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Yayın Prisoners’ dilemma in a spatially separated system based on spin–photon interactions(MDPI, 2022-09) Altıntaş, Azmi Ali; Özaydın, Fatih; Bayındır, Cihan; Bayrakçı, VeyselHaving access to ideal quantum mechanical resources, the prisoners’ dilemma can be ceased. Here, we propose a distributed quantum circuit to allow spatially separated prisoners to play the prisoners’ dilemma game. Decomposing the circuit into controlled-Z and single-qubit gates only, we design a corresponding spin–photon-interaction-based physical setup within the reach of current technology. In our setup, spins are considered to be the players’ logical qubits, which can be realized via nitrogen-vacancy centers in diamond or quantum dots coupled to optical cavities, and the game is played via a flying photon realizing logic operations by interacting with the spatially separated optical cavities to which the spin qubits are coupled. We also analyze the effect of the imperfect realization of two-qubit gates on the game, and discuss the revival of the dilemma and the emergence of new Nash equilibria.Yayın Microservices-based databank for Turkish hazelnut cultivars using IoT and semantic web technologies(John Wiley and Sons Ltd, 2024-03-30) Aydın, Şahin; Aldara, DieaaInformation and communication technologies (ICTs) can play a crucial role in facilitating access to comprehensive information on the quality standards of Turkish hazelnut cultivars. In this regard, this study introduces a Hazelnut Databank System (HDS) that utilizes the microservices architecture, an integrated software system supported by the Internet of Things (IoT) and semantic web, to categorize Turkish hazelnut cultivars. The study focuses on developing microservices using various programming languages and frameworks. Specifically, C# on the.NET Core Framework was used for both microservices and the web-based application implemented through the ASP.NET Core MVC Framework. Mobile-based software applications were created using Xamarin. Forms, and the IoT application was developed using the Python programming language. The data storage is facilitated through the MS SQL Server database. Additionally, the study incorporates the implementation of a hazelnut species classification system using the DNN + ResNet50 machine learning model, achieving an impressive accuracy rate of 95.77%. The overall usability of the system was evaluated, resulting in a score of 42 out of 50. By providing detailed information on Turkish hazelnut cultivars, the HDS has the potential to greatly improve hazelnut production quality in Turkey and increase awareness of hazelnut agriculture among relevant stakeholders.Yayın Evaluation of post-swallow residue with visual analysis of swallowing efficiency and safety in patients with idiopathic Parkinson's disease(Sage Publications Inc, 2023-12) Doruk, Can; Çaytemel, Berkay; Şahin, Erdi; Kara, Hakan; Samancı, Bedia; Abay, Sevinç Nisa; Bilgiç, Başar; Hanağası, Haşmet; Başaran, Bora; Enver, Necati; Rameau, AnaisObjectives: Dysphagia is common in idiopathic Parkinson's disease (IPD) and is associated with impairments in both swallowing safety and swallowing efficiency. The goals of this study were to define post-swallow residue patterns in people with IPD and describe pathophysiological endoscopic findings affecting residue accumulation. Methods: This was a prospective single-blinded cross-sectional cohort study of patients with the diagnosis of IPD recruited from a Movement Disorder Clinic. Clinical variables included patient age, cognitive function, and measures of disease severity, and laryngoscopic examinations with a flexible endoscopic evaluation of swallowing (FEES) were completed for each patient. Visual Analysis of Swallowing Efficiency and Safety (VASES) was used to analyze FEES. Post-swallow residue outcomes and non-residue endoscopic outcomes including the Bowing index, Penetration Aspiration Scale (PAS) score, premature leakage, and build-up phenomenon were evaluated. Multiple regression models were used to evaluate factors affecting the residue at different anatomic levels. Results: Overall 53 patients completed the study. The multiple regression analyses showed a relation between (1) the presence of residue at the level of oropharynx and epiglottis with premature leakage, (2) the presence of residue at the level of the laryngeal vestibule and vocal folds with build-up phenomenon, and (3) the presence of residue at the level of the hypopharynx, laryngeal vestibule, and subglottis with airway invasion. Conclusion: Residue pattern during FEES is associated with specific swallow dysfunctions in IPD. Using residue localization and quantification may be a helpful tool in assessing the impact of targeted swallowing interventions in patients with IPD and dysphagia.Yayın Quantum Zeno repeaters(Nature Research, 2022-09-12) Bayrakçı, Veysel; Özaydın, FatihQuantum repeaters pave the way for long-distance quantum communications and quantum Internet, and the idea of quantum repeaters is based on entanglement swapping which requires the implementation of controlled quantum gates. Frequently measuring a quantum system affects its dynamics which is known as the quantum Zeno effect (QZE). Beyond slowing down its evolution, QZE can be used to control the dynamics of a quantum system by introducing a carefully designed set of operations between measurements. Here, we propose an entanglement swapping protocol based on QZE, which achieves almost unit fidelity. Implementation of our protocol requires only simple frequent threshold measurements and single particle rotations. We extend the proposed entanglement swapping protocol to a series of repeater stations for constructing quantum Zeno repeaters which also achieve almost unit fidelity regardless of the number of repeaters. Requiring no controlled gates, our proposal reduces the quantum circuit complexity of quantum repeaters. Our work has potential to contribute to long distance quantum communications and quantum computing via quantum Zeno effect.Yayın Superactivating bound entanglement in quantum networks via quantum Zeno dynamics and a novel algorithm for optimized Zeno evolution(MDPI, 2023-01) Özaydın, Fatih; Bayrakçı, Veysel; Altıntaş, Azmi Ali; Bayındır, CihanAn arbitrary amount of entanglement shared among nodes of a quantum network might be nondistillable if the nodes lack the information on the entangled Bell pairs they share. Making such a system distillable, which is called the superactivation of bound entanglement (BE), was shown to be possible through systematic quantum teleportation between the nodes, requiring the implementation of controlled-gates scaling with the number of nodes. In this work, we show in two scenarios that the superactivation of BE is possible if nodes implement the proposed local quantum Zeno strategies based on only single qubit rotations and simple threshold measurements. In the first scenario we consider, we obtain a two-qubit distillable entanglement system as in the original superactivation proposal. In the second scenario, we show that superactivation can be achieved among the entire network of eight qubits in five nodes. In addition to obtaining all-particle distillable entanglement, the overall entanglement of the system in terms of the sum of bipartite cuts is increased. We also design a general algorithm with variable greediness for optimizing the QZD evolution tasks. Implementing our algorithm for the second scenario, we show that a significant improvement can be obtained by driving the initial BE system into a maximally entangled state. We believe our work contributes to quantum technologies from both practical and fundamental perspectives bridging nonlocality, bound entanglement and the quantum Zeno dynamics among a quantum network.Yayın Impact of novel coronavirus (COVID-19) on daily routines and air environment: evidence from Turkey(Springer, 2021-03) Ali, Hussain; Yılmaz, Gözde; Fareed, Zeeshan; Shahzad, Farrukh; Ahmad, MunirTurkish people are facing several problems because of the novel coronavirus (COVID-19), as the pandemic has brought about drastic changes to their daily routines. This study mainly investigates the impact of this pandemic on the daily routines of Turkish. It also unveils how COVID-19 affects the air environment. The adopted methods for data collection are based on open-ended questions and Facebook interviews as per recommended by QSR-International (2012). The sample of this study comprises of Turkish students as well as professional workers. The findings of the research show that there are eighteen different results of COVID-19 that have been identified according to the Turkish people’s daily routines. Results reveal that increasing unemployment, decrease in air contamination, high stress and depression, a slowdown in the economic growth, and the tourism industry are profoundly affected due to the COVID-19 in Turkey. Furthermore, on the one hand, the consequences of the pandemic are segregated into social problems and psychological issues in daily routines. On the other hand, they have shown a positive impact on the air environment. This study concludes that, amid the COVID-19 pandemic, the lives of the people in Turkey are subject to deterioration, while the air environment of Turkey is gradually improving.Yayın A review of recent innovations in remote health monitoring(Multidisciplinary Digital Publishing Institute (MDPI), 2023-12) Dalloul, Ahmed Hany; Miramirkhani, Farshad; Kouhalvandi, LidaThe development of remote health monitoring systems has focused on enhancing healthcare services’ efficiency and quality, particularly in chronic disease management and elderly care. These systems employ a range of sensors and wearable devices to track patients’ health status and offer real-time feedback to healthcare providers. This facilitates prompt interventions and reduces hospitalization rates. The aim of this study is to explore the latest developments in the realm of remote health monitoring systems. In this paper, we explore a wide range of domains, spanning antenna designs, small implantable antennas, on-body wearable solutions, and adaptable detection and imaging systems. Our research also delves into the methodological approaches used in monitoring systems, including the analysis of channel characteristics, advancements in wireless capsule endoscopy, and insightful investigations into sensing and imaging techniques. These advancements hold the potential to improve the accuracy and efficiency of monitoring, ultimately contributing to enhanced health outcomes for patients.Yayın Exploring