Use of sewer on-line total solids data in wastewater treatment plant modelling.

We describe a neural network model of a municipal wastewater treatment plant (WWTP) in which on-line total solids (TS) sewer data generated by a novel microwave sensor is used as a model input variable. The predictive performance of the model is compared with and without sewer data and with modelling with a traditional linear multiple linear regression (MLR) model. In addition, the benefits of using neural networks are discussed. According to our results, the neural network based MLP (multilayer perceptron) model provides a better estimate than the corresponding MLR model of WWTP effluent TS load. The inclusion of sewer TS data as an input variable improved the performance of the models. The results suggest that increased on-line sensing of WWTPs should be stressed and that neural networks are useful as a modelling tool due to their capability of handling the nonlinear and dynamic data of sewer and WWTP systems.

Characterisation of the chemical and biological properties of molecules with QSAR/QSPR and chemical grouping, and its application to a group of alkyl ethers.

This study presents a QSAR/QSPR modelling and chemical grouping (read-across) approach to provide information on the biological properties of a group of aliphatic ethers, with accurate biological predictions restricted to those physico-chemical and (eco)toxicological properties where the performance of QSAR/QSPR has been shown to be acceptable. The mathematical methods used ranged from multivariate regression models to PLS (partial least-squares), SVM (support vector machines) and Sammon's mapping. A novel grouping approach, based on a set of key descriptors, has been proposed to give a compact picture of the structural and biological properties of the compounds, and to provide a more mechanistic basis for the interpretations of chemical groups. Besides being a straightforward case study, the paper also exemplifies the capabilities and limitations of the methods in predictive toxicology on a more general level.