Karamanoğlu Mehmetbey University
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Dependence modelling on loss triangles: copula regression with unobserved effect
No full textClassical reserve calculation techniques assume that the loss amounts are independent. However, various dependency structures, such as accident year dependence, development year dependence, and calendar year dependence, exist. In this study, we assume the presence of an unobserved random effect both between and within lines of business. In order to model this effect, we propose a copula regression model with unobserved random effect in which we consider additive and multiplicative effect structure. We consider four different random effect distributions to model the unobserved random effect. The theoretical results are illustrated using a real loss triangle dataset for two dependent lines of business. Based on the results, we conclude that proposed model outperforms classical models
Some sociological, gastronomic and microbiological characteristics of Turkish sourdough breads
No full textBread is an indispensable staple food that has been consumed by humans since they settled. Thousands of breads and other products are made around the world with sourdough adventure that started approximately 6000 years ago. Tu rkiye, which has hosted numerous ancient civilizations (Hatti, Hittites, etc.) and has significant archaeological sites (Çatalho yu k, Go beklitepe, Karahantepe, etc.), possesses a wide variety of sourdoughs. In this study, the general characteristics of Turkish sourdough breads, their cultural values, and the health and technological effects of sourdough are explained in the light of the information obtained through the document examination method. The stoves or ovens where sourdough breads are baked, fuels, and kitchen utensils used in bread preparation are clarified. In Tu rkiye, up to 21 types of traditional sourdough-making methods have been find. It’s determined that sourdough types are made such as yoghurt water (zembek), ayran (waterry yoghurt), flower, chickpea, potato, onion, ash, grape, dew, tarhana, colostrum, pinecone and date sourdough. The most common microorganisms in Turkish sourdough include Lactobacillus plantarum, L. paraplantarum, L. brevis, L. pentosus, L. curvatus, Lactococcus lactis ssp. lactis, Saccharomyces cerevisiae, Kazachstania servazzii, and K. humilis. Sourdough breads display medium-high to high volumes such as Trabzon Vakfıkebir bread) while others are low-volume breads (such as yufka-phyllo dough, bazlama, pita-pide breads. The majority of these breads are produced using traditional methods and are baked in different wood-fired stoves and stone ovens burnt with kind of woods such as alder, oak, pine, fir, hornbeam, olive, willow, poplar, cherry, apple, plum, peach tree woods, plant and animal wastes. Turkish sourdough breads also have a positive effect on health, and sourdoughs have a technological improvement effect on bread. Turkish sourdough breads have many sociological and gastronomic features. © (2023), (Elite Scientific Publications). All Rights Reserved
Building an eco-friendly, biocompatible, and ratiometric NIR fluorescent sensor for the rapid detection of trace Pd2+ in real samples and living cells
No full textThe increasing industrial use of palladium has led to its environmental accumulation, raising concerns about its toxicity to aquatic life and human health. Therefore, fluorescent probes capable of detecting Pd2+ are highly beneficial. With this objective, a new near-infrared (NIR) fluorescent probe based on a cyanine dye, 2 ((E)-2-((E)2-((dimethylcarbamothioyl)oxy)-3-(2-((Z)-1,3,3-trimethylindolin-2ylidene)ethylidene)cyclohex - 1-en-1-yl) vinyl)-1,3,3-trimethyl-3H-indol-1-ium iodide (CNS), was synthesized for selective and rapid detection of Pd2+. The detection reaction followed the elimination of thiocarbamate moiety, leading to the highly fluorescent product. CNS demonstrated remarkable sensitivity (detection limit: 0.105 mu M), high selectivity, short response time (1.0 min), long lifetime (0.88 ns), and easily detectable color changes upon Pd2+ exposure. A CNS-loaded TLC strip integrated with a smartphone detection system was able to detect Pd2+ in solutions, soil, and drug samples. In addition, CNS enabled concentration-dependent detection of Pd2+ in onion roots and epidermis. Because of low cytotoxicity, good membrane permeability, NIR fluorescence, and high contrast, CNS has been successfully applied to Pd2+ bioimaging in living cells, targeting mitochondria. Compared to existing probes, CNS offers superior sensitivity, selectivity, and adaptability for sensing applications
Endomorphisms on prime rings with antiautomorphisms
No full textIn this paper, the authors explored functional identities involving endomorphisms (Gamma) and antiautomorphisms (Xi) on prime rings, focusing on their impact on commutativity. The results show that a prime ring R, where the characteristic of R is not equal to two, with an antiautomorphism Xi that is non-linear over the center ZR of the ring R, and an endomorphism Gamma satisfies commutativity under conditions such as Gamma(Xi(u)u)-/+[Xi(u),u]is an element of ZR, Gamma(Xi(u)u)-/+Xi(u)degrees u is an element of ZR, or Gamma(Xi(u)u)-/+ u Xi(u)is an element of ZR. Additionally, when Gamma is a non-identity endomorphism, commutativity follows if Gamma(Xi(u)u)-Xi(u)u is an element of ZR. Furthermore, R is either commutative or can be embedded in (2x2) matrices over a field if Gamma(Xi(u)u)+Xi(u)u is an element of ZR. Examples are provided to highlight the necessity of these conditions and to demonstrate the practical implications of the findings
Design and practical implementation of a novel hyperchaotic system generator based on Apéry's constant
No full textModern chaotic systems necessitate high levels of randomness and complexity, which can be achieved through adaptable seed functions. This paper proposes a new 2D Apéry chaotic system generator (2D-ACG) based on Apéry numbers to fulfill this need. The 2D-ACG generates various chaotic systems using classical seed functions. The effectiveness and the capabilities of 2D-ACG are demonstrated on three well-known example chaotic maps using pairs of seed functions such as Cos-Cos, Sin-Sin and Cos-Sin. The reliability of chaos metrics, such as the Lyapunov exponent (LE), sample entropy (SE), correlation dimension (CD), Kolmogorov entropy (KE), C0 test, and sensitivity, confirms the chaotic performance of these maps. This is further supported by a comparison with reported 2D chaotic systems. Furthermore, one of the maps derived from 2D-ACG has been implemented into an image encryption algorithm and has successfully passed the cryptanalysis tests. Additionally, the hardware implementation of 2D-ACG has been tested on a field programmable gate array (FPGA), thereby confirming its efficacy. The superior results obtained indicate that the proposed 2D-ACG, with its enhanced diversity and complex structure derived from the Apéry's constant, exhibits higher-performance chaotic characteristics
Enhanced photocatalytic hydrogen evolution via sic loaded ceo2 nanofiber composite
No full textCeO2 is a significant material in the photocatalytic hydrogen evolution reactions due to the high creating ability of oxygen vacancies, high chemical stability and excellent redox properties. However, the wide band gap of CeO2 limits the visible light absorption. In this study, SiC loaded to CeO2 nanofiber catalyst by electrospinning methods to improve the light absorption efficiency and increase the active surface area result in enhanced photocatalytic performance. In the photocatalytic hydrogen evolution reactions medium, which contain eosin Y dye and triethanolamine as a photosensitizer and an electron donor, respectively. The addition of SiC to CeO2 improve the visible light absorption rate, electron transfer efficiency. The hydrogen production rate of CeO2/SiC nanofiber catalyst reaches to 5208 μmol g−1 under visible light irradiation, it is approximately 13- and 2-times higher than SiC and CeO2 nanofiber, respectively. Furthermore, CeO2/SiC nanofiber catalyst maintain more than half of it is photocatalytic activity after 3 cycles of reactions. Therefore, the CeO2/SiC nanofiber catalyst will provide innovative approaches to achieve efficient photocatalytic water splitting in the future, enabling the development of catalytic studies. © 202
Machine learning-assisted evaluation of antioxidant and metal chelating capacities in in vitro propagated ceratophyllum demersum l. under different led light conditions
No full textThe aim of this study is to explore the effects of different LED light spectra on the antioxidant capacity of Ceratophyllum demersum L. under in vitro culture conditions, using machine learning techniques to predict and analyze the plant's metabolic responses. Both White and Red LEDs achieved 100% shoot regeneration, with Red LED producing the highest shoot count (85.27) and longest shoots (3.16 cm). Additionally, antioxidant analysis showed significant variations in phenolic and flavonoid content based on light and extraction methods. Red LED acetone extracts had the highest phenolic content (63.99 mu g GAE/mg), while Blue LED acetone extracts yielded the highest flavonoid content (167.58 mu g QE/mg). White LED acetone extracts showed the strongest DPPH scavenging activity (90.14% at 400 mu g/mL), indicating broad-spectrum light enhances antioxidants. Metal chelation was highest in White LED water extracts. Numerous machine learning techniques were employed to predict DPPH radical scavenging and metal chelation activities. XGBoost emerged as the top-performing algorithm for DPPH activity prediction, achieving the lowest MAE (3.754) and the highest R-2 (0.887), along with one of the lowest RMSE values (5.027). MLP (Multilayer Perceptron) also showed strong performance with relatively low RMSE (5.528) and MAE (4.200) on the test set. For metal chelation activity, Cubist demonstrated the best performance, with the lowest test RMSE (5.129) and MAE (4.141) values, along with one of the highest R-2 values (0.899). This study highlights the potential of machine learning algorithms in predicting antioxidant activities and the significant impact of light conditions on these activities
Parameter estimation and validation of cascaded DC-DC boost converters for renewable energy systems using the IGWO optimization algorithm
No full textThe voltage amplitude generated by renewable energy sources is often unstable, necessitating the use of power electronic circuits for effective grid integration. Among these, DC-DC converters play a critical role in maintaining a constant DC link voltage, typically 400 V or 800 V, at the input of inverter circuits that supply power to the load or the grid. The study focuses on the voltage gain behavior of a high-gain dual cascaded DC-DC boost converter designed for PV (photovoltaic) power systems. Using ANSYS Electronics software with its parametric solver, a comprehensive dataset was generated based on key parameters such as input voltage, power switch duty ratio, and switching frequency. The Improved Grey Wolf Optimizer (IGWO) algorithm was employed to estimate mathematical models for this dataset using linear and quadratic equations. The accuracy of the proposed models was validated across six test scenarios, demonstrating superior performance compared to traditional optimization algorithms, including Harmony Search (HS), Particle Swarm Optimization (PSO), Differential Evolution (DE), and the standard Grey Wolf Optimizer (GWO). Experimental validations yielded output voltages of 23.5 V and 36.1 V for input voltages of 4.8 V and 6.2 V, respectively, closely aligning with simulation results of 23.113 V and 36.447 V. The findings, supported by detailed simulations and graphical analyses, highlight the IGWO algorithm's precision and reliability in predicting converter output voltages under variable input conditions. This work advances renewable energy systems integration by enhancing the modeling and performance of cascaded DC-DC boost converters
Cryogen free 60 mhz 1h-nmr spectroscopy-based fingerprinting and chemometrics for the assessment of cold pressed black cumin (nigella sativa l.) seed oil adulteration
No full textWith current advances in the nuclear magnetic resonance (NMR) instrumentation, miniaturized cryogen-free low field spectrometers denote a technological breakup. This analytical strategy is utilized in wide range of scientific areas and provide an excellent approach to obtain data related for the structural characterization and fraud implementations in valuable edible oils. Herein, we aimed to study the feasibility and efficiency of cryogen-free benchtop NMR spectroscopy (60 MHz) with chemometrics for the detection of cold pressed black cumin (Nigella sativa L.) seed oil (BCSO) adulteration. This very simple and effortless procedure based on the glycerol backbone signals of triglycerides was highly adequate to detect adulteration qualitatively and quantitatively. The most popular chemometrics models of principle component analysis (PCA), hierarchical cluster analysis (HCA), soft independent modeling of class analogy analysis (SIMCA) and linear discriminant analysis (LDA) were built over the integrated data of NMR spectroscopy recorded from different oil samples. The partial least squares-regression (PLS-R) analysis models were also constructed to detect quantitative detection limits for the cheap refined cottonseed oils (CSOs) and sunflower oils (SFOs) in adulterated mixture sets (n = 144). The samples were acceptably classified in their own types with an accuracy of 100% by the SIMCA and LDA model. The PLS-R results revealed that the detection limits of adulterant were 0.03% for BCSO-CSO (R2 = 0.9999%) and 0.13% for BCSO-SFO binary mixtures (R2 = 0.9999%), respectively. Consequently, the low-field 1H-NMR spectroscopy allied with multivariate data analyses is expected, in the coming years, to become even more powerful analytical application for the detection of food frauds
The potential histopathological effect of sunset yellow fcf on lungs and hearts of developing mice
No full textPurpose: Existing research on the effects of azo dyes on human health is insufficient and often contradictory. Children are more exposed to the negative effects of food dyes than adults because they consume more foods and drinks containing food dyes. The research aimed to address the potential histopathological impacts of Sunset Yellow on the lungs and hearts of developing mice. Design/methodology/approach: About36 adult male Swiss albino mice were separated into six groups (n: 6). The groups were created, including three treatment groups (four, eight and 10 weeks old) and three control groups. Sunset Yellow (a dose level of 30 mg/kg/bw) per week was administered orally for 28 days to the treatment groups, while the control groups were not treated. On the final day of the research, the mice were sacrificed by cervical dislocation, and their lungs and hearts were removed. The tissues were preserved in 10% formaldehyde and processed through a series of alcohol and xylene. Then they were dyed with hematoxylin-eosin and evaluated under light and electron microscopy. Findings: Sunset Yellow caused significant increases in mean body weight (p: 0.013), lung weight (p: 0.011) and heart weight (p: 0.049). Hemorrhage, inflammation and vacuole formation were detected in lung tissue, while severe hemorrhage, vacuoles and degenerated cells were observed in heart muscle tissue. Notably, the histopathological changes in lung and heart tissues were more pronounced during the weaning period. Sunset Yellow induced histopathological and physiological abnormalities in the lungs and hearts of mice, suggesting it may adversely affect lung and heart development during weaning and adolescence. Therefore, restricting the use of Sunset Yellow may be warranted in early life stages. Research limitations/implications: Finally, as all studies have limitations, the research has limitations. The limitation of this study is the SY dose applied. Although the selected dose was determined based on the Acceptable Daily Intake (ADI) value used as a reference, investigating the effects of SY at different doses could be beneficial. Additionally, different analytical methods could be applied, and the results could be compared. In today’s society, challenges include a lack of knowledge about the effects of daily consumption of SY on health, limited and outdated resources on the subject and scarcity of field research. Originality/value: Sunset Yellow may be especially harmful during adolescence and adulthood. Highlights: • Sunset Yellow (SY) affected the lungs and hearts of mice developing.• SY caused a rise in the average bodyweight and relative organ weights.• Degeneration noted in lungs and hearts of all age groups of mice.• SY may be especially harmful during childhood and youth. Graphical abstract: (Figure presented.) © 2025, Emerald Publishing Limited