PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Article The Effect of Video Modeling on Gymnastics-Based Motor Skills in Children with Autism Spectrum Disorder(MDPI, 2026) Bozdag, Berkan; Sonmez, Huseyin Gazi; Turan, Ebru; Aldhahi, Monira I.; Kilinc, Omer; Ergin, Murat; Kocak, Calik VeliBackground and Objectives: While the effectiveness of video modeling (VM) in teaching academic, daily living, and social skills to individuals with Autism Spectrum Disorder (ASD) is frequently investigated, studies examining the use of VM in teaching gymnastics-based motor skills are limited. This study aimed to examine the effects of VM on the acquisition and maintenance of a gymnastics-based motor skills in preschool children with ASD. Methods: The study employed a multiple-probe method across participants in a single-subject research design. Three preschool children diagnosed with mild ASD participated in this study. Baseline, intervention, and follow-up data were systematically collected and analyzed. Social validity data were obtained through semi-structured interviews with parents and special education teachers. Results: The percentage of correct responses increased throughout the VM intervention sessions, and all participants reached the proficiency criterion. Follow-up data collected after the intervention showed that the acquired skill was maintained, and the percentages of correct responses ranged from 80% to 100%. Social validity findings revealed that both teachers and parents perceived VM as an effective and feasible teaching approach for teaching motor skills to children with ASD. Conclusions: The research findings demonstrate that VM is an effective and socially valid teaching method for teaching and maintaining gymnastics-based motor skills in preschool children with ASD. These results contribute to the existing literature by demonstrating the applicability of video modeling in the context of gymnastics-based training.Article Performance Evaluation of Multi-Modal Radar Signal Processing in Dense Co-Existent Environments(MDPI, 2026) Norouzian, Fatemeh; Bekar, Muge; Bekar, Ali; Gashinova, Marina; Pirkani, AnumThe wide-scale deployment of radars, distributed across a platform and across multiple platforms for reliable 360 degrees situational awareness (SA), introduces the challenge of radar interference. Interference can broadly be categorised as self-interference (between radars mounted on the same platform) and mutual interference (signals received from radars on other platforms). Both types of interference impede the reliability of SA delivered by such systems, particularly in dense environments where numerous radars operate simultaneously within the same frequency band. This work presents a comprehensive evaluation of a multi-modal beamforming approach that combines unfocused synthetic aperture radar with the traditional Multiple-Input, Multiple-Output beamformer to enhance radar resolution and suppress interference. Additionally, various aspects of sensor configurations defining hardware and software capabilities of state-of-the-art radars are discussed, and a systematic analysis of signal-to-interference-plus-noise ratio at each step of the processing is presented. Extensive simulations and experimental results in both automotive and maritime environments are shown to validate the effectiveness of the proposed approach.Article Raster Orientation Effects on the Adhesion of iCVD-Deposited PSA Thin Films on FDM-Printed PLA(MDPI, 2026-01-30) Yilmaz, Kurtulus; Gursoy, Mehmet; Gunes, Aydin; Karaman, MustafaThe adhesion performance of pressure-sensitive adhesive (PSA) thin films on additively manufactured polymers is strongly governed by surface anisotropy induced during printing. In this study, PSA thin films based on 2-ethylhexyl acrylate (EHA) and acrylic acid (AA) were deposited by initiated chemical vapor deposition (iCVD) onto fused deposition modeling (FDM) printed PLA substrates with different raster orientations (0 degrees, 30 degrees, 60 degrees, and 90 degrees). The deposited films exhibited high optical transparency on glass, and thicknesses consistent with the targeted deposition. Adhesion performance was evaluated using tensile and three-point bending tests, revealing a strong dependence on raster orientation. The 0 degrees raster orientation yielded the highest shear adhesion strengths, reaching 12.03 N/cm2 under tensile loading and 4.59 N/cm2 under bending, along with the largest failure displacements. In contrast, specimens printed at 90 degrees exhibited an approximately 47% reduction in tensile shear adhesion strength and limited deformation prior to failure. SEM analysis showed that