The aim of this paper is to determine the significant levels of some heavy metals such: lead, chromium, nickel and cadmium, were determined. Sources of pollution and their distribution according to presence of elements in the soils over the whole zone of the province of Maysan in southern of Iraq were investigated 36 soil samples from different zones: residential, industrial, commercial, agricultural and main roads, were collected from the soil surface and a depth of 30 cm and analyzed measuring of concentrations for heavy metals by a device ICP-MS technique. The results were compared with global standard levels of these elements in the soil.

Rheumatoid arthritis (RA) is a chronic inflammatory disease associated with decreased antioxidant state .This study aim to investigate the status of oxidant/antioxidant in a sample of  Iraqi patients with RA and the role of peroxynitrite and its natural scavenger uric acid in them .This case-controlled study was conducted at Baghdad teaching hospital /Baghdad from December 2010-May 2011 . Twenty-five patients with mean age 39 years and 25 apparently healthy subject as controls with mean age 29 years were included in the study .Investigations include estimation of serum levels of nitric oxide (NO)  ,peroxynitrite (PN) , malondialdehyde (MDA)  , and uric acid (UA) .Serum PN levels were significantly elevated in RA patients a

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

Worldwide, hundreds of millions of people have been infected with COVID-19 since December 2019; however, about 20% or less developed severe symptoms. The main aim of the current study was to  assess  the  relationship  between  the  severity of Covid-19 and different clinical and laboratory parameters. A total number of 466 Arabs have willingly joined this prospective cohort. Out of the total number, 297 subjects (63.7%) had negative COVID-19 tests, and thus, they were recruited as controls, while 169 subjects (36.3%) who tested positive for COVID-19 were enrolled as cases. Out of the total number of COVID-19 patients, 127 (75.15%) presented with mild symptoms, and 42 (24.85%) had severe symptoms. The age range for the partic

Background : Hyperglycosylated hCG a newly discovered variant of hCG which can be used as a predictor of invasion of trophoblastic cells in patient with gestational trophoblastic disease. Objectives : To measure hyperglycosylated human chorionic gonadotrophin and to assess how far it can be used as predictor of invasion in invasive mole and choriocarcinoma. Study design control study. Setting: : Case Gynecological department in Baghdad Teaching Hospital from January 2016 to January 2017. Patient and Methods : 60 women were enrolled in this study 30 of them were with gestational trophoblastic disease (no.= 30 ) the remainder were normal pregnancy (no. =30) , hCG –H level was measured in both groups. Results : Mean serum hCG-H le

The present study aims to study the correlation between visfatin levels and metabolic syndrome in Iraqi obese adolescence (with and without metabolic syndrome) and its relation with other studied biochemical parameters. Sixty obese adolescences were depended in this study (with and without metabolic syndrome), compared with (30) non-obese children as control group. This study was done in the period from April 2020 until the end of December 2020, in the National Diabetes Centre/Mustansiriya University, Baghdad/Iraq. There were no significant differences in age, height, waist circumferences (WC), and diastolic blood pressure (DBP) in the patients' groups. In contrast, a significant increase differs (p<0.05) was recorded in the values of

Background: Multiple sclerosis is a chronic heterogeneous demyelinating axonal and inflammatory disease involving the Central Nervous System [CNS] white matter with a possibility of gray matter involvement in which the insulating covers of nerve cells in the brain and spinal cord are damaged. This damage disrupts the ability of parts of the nervous system to communicate, resulting in a wide range of signs and symptoms. Cerebral venous insufficiency theory was raised as a possible etiology for the disease at 2008 by Zamboni an Italian cardiothoracic surgeon. This theory was defeated by Multiple Sclerosis[ MS] researchers and scientists who thought that the disease is an autoimmune rather than vascular.

Obj

The research aims to identify intelligence spiritual among a sample of students Baghdad University as well as to identify the differences between students in intelligence spiritual according to variable type (male - female), and variable area of ​​study (Science - a human) and variable (First grade - fourth grade), The research sample consisted of (300) students, were applied scale search - a spiritual Intelligence Scale (prepared by the researcher), has resulted in the search results for: -

The students of the University of Baghdad (sample) enjoyed a high level of spiritual intelligence.
- There are no differences between males and females in the spiritual intelligence.
- There

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc