Background: Hand, foot, and mouth disease is viral disease caused commonly by coxsackie virus A₁₆ virus. It is a mild disease and children usually recover with no specific treatment within 7 to 10 days. Rarely, this illness may be associated with aseptic meningitis were patient may need hospitalization.

Objective: To determine significance of clinical features of hand, foot and mouth disease.

Methods: A cross sectional study of cases with clinical features of hand, foot and mouth disease visiting the dermatological consultation unit of Al Kindy teaching hospital. Sampling was for Zyona and Edressi Quarter patients over the period of 1^st December 2017

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

In this work, a comparative analysis for the behavior and pattern of the variations of the IF2 and T Ionospheric indices was conducted for the minimum and maximum years of solar cycles 23 and 24. Also, the correlative relationship between the two ionospheric indices was examined for the seasonal periods spanning from August 1996 to November 2008 for solar cycle 23 and from December 2008 to November 2019 for solar cycle 24. Statistical calculations were performed to compare predicted values with observed values for the selected indices during the tested timeframes. The study's findings revealed that the behavior of the examined indices exhibited almost similar variations throughout the studied timeframe. The seasonal variations were

This research aims to clarify the role of Information Technology Competency (ITC) with dimensions' (IT Usage, IT Knowledge, and IT Operations) as an independent variable in the activation of Human Resources Management Practices (HRM Practices) as a dependent variable with dimensions' (Training and Development, Recruitment, Job Design, and Performance appraisal). Based on this, the correlation and effect relationships between the independent and dependent variables are determined by formulating two main hypotheses. There are a significant relationship and effect of IT competency with HRM practices within the dimensions. Furthermore, the scope and population of this research are the Informatics and Communications P

Background: The demand for esthetic orthodontic appliances is increasing; so the esthetic orthodontic archwires were introduced. Among them, Teflon and Epoxy coated stainless steel archwires. The amount of force available from the archwire depends on the structural properties and susceptibility to corrosion. All metallic alloys are changed during immersion in artificial saliva, chlorhexidine mouthwash andtoothpaste, but their behaviors differ from one type to another. They corrode at different rates, which lead to decrease the amount of force applied to the teeth. This in vitro study was designed to evaluate the corrosion pits in stainless steel archwires coated with Teflon and with Epoxy in dry and after immersion in artificial saliva, chl

In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .