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Assessment of Ambient Air Quality in Neonatal Incubators at Selected Sites of Baghdad Hospitals
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     An infant incubator in the neonatal intensive care unit (NICU) is a medical instrument of care that provides oxygen, warmth and moisture to a newborn baby. Due to environmental conditions affecting the infants foster babies may experience discomfort and pain at some point. Thus, this study aimed to assess ambient air quality in neonatal incubators to improve the environmental quality of neonatal intensive care units and safety. Air pollutants concentrations consisting of particulate matter (pm2.5, pm10), hydrocarbons (HOCH), volatile organic compounds (VOC), air quality index (AQI), humidity and temperature, were measured at four selected Baghdad hospitals (Al-Karkh and Rusafa) . The results showed that the increase in relative humidity (RH%) measured in all baby incubators and in all locations during the summer and winter seasons contributed to an increase in polluting gases emission inside the incubators, which was the highest measurement that gave significant difference for the incubator.
The highest recorded measurement with significant difference for pm2.5 was 73.78 ± 0.096 in site2 in winter, pm10  was 106.73 ± 0.05  in site1 in winter, HCHO was 0.148 ± 0.005 in site3 in winter, VOC was 673 ± 0.005mg/m3 in site2 in winter,  AQIwas 177.25 ± 0.5 in site2 in  winter, RH% was 53.887 in the site3 during the winter and temperature was 32.25°C in site3 in summer. It can be concluded that there is a relationship between relative humidity and temperature that affectedthe gases concentrations as it showed variations in gases and particle matters concentrations which affected the air quality inside the neonatal incubatorsthat in turn affected the health of the neonates, especially increased severity of asthma attacks and low Intelligence quotient (IQ) in children in the future.

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Estimation Methods for System Reliability Multi-Components model: Exponentiated Weibull Distribution
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        In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through  Monte Carlo simulation technique were made depend on mean squared error (MSE)  criteria

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