raster alignment parallel to the loading direction promoted extensive adhesive deformation and PSA fibrillation, whereas higher raster angles resulted in predominantly interfacial debonding. These results demonstrate that raster orientation is a critical design parameter for tuning PSA adhesion on FDM-printed PLA substrates without modifying adhesive chemistry.Editorial Advances in Natural Building and Construction Materials(MDPI, 2025-12-16) Strzalkowski, Pawel; Sousa, Luis; Koken, Ekin; Strzałkowski, PawełArticle Burg-Aided 2D MIMO Array Extrapolation for Improved Spatial Resolution(MDPI, 2025-10-12) Bekar, Muge; Bekar, Ali; Pirkani, Anum; Baker, Christopher John; Gashinova, MarinaIn this paper, the extrapolation of a 2D multiple-input multiple-output (MIMO) array is proposed using the Burg algorithm to achieve higher angular resolution beyond that of the corresponding 2D MIMO virtual array. The main advantage of such an approach is that it allows us to dramatically decrease both the physical size and the number of antenna elements of the MIMO array. The performance and limitations of the Burg algorithm are examined through both simulation and experimentation at 77 GHz. The experimental methodology used to acquire 3D data of range, azimuth and elevation information with the 1D MIMO off-the-shelf radar is described. Using this method, the performance of the proposed array can be tested experimentally, especially at frequencies where it is desired to assess the antenna response prior to fabricating the antenna.Article Role of Long Non-Coding RNA X-Inactive Transcript (XIST) in Neuroinflammation and Myelination: Insights From Cerebral Organoids and Implications for Multiple Sclerosis(MDPI, 2025-04-29) Pepe, Nihan Aktas; Acar, Busra; Zararsiz, Gozde Erturk; Guner, Serife Ayaz; Sen, Alaattin; Erturk Zararsiz, Gozde; Ayaz Guner, Serife; Aktas Pepe, NihanBackground/Objectives: X-inactive-specific transcript (XIST) is a factor that plays a role in neuroinflammation. This study investigated the role of XIST in neuronal development, neuroinflammation, myelination, and therapeutic responses within cerebral organoids in the context of Multiple Sclerosis (MS) pathogenesis. Methods: Human cerebral organoids with oligodendrocytes were produced from XIST-silenced H9 cells, and the mature organoids were subsequently treated with either FTY720 or DMF. Gene expression related to inflammation and myelination was subsequently analyzed via qRT-PCR. Immunofluorescence staining was used to assess the expression of proteins related to inflammation, myelination, and neuronal differentiation. Alpha-synuclein protein levels were also checked via ELISA. Finally, transcriptome analysis was conducted on the organoid samples. Results: XIST-silenced organoids presented a 2-fold increase in the expression of neuronal stem cells, excitatory neurons, microglia, and mature oligodendrocyte markers. In addition, XIST silencing increased IL-10 mRNA expression by 2-fold and MBP and PLP1 expression by 2.3- and 0.6-fold, respectively. Although XIST silencing tripled IBA1 protein expression, it did not affect organoid MBP expression. FTY720, but not DMF, distinguished MBP and IBA1 expression in XIST-silenced organoids. Furthermore, XIST silencing reduced the concentration of alpha-synuclein from 300 to 100 pg/mL, confirming its anti-inflammatory role. Transcriptomic and gene enrichment analyses revealed that the differentially expressed genes are involved in neural development and immune processes, suggesting the role of XIST in neuroinflammation. The silencing of XIST modified the expression of genes associated with inflammation, myelination, and neuronal growth in cerebral organoids, indicating a potential involvement in the pathogenesis of MS. Conclusions: XIST may contribute to the MS pathogenesis as well as neuroinflammatory diseases such as and Alzheimer's and Parkinson's diseases and may be a promising therapeutic target.Article Citation - WoS: 4Citation - Scopus: 4Evaluation of Selected Plant Phenolics Via Beta-Secretase Inhibition, Molecular Docking, and Gene Expression Related to Alzheimer's Disease(MDPI, 2024-10-28) Akyurek, Tugba Ucar; Orhan, Ilkay Erdogan; Deniz, F. Sezer Senol; Eren, Gokcen; Acar, Busra; Sen, Alaattin; Şenol Deniz, F. Sezer; Uçar Akyürek, TugbaBackground: The goal of the current study was to investigate the inhibitory activity of six phenolic compounds, i.e., rosmarinic acid, gallic acid, oleuropein, epigallocatechin gallate (EGCG), 3-hydroxytyrosol, and quercetin, against beta-site amyloid precursor protein cleaving enzyme-1 (BACE1), also known as beta-secretase or memapsin 2, which is implicated in the