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Identification of resistant pharmaceuticals in ozonation using QSAR modeling and their fate in electro-peroxone process

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Frontiers of Environmental Science & Engineering 2021年第5期15卷 325-338页

作者： Majid Mustafa Huijiao Wang Richard H.Lindberg Jerker Fick Yujue Wang Mats Tysklind Department of Chemistry UmeåUniversityUmeåS-90187Sweden School of Environment Beijing Key Laboratory for Emerging Organic Contaminants ControlState Key Joint Laboratory of Environmental Simulation and Pollution Control(Ministry of Education)Tsinghua UniversityBeijing100084China

The abatements of 89 pharmaceuticals in secondary effluent by ozonation and the electro-peroxone(E-peroxone)process were investigated.Based on the results,a quantitative structure-activity relationship(QSAR)model was developed to explore relationship between chemical structure of pharmaceuticals and their oxidation rates by ozone.The orthogonal projection to latent structure(OPLS)method was used to identify relevant chemical descriptors of the pharmaceuticals,from large number of descriptors,for model development.The resulting QSAR model,based on 44 molecular descriptors related to the ozone reactivity of the pharmaceuticals,showed high goodness of fit(R^(2)=0.963)and predictive power(Q^(2)=0.84).After validation,the model was used to predict second-order rate constants of 491 pharmaceuticals of special concern(k_(O_(3)))including the 89 studied experimentally.The predicted k_(O_(3))values and experimentally determined pseudo-first order rate constants of the pharmaceuticals’abatement during ozonation(k_(OZ))and the E-peroxone process(k_(EP))were then used to assess effects of switching from ozonation to the E-peroxone process on removal of these pharmaceuticals.The results indicate that the E-peroxone process could accelerate the abatement of pharmaceuticals with relatively low ozone reactivity(k_(O_(3))activity of pharmaceuticals of diverse chemistry and thus predict their fate in ozone-based processes.

关键词： Ozone Electro-peroxone Wastewater quantitative structure activity relationship Advanced oxidation processes

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Comparative Study of Variable Selection Using Genetic Algorithm with Various Types of Chromosomes

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Chinese Journal of Structural Chemistry 2010年第9期29卷 1431-1437页

作者：陈国华陆瑶夏之宁 School of Chemistry and Pharmaceutical Engineering Sichuan University of Science & Engineering College of Materials Science and Engineering Chongqing University College of Bioengineering Chongqing University

In this study,different methods of variable selection using the multilinear step-wise regression（MLR） and support vector regression（SVR） have been compared when the performance of genetic algorithms（GAs） using various types of chromosomes is used.The first method is a GA with binary chromosome（GA-BC） and the other is a GA with a fixed-length character chromosome（GA-FCC）.The overall prediction accuracy for the training set by means of 7-fold cross-validation was tested.All the regression models were evaluated by the test set.The poor prediction for the test set illustrates that the forward stepwise regression（FSR） model is easier to overfit for the training set.The results using SVR methods showed that the over-fitting could be overcome.Further,the over-fitting would be easier for the GA-BC-SVR method because too many variables fleetly induced into the model.The final optimal model was obtained with good predictive ability（R2 = 0.885,S = 0.469,Rcv2 = 0.700,Scv = 0.757,Rex2 = 0.692,Sex = 0.675） using GA-FCC-SVR method.Our investigation indicates the variable selection method using GA-FCC is the most appropriate for MLR and SVR methods.

关键词： support vector regression genetic algorithm variable selection quantitative structure activity relationship multiple linear regression

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