Many designs have been suggested for unipolar magnetic lenses based on changing the width of the inner bore and fixing the other geometrical parameters of the lens to improve the performance of unipolar magnetic lenses. The investigation of a study of each design included the calculation of its axial magnetic field the magnetization of the lens in addition to the magnetic flux density using the Finite Element Method (FEM) the Magnetic Electron Lenses Operation (MELOP) program version 1 at three different values of current density (6,4,2 A/mm²). As a result, the clearest values and behaviors were obtained at current density (2 A/mm²). it was found that the best magnetizing properties, the high

Abstract:

Investment in human capital of renewable energy can be relied upon to get to achieve the goals of development is important for Iraq through the intellectual community cards creative able to innovate and develop what is so is study the effect of human investment on economic growth through the adoption of the index of national income as a function of variables independent ( human capital, physical capital) and this is built on the premise that the relationship direct correlation between economic growth and human investment, and it can measure the return on human investment, which is an incentive to increase human capital through education and the development of the economy in general have shown th

A new derivative of PAM, acrylamide was copolymerized with succinic anhydride, and the reaction product reacted with three dyes, anthocyanin, bromophenol, and thymol. The prepared polymers were characterized by X-ray diffraction, FT-IR and UV-visible spectroscopy, proton nuclear magnetic resonance spectrometry, and thermal analysis. FT-IR spectroscopy showed the disappearance of two bands near 3450 and 3380 cm-1 for the stretching vibrations of the primary amine which indicates for the formation of amides. The UV-photolysis of aqueous solutions of different concentrations of the polymers was studied. Polyacrylamide-g-succinic anhydride showed an increase in polymerization under light. An increase of ~ 50% was observed for a 200 mg/L

Background: Systemic sclerosis (SSc) is a chronic autoimmune illness, which is consider by three main features: Sclerotic changes in the skin and internal organs, Vasculopathy of small blood vessels, Particular autoantibodies (1). The most important autoantibodies appeared significantly in SSc patients are anti-topoisomerase I autoantibody (Scl-70), anti-centromere autoantibody (ACA), and anti-RNA polymerase III autoantibody (RNAP3) (2). Anti-centromere antibodies (ACA) are infrequent in rheumatic conditions and in healthy persons but occur commonly in limited systemic sclerosis (CREST syndrome), and rarely appeared in the diffuse form of systemic sclerosis (3). Anti-Ro/SSA and antiLa/SSB, antibodies directed against Ro/La ribonucleoprot

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt