Exact Anisotropic Solutions of the Generalized TOV Equation

We explore gravitating relativistic spheres composed of an anisotropic, barotropic uid. We assume a bi-polytropic equation of state which has a linear and a power-law terms. The generalized Tolman-Oppenheimer-Volkoff (TOV) equation which describes the hydrostatic equilibrium is obtained. The full system of equations are solved for solutions which are regular at the origin and asymptotically flat. Conditions for the appearance of horizon and a basic treatment of stability are also discussed.Comment: 14 pages, 9 figure

Faktor Risiko yang Mempengaruhi Kesakitan Diare pada Balita

Data on diarrhea morbidity of children under five years of age, were analysed to study the risk factors influencing diarrhea prevalence. Data of Household Health Survey 1986 were used for the study. The prevalence of diarrhea among 26,139 children aged 0-59 months was 1.9%, the highest rate was among the age group of 12-23 months. Children born to parents without primary education had the highest risk of getting diarrhea (relative risk = RR = 1.46) as compared to those bom to parents with higher education. Children belonging to households of low economic status were more likely to have diarrhea (RR = 7.55) than those of better economic status. Children living in households without access to clean water (RR = 2.21) or latrine (RR = 1.54), had higher risk for diarrhea. More specific analysis of risk factors, by age groups based on the possible different cause of diarrhea, would be necessary for further direction of diarrhea disease control

Neural Network Modelling of Tds Concentrations in Shatt Al-Arab River Water

River water salinity is a big concern in many countries, considering agricultural and drinking usages. Therefore, prediction of amount of Total Dissolved Solid (TDS) is a necessary tool for planning and management of water resources. Shatt Al-Arab river basin in Basrah which is located in south of Iraq suffer from high salinity, therefore use of the water for irrigation and drinking has become problematic. In this regard, prediction of future TDS of Shatt Al-Arab river basin was studied using Artificial Neural Network (ANN). Data measured monthly from January 2007 up to December 2012 at monitoring station in the middle point along to the Shatt Al-Arab river has been used for training of the selected ANN. Some of water quality parameters such as, power of hydrogen (pH), Total Hardness (TH), Magnesium hardness (MgSO4), Calcium hardness (CaSO4), Chlorides (Cl), Sulphates (SO4), turbidity (TU) and electrical conductivity (EC) were considered as inputs for the ANN and Total Dissolved Solid (TDS) was the output of the model. The validation of the neural network model showed very good agreement for predictions of the TDS concentrations between observed and simulated values. The coefficient of correlation (R), during the validation process was found to be (1), and the mean squared error (MSE) was (0.075). This work supports the concept that the neural network approach is a successful method of modelling such complex and nonlinear behavior of TDS in the rivers with different environmental conditions