Background: Chronic subdural hematoma is a blood collection in the subdural space for more than 3 weeks from the onset of the bleeding. It is more likely to develop in infancy and after the age of 60 years. The incidence of subdural hematoma is 1- 2 per 100,000 people per year.
Objective: To delineate the most common feature aspects of SDH like age, predisposing factors, symptoms and signs and different types of management of the disease.
Patients and Methods: A prospective study of 40 patients from the period January 2012 - January 2014, and conducted in Gazi Al-Hariri Hospital of Surgical Specialties, disregarding the age, complaining of chronic subdural hematoma as proved by CT

This research which is entitled (Devine Beauty), aims at studying the philosophical and literary extensive visions of Andalusian poets in search of pleasure in the beauty of divine self and its impact on the formation of a philosophical frame of mind. It also attempts to investigate the aesthetic aspects that highlight the prestige and greatness and majesty of that absolute beauty.
The most important conclusion of the reach is the Bany Ahmar poets use the beauty of women and the pleasure of wine as cods to reach divine beauty and get the happiness desired with the reflection of absolute beauty in a clear philosophy and thinking of the kingdom of God Almighty.

In recent years, due to the economic benefits and technical advances of cloud
computing, huge amounts of data have been outsourced in the cloud. To protect the
privacy of their sensitive data, data owners have to encrypt their data prior
outsourcing it to the untrusted cloud servers. To facilitate searching over encrypted
data, several approaches have been provided. However, the majority of these
approaches handle Boolean search but not ranked search; a widely accepted
technique in the current information retrieval (IR) systems to retrieve only the top–k
relevant files. In this paper, propose a distributed secure ranked search scheme over
the encrypted cloud servers. Such scheme allows for the authorized user to

Testing is a vital phase in software development, and having the right amount of test data is an important aspect in speeding up the process. As a result of the integrationist optimization challenge, extensive testing may not always be practicable. There is also a shortage of resources, expenses, and schedules that impede the testing process. One way to explain combinational testing (CT) is as a basic strategy for creating new test cases. CT has been discussed by several scholars while establishing alternative tactics depending on the interactions between parameters. Thus, an investigation into current CT methods was started in order to better understand their capabilities and limitations. In this study, 97 publications were evalua

A 20 year-old male was admitted with a history of recurrent palpitations from 5 years. Baseline ECG revealed premature ventricular contractions (PVCs) with delta waves. Stress ECG showed short non-sustained Ventricular tachycardia (VT). Echocardiography showed moderate dilation of the left ventricle with mild reduced systolic function and Ejection fraction was estimated to be 42%. Right ventricle was mildly dilated and hypokinetic. Both atria were mildly dilated. The patient referred to CVC for EP study with possible ablation. The ablation of the focus led to complete suppression of the ectopy. Post-procedure ECG and echocardiography showed normalized rhythm and systolic function.

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a