Background: Congenital heart disease is one of the most common developmental anomalies in children. These patients commonly have poor oral health that increase caries risk. Dental management of children with congenital heart disease requires special attention, because of their heightened susceptibility to infectious endocarditis. The aims of this study were to assess the severity of dental caries of primary and permanent teeth and treatment needs in relation to nutritional indicator (Body Mass Index) among children with congenital heart disease. Materials and Methods: In this case-control study, case group consisted of 399 patients aged between 6-12 years old with congenital heart disease were examined for dental status in Ibn Al-Bitar spec

Recent studies have revealed some conflicting results about the health effects of caffeine. These studies are inconsistent in terms of design and population and source of consumed caffeine. In the current study, we aimed to evaluate the possible health effects of dietary caffeine intake among overweight and obese individuals.

In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

The research aims to find out the effect of Cognitive Acceleration strategy and random excitement strategy in achievement of geography material and developing the reflective thinking for students of literary fifth class . 

  the researcher depended a partial control experimental design with the three groups(the competence groups of the pre & post tests), The sample is deliberately selected  from first AL-Rusafah Directorate General of Education in Baghdad.  AL.fardoos Interme

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Coronavirus disease 2019 (COVID-19) is a flu-like infection caused by a novel virus known as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). After the widespread around the world, it was announced by the World Health Organization (WHO) as a global pandemic. The symptoms of COVID-19 may arise within 2 weeks and the severity ranged from mild with signs of respiratory infection to severe cases of organ failure and even death. Management of COVID-19 patients includes supportive treatment and pharmacological medications expected to be effective with no definitive cure of the disease. The aims of this study are highlighting the management protocol and supportive therapy especially vitamin D and manifesting the clinical symptoms b