In this research, the results of x-ray diffraction method were used to determine the uniform stress deformation and microstructure parameters of CuO nanoparticles to determine the lattice strain obtained and crystallite size and then to compare the results obtained by two model Halder Wagner and Size Strain Plot with the results of these methods of the same powder using equations during which the calculation of the size of the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (19.81nm) and the lattice strain (0.004065) of the Halder-wagner model respectively and for the ssp method were the results of the crystallite size (17.20nm) and lattice strain (0.000305) respectively. The sa

The purpose of this study is the activation of natural Iraqi bentonite that has been obtained from Wadi Bashira region, in the Western Desert of Iraq, to obtain the Nano particle sized then Nano-Quartz was extracted. This method included bentonite nano particles preparation by purification with HCl solution, calcination, the planetary ball mill to get bentonite in nanometer size and centrifugation to obtain the Nano-quartz. Results of quartz purification process were characterized by Fourier transforms infrared spectroscopy (FTIR), energy dispersive X-ray spectroscopy (EDS) and scanning electron microscope (SEM), particle size analyzer (PSA) and the X-rays diffraction (XRD). All tests have shown almost a clear decline in the proportion o

In this work copper nanopowder was created at different liquid
medias like DDDW, ethylene glycol and Polyvinylpyrrolidone
(PVP). Copper nanopowder prepared using explosion wire process
and investigated the effects of the exploding energy, wire diameter,
the type of liquid on the particle size, and the particles size
distribution. The nanoparticles are characterized by x-ray diffraction,
UV-visible absorption spectroscopy and transmission electron
microscopy (TEM). The x-ray diffraction results reveal that the
nanoparticles continue to routine lattice periodicity at reduced
particle size. The UV-Visible absorption spectrum of liquid solution
for copper nanoparticles shows sharp and single surface Plasmon
r

        In this paper, mixed spinel Co_0.4Zn_0.6Fe₂O₄ ferrite was synthesized by microwave-assisted combustion method. Photocatalytic activity of the as-synthesized sample was investigated against methylene blue dye at room temperature at different exposure times (60-360 min.) under visible light. Phase impurity and surface morphology which are investigated with XRD analysis and field emission- scanning electron microscopy, indicate that a cubic spinel unit cell structure with a crystilite size and lattice constant are 22.5048nm and 8.37Å, respectively. The saturation magnetization exhibited directly from the hysteresis loop is (70.20emu/g). Optical properties for the investigated ferrite

The purpose of this study was to determine the effect of lupine flour (L.f) and lupine protein concentrate (L.P.C) incorporation on chemical, nutritional and sensual qualities characteristics of biscuit (L.P.C) was prepared by isoelectric precipitation method. A standard recipe for biscuit preparation by wheat patent flour used as the control. Wheat flour in the control treatment was replaced with (L.f) and (L.P.C) at levels 10, 20 & 30%. Chemical composition of (L.f), (L.P.C) and biscuit treatments were studied. Results showed that protein contents were 35.35 & 75.80% for (L.F) and (L.P.C), respectively. While they amounted to 14.70, 16.16 & 18.61% for (L.f) incorporated biscuits and

teen sites Baghdad are made. The sites are divided into two groups, one in Karkh and the other in Rusafa. Assessing the underground conditions can be occurred by drilling vertical holes called exploratory boring into the ground, obtaining soil (disturbed and undisturbed) samples, and testing these samples in a laboratory (civil engineering laboratory /University of Baghdad). From disturbed, the tests involved the grain size analysis and then classified the soil, Atterberg limit, chemical test (organic content, sulphate content, gypsum content and chloride content). From undisturbed samples, the test involved the consolidation test (from this test, the following parameters can be obtained: initial void ratio eo, compression index cc, swel

The main aim of this paper is to explain the effect of the aggregation accounting information on the financial, investment, and operational, managerial decision-making and the evaluation of the financial statements after aggregate. The problem of this study is represented in administrative decision-making that takes place under differentiated accounting systems operating within a governmental economic unit that seeks at the same time to achieve a unified vision and goals for the organization. This study was conducted at the College of Administration and Economics /University of Baghdad, and it represents a sample from a community of governmental economic units that apply differentiated accounting systems. The study method is repr

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

     This paper develop conventional Runge-Kutta methods of order four and order five to solve ordinary differential equations with oscillating solutions. The new modified Runge-Kutta methods (MRK) contain the invalidation of phase lag, phase lag’s derivatives, and amplification error. Numerical tests from their outcomes show the robustness and competence of the new methods compared to the well-known Runge-Kutta methods in the scientific literature.

     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing