Objective(s): The main aim of the study is to determine the level of burden on mothers toward children with anorectal malformation.
Methodology: A descriptive study was carried out at Welfare Pediatric Teaching Hospital and Central Pediatric Teaching Hospital in Baghdad City. From November 15th, 2017 to April 29th, 2018. Convenient sample comprised of (140) children mothers with anorectal malformation were interviewed for the study. The instrument of study is composed of six domains related mothers' burden toward psychosocial burden as a result of child with anorectal malformation. Validity of the study instrument was determined through a panel of experts and the reliability of the questionnaire is determined in a pilot study among (14) mothers. Mothers who participated in the pilot study are excluded from the total study sample. The analysis of the data used was descriptive statistics and statistical inferential, in order to find the level of burden of congenital anomalies on mothers.
Results: The study findings indicate that there are highly significant burden impact on a mother who has a child with anorectal malformation.
Recommendations: The study recommended that Psychological support should be provided by health care professionals for the mothers who have children with anorectal malformation.
Laboratory model tests were performed to investigate the behavior of shallow and inclined skirted foundations placed on sandy soil with R.D%=30 and the extent of the impact of the positive and negative eccentric-inclined loading effect on them. To achieve the experimental tests, it was used a box of (600×600) mm cross-sectional and 600mm in height and a square footing of (50*50) mm and 10 mm in thickness attached to the skirt with Ds=0.5B and various an angle of (10°, 20°, 30°). The results showed that using skirts leads to a significant improvement in load-carrying capacity and decreased settlement. In addition, when the skirt angle increased, the ultimate load improved. Load-carrying capacity decreased with increasing eccentri
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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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Water stress has a negative impact on the yield and growth of crops worldwide and consequently has a global impact on food security. Many biochemical changes occur in plants as a response to water stress, such as activation of antioxidant systems. Molybdenum (Mo) plays an important part in activating the expression of many enzymes, such as CAT, POD, and SOD, as well as increasing the proline content. Mo therefore supports the defence system in plants and plays an important role in the defence system of mung bean plants growing under water stress conditions. Four concentrations of Mo (0, 15, 30, and 45 mg·L−1) were applied to plants, using two approaches: (a) seed soaking and (b) foliar application. Mung bean plants were subject
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