Erzincan Binali Yıldırım ÜniversitesiErzincan Binali Yıldırım ÜniversitesiAçık Erişim Arşivi · RDL Open

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  • ArticleYalnız künye2027
    A hybrid Fuzzy neural network approach for nonlinear control systems: Performance, adaptability, and robustness

    Can, Erol

    This study presents a Fuzzy Neural Network (FNN)-based control architecture for nonlinear control mapping and evaluates its performance using a stable second-order benchmark plant. The proposed FNN combines a compact seven-rule fuzzy structure with a hybrid AND/OR inference mechanism and a hybrid learning strategy based on Least Squares Estimation (LSE) and Gradient Descent (GD). Five operating-condition variables are used as fuzzy inputs, while Gaussian membership functions represent the antecedent variables. LSE is employed to estimate the consequent parameters, whereas GD is used to adapt the antecedent membership-function parameters during offline training. The proposed controller is compared with classical PID and conventional Fuzzy controllers, as well as Adaptive Neuro-Fuzzy Inference System (ANFIS), Takagi-Sugeno (TSK), and Interval Type-2 Fuzzy (IT2Fuzzy) controllers under common benchmark simulation conditions. The evaluation considers transient response, gain variations, external disturbances, measurement noise, and parameter perturbations. Under the reported nominal step-response comparison, the proposed FNN achieves a rise time of 0.72 s, a settling time of 1.28 s, and zero measured overshoot. The IT2-Fuzzy controller achieves an overshoot of 4.03%, whereas PID, conventional Fuzzy, ANFIS, and TSK exhibit overshoots of 16.30%, 12.63%, 14.77%, and 9.48%, respectively. Sensitivity and noise analyses further indicate that the proposed seven-rule architecture maintains favorable performance under the investigated parameter variations and measurement-noise conditions. The results demonstrate that the proposed FNN provides a compact and interpretable framework for nonlinear control mapping, offering favorable transient performance with limited rule complexity. Since the evaluation is based on numerical simulations, experimental validation on physical control platforms is required to further assess its practical applicability.

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  • ArticleYalnız künye2027
    Single-image generation using multi-scale vector quantization with autoregressive prior

    Yildiz, Eyyup

    Single-image generative models aim to learn internal statistics of a single training image and synthesize diverse, realistic samples without using large-scale datasets. However, current models rely either on multi-scale generative adversarial network (GAN) pyramids or on diffusion models, both of which require controlling the continuous latent space of the training image. In this paper, we introduce a new single-image generative model that utilizes image-specific discrete latent representation by integrating vector quantization with a coarse-to-fine multi-scale pyramid. Vector quantization serves as a dictionary of high-frequency textural features, ensuring preservation of local textures and fine details that are typically lost in continuous latent space. To generate new image samples, our model trains an autoregressive prior over the quantized token maps, allowing image synthesis to be performed in a quantized latent space rather than directly in pixel space. Extensive quantitative and qualitative experiments on Places50, SIGD, and COCO50 datasets demonstrate that our model consistently achieves competitive performance in image quality, diversity, and computational efficiency, as measured by SIFID, NIQE, NIMA, LPIPS, and MS-SSIM, compared with existing models. We further demonstrate the versatility of our model through various image manipulation tasks, including paint-to-image, harmonization, editing, and outpainting. In conclusion, we show that vector-quantized latent modeling is an effective alternative to GAN- and diffusion-based approaches for high-quality and diverse single-image generation and represents a notable improvement over existing models.

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  • ArticleYayıncıda açık erişim2027
    State-specific respiratory signatures for affective and stress recognition: Interpretable respiratory markers, autocorrelation lags, and compact CNN models

    Velichko, Andrei; Huyut, Mehmet Tahir

    Respiratory activity is a direct and interpretable physiological channel for wearable stress and affective-state recognition, yet many studies emphasize classification accuracy without identifying which respiratory properties separate different states. This work reframes RESP-based recognition as a joint predictive and explanatory problem. Using the chest respiratory channel of the WESAD dataset, we analyze 60 s windows under leave-one-subject-out validation and combine two complementary branches: compact raw-signal one-dimensional convolutional neural networks (1D-CNNs) and physically grouped handcrafted respiratory signatures. The primary application task is binary stress versus non-stress detection, while baseline, stress, amusement, and meditation are additionally analyzed in a one-vs-rest setting to reveal state-specific respiratory markers. The feature space is organized into respiratory timing, breath-to-breath variability, waveform statistics, spectral/time–frequency descriptors, and autocorrelation/nonlinear predictability descriptors, with the raw 60 s signal treated as a sixth representation for the CNN branch. We introduce autocorrelation transition lags (Zpm/Zmp) as interpretable markers of respiratory correlation scale and separately evaluate exploratory forecast-error-growth/Lyapunov-like descriptors. In the final CNN refit setting, the raw-signal model achieved the strongest stress-vs-rest performance (accuracy 96.72%, macro-F1 95.30%, MCC 90.61%). In contrast, compact feature models were stronger for baseline (MCC 65.34%), amusement (MCC 35.69%), and especially meditation (MCC 88.65%). Strict nested reanalysis of the auxiliary Top-20 stress search yielded mean MCC=82.29% versus 85.45% originally, indicating modest selection optimism. These results show that CNNs are most useful for the practical stress detector, whereas interpretable respiratory signatures provide stronger and more physiologically transparent state-specific markers for several non-stress conditions.

