Background: Depression is a state of low mood and aversion to activity, it can affect a person's thoughts, behavior and sense of well-being. It can affect oral health and lead to an increased risk of dental caries. Dental caries is the most common oral infectious diseases that stresses the immune system and causes changes in cellular and molecular components of peripheral blood and C-Reactive Protein is one of these components, considered a key biomarker of inflammation. This study was conducted to assess the effect of depression status on dental caries among 17 years old secondary school female students in relation to salivary C-Reactive Protein. Materials and Methods: A cross sectional study was carried and the whole sample composed of

A total of 96 stool samples were collected from children with bloody diarrhea from two hospitals in Baghdad. All samples were surveyed and examined for the presence of the Escherichia coli O157:H7 and differentiate it from other Non -Sorbitol Fermenting Escherichia coli (NSF E. coli). The Bacterial isolates were identifed by using morphological diagnostic methods, Samples were cultured on liquid enrichment medium, incubated at 37C? for 24 hrs, and then cultured on Cefixime Tellurite -Sorbitol MacConkey Agar (CT- SMAC). 32 non-sorbitol fermenting bacterial isolates were obtained of which 11 were identified as Escherichia coli by using traditional biochemical tests and API20E diagnostic system without differentiation between

Objectives: The study aimed to assess the level of pediatric nurses' knowledge toward children with Guillain-Barre
syndrome (GBS) and to find out the relationships between nurses' knowledge and their demographic data.
Methodology: A purposive “non probability” sample of (30) nurses was selected from medical neurological wards and
Respiratory Care Units of Children Welfare Pediatric Teaching Hospital, Child’s Center Pediatric Teaching Hospital,
AL-Kadhemia Teaching Hospital, Baghdad Teaching Hospital, and Neurological Science Hospital which has started
from March 5
th 2009 to April 30th 2009. The study instrument consists of two parts. The first part is concerned with
nurses' demographical characteristic and the

A total of (90) blood samples were collected from male patients infected with Toxoplasmosis who recovered from COVID- 19 and attended Kamal Alsamiraai Hospital from 15 January to 15 September 2021. We measured anti-Toxoplasma antibodies (IgG and IgM) detected by ELISA, whereas Anti-COVID-19 antibodies (IgG and IgM) were estimated using Elisa and Afilias. The semen characteristics were also studied among fertile, healthy individuals (control group) and sub-fertile patients. Results showed that the mean sperm count was high among the control group (40.5±1.3x 106/ml) compared with that of the sub-fertile patients (10.3±1.75 and 8.8±1.9 x 106/ml for oligozoospermia, and oligoasthenozoospermia respectively), and it was the highest (44.7±1.4

Asbestos is a hazard pollutant to human health, exposure to asbestos cause serious health effects and wide range of asbestos-related diseases such as asbestosis, lung cancer and malignant mesothelioma and it has been classified as carcinogen by the World Health Organization WHO which cause a carcinogenic effects. Fibers of asbestos are mainly released from friction product in brakes and clutch linings and from reinforce agent in the asbestos cement industry. The aim of this was to evaluate the levels of asbestos fibers in surroundings air of some dense traffic points in Baghdad, through winter 2020. Materials and Methods: Samples of airs was carried out by directing air flow to a mixed cellulose ester membrane filter mounted on an open face

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

In this research, beam expander, BEX, is explained and designed for illuminating the
remote flying target. The BEX is optically designed to be suited for Nd:YAG laser of given
specifications. The BEX is modified to be zoom one to meet the conditions of preventing the
receiving unit; i.e the photodetector, from getting saturated at near and far laser tracking.
Decollimation could be achieved by automatic motor, which controls zoom lens of the BEX
according to the required expansion ratio of beam expander