Background: Inflammatory bowel disease (IBD) is a collection of chronic, recurrent inflammatory illnesses of the gastrointestinal system, including Crohn's disease (CD). Infliximab is one of the biological medications used to treat CD. Therapeutic drug monitoring has evolved as a treatment in IBD, aiming to optimize benefit while meeting more demanding, objective end criteria. Objective: To determine the achievement of target trough level (TL), develop anti-drug antibodies (ADAs) to infliximab, assess response to therapy, and study TL relations with different variables. Methods: The present study was cross-sectional and conducted from May 2022 to November 2022. It included 40 CD patients allotted into 2 groups: group 1 patients ach

A method is developed for the determination of iron (III) in pharmaceutical preparations by coupling cloud point extraction (CPE) and UV-Vis spectrophotometry. The method is based on the reaction of Fe(III) with excess drug ciprofloxacin (CIPRO) in dilute H2SO4, forming a hydrophobic Fe(III)- CIPRO complex which can be extracted into a non-ionic surfactant Triton X-114, and iron ions are determined spectrophotometrically at absorption maximum of 437 nm. Several variables which impact on the extraction and determination of Fe (III) are optimized in order to maximize the extraction efficiency and improve the sensitivity of the method. The interferences study is also considered to check the accuracy of the procedure. The results hav

This paper proposes a new structure of the hybrid 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. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

The research studied and analyzed the hybrid parallel-series systems of asymmetrical components by applying different experiments of simulations used to estimate the reliability function of those systems through the use of the maximum likelihood method as well as the Bayes standard method via both symmetrical and asymmetrical loss functions following Rayleigh distribution and Informative Prior distribution. The simulation experiments included different sizes of samples and default parameters which were then compared with one another depending on Square Error averages. Following that was the application of Bayes standard method by the Entropy Loss function that proved successful throughout the experimental side in finding the reliability fun

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

This paper addresses the factors responsible for changes in crude oil prices, in real market and financial sector. In order to prepare the analytical background for further investigation, it highlights the patterns of correlations of the real oil price and the most related prices of assets, exchange rate and government bond yield. The paper reviews the statistical behavior of oil price, quantities and the  global macroeconomic environment. Topics discussed include the theory of differential rent and scarcity effect ,the role of  future market and speculation, strategies of energy of the major economies to investigate the prospects of oil market and the potential demand for  OPEC's oil.  The paper explores the

Noor Oil Field is one of Iraqi oil fields located in Missan province / Amarah city. This field is not subjected to licensing rounds, but depends on the national effort of  Missan Oil Company. The first two wells in the field were drilled in seventies and were  not opened to production until 2009. The aim of this study is to study the possibility of using the method of gas lift to increase the productivity of this field . PROSPER software was used to design the continuous  gas lift by using maximum production rate in the design.

   The design was made after comparing  the measured pressure with the calculated pressure, this comparison  show  that the method of Beggs-Brill and Petroleum Exper