This research provides a new method to study praise poetry that can be used as a course to teach English and Arabic to students in the College of Education. This research answers two questions: Is it possible to examine praise poetry as a tagmeme? Is this analysis of great help in teaching English and Arabic to students in the College of Education? The data that will be chosen for the purpose of analysis are two of Shakespeare's sonnets and two of AL Mulik's poems. The sonnets selected for this purpose are 17 and 18. AL Mulik's poems selected for the same purpose are 8 and 9. Each line in both English and Arabic data is numbered by the researcher herself. Then, those lines are grouped into sentences to facilitate the process of analysis. The researcher has relied on Pike and Pike (1977) model for the analysis. The study has reached that AL Mulik's poems and the sonnets are considered as tagmeme and that there is a connection between a AL Mulik's poems and the sonnets. The analysis conducted in this research can be of great help to teach students learning English and Arabic in the College of Education because it supplies them with a novice method of studying the texts to be learned.
Objective(s): The aims of present study to findout the effect of aeromedical evacuation program on flight medics’ knowledge.
Methods: A pre-experimental design is carried in army aviation bases in Iraq, for the period of April 1st 2019 to October 25th 2019. Non-probability "purposive" sample of (30) flight medics are selected from army aviation bases. The questionnaire consisted of two main parts: the demographic characteristics of air paramedics, and the second part included five axes, which are (50) paragraphs related to the knowledge of air paramedics towards emergency injuries. The researcher used the statistical program version 20 to analyze the data, and the stability of the questionnaire was measured through the pre and post
Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
In this research, I estimate the reliability function of cluster function by using the seemingly unrelate
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Background: Osteoporosis is a systemic skeletal disorder that has an impact on general health, dental health and salivary composition. The mineralization of teeth happens simultaneously with that of the skeleton, but if mineral metabolism is disrupted, tooth failures will resemble those that affect bone tissue. Vitamin D plays a key role in bone and tooth mineralization.
Objective: to evaluate the impact of osteoporosis on teeth decay in relation to salivary vitamin D among menopause in Baghdad city.
Subjects and Methods: This study was cross sectional study. The study group consists of
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The research aims at identifying the extent to which the top management in the organization is interested in managing the talents of its employees, through which it can face the competing organizations, as well as the great challenges faced by all organizations in recent years. The task of attracting and maintaining talented human resources is one of the biggest challenges facing Organizations
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Multiple sclerosis (MS) is a chronic, inflammatory, immune mediated disease of the central nervous system, mostly affecting young adults with mean age of 30 years, twice as high in women compared to men. The etiology of MS is not fully elucidated. MS symptoms are directly related to demyelination and axonal loss, along with other psychological symptoms, can result in functional limitations, disability and reduced quality of life (QoL). The QoL assessments in patients with a chronic disease may contribute to improving treatment and could even be of prognostic value. The goals of this study were to compare the QoL of Iraqi patients with relapsing remitting multiple sclerosis (RRMS),using three different diseas
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is
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