Abstract Background The aim of this study was to identify differences in oral cancer incidence among sexes, age groups and oral sites over time in Iraqi population. Methods Data was obtained from Iraqi cancer registry, differences and trends were assessed with the Wilcoxon matched-pairs signed-ranks test and Regression test, respectively. Results In Iraq from 2000 to 2008, there were 1787 new cases of oral cancer registered, 1035 in men and 752 in women. Cancer at all oral sites affected men more than women. The Tongue other (ICD-02) is the most frequent site follow by lip (ICD-00). Conclusion The decrease in the percent of oral cancer incidence in Iraq not compatible with the high percent of exposure to the risk factors, Iraqi cancer regis

A CRITICAL OVERVIEW IN SELECTED POEMS

This study was conducted at the field of poultry-Abu Gharib/department of Animal Production/college of agricultural engineering Sciences-university of Baghdad, during the period from 12/10/2019 to 24/11/2019 duration (42 days), to demonstrate the effect of adding different levels of Allicin to broiler diet on Glutathione level in blood and histological of thymus gland, total of 225 Ross 308 chicks was used. Birds were randomly distributed into five treatment groups which were: First treatment T1: without additives to diet (control), other treatments T2, T3, T4, T5 was added Allicin at a rate of (800,600,400,200 mg/Kg diet) respectively, and Allicin was added from first day until the end of the experiment for all addition treatments, results

For many years, reading rate as word correct per minute (WCPM) has been investigated by many researchers as an indicator of learners’ level of oral reading speed, accuracy, and comprehension. The aim of the study is to predict the levels of WCPM using three machine learning algorithms which are Ensemble Classifier (EC), Decision Tree (DT), and K- Nearest Neighbor (KNN). The data of this study were collected from 100 Kurdish EFL students in the 2^nd-year, English language department, at the University of Duhok in 2021. The outcomes showed that the ensemble classifier (EC) obtained the highest accuracy of testing results with a value of 94%. Also, EC recorded the highest precision, recall, and F1 scores with values of 0.92 for

In light of what constitutes the cultural factor from a great importance in the context of the incorporation of an active and participant civil society in the process of democracy- building and the achievement of political development, this article tries to look at the concept of the political culture and the civil society with the stand on the nature of existing relationship between them in its theoretical part, then the move to dissection of the civil society crisis in Algeria under the prevalent cultural values for understanding the relationship between the two variables in its empirical part, as a step towards the detection on the pivoting of democratic values in activating the political participation and attainment the democratic co

The study aimed to identify career engagement among school principals, the researcher used descriptive approach and reached the study sample (230) school, principals. The researcher instruments used: career engagement, has been checked and face validity, and construction and consistency of the instruments using internal consistency Cronbach's alpha The study came to the following findings: - The degree of career engagement among school principals was (29.0200) this refers to a higher level, compared with the theoretical average of (27) and the study showed that the results showed no significant statistical differences between school principals in the level of career engagement due to the variable sex.

  Body odour is the smell caused by bacteria feeding on sweat on the skin, especially in the armpit and groin area. Fifty-four volunteers from students and employees of college of Education Ibn Al- Haitham, were surveyed. Data were obtained concerning: subject details and microbial examination. The following conclusions were reached:  1) coagulase negative Staphylococcus was the most common isolate. 2) The most effective antibiotics were amikacin, ciprofloxacin, vancomycin, cephalothin, tobramycin, gentamycin respectively and were least sensitive to methicillin and penicillin G. 3) Alum zirconium and alum chlorohydrate were the most effective antiperspirants.

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

The deprivation Some of the children to exercise some fine motor activities a big problem , as a consequence, this problem plays of the delay in motor development during early childhood , Usually it happens to be the reasons for the lack of the right place to play , and the lack of the presence of the tools needed to play motor, or fear excessive protection by parents for their children as a result of lack of awareness of the importance of physical activity for the child to use his fingertips and fine his muscles . In addition to that small percentage of children spend most of their time in the daily activities and skills of non-motor , Such aswatching television, or play video games or they tend to play computer and mobile but they are

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv