Background: Asthma is a disease of the airways characterized by chronic inflammation associated with airway hyper-responsiveness and airway wall remodeling. Aims of the study: The aims of this study was to determine the prevalence of oral manifestations , identify different microorganism from oral micro flora and determination of salivary IgA and salivary flow rate in asthmatic patients taking different dose of Prednisolone in comparison with control group. Subjects, materials and methods: The study included 17 patients under treatment with Prednisolone (10-20 mg),15 patients take (20-30 mg) of Prednisolone and other 18 patients take (30 – 40mg) of Prednisolone, and 25 healthy control group (10 male and 15 female). Results : The mo

Blockchain represents a new promising technology with a huge economic impact resulting from its uses in various fields such as digital currency and banking; malware represents a serious threat to users, and there are many differences in the effectiveness of antivirus software used to deal with the problem of malware. This chapter has developed a coefficient for measuring the effectiveness of antivirus software. This chapter evaluates the effectiveness of antivirus software by conducting tests on a group of protection programs using a folder containing an amount of data. These programs are applied to combat viruses contained in this folder. The study revealed that the effectiveness of antivirus software is as follows: AVG scored 0%,

Laser assisted skin wound closure offers many distinct advantages over conventional closure
techniques. The objective of this in vitro experimental study, carried out at the Institute of Laser for
Postgraduate Studies/Baghdad University, was to determine the effectiveness of 980 nm diode laser in
welding of human skin wounds. Multiple 3-4 cm long full thickness incisions in a specimen of human
skin obtained from the discarded panniculus of an Abdominoplasty operation were tried to be laser
welded using a 4 mm spot diameter laser beam from a 980 nm diode laser at different laser parameters
and modes of action. The tensile strength at the weld site was analyzed experimentally. Although laser
assisted wound welding did

Terrestrial Laser Scanning (TLS) can be used to detect damage and analyze volumetric changes in large structural test specimens. Compared to traditional imaging and surface analysis methods, the primary reason for using 3D scanning is the difficulty of attaching targets to towers of varying heights, as well as the fact that some towers are covered with insulating materials that obscure key landmarks. In addition, the large number of incoming and outgoing pipes and stairs attached to the towers further complicates traditional assessment methods. This research focuses on assessing the damage to the three refining towers at the Baiji Refinery facility. Scanning was performed using a 3D laser scanner with HDR color imaging, capturing da

Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification