A New Approach Based on Artificial Neural Networks for Prediction of High Pressure Vapor-liquid Equilibrium

Abstract: An optimal oil recovery technique for keep a high pressure in oil reservoirs and maintain the oil extraction is Nitrogen injection. Therefore, an extensive comprehending of the phase behavior of the N2 and the crude oil is necessary for applications of N2 in increased oil recovery. In this work a new method based on Artificial Neural N etworks (ANN) for prediction of vapor-liquid equilibrium data of nitrogen-n-pentane system has been proposed. Experimental data were collected from the new research that was done based on static analytical method and after pre-treating were used for training the network. Among this training the back-propagation learning algorithm with various training such as Scaled Conjugate Gradient (SCG), Levenberg-Marquardt (LM), and Resilient Back propagation (RP) methods were used. The most successfully algorithm with suitable number of seven neurons in the hidden layer which gives the minimum Mean Square Error (MSE) is found to be the LM algorithm. Results showed the best estimation performance of ANN and its capability for prediction of the equilibrium data

Risk factors for in-hospital mortality among patients with coronavirus-19 in Isfahan City, Iran

Background: The aim of the study is to explore the risk factors of mortality for hospitalized patients in three designated hospitals in Isfahan province.Materials and Methods: This retrospective cohort study was conducted on all positive coronavirus disease (COVID)-19 patients admitted to Khorshid, Isabn Maryam, and Amin hospitals in Isfahan province. The demographic, clinical, laboratory, and outcome data of patients who were died or discharged from February 24, 2020, to April 18, 2020, were extracted from patient's medical records.Results: Overall 1044 COVID-19 patients were included in this analysis. Based on the findings of this study, older age (& GE;65 years) (adjusted hazard ratio [aHR]: 2.06; 95% confidence interval [CI]: 1.13-3.76), chronic obstructive pulmonary disease (COPD) history (aHR: 2.52; 95% CI: 1.09-5.83), white blood cell (WBC) counts more than 10 x 103/L (aHR: 3.05; 95% CI: 1.42-6.55), Hb level < 13 gr/L (aHR: 2.82; 95% CI: 1.34-5.93), bilateral pulmonary infiltrates (aHR: 2.02; 95% CI: 1.12-3.64) at admission, development of acute respiratory distress syndrome (ARDS) (aHR: 1.87; 95% CI: 1.01-3.47), and intensive care unit (ICU) admission (aHR: 2.09; 95% CI: 1.04-4.18) during hospitalization were risk factors for in-hospital mortality in patients with COVID-19.Conclusions: Multiple factors were found related to the severity and death among COVID-19 patients. We were found that older age (& GE;65 years) with COPD history, high level of WBC, low level of Hb (< 13 g/L), bilateral pulmonary infiltrates at admission, development of ARDS, and ICU admission during hospitalization were identified as risk factors of death among COVID-19 patients. More related studies are needed in the futur