Objective- the study aim to determine the cardiac patient knowledge about anticoagulant medications using and its relationship with demographic data(age. gender. level of education. occupational). Methodology- A descriptive study(quasi-experimental)design was carried out to determine cardiac patient knowledge consider to using anticoagulant medications . Starting from(1th Jun 2017 to5th October 2018).To achieve the objectives of the study, a non-probability sample (a purposive sample) consisted of random sample comprised of (30) patients were taken anticoagulant medications ..The measurement of patient knowledge were collected through the use of questionnaire which is related to patient knowledge toward using the anticoagulant medications. The questionnaire was interview with cardiac patients who were attended coronary care unit at Al-Sadder Teaching Hospital, and Missan Center of Cardiac Disease and in the Medical Consulting after obtaining agreement from the patients throughout using arabic version of questionnaire. The researcher conducted private meeting with each patient who spends about 25-30 minute to respond to the interview which were developed for the purpose of the study. Instrument validity was determined through content validity, by a panel of experts. Reliability of the instrument was determined through the use of Cronbach Alfa which was (0.85) which are strong acceptable for acute myocardial infarction patients'. Analysis of data was performed through the application of descriptive statistics (frequency, percentage) and inferential statistics (t-test and one way analysis of variance) . Result. when we using mean of score the study showed that low level of knowledge for some items and moderate level of knowledge to other items when ( Low 0.0-0.33) (Moderate 0.34-0.76) (0.67-1.0High).and the result study showed no significant differences between cardiac patient knowledge and demographic data (age, gender ,level of education, occupational) . Recommendation-The researchers recommend the implementation of continuous education programs for cardiac patient about using anticoagulant drugs
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Copper (Cu) is an essential trace element for the efficient functioning of living organisms. Cu can enter the body in different ways, and when it surpasses the range of biological tolerance, it can have negative consequences. The use of different nanoparticles, especially metal oxide nanoparticles, is increasingly being expanded in the fields of industry and biomedical materials. However, the impact of these nanoparticles on human health is still not completely elucidated. This comparative study was conducted to evaluate the impacts of copper oxide nanoparticles (CuO NPs) and copper sulphate (CuSO4 0.5 (H2O)) on infertility and reproductive function in male albino mice BALB/c. Body weight, the weight of male reproductive organs, mal
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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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