Background: Swine influenza (also Called pig influenza, swine flu, hog flu and pig flu) is an infection by any one of several types of swine influenza virus (SIV) or S-OIV (Swine-Origin influenza virus) is any strain of the influenza family of viruses that is endemic in pigs. Patients and Methods:- Ninety patients with there families suspected of swine flu who were admitted to Central Teaching Hospital of Pediatric in Baghdad seventy one from Baghdad Al-Kerkh, twelve from Baghdad Al-Rasafa and seven other Iraqi Governorate (1 in Suleimaniya, 2 in Baquba, 4 in Anbar) they were included in a prospective study started from the 1st October till the 30 th of November 2009. Results:- The study revealed from )90( suspected cases the H1N1 Virus Pos

The development of low profile gamma-ray detectors has encouraged the production of small field of view (SFOV) hand-held imaging devices for use at the patient bedside and in operating theatres. Early development of these SFOV cameras was focussed on a single modality—gamma ray imaging. Recently, a hybrid system—gamma plus optical imaging—has been developed. This combination of optical and gamma cameras enables high spatial resolution multi-modal imaging, giving a superimposed scintigraphic and optical image. Hybrid imaging offers new possibilities for assisting clinicians and surgeons in localising the site of uptake in procedures such as sentinel node detection. The hybrid camera concept can be extended to a multimodal detec

Background: Joubert syndrome (JS) is a very rare autosomal recessive disorder characterized by agenesis of cerebellar vermis, abnormal eye movements, respiratory irregularities, and delayed generalized motor development. Retinal dystrophy and cystic kidneys may also be associated with this clinical syndrome. The importance of recognizing JS is related to the outcome and its potential complications. This syndrome is difficult to diagnose clinically because of its variable phenotype. Its neuroimaging hallmarks include the characteristic molar tooth sign and bat wing-shaped fourth ventricle

     As a result of the emergence of new business paradigms and the development of the digital economy, the interaction between operations, services, things, and software across numerous fields and communities may now be processed through value chain networks. Despite the integration of all data networks, computing models, and distributed software that provides a broader cloud computing solution, the security solution is missing or inadequate, and more work is required to strengthen security requirements such as mutual entity trustworthiness, access controls, identity management, and data protection, all aspects of detecting and preventing attacks or threats. In order to combat cybersecurity threats, various international organizatio

Data mining is one of the most popular analysis methods in medical research. It involves finding patterns and correlations in previously unknown datasets. Data mining encompasses various areas of biomedical research, including data collection, clinical decision support, illness or safety monitoring, public health, and inquiry research. Health analytics frequently uses computational methods for data mining, such as clustering, classification, and regression. Studies of large numbers of diverse heterogeneous documents, including biological and electronic information, provided extensive material to medical and health studies.

The concept of transitional justice is newly emerging, as it was mainly associated with addressing issues of serious breaches and abuses of human rights during conflicts and situations resulting from violence and the use of force in societies that are in the process of democratization, as transitional justice aims primarily to restore civil peace and rebuild institutions The state needs multidimensional justice: a judicial system that achieves the rule of law, corrective restoration of the wounds of the past, and a distributive characteristic of the redistribution of wealth.

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from