الخلفية: العقدية المقيحة المعروفة أيضًا باسم ""(GAS) هي احدى مسببات الأمراض ذات الأهمية الصحية العامة، حيث تصيب 18.1 مليون شخص في جميع أنحاء العالم وتقتل 500000 شخص كل عام. الهدف: حددت هذه المراجعة المقالات المنشورة حول عوامل الخطر واستراتيجيات الوقاية والسيطرة لأمراض المكورات العقدية. المواد والأساليب: تم إجراء بحث منهجي لتحديد الأوراق المنشورة على قواعد البيانات الإلكترونية Web of Science و PubMed و Scopus و Google Scholar في مح

Abstract: Recombinant human bone morphogenetic protein-2 (rhBMP-2) and platelet-rich fibrin (PRF) bioactive materials have been used to enhance healing and improve dental implant stability. This study aimed to compare the effect of rhBMP-2 and PRF bioactive materials on dental implant stability at different intervals and to evaluate the correlation of implant length and diameter with implant stability. Two bioactive materials were compared to evaluate their effect on dental implant stability. A total of 32 patients (102 dental implants) were divided into 3 groups: 24 dental implants with bone morphogenetic protein (BMP), 27 dental implants with PRF, and 51 dental implants without BMP or PRF (control group). Data were statistically analyzed

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

Hartree-Fock (HF) method relies in the calculations of nonlinear optical properties (NLO) for benzoic acid molecule. Also, another theoretical study is conducted by using the TD-DFT Density Functional Theory through B3LYP/High Base Set 6-311++G (2d,2p) on Gaussian program09. Moreover, an experimental study has been done to obtain the electrons spectrum for benzoic acid with and without ethanol. While the experimental study is done by using UV/VIS. spectrophotometer. Energy gap values of electronic transition between HOMO and LUMO is obtained from theoretical and experimental results. Consequently, the theoretical result for determining the energy gap calculated from EHOMO-LUMO wasvery close to the results of UV / VIS. spectrum. A theoretica

The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone

The assessment of data quality from different sources can be considered as a key challenge in supporting effective geospatial data integration and promoting collaboration in mapping projects. This paper presents a methodology for assessing positional and shape quality for authoritative large-scale data, such as Ordnance Survey (OS) UK data and General Directorate for Survey (GDS) Iraq data, and Volunteered Geographic Information (VGI), such as OpenStreetMap (OSM) data, with the intention of assessing possible integration. It is based on the measurement of discrepancies among the datasets, addressing positional accuracy and shape fidelity, using standard procedures and also directional statistics. Line feature comparison has been und

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr