The theory of Topological Space Fiber is a new and essential branch of mathematics, less than three decades old, which is created in forced topologies. It was a very useful tool and played a central role in the theory of symmetry. Furthermore, interdependence is one of the main things considered in topology fiber theory. In this regard, we present the concept of topological spaces α associated with them and study the most important results.

The physical behavior for the energy distribution function (EDF) of the reactant particles depending upon the gases (fuel) temperature are completely described by a physical model covering the global formulas controlling the EDF profile. Results about the energy distribution for the reactant system indicate a standard EDF, in which it’s arrive a steady state form shape and intern lead to fix the optimum selected temperature.

Based on the diazotization reaction of 4-aminoacetophenone with sodium nitrite in acid medium to form diazonium salt, which was coupled with Methyldopa to form a violet reddish soluble azo dye with maximum absorbance at 560 nm,a batch procedure had been developed for the estamination of Methyldopa. Under optimum experimental parameters affecting on the development and stability of the colored product, Beer´s law obeyed in the range (0.5-45) ?g.ml-1 with a correlation coefficient (0.9979).The proposed method was successfully applied to the determination of Methyldopa in either pure form and in commercial brands of pharmaceuticals, no interference was observed from common excipients in the formulations. The analytical results obtained by app

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

This contribution aims to investigate volume-dependent thermal and mechanical properties of the two most studied phases of molybdenum nitride (c-MoN and h-MoN) by means of the quasi-harmonic approximation approach (QHA) via first-principles calculations up to their melting point and a pressure of 12 GPa. Lattice constants, band gaps, and bulk modulus at 0 K match corresponding experimental measurements well. Calculated Bader’s charges indicate that Mo–N bonds exhibit a more ionic nature in the cubic MoN phase. Based on estimated Gibbs free energies, the cubic phase presents thermodynamic stability higher than that detected for hexagonl, with no phase transition observed in the selected T–P conditions as detected experimentall