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

Nano TiO₂ thin films on glass substrates were prepared at a constant temperature of (373 K) and base vacuum (10_-3 mbar), by pulsed laser deposition (PLD) using Nd:YAG laser at 1064 nm wavelength. The effects of different laser energies between (700-1000)mJ on the properties of TiO₂ films was investigated. TiO₂ thin films were characterized by X-ray diffraction (XRD) measurements have shown that the polycrystalline TiO₂ prepared at laser energy 1000 mJ. Preparation also includes optical transmittance and absorption measurements as well as measuring the uniformity of the surface of these films. Optimum parameters have been identified for the growth of high-quality TiO₂ films

In this work, the calculation of matter density distributions, elastic charge form factors and size radii for halo 11Be, 19C and 11Li nuclei are calculated. Each nuclide under study are divided into two parts; one for core part and the second for halo part. The core part are studied using harmonic-oscillator radial wave functions, while the halo part are studied using the radial wave functions of Woods-Saxon potential. A very good agreement are obtained with experimental data for matter density distributions and available size radii. Besides, the quadrupole moment for 11Li are generated.

In this investigation, the mechanical properties and microstructure of Metal Matrix Composites (MMCs) of Al.6061 alloy reinforced by ceramic materials SiC and Al₂O₃ with different additive percentages 2.5, 5, 7.5, and 10 wt.% for the particle size of 53 µ_m are studied. Metal matrix composites were prepared by stir casting using vortex technique and then treated thermally by solution heat treatment at 530 ⁰C for 1 hr. and followed by aging at 175 ⁰C with different periods. Mechanical tests were done for the samples before and after heat treatment, such as impact test, hardness test, and tensile test. Also, the microstructure of the metal matrix composites was examine

The study aimed to investigate the effect of different times as follows 0.5, 1.00, 2.00 and 3.00 hrs, type of solvent (acetone, methanol and ethanol) and temperature (~ 25 and 50)ºc on curcumin percentage yield from turmeric rhizomes. The results showed significant differences (p? 0.05) in all variables. The curcumin content which were determined spectrophotometrically ranged between (0.55-2.90) %. The maximum yield was obtained when temperature, time and solvent were 50ºC, 3 hrs and acetone, respectively.

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

Electro-kinetic remediation technology is one of the developing technologies that offer great promise for the cleanup of soils contaminated with heavy metals. A numerical model was formulated to simulate copper (Cu) transport under an electric field using one-dimensional diffusion-advection equations describing the contaminant transport driven by chemical and electrical gradients in soil during the electro-kinetic remediation as a function of time and space. This model included complex physicochemical factors affecting the transport phenomena, such as soil pH value, aqueous phase reaction, adsorption, and precipitation. One-dimensional finitedifference computer program successfully predicted meaningful values for soil pH profiles and Cu

This article aims to identify the views of media elites on citizen journalism, a new media genre that strays away from the foundations and ethics of professional journalism, thus calling for in-depth exploration and scrutiny into the genre and its commitment to the professional standards of journalism.

For this purpose, the researcher opted for the survey method by distributing a questionnaire to a purposive sample consisting of 407 media elites. The research is also based on Habermas' public sphere theory.

This study aimed to explore the manufacture of high-fat pellets for obesity induction diets in male Wistar rats and determined its effect on lipid profiles and body mass index. It was an experimental laboratory method with a post-test randomized control group. Formulation of high-fat pellets (HFD) and physico-chemical characteristics of pellets were conducted in September 2019. This study used about 28 male Wistar white rats, two months old, and 150-200 g body weight. Rats were acclimatized for seven days, then divided into four groups: 7 rats were given a standard feed of Confeed PARS CP594 (P0), and three groups (P1, P2, P3) were given high-fat feed (HFD FII) 30 g/head/day. The result showed that the mean fat content of Formula II pell

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne