Leishmania major is a protozoan parasite that causes cutaneous Leishmaniasis disease in human beings and animals. The disease is prevalent in tropical and semitropical countries and has great health importance. The present study aimed to identify the histological changes in the organs infected with L. major and to provide a sophisticated diagnostic method for infection through detecting TGF-β cytokine by immunohistochemistry technique(IHC) from October 2020 to January 2021. A total of 40 samples of paraffin blocks were used for different organs including skin, spleen, liver, kidney, and heart of male and female BALB/c mice, aged 6-8 weeks, which were previously infected subcutaneously with L. major promastigotes at a dose of 1×107 promast

At atmospheric pressure and at a frequency of 9.1 kHz, a constructed magnetically stabilized tornado gliding arc discharge (MSGAD) system was utilized in this study to generate a non-thermal plasma with an alternating voltage source from 2,4,6,8 to 10 kV. Argon gas was used to generate the arc plasma with an adjustable flow rate using a flow meter regulator to stabilize the gas flow rate to 2 L/min. A gliding plasma discharge is achieved by a magnetic field for the purpose of a planned investigation. The influence of the magnetically stabilized tornado gliding arc discharge parameters such as magnetic field and applied voltage on microscopic tornado plasma parameters was studied. The electron temperature1was measured using a Boltzmann plot

The experiment was conducted in the botanical garden of the Department of Life Sciences/ College of Education for Pure Sciences Ibn Al-Haitham for the growing season 2021- 2020 in order to study the effect of urea and NPK fertilizer on some physiological characteristics of watercress plants. The seeds were sown on 10/15/2020 in plastic bags weighing 10 kg of soil. The shoots were sprayed with urea at three concentrations (0, 50, 100) mg L-1 in two sprays, and NPK fertilizer was added as a ground addition at three levels (0, 100, 200) kg H-1 in two sprays in conjunction with urea spraying. The results of the study showed a significant effect for the single treatments. The treatment of spraying with urea at a concentration of 50 mg l-1 . was

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and

The subject of an valuation of quality of construction projects is one of the topics which it becomes necessary of the absence of the quantity standards in measuring the control works and the quality valuation standards in constructional projects. In the time being it depends on the experience of the workers which leads to an apparent differences in the valuation.

The idea of this research came to put the standards to evaluate the quality of the projects in a special system depending on quantity scale nor quality specifying in order to prepare an expert system “ Crystal “ to apply this special system to able the engineers to valuate the quality of their projects easily and in more accurate ways.

Plasma physics and digital image processing technique (DIPT) were utilized in this research to show the effect of the cold plasma (plasma needle) on blood cells. The second order statistical features were used to study this effect. Different samples were used to reach the aim of this paper; the patients have leukemia and their leukocytes number was abnormal. By studying the results of statistical features (mean, variance, energy and entropy), it is concluded that the blood cells of the sample showed a good response to the cold plasma.

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett