Background. Gene polymorphisms affect etanercept’s pharmacokinetics, pharmacodynamics, and side effects. This effect is evidenced by the extensive genetic variation in the drug’s targets. Objectives. This study aims to find the association between different genotypes of the promoter region of the TNF-α gene at -308G/A(rs1800629), -857C/T(rs1799724), -863 C/A(rs1800630), -1031 T/C (rs1799964), -806 C/T (rs4248158) and -376 G/A (rs1800750) and the side effects of ETN that occurred to Iraqi RA patients. Method. The trial included patients with rheumatoid arthritis who had been using ETN for at least six months. The participants were from the Baghdad Teaching Hospital Rheumatology Unit. The PCR was sequenced to determine the polymo

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

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

Tin dioxide (SnO2) were mixed with (TiO2 and CuO) with concentration ratio (50, 60, 70, 80 and 90) wt% films deposited on single crystal Si and glass substrates at (523 K) by spray pyrolysis technique from aqueous solutions containing tin (II) dichloride Dihydrate (SnCl2, 2H2O), dehydrate copper chloride (CuCl2.2H2O) and Titanium(III) chloride (TiCl3) with molarities (0.2 M). The results of electrical properties and analysis of gas sensing properties of films are presented in this report. Hall measurement showed that films were n-type converted to p- type as titanium and copper oxide added at (50) % ratio. The D.C conductivity measurements referred that there are two mechanisms responsible about the conductivity, hence it possess two act

Optical fibers were produced by the system manufactured for this purpose and then, PMMA core of polymer optical fiber (POF) and PMMA doped Rhodamine B (RhB) claddings were studied and determine their UV–vis absorption and emission. The study adopted the mechanism of lateral pumping of the product polymer optical fiber by using laser with 404 nm excitation to study optical specifications of the factory fiber. It was noted that there were blue shift in maximum peak wavelength in absorption and fluorescence from the doped polymer before use it as clad. The obtained results by using the doping polymer with (RhB) for clad the amplified spontaneous emission ASE seems in fluorescence study. The side excitation shows that there were no an over

 Polyaniline organic Semiconductor polymer was prepared by oxidation polymerization by adding hydrochloric acid concentration of 0.1M and potassium per sulfate concentration of 0.2M to 0.1M of aniline at room temperature, the polymer was deposited at glass substrate, the structural and optical properties were studies through UV-VIS, IR, XRD measurements, films have been operated as a sensor of vapor  H₂SO₄ and HCl  acids.