Objective: To find out if there are any significant differences between these women's knowledge in the
management of Breast Self-Examination in study and control group regarding some variables.
Methodology: A quasi-experimental design was used. A purposive "non-probability" sample of (260) women who
are employee and students in both colleges (Nursing and Health and Medical Technologies) was selected. The
sample consists of two groups, experimental group (130) includes those in (Nursing college), and control group
(130) in (Health and Medical Technologies). A questionnaire was constructed which included demographic
information, reproductive information, family history, previous medical history, and information about women's
knowledge in managing breast-self examination (BSE). Data were collected through the use of the questionnaire, the
application of the educational program. A post-test was done for the study only which uses the lectures, booklet,
training practices of BSE, and video film. Data analysis was performed through the application of descriptive and
inferential statistical approaches.
Results: There are significant associations between women's knowledge regarding managing BSE and their marital
status, infertility status, lactation and second degree consanguinity; also the study concluded that the educational
program of BSE is necessary for all women in different age groups, with different medical histories, educational
level, occupational status, and considered as an effective mean for the reinforcement of improvement of women's
knowledge regarding managing BSE.
Recommendations: Implementation of proposed model of continuous medical education for women for BSE within
the scope of their work.
Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil
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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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Azo derivative ligand[H3L] have been synthesized by the reaction of diazonium salt of p-amino benzoic acid with orcinol in(1:1)mole ratio. The bidente ligand was reacted with the metal ions MnII,FeIIandCrIIIin(2:1)mole ratio via reflux in ethanol using Et3N as a base to give complexes of the general formula: [ M(H2L)2(H2O)x]Cly The synthesized compounds were characterized by spectroscopic methods[ I.R , UV-Vis, A.A and H1 NMR]along with melting point, chloride content and conductivity measurements. The complexes were screend for their in vitro antibacterial activity against one strain of staphylococcus as Gram(+) positive and one strain of pseudomonas as Gram(-) Negative, using the agar diffusion technique.