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  • ArticleYalnız künye2027
    Rosmarinic Acid Attenuates Isoniazid-Induced Neurotoxicity by Restoring Mitochondrial Dynamics and Suppressing Oxidative Stress, Ferroptosis, Neuroinflammation, and Apoptosis

    Bolat, Merve; Karaarslan, Tuba; Teki̇n, Samet; Derelİ, Esra; Atasever, Aslıhan; Laçi̇n, Burak Batuhan; Aktaş Şenocak, Esra; Aykurt, Furkan; Şengül, Emin; Çelebi̇, Fikret

    Despite the continued global burden of tuberculosis and the essential role of isoniazid (INH) in first-line antituberculosis therapy, INH-induced neurotoxicity remains a major clinical challenge that compromises treatment adherence, and effective, well-characterized neuroprotective strategies are still lacking. This study investigated the neuroprotective effects of rosmarinic acid (RA) against INH-induced neurotoxicity, evaluating oxidative stress, inflammation, iron metabolism, energy homeostasis, mitochondrial dynamics, ferroptosis, and apoptosis using biochemical, molecular, and histopathological approaches. INH markedly increased malondialdehyde while reducing superoxide dismutase and glutathione, and increased TNF-α, IL-1β, and IL-6 while decreasing IL-10. INH also disturbed iron homeostasis (increased Fe²⁺), impaired energy metabolism (reduced ATP), and disrupted mitochondrial dynamics (increased Drp-1; decreased Mfn-2 and PGC-1α). NF-κB activation was accompanied by increased ACSL4 and decreased GPX4 and FTH1, reflecting ferroptosis, alongside increased Bax, Caspase-3, and Cytochrome c and reduced Bcl-2, indicating mitochondrial apoptosis. RA treatment suppressed oxidative stress, enhanced antioxidant defense, attenuated inflammation, restored iron and energy homeostasis, improved mitochondrial dynamics, and inhibited NF-κB activation, ferroptosis, and apoptosis. These findings demonstrate that RA exerts potent neuroprotective effects against INH-induced brain injury by simultaneously targeting oxidative stress, mitochondrial dysfunction, iron dyshomeostasis, neuroinflammation, ferroptosis, and apoptosis. To our knowledge, this is among the first studies to comprehensively address these interconnected pathways, including ferroptosis and iron dyshomeostasis, in INH-induced neurotoxicity. RA may thus represent a promising therapeutic candidate for preventing INH-induced neurotoxicity.

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  • ArticleYayıncıda açık erişim2027
    From extraction to ocular delivery: An integrated approach using apigenin and apigenin 7-O-glucoside nanosuspensions to treat corneal neovascularization

    Aytekin, Eren; Gözcü, Sefa; Polat, Heybet Kerem; Akşit, Hüseyin; Karakuyu, Nasıf Fatih; Kurt, Nihat; Sofu, Gülşah Usta; Akkaya, Züleyha Yalnız; Tebrizi, Behzat; Çalış, Sema

    Corneal neovascularization (CV) is a vision-threatening condition characterized by the pathological ingrowth of blood vessels. While corticosteroids and anti-VEGF agents are standard treatments, their prolonged use is associated with significant ocular side effects. This study aimed to develop and optimize nanosuspensions of Apigenin (APG) and Apigenin-7-O-glucoside (APG 7) to enhance their ocular bioavailability and evaluate their efficacy in the treatment of CV. APG and APG 7 were isolated from Petroselinum crispum . Nanosuspensions were formulated using an anti-solvent precipitation method, optimized via a 23 factorial design considering PVA concentration, Span 80 concentration, and homogenization speed. The physical properties, including particle size, PDI, and zeta potential, were characterized. In vivo efficacy was assessed over a 7-day treatment period in an alkali-burn induced rat CV model through clinical scoring, histopathology, and immunohistochemical analysis of VEGFA and IL-6 expression. The optimized APG nanosuspensions exhibited a mean particle size of ∼166.9 nm with high stability. In vivo studies demonstrated that 0.05% APG nanosuspension significantly inhibited corneal angiogenesis, reduced stromal edema, and downregulated VEGFA and IL-6 expression compared to the untreated injury group (p < 0.05). Conversely, APG 7 formulations failed to show significant therapeutic efficacy, likely due to limited corneal permeability attributed to the glycoside moiety. The 0.05% APG nanosuspension presents a promising, non-invasive therapeutic alternative for CV management, offering effective anti-angiogenic activity with improved ocular delivery characteristics.

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  • ArticleYalnız künye2027
    Synthesis, structural characterization, and in vitro and in silico anticancer evaluation of chalcone-based heterocyclic and boron difluoride derivatives

    Serdaroğlu, Vildan; Demir, Fatma; Aydın, Ali; Türkmenoğlu, Burçin; Kahriman, Nuran

    In this research, a series of novel bioactive heterocyclic polar compounds were designed and synthesized by incorporating various functional groups to enhance their biological and functional properties. The work involved the synthesis of chalcone (1–9, 10–18), boron difluoride complex (19–21), pyrazoline (22–25), and pyrimidine (26–37) compounds with their structures characterized through spectral techniques including NMR (1H, 13C (APT), 1H–1H COSY), FT-IR spectroscopies, LC-MS spectrometry. The anticancer potential of all compounds was assessed using lung cancer cell lines (A549, Calu1, H1650), brain cancer cell lines (A172, C6, B35), as well as normal lung (Beas2B) and chondrocyte (HC) cell lines. Compounds exhibiting a GI50 value below 3.0 µg/mL and a TGI value under 100 µg/mL were classified as having anticancer activity, based on comparisons with the reference drug 5-fluorouracil (5FU). Overall, compounds 24, 34, and 36 emerged as the most promising lead candidates by combining potent antiproliferative activity, favorable GI50-derived selectivity indices, and low toxicity toward normal cells, whereas compounds 2, 32, and 35 demonstrated the highest overall biological potency across multiple cancer cell lines. Representative GI50 values as low as 1.0–1.2 µg/mL, TGI values as low as 1.3–2.5 µg/mL, and LC50 values generally exceeding 500 µg/mL in normal cell lines were obtained in the most responsive models, supporting the potential of these derivatives for further anticancer development. To support these detailed in vitro studies, the most active compounds targeting TP53, EGFR, Akt1, mTOR, ERK2, and caspase 3, which are effective in lung and brain cancer pathways, were interacted via in silico molecular docking. Through molecular docking, the interaction values of compounds 2, 6, 7, 8, 13, 14, 17, 18, 24, 27, 32, 35, 36, and 37 with the determined targets were calculated, and their potential as promising lead candidates for drug development was analyzed.

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  • ArticleYalnız künye2026
    Adaptive hybrid control algorithm for integrated wind-solar energy systems: Enhancing efficiency and minimizing environmental impact

    Can, Erol

    This study introduces a three-tier adaptive control strategy designed for hybrid wind - solar energy systems, with the goal of optimizing energy capture, stabilizing the DC bus voltage, and enhancing overall system performance under varying environmental conditions. The control framework incorporates a TSR-based Maximum Power Point Tracking (MPPT) method for the wind turbine, a temperature-sensitive Perturb-and-Observe (P&O) MPPT for the photovoltaic array, and a real-time energy coordination system that dynamically adjusts the power allocation between wind and solar sources based on their instantaneous availability. A conventional Proportional-Integral (PI) controller manages the DC bus voltage, minimizing fluctuations and ensuring seamless integration with energy storage or the grid. The proposed approach is adaptable to both off-grid and grid-connected microgrids and is computationally efficient for real-time application. Simulation results from four typical scenarios - including high wind/low solar, low wind/high solar, intermittent generation, and balanced generation - show system efficiencies consistently exceeding 92%, along with a substantial reduction in voltage ripple when compared to traditional MPPT techniques. These findings validate the effectiveness of the coordinated control strategy in maintaining power quality, system reliability, and stable energy output, offering a scalable and practical solution for integrating renewable energy into microgrid systems.

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  • ArticleYalnız künye2026
    Enhanced wheat (Triticum aestivum) performance: effects of PGPR-enriched on yield and biochemical profiles

    Yildiran Sogurtlupinar, Sevda; Inanç, Merve; Keçe, Yusuf Murat; Tarhan, Leyla; Sogutmaz Ozdemir, Bahar; Sahin, Fikrettin; Turan, Metin; Günes, Adem

    Plant growth-promoting rhizobacteria (PGPR) are increasingly applied in sustainable agriculture to enhance plant growth, improve yield, and induce tolerance to stress condition while reducing chemical inputs. Tuff, a porous volcanic material with high water-holding and cation exchange capacity, was used as a carrier to inoculate and deliver PGPR to the plant root zone. This two-year greenhouse study evaluated the effects of PGPR-inoculated tuff (T1) compared with non-inoculated tuff (T0, control) on the growth, physiological performance, antioxidant enzyme activities, and biochemical profiles of 'K & imath;rik' wheat. Large tuff (9 & times; 14 & times; 11 mm) were inoculated with approximately 4.8 & times; 1010 cfu/g PGPR and applied to the root zone of each plant. PGPR application increased grain yield by 20.43% and significantly improved chlorophyll content, stomatal conductance, membrane permeability, and photosynthetic rate. Antioxidant enzymes, including CAT, SOD, and POD, showed increases of 11.43, 14.83, and 10.71%, respectively. Levels of IAA (13.59%), GA (7%), and SA (9.27%) were elevated, whereas ABA decreased by 16.67%. Amino acid and organic acid contents were generally enhanced, along with significant increases in nutrient element concentrations, most notably P (18.49%), Cu (10.61%), and Fe (9.99%); in contrast, Na and B concentrations decreased by 5 and 3.48%, respectively. These findings indicate that PGPR-inoculated tuff can improve nutrient availability and growth and physiological performance in wheat, offering a low-cost, scalable biological input to complement conventional fertilization in sustainable wheat production. Further field studies comparing this approach with standard chemical fertilization are needed to confirm its practical applicability and support broader adoption.

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  • ArticleAçık Erişim2026
    Adaptation of the Systematic Assessment of Book Reading Tool (SABR-2.2) into Turkish

    Sahin, Figen; Benli, Gokce Karaman; Teke, Nergiz; Yilmaz, Arif; Demir, Ergul; Kinik, Elif Kural; Bad, Tugba

    This study aims to adapt SABR-2.2 to the Turkish language and culture. The tool was developed to evaluate the quality of preschool teachers' book-reading activities with children. The adaptation of the SABR-2.2 was conducted in line with the theoretical and practical models and criteria. A total of 150 volunteer preschool teachers employed in preschools and kindergartens in Ankara participated in the study. According to the results, the factor loadings for 11 items ranged from .40 to .83, accounted for 46% of the total variance, and indicated a unidimensional structure. The goodness-of-fit indices obtained from the confirmatory analyses (chi 2/df indicated an acceptable to good level of model-data fit. For the 11-item scale, Cronbach's alpha was .81, and McDonald's omega was .90. These values indicate that the scale works with high internal consistency. In addition, the total scores obtained from the scale seem to provide high discrimination between the lower and upper groups. In line with these findings, the scale is considered a valid and reliable instrument for evaluating teachers' book reading practices in the Turkish culture.

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  • ArticleAçık Erişim2026
    Effect of heat treatment conditions on the microstructure, surface roughness, dimensional accuracy, and geometric tolerances of inconel 718 alloy produced by selective laser melting

    Cemaloglu, Fulya; Özlü, Bares; Demir, Halil

    In this study, the effects of different heat treatment conditions applied to Inconel 718 alloy produced by the Selective Laser Melting (SLM) method on microstructure, surface roughness, dimensional accuracy, and geometric tolerances were experimentally investigated. Five specimens with nominal dimensions of 22 & times;22 & times;55 mm were produced; one was kept as the as-built sample, while the others were subjected to heat treatment under the conditions of 980-1.5h, 800-1h, 800-4h, and 800-32h. Microstructural analyses indicated that the heat treatments reduced the melt pool traces and resulted in a more homogeneous structure. Surface roughness measurements showed that the average roughness value of the as-built sample was 12.946 & micro;m, whereas roughness decreased under all heat treatment conditions. The lowest value was measured as 10,065 & micro;m after aging at 800-32h, corresponding to an improvement of 22,25 %. In terms of dimensional accuracy, the lowest deviations were obtained in the as-built specimen. In contrast, under the 800-32h condition, maximum deviations of up to 0.86% were detected in certain dimensions. Parallelism tolerances increased after long-term aging, whereas the lowest deviation in perpendicularity tolerance was obtained under the 980-1.5h condition. The findings indicate that while long-term aging improves surface quality, it may adversely affect certain dimensional and geometric characteristics.

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AlanDeğerDil
dc.date.accessioned2026-10-20T15:26:00.383728704Z
dc.date.available2026-10-20T15:26:00.383728704Z
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/22846
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleErzincan Binali Yıldırım Üniversitesitr
dc.titleErzincan Binali Yıldırım Universityen
dspace.entity.typeOrgUnit
organization.identifier.codeebyu
organization.unitTypeuniversity