Background:With an increasing burden of accidents in young age group and particularly among school children, the need of introducing BLS and First response training to the school teachers have become essential. Evidence shows that spontaneous response of the teachers in emergencies is less than 30% and knowledge of basic principles of first Aid is deficient in more than 19% of them. Objective: This study aims to assess existing knowledge, attitudes, and practices towards first aid among schoolteachers and members of school's management committee in Al-Madinah, Saudi Arabia in order to identify the gaps regarding this critical public health problem. Methods: A cross sectional study has been conducted during OctoberDecember 2013, over a sample of 341 school instructors by using non probability quota sampling technique where one third were Saudi male & two third of the sample were female instructors in governmental schools in Al-Madinah . Results: Out of the total responders, 67.3% were less than 40 years old, while 88 % were ever married and 85.7% were of high education. It was found that 93.3% had more than two years of service.It was shown that 30.18% of the participants had encountered with an emergency condition during their service and 29% of them applied the first aid themselves.Overall knowledge of participants was found to be maximal for managing bleeding wounds (76.3%). While minimal knowledge was reported for CPR only by (7.4%) of participants. Regarding attitude of participants, a vast majority (92%) identified need of proper first aid training program in schools. Conclusion:The study showed that our schoolteachers had low level of knowledge about first aid for the emergencies occurring in school. Most of them preferred to call others for help.Copy Right, IJAR, 2016,. All rights reserved.

Background: Lymphedema is a condition in which excessive fluid accumulates in soft tissues. It is a common complication of breast cancer treatments. It can lead to serious consequences and interfere with the activity of daily living. This study aimed to determine the level of awareness of breast-cancer-related lymphedema (BCRL) among women with breast cancer in the Kingdom of Saudi Arabia. This was a descriptive quantitative cross-sectional design that included a convenience sample of women diagnosed with breast cancer in the Kingdom of Saudi Arabia. Data were collected by distributing a self-administrated online questionnaire consisting of four parts, including demographic data (five items), the status of education about BCRL (three items), basic medical history of breast cancer (six items), and BCRL level of awareness of risk factors and management (nine items). Results: In total, 95 out of 135 of participants did not know about lymphedema, 119 of the participants (88.1%) did not receive any explanation about the possibility of lymphedema from their medical team before surgery, and 121 of them (89.6%) did not receive it after surgery. The most significant factor affecting participants’ level of awareness regarding BCRL was the lack of information about the possibility of BCRL occurrence, which was not provided to them by the medical team. Recommendation: Early and continuous education for future management is essential to prevent problems related to BCRL and improve quality of life.

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Analyzing big data poses a great challenge for numerous researchers to explore the data structure. Dimension reduction methods can be used to reduce data dimensionality, taking it from occupying a high-dimensional space to existing in a lower-dimensional space while retaining as much information as possible. Principal Component Analysis is one of the most popular used to reduce the dimensional space. The bootstrap sample is obtained by randomly sampling n times with replacement from the original sample, the method provides easy tool to understand the interactive component and develop the process. There are not enough researches discussed the stability of PCA method using bootstrap method. In this paper, the bootstrap method is used to analyze the stability of PCA results and to estimate the number of PCA in efficient way. The method is used to estimate the number of PCA that needed to classify the data set, and the effectiveness of the discussed techniques is demonstrated through real data sets.

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