Objective(s): This study aims at determining the effectiveness of an educational program on knowledge of high school students' knowledge about substance abuse and its health consequences, and to find out the association between students’ knowledge about substance abuse and its health consequences and their demographic data of age, socioeconomic status, and educational level of parents.
Methodology: A quasi-experimental study is conducted for the period of October 28th, 2019 to March 30th, 2020. The study sample included a nonprobability “purposive” sample of (124) male students (62) students for the control group and (62) students for the study group, aged (14-19) years who are selected from Al-Hikma High School for Boys in Kirkuk City, Iraq. A self-report questionnaire is used for data collection which has included three parts; the first part deals with the students' demographic information, the second part includes students' knowledge about substances and the third part is about students' knowledge of the health effects of substance abuse.
Results: The study results reveal that there is a significant difference in students' knowledge about substance abuse and its health consequences between the post-test knowledge score of the study group. There is no significant relationship between students'' knowledge and their demographic variables of age, parents’ education, and socio-economic status.
Recommendations: The study recommends that providing of an educational program about substance abuse and their consequences as part of the curriculum in high schools is essential and encouraging collaboration between the Ministry of Health and Environment and the Ministry of Education to prevent substance abuse among students.
This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff
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... Show MoreLow-temperature stratification, high-volumetric storage capacity, and less-complicated material processing make phase-changing materials (PCMs) very suitable candidates for solar energy storage applications. However, their poor heat diffusivities and suboptimal containment designs severely limit their decent storage capabilities. In these systems, the arrangement of tubes conveying the heat transport fluid (HTF) plays a crucial role in heat communication between the PCM and HTF during phase transition. This study investigates a helical coil tube-and-shell thermal storage system integrated with a novel central return tube to enhance heat transfer effectiveness. Three-dimensional computational fluid dynamics simulations compare the proposed d
... Show MoreVolatile organic compounds (VOCs) from uninfested and infested broccoli plant samples with green peach aphid