This research presents a comparison of performance between recycled single stage and double stage hydrocyclones in separating water from water/kerosene emulsion. The comparison included several factors such as: inlet flow rate (3,5,7,9, and 11 L/min), water feed concentration (5% and 15% by volume), and split ratio (0.1 and 0.9). The comparison extended to include the recycle operation; once and twice recycles. The results showed that increasing flow rate as well as the split ratio enhancing the separation efficiency for the two modes of operation. On the contrary, reducing the feed concentration gave high efficiencies for the modes. The operation with two cycles was more efficient than one cycle. The maximum obtained effici

In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in di

Thirty nine (12.8%) isolates of Staphylococcus aureus were isolated from 304 healthy human (Nasal swabs). It was found that percentage of males that have S. aureus is more than female's percentage. These isolates (39) were tested with different tests. Twenty seven isolates (69.23 %) were positive for Staphylococcus protein —A (SPA) ,thirty seven ( 94.8 %) were positive for tube coagulase , thirty five ( 89.7 % ) were positive with clumping factor and thirty two ( 82.05 %) had 13 — hemolytic on blood agar. It was found that 100% of the isolates (39 isolates) were positive with one, two or three tests (tube coagulase, clumping factor and SPA).

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

The current work reports a new Schiff base [N1-benzylidenebenezene-1,2-diamine(L) = C20H16N2] has been synthesized from benzaldehyde (C6H5CHO) and O- aminoaniline (O-C6H4(NH2)2. Metal mixed ligand complexes of the Schiff base were prepared from chloride salts of Zn(II), Cd(II) and Hg(II) in ethanol and 8-hydroxyquinoline(8HQ)(C9H7NO) containing sodium hydroxide. All the complexes were characterized on the basis of their; FT-IR and U.V spectra, melting point, molar conductance, and determination of the percentage of the metal in the complexes by flame (AAS). In the all complexes, (8HQ) behaves as a bidentate ligand as primary ligand through –-OH phenolic group and –N groups of pyridine group. Also, the prepared ligand (L) was bidentate i

Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T

Rheumatoid arthritis is an autoimmune diseasecharacterized by chronic inflammationthat affects joints and cartilage. Bone complications such asRA-relatedosteoporosis are one of the most extra-articular manifestations. Many inflammatory mediators are released during RA disease pathophysiology; these mediators stimulate osteoclast genesis of bone by direct effects on RANKL and OPG. The study aimedto measure RANKL, OPG in RA patients treated with Etanercept only and other groups treated with Methotrexate onlyat baseline and after three months to evaluate bone state. An observational case-control prospective study was done on 30 RA patients who received MTX, 30 RA patients who received ETN, and 30 healthy,age-matched control groups. The

CUPPER(||)AND MERCURY (||)Complexes WITH SCHIFF BASE LIGAND FROM BENZIDIN WITH ISATIN AND BENZOIN:SYNTHESIS,SPECTRAL CHARACTERIZATION, THERMAL STUDIES AND BIOLOGICAL ACTIVITIES

The magnetic properties of a pure Nickel metal and Nickel-Zinc-Manganese ferrites having the chemical formula Ni_0.1(Zn_0.4Mn_0.6)_0.9Fe₂O₄ were studied. The phase formation and crystal structure was studied by using x-ray diffraction which confirmed the formation of pure single spinel cubic phase with space group (Fd3m) in the ferrite. The samples microstructure was studied with scanning electron microstructure and EDX. The magnetic properties of the ferrite and nickel metal were characterized by using a laboratory setup with a magnetic field in the range from 0-500 G. The ferrite showed perfect soft spinel phase behavior while the nickel sample showed higher magnetic loss an

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the