Beta thalassemia major (BTM) is a genetic disorder that has been linked to an increased risk of contracting blood-borne viral infections, primarily due to the frequent blood transfusions required to manage the condition. One such virus that can be transmitted through blood is the Human Parvovirus B19 (B19V). The aim of this study was to investigate the frequency and molecular detection of B19V. This study included 60 blood donors as controls and 120 BTM patients. B19V was identified by serology, which measured B19-IgG and B19-IgM antibodies. Nested Polymerase Chain Reaction (nPCR) was employed to target the VP1/VP2 structural proteins. The results showed that B19V seropositivity represents 27.5% (33 out of 120) in BTM patients, and

Introduction The abortions reasons in several circumstances yet are mysterious, nevertheless the bacterial toxicities signify a main reason in abortion, where germs seems to be the utmost elaborate pathogens (Khameneh et.al., 2014) and (Oliver and Overton ,2014). Between numerous germs, Humano

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

This research aims to find how three different types of mouthwashes affect the depth of artificial white spot lesions. Teeth with various depths of white spot lesions were immersed in either splat mouthwash, Biorepair mouthwash, Sensodyne mouthwash, or artificial saliva (control)twice daily for one minute for 4 weeks and 8 weeks at 37°C. After this immersion procedure, lesion depth was measured using a diagnosed pen score. A one-way analysis of variance, Dunnett T3 and Tukey's post hoc α = .05 were used to analyze the testing data. Splat mouthwash enhanced the WSL remineralization and made the lowest ΔF compared with other mouthwashes in shallow and deep enamel after 4 and 8 weeks of treatment. In the repair groups, after 4 weeks

The study aims to identify the level of cognitive beliefs, as well as to identify the level of self-organized learning strategies among intermediate school students. The study also aims to identify the differences in the level of self-organized learning strategies among intermediate school students in term of gender, branch (scientific, literary). In order to achieve the research objectives, the researcher designed a scale to measure the cognitive beliefs. As for the scale of self-organized learning strategies, the researcher adopted a scale of (Pintrich et al. 1991), which was translated by (Izzat Abdelhamid, 1999) , For self-organized learning strategies, the sample consisted of (400) students from the research population, whic