Renal function tests are commonly used in clinical practice to look for renal disease, the most common includes the serum urea, uric acid and creatinine. Heart failure patients have a higher incidence of renal function test abnormalities than individuals who do not have heart failure disease. Fifty subjects of adults (male) were divided in to two groups, 25 subjects (healthy) as control (group1) and 25 subjects with heart failure (group 2). Our results indicate that serum uric acid, urea, and creatinine values were significantly elevated (P≤0.05) in patients group (2) compared with healthy group (1). The results also showed, the effect of age categories on uric acid blood urea nitrogen and creatinine values (P≤0.05) and there were no si

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

The main purpose of this paper, is to characterize new admissible classes of linear operator in terms of seven-parameter Mittag-Leffler function, and discuss sufficient conditions in order to achieve certain third-order differential subordination and superordination results. In addition, some linked sandwich theorems involving these classes had been obtained.  

In this study, a double frequency Q-switching Nd:YAG laser beam (1064 nm and λ= 532 nm, repetition rate 6 Hz and the pulse duration 10ns) have been used, to deposit TiO2 pure and nanocomposites thin films with noble metal (Ag) at various concentration ratios of (0, 10, 20, 30, 40 and 50 wt.%) on glass and p-Si wafer (111) substrates using Pulse Laser Deposition (PLD) technique. Many growth parameters have been considered to specify the optimum condition, namely substrate temperature (300˚C), oxygen pressure (2.8×10-4 mbar), laser energy (700) mJ and the number of laser shots was 400 pulses with thickness of about 170 nm. The surface morphology of the thin films has been studied by using atomic force microscopes (AFM). The Root Mean Sq

This research presents the possibility of using banana peel (arising from agricultural production waste) as biosorbent for removal of copper from simulated aqueous solution. Batch sorption experiments were performed as a function of pH, sorbent dose, and contact time. The optimal pH value of Copper (II) removal by banana peel was 6. The amount of sorbed metal ions was calculated as 52.632 mg/g. Sorption kinetic data were tested using pseudo-first order, and pseudo-second order models. Kinetic studies showed that the sorption followed a pseudo second order reaction due to the high correlation coefficient and the agreement between the experimental and calculated values of q_e. Thermodynamic parameters such as enthalpy change (ΔH

Light isotopes, especially closed shell nuclei, have significance in thermonuclear reactions of the Carbon-Nitrogen-Oxygen (CNO) cycle in stars. In this research, 12C(p, γ) 13N and 14N(p, γ) 15O reactions have been calculated by means of Matlab codes to find the reaction rate across a temperature range of 0.006 to 10 GK using non-resonant parts, as well as the astrophysical S- factor S(E) at low energies. It was concluded that the high binding energy of 12C and 14N nuclei make the reaction less probable thus enabling other competitive processes to develop, which enhances the probability of other competitive proton reactions in the CNO cycle.

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Sphingolipids (SLs) are major structural constituents of eukaryotes, including the kinetoplastid parasite Leishmania. SLs are important for cellular trafficking and signaling and participate in different cell functions, such as, differentiation and cell death (apoptosis). In this study we have investigated the viability of Leishmania major wild type (W.T) and L. major knockout LmLCB2, one of two subunits of serine palmitoyl transferase (SPT) after treatment with myriocin (potent inhibitor of SPT) in order to detect the survival and proliferation of the parasites in vitro. This is to focus on the de novo sphingolipids biosynthesis pathway in both Leishmania wild type which can synthesize SPT and knockout Leishmania which genetically ablated

     This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s