Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Non-Contact Acoustic Screening for Sleep Apnea: A Subject-Aware Deep Learning Approach(Springer Science and Business Media Deutschland GmbH, 2026-02-11) Aygün Çakıroğlu, M.; Kizilkaya Aydoǧan, E.; Bolatturk, Ö.F.; Aydoğan, S.; Ismailoǧullari, S.; Delice, Y.Purpose: To explore the feasibility of using camera-derived, non-contact audio synchronized with PSG for clinically relevant sleep-apnea classification, and to benchmark compact deep models under a subject-aware design using a previously unstudied, real-world dataset. Methods: Thirty-two adults underwent simultaneous polysomnography (PSG) and camera-based non-contact audio recording. The synchronized audio segments were used to train and compare three compact deep-learning architectures (convolutional, attention-augmented, and transformer-based) under a subject-aware evaluation design that prevented identity leakage. Model performance and calibration were assessed at both segment and subject levels using standard statistical tests. Results: Subject-level evaluation was based on a very small, imbalanced test set of six subjects (one positive). Within this limited yet previously unstudied local dataset, the CNN_trans model achieved an apparent perfect ranking performance (AUC = 1.00; 95% CI 0.00–1.00), though this likely reflects the small, imbalanced test cohort, with recall = 1.00 and precision = 0.55. The wide confidence interval reflects substantial statistical uncertainty, and DeLong comparisons showed no significant AUC difference between CNN_trans and CNN_att (ΔAUC = − 0.042; p = 0.43). Conclusion: PSG-synchronized, non-contact audio supports accurate and well-calibrated sleep-apnea classification with compact deep models. This subject-aware evaluation suggests that contactless acoustic monitoring may have potential clinical relevance, motivating larger, multi-site validation. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026.Article Citation - WoS: 1Two-Local Modifications of Sachdev-Ye Model With Quantum Chaos(American Physical Society, 2026-01-27) Hanada, M.; Van Leuven, S.; Oktay, O.; Tezuka, M.The Sachdev-Ye-Kitaev (SYK) model may provide us with a good starting point for the experimental study of quantum chaos and holography in the laboratory. Still, the four-local interaction of fermions makes quantum simulation challenging, and it would be good to search for simpler models that keep the essence. In this paper, we argue that the four-local interaction may not be important by introducing a few models that have two-local interactions. The first model is a generalization of the spin-SYK model, which is obtained by replacing the spin variables with SU(d) generators. Simulations of this class of models might be straightforward on qudit-based quantum devices. We study the case of d=3,4,5,6 numerically and observe quantum chaos already for two-local interactions in a wide energy range. We also introduce modifications of spin-SYK and SYK models that have similar structures as the SU(d) model (e.g., H=∑p,qJpqχpχp+1χqχq+1 instead of the original SYK Hamiltonian H=∑p,q,r,sJpqrsχpχqχrχs), which shows strongly chaotic features although the interaction is essentially two-local. These models may be a good starting point for the quantum simulation of the original SYK model. ©2026 American Physical Society.Article Noninvasive Condition Monitoring for Eccentricity Fault Detection in Large Hydro Generators(TÜBİTAK Scientific & Technological Research Council Turkey, 2026-01-16) Lemeski, Atena Tazikeh; Tekgun, Didem; Keysan, Ozan; Leblebicioglu, Kemal; Gol, Murat; Leblebicioglu, Mehmet KemalEccentricity faults in electric machines remain a critical concern, as they generate uneven magnetic forces that increase vibration and noise, ultimately raising the risk of premature motor failure. This study proposes a method for the early detection of dynamic eccentricity (DE) faults in hydropower plants through an advanced optimization-based parameter identification technique integrated with finite element analysis (FEA). Finite element modeling (FEM) is first used to analyze an existing salient-pole synchronous generator (SPSG) from a hydroelectric power plant in T & uuml;rkiye. The effects of DE faults on the SPSG's magnetic equivalent circuit parameters are then examined under various fault severities. A comprehensive hydropower plant model-including the synchronous generator, governor, and excitation system-is developed in MATLAB/Simulink, with all input parameters obtained from real plant data and equivalent circuit variations extracted from FEA. After completing the modeling stage, including fault scenarios, MATLAB and Simulink are employed together to estimate key magnetic equivalent circuit parameters using a modified particle swarm optimization (MPSO) algorithm, achieving highly accurate parameter estimation. Since the hydropower system allows measurement of the three-phase output currents, parameter estimation is performed based on current variations under different fault conditions. The simulation results verify the method's ability to detect faults with high accuracy; thus, this integrated and noninvasive approach provides a robust framework for ensuring the operational reliability and longevity of large hydro generators.Article Citation - WoS: 2Citation - Scopus: 2A Novel Biomass-Derived Reductant for Nitric Acid Dissolution of Manganiferous Iron Ore: Comparative Assessment of Organic Reductants(MDPI, 2025-12-31) Top, Soner; Altiner, Mahmut; Vapur, Huseyin; Kursunoglu, Sait; Stopic, SreckoThis study investigates the selective dissolution of manganese from a manganiferous iron ore using nitric acid (HNO3) in the presence of various organic reductants. A series of leaching experiments was performed to evaluate the effects of temperature, reductant type, and leaching time on Mn recovery, with particular emphasis on biomass (horse dung) and tartaric acid as novel reducing agents. The dissolution behaviour of Fe, Mn, Mg, Ca, and Al was systematically examined, revealing that Mn extraction was strongly enhanced in the presence of reductants, while Fe dissolution remained below 10% under all conditions. The maximum Mn dissolution exceeded 90% at 90 degrees C using biomass and reached nearly 85%-90% with tartaric acid at elevated temperatures. Kinetic studies were conducted by applying reaction order models and the shrinking core model. The results indicated that Mn dissolution in HNO3 medium is predominantly controlled by surface chemical reaction, with Arrhenius analysis yielding activation energies of 27.74 kJ/mol for biomass and 21.26 kJ/mol for tartaric acid. These relatively low values confirm the efficiency of organic reductants in facilitating Mn reduction and dissolution. To sum up, comparison of reductant efficiency revealed that, at the lowest concentrations, the dissolution of Mn followed the sequence glucose > sucrose > oxalic acid > tartaric acid > maleic acid > biomass > citric acid > acetic acid. At the highest concentrations, the trend shifted, with citric acid emerging as the most effective, followed by tartaric acid > oxalic acid > glucose > sucrose > maleic acid > biomass > acetic acid.Article Citation - WoS: 1Citation - Scopus: 1Unit Sizing and Feasibility Analysis of Green Hydrogen Storage Utilizing Excess Energy for Energy Islands(MDPI, 2026-01-14) Koca, Kemal; Dursun, Erkan; Bekci, Eyup; Ucar, Suat; Akpolat, Alper Nabi; Tsami, Maria; Borg, Ruben PaulThis study examines whether green hydrogen production using combined wind and solar energy on Marmara Island can meet the island's electricity demand and fuel the fuel needs of a hydrogen-powered ferry. A hybrid system consisting of a 10 MW wind farm, a 3 MW solar PV system, and a PEM electrolyzer sized to meet the island's hydrogen demand was modeled for the island, located in the southwestern Sea of Marmara. The hydrogen production potential, energy flows, and techno-economic performance were evaluated using HOMER-Pro 3.18.4 version. According to the simulation results, the hybrid system generates approximately 62.6 GWh of electricity annually, achieving an 82.8% renewable energy share. A significant portion of the produced energy is transferred to the electrolyzer, producing approximately 729 tons of green hydrogen annually. The economic analysis demonstrates that the system is financially viable, with a net present cost of USD 61.53 million and a levelized energy cost of USD 0.175/kWh. Additionally, the design has the potential to reduce approximately 2637 tons of CO2 emissions over a 25-year period. The results demonstrate that integrating renewable energy sources with hydrogen production can provide a cost-effective and low-carbon solution for isolated communities such as islands, strengthening energy independence and supporting sustainable transportation options. It has been demonstrated that hydrogen produced by PEM electrolyzers powered by excess energy from the hybrid system could provide a reliable fuel source for hydrogen-fueled ferries operating between Marmara Island and the mainland. Overall, the findings indicate that pairing renewable energy generation with hydrogen production offers a realistic pathway for islands seeking cleaner transportation options and greater energy independence.Article Enhanced Photoluminescence and Stability of CsPbBr3 Perovskite Nanocrystals Through AuCl Doping(Springer, 2026-02) Khorasani, Azam; Mutlugun, EvrenThis study delves into the transformative effects of inorganic gold chloride (AuCl) doping on all-inorganic cesium lead bromide (CsPbBr3) colloidal perovskite quantum dots (PeQDs). Using a precise hot injection synthesis method, AuCl was introduced at concentrations ranging from 0 to 10%, enabling a comprehensive analysis of its impact on the structural, morphological, and optical characteristics of CsPbBr3 PeQDs. We systematically investigated how varying AuCl levels influence photoluminescence (PL), PL quantum yield (PLQY), and the stability of these quantum dots. Advanced characterization techniques, including X-ray diffraction (XRD), scanning transmission electron microscopy (STEM), energy dispersive X-ray analysis (EDX), Fourier-transform infrared spectroscopy (FTIR), UV-Vis absorption, steady-state PL, absolute PL measurement, and time-resolved PL (TRPL), provided a detailed insight into these changes. Our findings indicate that AuCl doping is successfully integrated into CsPbBr3 PeQDs, with 5% identified as the optimal concentration. At this level, the quantum dots show enhanced PLQY, superior crystallinity, and increased stability at 50 degrees C and in ethanol solvent compared to undoped samples. While higher doping levels reduce QY and PL slightly, they still outperform the undoped CsPbBr3 PeQDs. These results demonstrate that AuCl doping can fine-tune the structural and optical properties of CsPbBr3 PeQDs, marking a significant step forward in developing tailored materials for advanced optoelectronic applications.Article Densification-Induced Chemical Reorganization and Mechanical Enhancement in Amorphous Si2BC3N(Elsevier, 2026-02) Durandurdu, MuratThe atomistic mechanisms that govern the mechanical performance of amorphous silicon-boron carbonitride (SiBCN) ceramics remain insufficiently understood, particularly regarding the role of density. Here, we employ ab initio molecular dynamics simulations to elucidate the structural evolution and mechanical response of low-density (LDA, 2.20 g/cm3) and high-density (HDA, 2.53 g/cm3) amorphous Si2BC3N prepared via melt-quench. The HDA phase exhibits markedly higher atomic packing and network connectivity, accompanied by a nontrivial chemical reorganization. Densification significantly enhances heteronuclear bonding-especially Si-C coordination-while suppressing C-C and Si-Si homopolar bonds. These changes yield substantial mechanical strengthening: the HDA phase exhibits a 48% increase in bulk modulus (130 GPa vs. 88 GPa), along with elevated Young's (266 GPa) and shear (112 GPa) moduli. Our findings reveal a clear density-structure-property relationship in amorphous SiBCN, demonstrating that densification suppresses weak self-bonded motifs and promotes a robust, interconnected atomic network. This insight provides a pathway for designing high-performance amorphous SiBCN ceramics for extreme-environment applications.Article Supervised Learning-Driven Dead Band Control of Occupant Thermostats for Energy-Efficient Residential HVAC(Elsevier, 2026-03) Savasci, Alper; Ceylan, Oguzhan; Paudyal, SumitHeating, ventilation, and air conditioning (HVAC) systems play a crucial role in demand-side management (DSM) by shaping residential electricity consumption and enabling flexible, grid-responsive operation. Thermostats in HVAC systems regulate indoor temperature as part of a closed-loop control framework, typically incorporating a fixed temperature dead band-a range around the setpoint where no action is taken-to reduce energy use and prevent frequent cycling of the HVAC system. Although essential for efficiency and equipment longevity, fixed dead bands limit adaptability, as dynamically adjusting them under varying environmental conditions remains