ABSTRACT Background: stress is the reactions of the body to forces of a deleterious nature, infections and various abnormal states that tend to disturb its normal physiological equilibrium; It is described as adverse emotions or reactions to unpleasant experiences; Thus, any real or perceived physical, social, or psychological event or stimulus that causes bodies to react or respond have deleterious effects on the general and oral health. The aims of this study were to assess the severity of dental caries among the students with different categories of stressful life events in relation to physicochemical characteristics of whole stimulated saliva. Materials and Methods: the total sample is composed of 300 students (males only) aged 17-18 years old, who are randomly selected from 10 school in the First Al-Karkh/Baghdad. The total sample classified into three categories (less stress, more stress, accumulative stress) according to stressful life events scale (SLE); the sub sample consist of 60 students who are randomly selected from the total sample each category composed of 20 students. Diagnosis and recording of dental caries was assessed according to Decay, Missed, Filled surface index (D1-4MFS) of Muhlemann (1976). Stimulated salivary samples were collected from the 60 students then measuring salivary flow rate; and chemically analyzed to determine salivary interlukin-6 (IL-6), cortisol, and total protein. All data were analyzed using SPSS version 21. Results: Results recorded the highest mean rank value of (DMFS) was among the accumulative stress category of stressful life events scale followed by more stress category, the lowest mean rank value was among less stress category with statistically high significant difference (P< 0.001). For the severity of dental caries (DS) Fraction was higher among the accumulative stress category than more stress and less stress categories respectively (P< 0.001). According to the grades of lesion severity, for all fractions the higher mean rank values was among accumulative stress category with no statically differences except for (D2) was significant (P< 0.05). The data from salivary analysis showed that, the highest values of salivary total protein and (IL-6) were among the accumulative stress category, followed by more stress then the lowest value among less stress category, while the cortisol showed the opposite picture, however all these differences were not significant. DMFS correlated positively with flow rate among less stress and accumulative stress categories and negatively with more stress category, while for (DS) correlated negatively with flow rate with highly significant for more stress category and accumulative category and positively related with significant for low stress category. The salivary constituents showed negative correlation with (DMFS) for all categories of stressful life events scale except for IL-6 and cortisol were positively correlated for accumulative category with non-significant difference. Conclusion: The study revealed that, stressful life events have a significant deleterious impact on the oral and dental health including caries experience as well as the effect on the normal levels of salivary constituents.
In this paper Heun method has been used to find numerical solution for first order nonlinear functional differential equation. Moreover, this method has been modified in order to treat system of nonlinear functional differential equations .two numerical examples are given for conciliated the results of this method.
This investigation aimed to explain the mechanism of MFCA by applying this method on air-cooled engine factory which was suffering from high production cost. The results of this study revealed that MFCA is a useful tool to identify losses and inefficiencies of the production process. It is found that the factory is suffering from high losses due to material energy and system losses. In conclusion, it is calculated that system losses are the highest among all the losses due to inefficient use of available production capacity.
In this paper has been building a statistical model of the Saudi financial market using GARCH models that take into account Volatility in prices during periods of circulation, were also study the effect of the type of random error distribution of the time series on the accuracy of the statistical model, as it were studied two types of statistical distributions are normal distribution and the T distribution. and found by application of a measured data that the best model for the Saudi market is GARCH (1,1) model when the random error distributed t. student's .
Background: Gastro oesophageal reflux disease (GERD) is characterized by diverse symptoms. There is an evidence for a genetic component to Gastro oesophageal reflux disease as supported by familial aggregation of this disease. Aim of the study was to investigate whether certain human leucocyte antigen genes HLA-DRB1 are associated with (GERD).Methods: Patients and controls were prospectively recruited from GIT center at Al-Kindy Teaching Hospital (Baghdad-Iraq) between January 2014 and July 2016. Sixty Iraqi Arab Muslim patients with a history of heartburn and dyspepsia were compared with 100 Iraqi Arab Muslims controls. All study patients and control groups underwent upper gastrointestinal endoscopic examinations and their serums were anal
... Show MoreThe utilization of sugarcane molasses (SCM), a byproduct of sugar refining, offers a promising bio-based alternative to conventional chemical admixtures in cementitious systems. This study investigates the effects of SCM at five dosage levels, 0.25%, 0.50%, 0.75%, 1.00%, and 1.25% by weight of cement, on cement mortar performance across fresh, mechanical, thermal, durability, and density criteria. A comprehensive experimental methodology was employed, including flow table testing, compressive strength (7, 14, and 28 days) and flexural strength measurements, embedded thermal sensors for real-time hydration monitoring, water absorption and chloride ion penetration tests, as well as 28-day density determination. Results revealed clear
... Show MoreSelf-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
... Show MoreMicroalgae have been increasingly used for wastewater treatment due to their capacity to assimilate nutrients. Samples of wastewater were taken from the Erbil wastewater channel near Dhahibha village in northern Iraq. The microalga Coelastrella sp. was used in three doses (0.2, 1, and 2g. l-1) in this experiment for 21 days, samples were periodically (every 3 days) analyzed for physicochemical parameters such as pH, EC, Phosphate, Nitrate, and BOD5, in addition to, Chlorophyll a concentration. Results showed that the highest dose 2g.l-1 was the most effective dose for removing nutrients, confirmed by significant differences (p≤0.05) between all doses. The highest removal percentage was
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