Gastritis can be defined as histological inflammation of the gastric mucosa. It can be classified according to the time course of the disease as acute or chronic, histological findings, anatomic location, and pathological mechanisms. The objective of this study was to evaluation of serum levels of the proinflammatory cytokines IL-8, IL-17 and IL-22 in Helicobacter pylori infection and their association with the degree of gastritis histopathology in a sample of Iraqi patients. The case-control prospective study consists of 60 patients who attended the Gastrointestinal Tract Center at Al-Kindy Teaching Hospital during the period from December 2019 to April 2020. In addition, the control group included 60 apparently healthy individuals. Bio

Academic writing is a key skill for success in academic life, particularly for graduate students of a foreign language. The importance of writing to academic culture, practice, and knowledge building has led to a great deal of research in many fields, including rhetoric and composition, linguistics, applied linguistics, and English for Academic Purposes (EAP). Often, studies and research investigating academic writing are motivated by the need to inform the learning of writing to native and non-native English-speaking students, through both descriptions of professional academic writing as well as through comparisons of novice writer (native and non-native Englishspeaking) and expert production. However, while learning about academic writing

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

The biggest problem of structural materials for fusion reactor is the damage caused by the fusion product neutrons to the structural material. If this problem is overcomed, an important milestone will be left behind in fusion energy. One of the important problems of the structural material is that nuclei forming the structural material interacting with fusion neutrons are transmuted to stable or radioactive nuclei via (n, x) (x; alpha, proton, gamma etc.) reactions. In particular, the concentration of helium gas in the structural material increases through deuteron- tritium (D-T) and (n, α) reactions, and this increase significantly changes the microstructure and the properties of the structural materials. T

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

A simple, sensitive and rapid method was used for the estimate of: Propranolol with Bi (III) to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on a reaction between propranolol and Bi (III) in an aqueous medium to obtain a yellow precipitate. Optimum parameters were studied to increase the sensitivity for the developed method. A linear range for calibration graph was 0.1-25 mmol/L for cell A and 1-40 mmol/L for cell B, and LOD 51.8698 ng/200 µL and 363.0886 ng /200 µL , respectively to cell A and cell B with correlation coefficient (r) 0.9975 for cell A, 0.9966 for cell B, RSD% was lower than 1%, (n = 8) for the

Background: Polymethyl methacrylate (PMMA) is the most commonly used material in denture fabrication. The material is far from ideal in fulfilling the mechanical requirement. The purpose of this study was to evaluate the effect of addition of 3% wt of treated (silanized) Titanium oxide Nano filler on some physical and mechanical properties of heat cured acrylic denture base material. Materials and methods: 100 specimens were constructed, 50 specimens were prepared from heat cure PMMA without additives (control) and 50 specimens were prepared from heat cure PMMA with the addition of TiO2 Nano fillers. Each group was divided into 5 sub groups according to the test performed which was mixed by probe ultra-sonication machine. Results: A highly