In this research, damping properties for composite materials were evaluated using logarithmic decrement method to study the effect of reinforcements on the damping ratio of the epoxy matrix. Three stages of composites were prepared in this research. The first stage included preparing binary blends of epoxy (EP) and different weight percentages of polysulfide rubber (PSR) (0%, 2.5%, 5%, 7.5% and 10%). It was found that the weight percentage 5% of polysulfide was the best percentage, which gives the best mechanical properties for the blend matrix. The advantage of this blend matrix is that; it mediates between the brittle properties of epoxy and the flexible properties of a blend matrix with the highest percentage of PSR. The second stage included reinforcing the best blend matrix of epoxy-polysulfide (the blend matrix with the best percentage of polysulfide resulted from the previous stage), by different volume percentages of short fibers (Carbon& Glass) separately and randomly. The volume percentages of fibers were (2.5%, 5%, 7.5%, and 10%). The third stage included reinforcing the blend composites with highest percentages of carbon and glass fiber, by different weight percentages of nano-particles (Red mud& Fly ash) separately. The weight percentages of particles were (0.5%, 1%, 1.5%, and 2%). The experimental results showed that blending polysulfide rubber with epoxy increased the damping ratio. As for reinforcement materials, they decreased the damping ratio, where glass fiber composites have significantly higher damping ratio than other composites.
Background: Inflammatory bowel disease (IBD) is a collection of chronic, recurrent inflammatory illnesses of the gastrointestinal system, including Crohn's disease (CD). Infliximab is one of the biological medications used to treat CD. Therapeutic drug monitoring has evolved as a treatment in IBD, aiming to optimize benefit while meeting more demanding, objective end criteria. Objective: To determine the achievement of target trough level (TL), develop anti-drug antibodies (ADAs) to infliximab, assess response to therapy, and study TL relations with different variables. Methods: The present study was cross-sectional and conducted from May 2022 to November 2022. It included 40 CD patients allotted into 2 groups: group 1 patients ach
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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Abstract: Urinary Tract Infections (UTIs) are the most common bacterial infection in humans and a major cause of morbidity and they are the most common cause of hospital visits worldwide. Proper knowledge in identifying factors associated with urinary tract infection may allow the intervention to easily control of the disease in a timely manner. Therefore, the purpose of the study is determining the prevalence of UTI, diagnosis of causative bacterial agents and identifying the factors associated to the urinary tract infection among patients attending Medical City Hospital in Baghdad, Iraq. A total of 237, morning mid-stream urine samples were collected aseptically and the samples were diagnosed according to the standard methods. I
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