In this work, nanostructure zinc sulfide (ZnS) thin films at temperature of substrate 450 oC and thickness (120) nm have been produced by chemical spray pyrolysis method. The X-Ray Diffraction (XRD) measurements of the film showed that they have a polycrystalline structure and possessed a hexagonal phase with strong crystalline orientation of (103). The grain size was measured using scanning electron microscope (SEM) which was approximately equal to 80 nm. The linear optical measurements showed that ZnS nanostructure has direct energy gap. Nonlinear optical properties experiments were performed using Q-switched 532 nm Nd:YAG laser Z-scan system. The nonlinear refractive index (n2) and nonlinear absorption coefficient (β) estimated for ZnS nanostructure for different intensities of laser beam. It has been found that n2 and β were decreased with increasing of intensity of incident laser beam. Also, two photon absorption has been observed. The first type of n2 was positive nonlinear reflective index and the second type of n2 was self-focusing nonlinear refractive index for the sample.
Opportunistic fungal infections due to the immune- compromised status of renal transplant patients are related to high rates of morbidity and mortality regardless of their minor incidence. Delayed in identification of invasive fungal infections (IFIs), will lead to delayed treatment and results in high mortality in those populations. The study aimed to assess the frequency of invasive fungal infection in kidney transplant recipients by conventional and molecular methods. This study included 100 kidney transplant recipients (KTR) (75 males, and 25 females), collected from the Centre of Kidney Diseases and Transplantation in the Medical City of Baghdad. Blood samples were collected during the period from June 2018 to April 2019. Twent
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Context and its influence in direction of reference by Abi Hussein Al Basri
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This study was conducted to determine the activity of plant Sesbania rostrata and two isolate from arbuscular mycorrhizae fungi (A,B) as a bioremediation of soil polluted by cadmium and lead elements in north and south of Baghdad city. The results showed that the average of soil pollution by cadmium and lead elements in north of Baghdad was less than the average of soil pollution in the south of Baghdad which recorded 10.0, 9.0 mg/kg and 27.0, 25.0 mg/kg respectively. The plant Sesbania recorded ability to accumulate the lead element in shoot system 19.65 mg/kg and in root system 27.2 mg/kg and for cadmium element 19.6, 24.6 mg/kg in shoot and root respectively. The results showed that the isolate A from soil pollution is more effected
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In the present work, the nuclear shell model with Hartree–Fock (HF) calculations have been used to investigate the nuclear structure of 24Mg nucleus. Particularly, elastic and inelastic electron scattering form factors and transition probabilities have been calculated for low-lying positive and negative states. The sd and sdpf shell model spaces have been used to calculate the one-body density matrix elements (OBDM) for positive and negative parity states respectively. Skyrme-Hartree-Fock (SHF) with different parameterizations has been tested with shell model calculation as a single particle potential for reproducing the experimental data along with a harmonic oscillator (HO) and Woods-Saxo
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Abstract
The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.
In this, search th
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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
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