he study aimed to purify of Leucine aminopeptidase (LAP) from sera of hyperthyroidism patients and its relation to some thyroid hormones (TSH, T 3 , T 4 ) of subclinical hyperthyroidism and hyperthyroidism patients with lipid peroxidation levels that may be play a role in this diseases. Specimens were collected during the time from Nov 2017 until Jan 2018 from Endocrine and Diabetes Center, blood samples were collected from fifty healthy control and one hundred patients, patients were divided into two groups consisted of (50) with hyperthyroidism and (50) with subclinical hyperthyroidism. The aged for all subjects ranged (15-60) years with body mass ranged ((25- 29) kg/m 2 . The purification is done by addition of ammonium sulfate, dial

Background: Periodontal diseases are bacterial infections of the gingiva, bone and attachment fibers that support the teeth and hold them in the jaw. α-amylase is an enzyme, produced mainly by parotid gland and it seems to play a role in maintaining mucosal immunity. Aims of the study: Determine the salivary levels of α-Amylase and flow rate and their correlations with clinical periodontal parameters(Plaque Index , Gingival Index , Bleeding on Probing , Probing Pocket Depth , and Clinical Attachment Level ) and the correlation between α-Amylase with flow rate of study groups that consist of ( patients had gingivitis and patients had chronic periodontitis with different severities(mild ,moderate ,severe) and control group . Ma

Let G be a graph, each edge e of which is given a weight w(e). The shortest path problem is a path of minimum weight connecting two specified vertices a and b, and from it we have a pre-topology. Furthermore, we study the restriction and separators in pre-topology generated by the shortest path problems. Finally, we study the rate of liaison in pre-topology between two subgraphs. It is formally shown that the new distance measure is a metric

A laboratory experiment studied the effects of the green tea (Camellia sinensis L.) aqueous extract at concentrations of 10, 20, and 30 ppm on the germination and growth traits of the mung bean (Vigna radiata L.), carried out in 2021 at the Department of Biology, College of Education for Pure Sciences, Ibn Al-Haitham, University of Baghdad, Iraq. The results showed that Camellia sinensis green tea extracts played a vital role by significantly boosting all the examined characteristics compared with the control treatment. The aqueous extract of Green tea at concentrations of 10 and 20 ppm gave the best performance in increasing germination rates, germination speed, plant promoter indicator, and seedling strength compared with the control trea

       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

Metabolic dysregulation and obesity are associated with many metabolic alterations, including impairment of insulin sensitivity and dyslipidemia. Recent studies highlight the key role of phosphatidylinositol 3,4,5-triphosphate-dependent Rac exchange proteins (PREX proteins) in the pathogenesis of obesity, advocating further elucidation of their potential therapeutic implications. The present study aimed to estimate the serum level of PREX proteins and its potential association with insulin resistance markers and plasma lipids level in obese and overweight non-diabetic patients. The study included 30 persons classified as obese, 30 as overweight, and 30 healthy individuals of similar age and gender. The levels of PREX1 and PREX2 were

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col