineering(IOP Publishing Ltd, 2023) Özenler, Aylin Kara; Distler, Thomas; Tıhmınlıoğlu, Funda; Boccaccini, Aldo RThe development of biomaterial inks suitable for biofabrication and mimicking the physicochemical properties of the extracellular matrix is essential for the application of bioprinting technology in tissue engineering (TE). The use of animal-derived proteinous materials, such as jellyfish collagen, or fish scale (FS) gelatin (GEL), has become an important pillar in biomaterial ink design to increase the bioactivity of hydrogels. However, besides the extraction of proteinous structures, the use of structurally intact FS as an additive could increase biocompatibility and bioactivity of hydrogels due to its organic (collagen) and inorganic (hydroxyapatite) contents, while simultaneously enhancing mechanical strength in three-dimensional (3D) printing applications. To test this hypothesis, we present here a composite biomaterial ink composed of FS and alginate dialdehyde (ADA)-GEL for 3D bioprinting applications. We fabricate 3D cell-laden hydrogels using mouse pre-osteoblast MC3T3-E1 cells. We evaluate the physicochemical and mechanical properties of FS incorporated ADA-GEL biomaterial inks as well as the bioactivity and cytocompatibility of cell-laden hydrogels. Due to the distinctive collagen orientation of the FS, the compressive strength of the hydrogels significantly increased with increasing FS particle content. Addition of FS also provided a tool to tune hydrogel stiffness. FS particles were homogeneously incorporated into the hydrogels. Particle-matrix integration was confirmed via scanning electron microscopy. FS incorporation in the ADA-GEL matrix increased the osteogenic differentiation of MC3T3-E1 cells in comparison to pristine ADA-GEL, as FS incorporation led to increased ALP activity and osteocalcin secretion of MC3T3-E1 cells. Due to the significantly increased stiffness and supported osteoinductivity of the hydrogels, FS structure as a natural collagen and hydroxyapatite source contributed to the biomaterial ink properties for bone engineering applications. Our findings indicate that ADA-GEL/FS represents a new biomaterial ink formulation with great potential for 3D bioprinting, and FS is confirmed as a promising additive for bone TE applications.Article Citation - WoS: 19Citation - Scopus: 15A New Calibration Method for Charm Jet Identification Validated With Proton-Proton Collision Events at Root S=13 Tev(IOP Publishing Ltd, 2022) Tumasyan, A.; Karapınar, GülerMany measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb(-1) at root s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.Article Citation - WoS: 5Citation - Scopus: 32Performance of the Cms Muon Trigger System in Proton-Proton Collisions at ?s = 13 Tev(IOP Publishing Ltd, 2021) CMS Collaboration; Karapınar, GülerThe muon trigger system of the CMS experiment uses a combination of hardware and software to identify events containing a muon. During Run 2 (covering 2015-2018) the LHC achieved instantaneous luminosities as high as 2 × 10 cm s while delivering proton-proton collisions at ?s = 13 TeV. The challenge for the trigger system of the CMS experiment is to reduce the registered event rate from about 40 MHz to about 1 kHz. Significant improvements important for the success of the CMS physics program have been made to the muon trigger system via improved muon reconstruction and identification algorithms since the end of Run 1 and throughout the Run 2 data-taking period. The new algorithms maintain the acceptance of the muon triggers at the same or even lower rate throughout the data-taking period despite the increasing number of additional proton-proton interactions in each LHC bunch crossing. In this paper, the algorithms used in 2015 and 2016 and their improvements throughout 2017 and 2018 are described. Measurements of the CMS muon trigger performance for this data-taking period are presented, including efficiencies, transverse momentum resolution, trigger rates, and the purity of the selected muon sample. This paper focuses on the single- and double-muon triggers with the lowest sustainable transverse momentum thresholds used by CMS. The efficiency is measured in a transverse momentum range from 8 to several hundred GeV. © 2021 CERN for the benefit of the CMS collaboration.