Quantitative structure–activity relationship model for prediction study of corrosion inhibition efficiency using two‐stage sparse multiple linear regression

Abstract

A new quantitative structure-activity relationship (QSAR) of the inhibition of mild steel corrosion in 1 M hydrochloric acid using furan derivatives was developed by proposing two-stage sparse multiple linear regression. The sparse multiple linear regression using ridge penalty and sparse multiple linear regression using elastic net (SMLRE) were used to develop the QSAR model. The results show that the SMLRE-based model possesses high predictive power compared with sparse multiple linear regression using ridge penalty-based model according to the mean-squared errors for both training and test datasets, leave-one-out internal validation (Q 2 int = 0.98), and external validation (Q 2 ext = 0.95). In addition, the results of applicability domain assessment using the leverage approach reveal a reliable and robust SMLRE-based model. In conclusion, the developed QSAR model using SMLRE can be efficiently used in the studies of corrosion inhibition efficiency.

Prediction of blood lead level in maternal and fetal us-ing generalized linear model

“…These explanatory variables are: 1 x (Residence, 1 for urban and 0 for rural), 2 x (Pica, 1 for No and 2 for yes), 3 x (Physical activity), 4 x (Chronic disease, 1 for No and 2 for Yes), 5 x (Smoking of mother), 6 x (Smoking of father), 7 x (Diary products intake of mother), and 8 x (Calcium intake of mother). The GLM equation is 1 Using the function glm in STATA 10 program, the obtained results showed in Table 1. From Deviance = 32.656998/( Residual df = 341) the lack of fit for this equation is good since it equal to 0.0957 < 1.…”

“…Great attention has been directed to study maternal and fetal blood lead levels since pregnant women and young children are the most sensitive populations to the lead exposure from various sources [1]. The data was taken from [1], which are representing 350 pregnant women.…”

“…The data was taken from [1], which are representing 350 pregnant women. The obtained data were taken directly from mothers themselves through questionnaire form.…”

“…The classical linear model assumes that the mean of the response variable y is a linear function of a set of predictor variables [1][2][3][4][5][6][7], and that the response variable is continuous and normally distributed with constant variance. As a matter of fact, in many applications, the response variable is categorical or consists of counts or is continuous but non normal, so the ordinary least square method can't be applied to find the regression models [8][9][10][11][12][13][14][15].…”

A novel molecular descriptor selection method inQSARclassification model based on weighted penalized logistic regression

“…The application of the quantitative structure–activity relationship (QSAR) modeling in the field of computational chemistry is widely used . The basic idea behind QSAR modeling is to explore the relationships between the structure of a chemical compound (molecule) and its related chemical and biological activity . The QSAR modeling, in general, is an application of statistical or mathematical methods to develop a model to accurately predict or classify the biological activity of molecules based on their molecular descriptors (structural properties) .…”