Objectives: Determine the age and gender distribution of children who experience diabetes mellitus (DM) under
the age of 15 years and the presence of some associated factors that might be a predisposing factor for the
disease including obesity.
Methodology: A cross-sectional study was conducted at diabetic clinic in Children Welfare Teaching Hospital
in Baghdad City during 2006. The study sample included diabetic children less than 15 years of age. Data were
taken from the patients' record and by direct interview with the patients' parents. Information included
demographic data, as well as past history of the patient and his/her family relative to diabetes and other immune
diseases.
Results: Data analysis showed t

Demodex spp. mites are external obligate parasites; they are transmitted between hosts through direct contact, and may induce several dermatological symptoms when found in large numbers. However, these symptoms may be similar to other commonly known diseases; this often leads dermatologists to neglect the pathogenic role of these mites. Therefore, a better diagnosis is recommended in order to avoid mistreatment. The aim of this study was to investigate the correlation between Demodex mites and dermatological diseases. Infestation rates in patients suffering from acne, rosacea, folliculitis, and psoriasis were compared with asymptomatic patients, along with the mites’ relation to gender, age, personal hygiene, tim

This research aims at identifying the commitment of satellite news channels in Arabic to the set of important standards that reflect their credibility in dealing with the media material, and considering that these channels give special importance to events in Iraq, as well as the Arab region and the world, decide to choose them and study them with a problem The research was a question about the level of credibility of Iraqi media. This research is descriptive research, which used the survey method on an objective sample of 245 items, while the questionnaire was used as a data collection tool. Seven channels were selected in Arabic for the study. The three most watched channels were chosen. These channels included the channels of Russia t

Many studies revealed that Chlamydia trachomatis is the most prevalent bacteria “that cause sexually transmitted infections in the world.^. Most of these infections are asymptomatic and there is a remarkable relationship between CT infections and male infertility. Therefore, “the present study is established to determine the effect of Chlamydia trachomatis infection on seminal fluid quality in males suffering from infertility compared with fertile males.. “Semen samples were collected from 63 infertile male and 13 fertile male as control group, attending the clinical laboratory for routine seminal fluid analysis. Seminal fluid was analyzed according to World Health Organization guidelines, the whole geno

Delays and disruption are a common issue in both community and personal building programs The problem exists all throughout the world, but it is particularly prevalent in Iraq, where millions of dollars are squandered each time as a outcome. Delays and interruptions may have serious consequences not just for Iraq's construction plans, but also for the country's economic and social status. While numerous studies have been conducted to investigate the factors driving delays and disruption in Iraqi construction projects, slight consideration has been given to by what means project management implements and approaches have affected the occurrence of project delays and disruption. After analyzing the crucial reasons for delays and instability in

Aflatoxin B1 (AFB1) is a mycotoxin produced mainly by fungi Aspergillus flavus in food and animals feed. It is considered as a carcinogenic toxin for human and animals. The current study is designed to investigate the incidence of mycoflora in twenty four samples of local stored maize collected from Iraqi governorates; investigate the presence of aflatoxin B1 on these samples using TLC and ELISA techniques. The fungi recovered from maize samples were Aspergillus flavus (18.57 % ), Fusarium spp. (12.8 % ), A. ocraceus (9.96 % ) , A. terrus (9.07 % ), A. fumigatus (8.46 % ) , Alternaria spp. (6.40 % ) Rhizopus spp. (4.98 % ), A. niger spp., A. oryzae spp. (4.80 % ), Penicillium spp. (4.53 %) A. versicolor spp., Rhizoctonia spp. (4.27 %), A

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing