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Biochemical properties, organic acid composition, and mineral content of black (Morus nigra L.), white (M. alba L.), and red (M. rubra L.) mulberry genotypes
No full textMulberries (Morus spp.) represent a fruit crop of considerable agricultural, economic, and medicinal importance. In the present study, 22 genotypes belonging to M. nigra (black mulberry), M. alba (white mulberry), and M. rubra (red mulberry) were evaluated for their pomological traits, biochemical composition, and mineral content. Among the investigated genotypes, ‘Çınar-4’ exhibited the highest soluble solids concentration (43.9%), whereas ‘Çüngüş−5’ produced the largest fruits (5.00 g, 27.18 mm in length). The genotype ‘Sur-3’ displayed the maximum total phenolic content (98.02 mg GAE 100 g−1 FW) and antioxidant capacity (17.3 µmol Trolox g−1 FW). Multiple regression analysis (MRA) identified total phenolic content (β = 0.56, p ≤ 0.001) and chlorogenic acid (β = 0.35, p ≤ 0.05) as the major determinants of antioxidant potential. Principal component analysis (PCA) indicated that the first three principal components accounted for 54.73% of the overall variance. Heat map analysis (HMA) further separated the genotypes into distinct clusters, with ‘Silvan-1’ emerging as the most mineral-dense genotype, particularly rich in potassium and calcium. Collectively, these findings provide an in-depth characterization of the biochemical and nutritional diversity within mulberry germplasm, underscoring their value for functional food development and genetic improvement strategies. In particular, ‘Sur-3’ is highlighted as a superior candidate for its elevated phenolic and antioxidant profile, while ‘Silvan-1’ is distinguished by its exceptional mineral composition
Coupled effects of magnetic fields and hydrogenic impurities on the absorption coefficients and refractive index changes in multilayer-quantum dot systems
No full textThis study investigates the optical characteristics of multilayered spherical quantum dots (MSQDs) through the application of the finite element method (FEM). We systematically examine the effects of varying layer dimensions, the presence of a shallow hydrogenic donor impurity, and the application of an external magnetic field on the linear, third-order nonlinear, and total optical absorption coefficients (OACs), as well as refractive index variations. The results reveal strong correlations between structural parameters, magnetic field and shallow donor impurity. In particular, small adjustments in layer thicknesses lead to significant changes in both linear and third-order nonlinear absorption, underscoring the critical influence of quantum confinement. Moreover, the magnetic field is shown to play a pivotal role in tuning the optical properties of the system, markedly affecting both absorption behavior and refractive index modulation. This work provides a comprehensive understanding of how geometrical parameters, impurity presence, and magnetic fields collectively influence the optoelectronic properties of MSQDs. These findings not only deepen fundamental insight but also offer strategic guidance for the design of advanced nanophotonic devices with tailored optical functionalities
Properties of the Set of L∞ Trajectories of the Control Systems With Limited Control Resources
No full textIn this paper, the set of trajectories of the control system described by Urysohn type integral equation is considered. It is assumed that the system is nonlinear with respect to the state vector and affine with respect to the control vector. The closed ball of the space (Formula presented.), is chosen as the set of admissible control functions. The trajectory of the system is defined as multivariable Lebesgue measurable function from the space (Formula presented.) that satisfies the system's equation almost everywhere. Boundedness of the set of trajectories is shown, and it is proved that every sequence of trajectories has a subsequence that converges almost everywhere to a system's trajectory. Existence of the optimal process in the optimal control problem with linear quality functional is presented. It is shown that every trajectory is robust with respect to the fast consumption of the remaining control resource and the set of trajectories as a set valued map depending on (Formula presented.) is continuous with respect to (Formula presented.) in the Hausdorff pseudometric generated by the norm of the space (Formula presented.)
Serratus Posterior Superior Intercostal Plane Block for Analgesia in Arthroscopic Shoulder Surgery: A Case Series.
No full textAccurate prediction of Gamow-Teller beta-decay matrix elements via machine learning: implications for nuclear structure
No full textAccurate prediction of Gamow-Teller (GT) beta decay matrix elements [M(GT)] is essential for elucidating complex nuclear structure phenomena and understanding astrophysical processes. In this study, we employed five advanced machine learning models (Cubist, Support Vector Regression, Extreme Gradient Boosting, Random Forest, and Bayesian Regularized Neural Networks) to predict GT beta decay matrix elements in sd-shell nuclei, using experimental data from NNDC/ENSDF, NUBASE2016, and AME2016. This study systematically compared the predictive performance of traditional theoretical approaches (including the USDB, IM-SRG, CCEI, and CEFT) to that of advanced machine learning models trained based on experimental observations. Our primary objective was to determine whether data-driven models could achieve higher predictive accuracy than computationally expensive theoretical models by learning the complex and nonlinear relationships among experimental parameters that reflect nuclear structure and decay dynamics. The results demonstrate that the Cubist model achieves a significantly lower RMSE (0.073 in the full parameter modeling approach and 0.112 in the reduced parameter modeling approach) and high coefficients of determination (R² = 0.901 and 0.919, respectively), thereby outperforming traditional methods. Furthermore, SHapley Additive exPlanations (SHAP) analysis revealed that a minimal set of critical nuclear parameters predominantly governs GT decay dynamics, thereby enhancing model interpretability without compromising predictive accuracy. Complementing these findings, an online calculator was developed to facilitate rapid, high-fidelity predictions of GT matrix elements. Overall, our study demonstrates that a data-driven approach outperforms established theoretical models. More importantly, by identifying the minimal set of physical observables that govern GT transitions, our work provides crucial insights into the underlying physics of nuclear structure and offers a new benchmark for refining future theoretical models and astrophysical calculations
In silico investigation of the efficacy of benzopyrazine derivatives on breast cancer by VEGFR2 inhibition using ML/DL based CADD software
No full textAngiogenesis is a critical pathway for cancer; The formation of new blood vessels is essential for the growth and metastasis of tumors. VEGF and its receptor VEGFR also play important roles in angiogenesis. VEGFR2 stands out as an important therapeutic target for breast cancer treatment. In this study, the interaction between benzopyrazine derivatives and VEGFR2 was evaluated using computer-based drug design (CADD) models, bioinformatics analyses and complementary computational methods. Biological activity predictions were made by developing the interaction data of 49 benzopyrazine-derived compounds in a virtual environment and by developing a QSAR model. Binding stability of proteins in newly designed structures was demonstrated with molecular dynamics simulations. ADMET predictions reveal that these tables have appropriate pharmacokinetic metabolism. Synthesizability of compounds with the best docking scores was calculated with artificial intelligence using the Retroscheme software. For compound number 46, which has the highest potential, molecular dynamics simulation data for 500 ns were calculated via the Desmond interface and its binding was interpreted. The study particularly shows that compound 46 may be an effective VEGFR2 inhibitor in the treatment of breast cancer
Exploring the potential of the pratfall effect in travel influencer marketing
No full textThis study introduces the use of the pratfall effect as a novel concept in increasing the efficiency and effectiveness of social media influencers (SMIs) in tourism. Drawing on the stereotype content model, the study examines whether the pratfall effect can be associated with perceived warmth and competence and ultimately relates to the travel intentions of customers through its link to travel inspiration. The study also investigates the moderating roles of central and peripheral processing routes based on the elaboration likelihood model. Using a scenario-based survey design, data were collected from 234 Turkish Instagram users who actively follow SMIs. Findings reveal that pratfall-induced perceived warmth and competence toward the SMI are associated with travel inspiration, which mediates followers' travel intentions. The strengths of these effects vary according to the message processing routes of the followers. While peripheral processing corresponds with increased warmth perceptions, central processing relates to enhanced competence perceptions of the SMI. These findings extend the SMI literature and offer practical implications for tourism practitioners to develop efficient and effective influencer marketing strategies.</ul
No cytotoxic silver(I) complexes as antibacterial and antibiofilm agents with BSA and DNA binding properties
No full textAims: A synthesis of four silver(I) complexes was conducted, and they were evaluated for their antimicrobial properties and their ability to inhibit the formation of biofilms. Additionally, their binding affinities to DNA and BSA were investigated. Materials & methods: The complexes, chloro[1-isopropyl-3-(3-methylbenzyl)-5,6-dimethylbenzimidazole-2-ylidene]silver(I) (2a), chloro[1-isopropyl-3-(3-chlorobenzyl)-5,6-dimethylbenzimidazole-2-ylidene]silver(I) (2b), chloro[1-methallyl-3-(3-methybenzyl)-5,6-dimethylbenzimidazole-2-ylidene]silver(I) (2c) and chloro[1-methallyl-3-(3-chlorobenzyl)-5,6-dimethylbenzimidazole-2-ylidene]silver(I) (2d) were prepared in 82–84% yields and fully characterized. The biological properties of both ligands and complexes were evaluated in vitro against S.aureus, E.faecalis, E.coli, A.baumannii, C.albicans, DNA and BSA. Results and conclusions: The complexes 2a-d exhibited a significant inhibitory effect on diverse bacterial biofilms, with percentages ranging from 73.6% to 80.3% for S.aureus, 69.5% to 85.9% for E.faecalis, 76.9% to 88.6% for E.coli, 75.9% to 84.6% for A.baumannii and 70.1% to 82.3% for C.albicans. The most significant activities were observed with complex 2b at 8.5 µM. It was observed that silver(I) complexes exhibited more effective binding to DNA (4.92 × 103 for 2a), while NHC precursors displayed a higher binding affinity for BSA (5.52 × 104 with 1-isopropyl-3-(3-methylbenzyl)-5,6-dimethylbenzimidazole chloride). While the precursors of ligands exhibited significant toxicity at their highest MIC concentrations, the complexes demonstrated minimal toxicity