Background: Automobile spray painting is considered an occupation with a high risk of respiratory impairment and asthma. Exposure to organic solvents used for spraying might be of high risk for development of dysfunction in other organs.
Objective: The study was designed to evaluate the pulmonary and hepatic toxicity due to exposure of automobile painters to organic solvents in work places within the Baghdad governorate area.
Methods: Thirty cross sectional selected male workers employed in automobile body paint shops in two industrial areas within Baghdad city (Al-Sheikh Omar and Al-Rasheed camp regions) were recruited to the study during the period from March to May 2012. Thirty non-exposed students and employees in the college of pharmacy-University of Baghdad, age matched with workers, were included as control group. Pulmonary function test (PFT) was performed for all subjects using flow spirometry and blood samples were obtained for evaluation of serum transaminases (AST and ALT), in addition to serum levels of total bilirubin and albumin. The results were correlated with age of workers and duration of exposure.
Results: The results indicated significant decrease in PFT markers (FVC, FEV1, FEV1/FVC and PEF) compared to control group, while liver function did not significantly affected. Correlation of the PFT markers with age and duration of exposure reveals non significant values.
Conclusion: Spray painting is an occupation which involves the risk of respiratory impairment and also confirms the need of regular medical examinations and implementation of appropriate measures to prevent adverse respiratory effects of workplace exposure in automobile spray painters.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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Net pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.
This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.
The Mishrif formation was
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In this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.
Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
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This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.
The aim of this research is to recognize the tasks undertaken by the headmasters of intermediate schools concerning time- administration, in accordance to the viewpoints of the headmasters of intermediate schools in the Administration of Education of Al-Karkh the Third. The sample of this research consists of (60) headmasters and &n
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