pathogenesis of Alzheimer's disease (AD). Methods and Results: The inhibitory potential against BACE1, molecular docking simulations, as well as neurotoxicity and the effect on the AD-related gene expression of the selected phenolics were tested. BACE1 inhibitory activity was carried out using the ELISA microplate assay via fluorescence resonance energy transfer (FRET) technology. Molecular docking experiments were performed in the human BACE1 active site (PDB code: 2WJO). Neurotoxicity of the compounds was carried out in SH-SY5Y, a human neuroblastoma cell line, by the Alamar Blue method. A gene expression analysis of the compounds on fourteen genes linked to AD was conducted using the real-time polymerase chain reaction (RT-PCR) method. Rosmarinic acid, EGCG, oleuropein, and quercetin (also used as the reference) were able to inhibit BACE1 with their respective IC50 values 4.06 +/- 0.68, 1.62 +/- 0.12, 9.87 +/- 1.01, and 3.16 +/- 0.30 mM. The inhibitory compounds were observed to occupy the non-catalytic site of the BACE1. However, hydrogen bonds were found to be present between rosmarinic acid and EGCG and aspartic amino acid D228 in the catalytic site. Oleuropein and quercetin effectively suppressed the expression of PSEN, APOE, and CLU, which are recognized to be linked to the pathogenesis of AD. Conclusions: The outcomes of the work bring quercetin, EGCG, and rosmarinic acid to the forefront as promising BACE1 inhibitors.Article Citation - WoS: 2Citation - Scopus: 4Deep-Learning AI-Model for Predicting Dental Plaque in the Young Permanent Teeth of Children Aged 8-13 Years(MDPI, 2025-04-07) Tez, Banu Cicek; Guzel, Yasin; Eliacik, Bahar Basak Kiziltan; Aydin, Zafer; Kızıltan Eliaçık, Bahar BaşakBackground/Objectives: Dental plaque is a significant contributor to various prevalent oral health conditions, including caries, gingivitis, and periodontitis. Consequently, its detection and management are of paramount importance for maintaining oral health. Manual plaque assessment is time-consuming, error-prone, and particularly challenging in uncooperative pediatric patients. These limitations have encouraged researchers to seek faster, more reliable methods. Accordingly, this study aims to develop a deep learning model for detecting and segmenting plaque in young permanent teeth and to evaluate its diagnostic precision. Methods: The dataset comprises 506 dental images from 31 patients aged between 8 and 13 years. Six state-of-the-art models were trained and evaluated using this dataset. The U-Net Transformer model, which yielded the best performance, was further compared against three experienced pediatric dentists for clinical feasibility using 35 randomly selected images from the test set. The clinical trial was registered on under the ID NCT06603233 (1 June 2023). Results: The Intersection over Union (IoU) score of the U-Net Transformer on the test set was measured as 0.7845, and the p-values obtained from the three t-tests conducted for comparison with dentists were found to be below 0.05. Compared with three experienced pediatric dentists, the deep learning model exhibited clinically superior performance in the detection and segmentation of dental plaque in young permanent teeth. Conclusions: This finding highlights the potential of AI-driven technologies in enhancing the accuracy and reliability of dental plaque detection and segmentation in pediatric dentistry.Article Citation - WoS: 2Citation - Scopus: 2Context-Aware Beam Selection for IRS-Assisted Mmwave V2I Communications(MDPI, 2025-06-24) Suarez del Valle, Ricardo; Kose, Abdulkadir; Lee, HaeyoungMillimeter wave (mmWave) technology, with its ultra-high bandwidth and low latency, holds significant promise for vehicle-to-everything (V2X) communications. However, it faces challenges such as high propagation losses and limited coverage in dense urban vehicular environments. Intelligent Reflecting Surfaces (IRSs) help address these issues by enhancing mmWave signal paths around obstacles, thereby maintaining reliable communication. This paper introduces a novel Contextual Multi-Armed Bandit (C-MAB) algorithm designed to dynamically adapt beam and IRS selections based on real-time environmental context. Simulation results demonstrate that the proposed C-MAB approach significantly improves link stability, doubling average beam sojourn times compared to traditional SNR-based strategies and standard MAB methods, and achieving gains of up to four times the performance in scenarios with IRS assistance. This approach enables optimized resource allocation and significantly improves coverage, data rate, and resource utilization compared to conventional methods.