Background: Opportunistic viral infections make an important threat to renal transplantation recipients (RTRs), and with the use of more intense newly-developed immunosuppressive drugs; the risk of renal allograft loss due to reactivation of these viruses has increased considerably. At the top priority of these viruses lie BK polyomavirus (BKV) and human cytomegalovirus (CMV). Reactivation of these viruses in these chronically immunosuppressed RTRs can lead to renal impairment and subsequently allograft loss, unless early detected and properly treated. Objectives: The study aimed to detect and quantify plasma viral load of BKV and CMV in RTRs using quantitative real time PCR (qRT-PCR), in order to study the prevalence of these two viruses i

The objective of this research is to study the possibility of reducing the reflectivity of the front surface of a silicon cell (Si / Si) by using a theoretical design for a single-layer Antireflection Coatings with a thickness of one quarter of the design wavelength. Then, Mathematical programs in MATLAB (10) were designed to study the quantitative efficiency of the cell as a function of the change in the particle size of the coating within the range (400 - 700 nm) wavelength of the visible state of the vertical and oblique state at the (45°) angle. (Ge) was used as an anti-reflective material. It was found that the highest quantitative efficiency was (96.9004%) at design wavelength (λ0= 550 nm)

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

In this research the relation between skin resistances and standard penetration test of over consolidated
clay soils has been studied. The research includes doing boreholes at Babil governorate in Iraq to get
undisturbed samples and standard penetration test. Determination skin friction from direct shear test between
smooth concrete and soil was explored in laboratory for design purposes and correlated with standard
penetration test values. In many foundation design problems, the shear strength between soil and
foundation materials were estimated or correlated without any direct methods for measurement.
Twelve strain controlled direct shear tests were performed simulate the shear strength interaction
between smooth c

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin