Biomedical subjects
Publications and source records attributed to A J Chalk.
A range of selective media was used to culture the microbial flora of the dental plaque, tongue and palate, The subjects were five young men who smoked more than twenty cigarettes a day and four who did not smoke. Neisseriae were less numerous on the mucosal surfaces of the smokers.
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We present QSPR models for normal boiling points employing a neural network approach and descriptors calculated using semiempirical MO theory (AM1 and PM3). These models are based on a data set of 6000 compounds with widely varying functionality and should therefore be applicable to a diverse range of systems. We include cross-validation by simultaneously training 10 different networks, each with different training and test sets. The predicted boiling point is given by the mean of the 10 results, and the individual error of each compound is related to the standard deviation of these predictions. For our best model we find that the standard deviation of the training error is 16.5 K for 6000 compounds and the correlation coefficient (R2) between our prediction and experiment is 0.96. We also examine the effect of different conformations and tautomerism on our calculated results. Large deviations between our predictions and experiment can generally be explained by experimental errors or problems with the semiempirical methods.
We present a temperature-dependent model for vapor pressure based on a feed-forward neural net and descriptors calculated using AM1 semiempirical MO-theory. This model is based on a set of 7681 measurements at various temperatures performed on 2349 molecules. We employ a 10-fold cross-validation scheme that allows us to estimate errors for individual predictions. For the training set we find a standard deviation of the error s = 0.322 and a correlation coefficient (R(2)) of 0.976. The corresponding values for the validation set are s = 0.326 and R(2) = 0.976. We thoroughly investigate the temperature-dependence of our predictions to ensure that our model behaves in a physically reasonable manner. As a further test of temperature-dependence, we also examine the accuracy of our vapor pressure model in predicting the related physical properties, the boiling point, and the enthalpy of vaporization.