In this study, we set up and analyze a cancer growth model that integrates a chemotherapy drug with the impact of vitamins in boosting and strengthening the immune system. The aim of this study is to determine the minimal amount of treatment required to eliminate cancer, which will help to reduce harm to patients. It is assumed that vitamins come from organic foods and beverages. The chemotherapy drug is added to delay and eliminate tumor cell growth and division. To that end, we suggest the tumor-immune model, composed of the interaction of tumor and immune cells, which is composed of two ordinary differential equations. The model’s fundamental mathematical properties, such as positivity, boundedness, and equilibrium existence, are exami

Refractive indices (nD), viscosities (η) and densities (ρ) were deliberated for the binary mixtures created by dipropyl amine with 1-octanol, 1-heptanol, 1-hexanol, 1-pentanol and tert-pentyl alcohol at temperature 298.15 K over the perfect installation extent. The function of Redlich-Kister were used to calculate and renovated of the refractive index deviations (∆nD), viscosity deviations (ηE), excess molar Gibbs free energy (∆G*E) and excess molar volumes (VmE) The standard errors and coefficients were respected by this function. The values of ∆nD, ηE, VmE and ∆G*E were plotted against mole fraction of dipropyl amine. In all cases the obtained ηE, ∆G*E, VmE and ∆nD values were negative at 298.15K. Effect of carbo

Azo-Schiff base compounds (L1 and L2) have been synthesized from the reaction of m-hydroxy benzoic acid with 1,5-dimethyl-3-[2-(5-methyl-1H-indol-3-yl)-ethylimino]-2-phenyl-2,3- dihydro-1H-pyrazol-4-ylamine and with 3-[2-(1H-indol-3-yl)-ethylimino]-1,5-dimethyl-2-phenyl- 2,3-dihydro-1H-pyrazol-4-ylamine. The free ligands and their complexes were characterized based on elemental analysis, determination of metal, molar conductivity, (1H, 13C) NMR, UV–vis, FT-IR, mass spectra and thermal analysis (TGA). The molar conductance data revealed that all the complexes are non-electrolytes. The study of complex formation via molar ratio in DMF solution has been investigated and results were consistent to those found in the solid complexes with a rat

Microbiological contamination by fungi impacts the quality and safety of wheat grain storage. This study aimed to evaluate the efficacy of cold plasma in restricting the growth of the fungus, Aspergillus niger, which was isolated from wheat grains. A dielectric barrier discharge (DBD) operating at atmospheric pressure generated cold plasma that was used to treat the fungus, and the impact of this treatment was investigated at various periods  1, 2, 4, 6, and 15 minutes. The results revealed a highly significant decrease in the growth and number of spores of Aspergillus niger compared to the controls. This study revealed an efficient technique for enhancing wheat grain storage that could be a foundation for further large-scale studies.

The insulation system of a machine coil includes several layers made of materials with different characteristics. The effective insulation design of machine coils, especially in the machine end winding, depends upon an accurate model of the stress grading system. This paper proposes a modeling approach to predict the transient overvoltage, electric field, and heat generation in machine coils with a stress grading system, considering the variation of physical properties in the insulation layers. A non-uniform line model is used to divide the coil in different segments based on material properties and lengths: overhang, stress grading and slot. The cascaded connection of chain matrices is used to connect segments for the representation of the

The Purpose of this research is a comparison between two types of multivariate GARCH models BEKK and DVECH to forecast using financial time series which are the series of daily Iraqi dinar exchange rate with dollar, the global daily of Oil price with dollar and the global daily of gold price with dollar for the period from 01/01/2014 till 01/01/2016.The estimation, testing and forecasting process has been computed through the program RATS. Three time series have been transferred to the three asset returns to get the Stationarity, some tests were conducted including Ljung- Box, Multivariate Q and Multivariate ARCH to Returns Series and Residuals Series for both models with comparison between the estimation and for

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al