challenging for occupants. To address this limitation, we propose a machine learning (ML)-based dead band tuning framework that optimally adjusts thermostat settings in real time. The method integrates conventional optimization with data-driven modeling: a mixed-integer linear programming (MILP) model is first used to gen erate optimal dead band values under measured outdoor temperature records (diverse seasonal weather scenarios) which are then employed to train the ML-based predictor to learn a real-time discrete dead band decision policy that approximates the MILP-optimal hysteresis-aware decisions. Among the evaluated models, Random Forest demonstrates superior predictive performance, achieving a mean squared error (MSE) of 0.0399 and a coefficient of determination (R2) of 95.75 %.Article Performance Boost in QLEDs Using Octanethiol-Capped Core/Shell Quantum Dots(IOP Publishing Ltd, 2026-01-07) Yazici, Ahmet F.; Yuruc, Adnan M.; Kelestemur, Yusuf; Serin, Ramis Berkay; Kacar, Rifat; Ulku, Alper; Mutlugun, EvrenQuantum dots attract significant attention as one of the most promising colloidal nanocrystals with unique optical properties and potential applications for the next generation of display technology. In this paper, we evaluate the performance of CdZnSeS-based alloyed-shell quantum dots (QDs) for electroluminescence devices upon additional shell growth and ligand exchange. This includes core/shell (C/S) and core/shell/shell (C/S/S) QDs, whose latter includes an additional ZnS shell and octanethiol (OT) ligands. We present detailed characterizations of QDs using transmission electron microscopy, XRD, and various spectroscopic techniques and demonstrate their QD light emitting (QLEDs). We find the photoluminescence quantum yield of C/S/S QDs increased from 68.8% to 88.7% compared to C/S QDs whereas the emission linewidth narrows from 22.2 nm to 20.8 nm. QLEDs fabricated with C/S/S QDs exhibit a higher peak external quantum efficiency (EQE) of 4.1% and maximum luminance of 85 000 cd m-2, compared to 2.3% EQE and 67 000 cd m-2 for C/S QLEDs. In this respect, the OT-assisted shell growth significantly improves the optical property of QDs and performance of QLEDs, likely attributed to the enhanced charge balance and increased radiative recombination rate.Article A Small Indole Derivative Isolated From Caper (Capparis Ovata) as an Inducer of P53-Mediated Apoptosis in Prostate Cancer: Comprehensive In Vitro and In Silico Studies(Wiley, 2025-12-31) Acar, Ozden Ozgun; Gazioglu, Isil; Oruc, Hatice; Kale, Elif; Senol, Halil; Topcu, Gulacti; Sen, AlaattinNatural products with stunning chemical diversity have been extensively researched for their anticancer potential for more than fifty years. This study aimed to determine the effect of indole derivative 1H-indole-2-hydroxy-3-carboxylic acid (IHCA), isolated as a novel alkaloid from Capparis ovata, on selected tumor suppressor, apoptotic, and cell cycle regulatory genes, which are known to be important in cancer pathophysiology, on Caco-2 and LNCaP cells in comparison with Taxol. The molecular mechanism of IHCA's anticancer activity is essentially undefined. Different concentrations of IHCA increased the expression levels of apoptosis-related genes, including BCL-2 and TNF-alpha. In addition, the tumor suppressor genes PTEN, P53, and RB were increased in LNCaP and Caco-2 cells. KRAS, an oncogenic gene, was significantly downregulated by IHCA in LNCaP cells. Western blot results showed that the protein expression levels of P53 and PTEN in LNCaP cells were increased when treated with IHCA, whereas CDK4 and TNF-alpha were decreased. Finally, IHCA and doxorubicin significantly increased P53-driven luciferase activity compared to the control. The results strongly suggest that the novel natural compound IHCA has an anticancer effect involving the regulation of the P53 gene and its networks in vitro. The molecular docking and MD simulation analyses reveal that IHCA exhibits superior binding potential to the MDM2 protein compared to Nutlin-3a. MD simulations further confirm that IHCA maintains a more stable and consistent interaction with MDM2, as indicated by lower RMSD values and reduced ligand fluctuation. These results highlight IHCA's potential as a more effective MDM2 inhibitor, suggesting its promise as a lead compound for anticancer drug development.Clinical Trial Registration: Not applicable.