the impact of Flash technique on test anxiety among adolescents(SAGE Publications Ltd, 2025-07) Çitil Akyol, Canan; İnci İzmir, Sevim BerrinThis study aims to investigate the specific effects of Flash Technique (FT) on adolescents with test anxiety. This follow-up study consists of 38 adolescents, 14–17 years of age (M = 15.39, SD = 1.13). Pre-post assessments were conducted using the Test Anxiety Inventory (TAI), Scale of Attitudes Negatively Affecting the Performance I/Test (POET), and Beck Anxiety Inventory (BAI) at baseline, at the end of the 4thand 12thweeks of therapy. The FT was applied for 12 weeks, with one weekly session as an intervention. As a result of the therapy process, the baseline means of total BAI scores decreased from 25.26 to 2.18; the baseline means of TAI decreased from 149.79 to 39.13, and the baseline mean of POET decreased from 298.47 to 73.84 at the end of the 12th week of therapy. Also, the baseline means of SUD scores decreased from 9.42 to zero at the end of the 12th week of treatment. All the adolescents showed complete improvement after the 12th week of the FT. The study findings showed that the test anxiety symptoms significantly decreased with the treatment of the FT. FT can be an effective intervention for test anxiety in adolescents.Yayın Adaptive locally connected recurrent unit (ALCRU)(Springer Science and Business Media Deutschland GmbH, 2025-07-03) Özçelik, Şuayb Talha; Tek, Faik BorayResearch has shown that adaptive locally connected neurons outperform their fully connected (dense) counterparts, motivating this study on the development of the Adaptive Locally Connected Recurrent Unit (ALCRU). ALCRU modifies the Simple Recurrent Neuron Model (SimpleRNN) by incorporating spatial coordinate spaces for input and hidden state vectors, facilitating the learning of parametric local receptive fields. These modifications add four trainable parameters per neuron, resulting in a minor increase in computational complexity. ALCRU is implemented using standard frameworks and trained with back-propagation-based optimizers. We evaluate the performance of ALCRU using diverse benchmark datasets, including IMDb for sentiment analysis, AdditionRNN for sequence modelling, and the Weather dataset for time-series forecasting. Results show that ALCRU achieves accuracy and loss metrics comparable to GRU and LSTM while consistently outperforming SimpleRNN. In particular, experiments with longer sequence lengths on AdditionRNN and increased input dimensions on IMDb highlight ALCRU’s superior scalability and efficiency in processing complex data sequences. In terms of computational efficiency, ALCRU demonstrates a considerable speed advantage over gated models like LSTM and GRU, though it is slower than SimpleRNN. These findings suggest that adaptive local connectivity enhances both the accuracy and efficiency of recurrent neural networks, offering a promising alternative to standard architectures.Yayın Electroencephalography signatures associated with developmental dyslexia identified using principal component analysis(Multidisciplinary Digital Publishing Institute (MDPI), 2025-08-27) Eroğlu, Günet; Harb, Mhd Raja AbouBackground/Objectives: Developmental dyslexia is characterised by neuropsychological processing deficits and marked hemispheric functional asymmetries. To uncover latent neurophysiological features linked to reading impairment, we applied dimensionality reduction and clustering techniques to high-density electroencephalographic (EEG) recordings. We further examined the functional relevance of these features to reading performance under standardised test conditions. Methods: EEG data were collected from 200 children (100 with dyslexia and 100 age- and IQ-matched typically developing controls). Principal Component Analysis (PCA) was applied to high-dimensional EEG spectral power datasets to extract latent neurophysiological components. Twelve principal components, collectively accounting for 84.2% of the variance, were retained. K-means clustering was performed on the PCA-derived components to classify participants. Group differences in spectral power were evaluated, and correlations between principal component scores and reading fluency, measured by the TILLS Reading Fluency Subtest, were computed. Results: K-means clustering trained on PCA-derived features achieved a classification accuracy of 89.5% (silhouette coefficient = 0.67). Dyslexic participants exhibited significantly higher right parietal–occipital alpha (P8) power compared to controls (mean = 3.77 ± 0.61 vs. 2.74 ± 0.56; p < 0.001). Within the dyslexic group, PC1 scores were strongly negatively correlated with reading fluency (r = −0.61, p < 0.001), underscoring the functional relevance of EEG-derived components to behavioural reading performance. Conclusions: PCA-derived EEG patterns can distinguish between dyslexic and typically developing children with high accuracy, revealing spectral power differences consistent with atypical hemispheric specialisation. These results suggest that EEG-derived neurophysiological features hold promise for early dyslexia screening. However, before EEG can be firmly established as a reliable molecular biomarker, further multimodal research integrating EEG with immunological, neurochemical, and genetic measures is warranted.
