Acne vulgaris is a very common, chronic disorder, involving inflammation of the pilosebaceous units that can be varied in presentation and difficult to treat. Inflammatory acne may yield both scarring and pigmentary changes so early and adequate therapy will, in all cases, decrease its severity and may entirely suppress this disease. Serratiopeptidase has anti-inflammatory, anti-edemic and fibrinolytic activity and acts rapidly on localized inflammation. Serratiopeptidase was added in aim to hasten acne resolution. During March to July 2010, A comparative study for a 50 healthy patient suffering from acne was divided into 2 groups: 1^st group treated by common acne modalities and the 2^nd one with same modalities

In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot

Abstract:

The main objective of the research is to build an optimal investment portfolio of stocks’ listed at the Iraqi Stock Exchange after employing the multi-objective genetic algorithm within the period of time between 1/1/2006 and 1/6/2018 in the light of closing prices (43) companies after the completion of their data and met the conditions of the inspection, as the literature review has supported the diagnosis of the knowledge gap and the identification of deficiencies in the level of experimentation was the current direction of research was to reflect the aspects of the unseen and untreated by other researchers in particular, the missing data and non-reversed pieces the reality of trading at the level of compani

 Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved.  In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)

Background: The novel coronavirus disease (COVID-19) is caused by Severe acute respiratory syndrome coronavirus 2 (SARS-Cov2) which utilizes angiotensin converting enzyme2 (ACE2) to invade the host cells. This membrane-bound peptidase is widely distributed in the body; its activity antagonizes the renin-angiotensin-aldosterone system (RAAS). Once SARS-Cov2 enters the cell, it causes downregulation of ACE2, resulting in the unopposed activation of RAAS. The unregulated activity of the RAAS system can deteriorate the prognosis in COVID-19 patients. A soluble form of ACE2 (sACE2) was reported to have a role in the SARS-Cov2 invasion of the susceptible cells.

Aim of the study: This study aims to inve

Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

The main objective of this paper is to develop and validate flow injection method, a precise, accurate, simple, economic, low cost and specific turbidimetric method for the quantitative determination of mebeverine hydrochloride (MbH) in pharmaceutical preparations.  A homemade NAG Dual & Solo (0-180º) analyser which contains two identical detections units (cell 1 and 2) was applied for turbidity measurements. The developed method was optimized for different chemical and physical parameters such as perception reagent concentrations, aqueous salts solutions, flow rate, the intensity of the sources light, sample volume, mixing coil and purge time. The correlation coefficients (r) of the developed method were 0.9980 and 0.9986 for