In this research, 152 clinical samples were collected from different hospitals in
Baghdad city, 30 isolates of Proteus spp. were identified from urine, wounds and
burns by using different bacteriological and biochemical assays. It was found that 20
(66.6%) samples were identifies as Proteus mirabilis and 10 (33.3%) samples were
Proteus vulgaris. Among the 30 isolates of Proteus spp., 18 isolates (60%) were
isolated from urine samples; 7 (23.3%) isolates from wounds samples and 5 (16.6%)
isolates from burns samples. Out of 20 isolates of P. mirabilis, 13 (65%) isolates
were from urine samples, 4 (20%) isolates were isolated from wounds samples and 3
(15%) isolates from burns. According to the gender, out of 30 Prot

Background: Insufficient sleep due to excessive media use is linked to decrease physical activity, poor nutrition, obesity, and decreased overall health-related quality of life.

Objectives: To assess the effect of using the internet and social media on the sleep of 4th-stage secondary school students.

Subjects and Methods: Cross-sectional study with the analytic element; for 500 secondary school students, obtained by choosing two schools randomly from each of the six educational directorates, by using a structured questionnaire.

Result: Secondary scho

Al-Yusifia river was assessed at three sampling stations with study period from Autumn 2010 to the end of Summer 2011. The present investigation was carried out on diversity of fungi and bacteria from Al-Yusifia river, Baghdad city. During the study, a total of 12 fungal genus and 6 bacterial genus were isolated during the year seasons. The dominant fungus at the three stations were Penicillium sp., then Rhizopus and Trichophyton   megninii while the dominant bacteria was Escherichia coli and Klebsiella sp.

            The higher

     This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being  0.66975075, 0.470

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19) which represents a global public health crisis. Based on recent published studies, this review discusses current evidence related to the transmission, clinical characteristics, diagnosis, management and prevention of COVID-19. It is hoped that this review article will provide a benefit for the public to well understand and deal with this new virus, and give a reference for future researches.

     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

Many studies dealt with the consequences of  SARS CoV-2  (which cause COVID-19 infection) on the nervous system especially sensory nerves where the virus causes loss of taste and smell as it’s known, and may affect auditory nerves and be the expected cause of some hearing problems. A case-control analytic study was performed on a connivance sample of society of university students from a medical faculty. Each participant filled out a questionnaire contains demographic data and general, auditory and respiratory health condition, in addition to vaccination status. In the other side, the audio- examinations were performed on the study sample including Pure Tone Audiometry (PTA) and tympanometry. Two statistical methods; chi-square and t

Background: Juvenile idiopathic arthritis (JIA) is a chronic disease of childhood. Increased prevalence of periodontal disease and dental caries in juvenile idiopathic arthritis is due to difficulties in executing good oral hygiene. This study was conducted to assess oral health status in patients with Juvenile idiopathic arthritis according to age and duration of illness. Materials and methods: A research was conducted among Juvenile idiopathic arthritis patients attending Baghdad Teaching Hospital with different age and both gender, underwent a clinical evaluation of their dental and oral condition. Diagnosis of dental caries was done according to the criteria of WHO (1997). Dental plaque, gingival condition, calculus were assessed by PI/