A STUDY ON THE INTERACTION BETWEEN CH_3OH AND H_2CO MOLECULES IN TERMS OF THE PROPERTIES OF CHARGE DENSITY DISTRIBUTIONS

Two possible complexes formed by the interaction of CH_3OH and H_2CO,one hydrogen-bonded (Ⅰ)and one donor-acceptor complex(Ⅱ),have been reported in the previous paper.Based on the ab initio 6-31G basis set calculations,the properties of the charge density for the complexeshave been analyzed using the theory of atoms in molecules.The nature of the complex formation has been discussed in terms of the properties of the charge density distributions.

Representation of phase behavior of associating fluids using EOS

Associating fluids containing water and alkanols show a strong non-ideal behaviour on thermodynamic properties Simple cubic equations of state （EOS）. such as the Peng-Robinson （PR） equation, with conventional mixing rules are popular lbr its simplicity and eas3＇ implementation. However it is incapable of reliably representing the phase behaviour of associating mixtures. An effort has been made in this study to develop a new model in which the non-densit3＇-dependent mixing rules are applied to the PR EOS to represent the phase behaviour of associating fluids. The proposed model takes into account of the polarity in the attractive term of the EOS by including both the conventional random mixing term and the asymmetric interaction term. The proposed model has been successfully applied to the calculation of the vapor-liquid equilibrium （VLE） and liquid-liquid equilibrium （LLE） of fluids containing water, alkanols, acid gases, and hydrocarbons. A satisfactory agreement between the predictions of the proposed model and the experimental data in the literature is reached.

The quest for conditional independence in prospectivity modeling： weights-of-evidence, boost weights-of-evidence, and logistic regression

The objective of prospectivity modeling is prediction of the conditional probability of the presence T = 1 or absence T = 0 of a target T given favorable or prohibitive predictors B, or construction of a two classes {0,1} classification of T. A special case of logistic regression called weights-of-evidence （WofE） is geolo- gists＇ favorite method of prospectivity modeling due to its apparent simplicity. However, the numerical simplicity is deceiving as it is implied by the severe mathematical modeling assumption of joint conditional independence of all predictors given the target. General weights of evidence are explicitly introduced which are as simple to estimate as conventional weights, i.e., by counting, but do not require conditional independence. Complementary to the regres- sion view is the classification view on prospectivity modeling. Boosting is the construction of a strong classifier from a set of weak classifiers. From the regression point of view it is closely related to logistic regression. Boost weights-of-evidence （BoostWofE） was introduced into prospectivity modeling to counterbalance violations of the assumption of conditional independence even though relaxation of modeling assumptions with respect to weak classifiers was not the （initial） purpose of boosting. In the original publication of BoostWofE a fabricated dataset was used to ＂validate＂ this approach. Using the same fabricated dataset it is shown that BoostWofE cannot generally compensate lacking condi- tional independence whatever the consecutively proces- sing order of predictors. Thus the alleged features of BoostWofE are disproved by way of counterexamples, while theoretical findings are confirmed that logistic regression including interaction terms can exactly com- pensate violations of joint conditional independence if the predictors are indicators.