QUANTITATIVE STRUCTURE-ACTIVITY-RELATIONSHIPS FOR TOXICITY OF PHENOLS USING REGRESSION-ANALYSIS AND COMPUTATIONAL NEURAL NETWORKS

Quantitative structure-toxicity models were developed that directly link the molecular structures of a et of 50 alkYlated and/or halogenated phenols with their polar narcosis toxicity, expressed as the negative logarithm of the IGC50 (50% growth inhibitor

A STUDY OF ION KINETIC-ENERGY SPECTROMETRY OF ORTHO-DICHLORO, META-DICHLORO AND PARA-DICHLORO BENZENE DOUBLY CHARGED IONS [C6H4CL2]2+ AND [C6H3CL]2+ IN GAS-PHASE

The unimolecular Charge separation reactions of the doubly charged ions [C6H4Cl2]2+, [C6H3Cl]2+ produced in the ion source by electron impact from o-, m-, and p-dichloro benzene have been studied using mass analysed ion kinetic energy spectrometry. The values of kinetic energy releases (T) can be calculated from the energy dispersion of product ions. As T essentially reflects the release of coulombic energy, which can be used to calculate the approximate distances R between the two charges immediately before decomposition of the ions. From these data, some structural information about transiton states could be provided. The ECID and CID processes of above doubly charged ions, have also been studied. We found that the CID reactions of (C6H4Cl2)2+ could be used to distinguish three dichloro benzene isomers.

社会形势预警的几种建模方法比较

Based on social survey data conducted by local research group in some counties executed in the nearly past five years in China, the author proposed and solved two kernel problems in the field of social situation forecasting: i) How can the attitudes’ data on individual level be integrated with social situation data on macrolevel; ii) How can the powers of forecasting models’ constructed by different statistic methods be compared? Five integrative statistics were applied to the research: 1) algorithm average (MEAN); 2) standard deviation (SD); 3) coefficient variability (CV); 4) mixed secondary moment (M2); 5) Tendency (TD). To solve the former problem, the five statistics were taken to synthesize the individual and mocrolevel data of social situations on the levels of counties’ regions, and form novel integrative datasets, from the basis of which, the latter problem was accomplished by the author: modeling methods such as Multiple Regression Analysis (MRA), Discriminant Analysis (DA) and Support Vector Machine (SVM) were used to construct several forecasting models. Meanwhile, on the dimensions of stepwise vs. enter, short-term vs. long-term forecasting and different integrative (statistic) models, meta-analysis and power analysis were taken to compare the predicting power of each model within and among modeling methods. Finally, it can be concluded from the research of the dissertation: 1) Exactly significant difference exists among different integrative (statistic) models, in which, tendency (TD) integrative models have the highest power, but coefficient variability (CV) ones have the lowest; 2) There is no significant difference of the power between stepwise and enter models as well as short-term and long-term forecasting models; 3) There is significant difference among models constructed by different methods, of which, support vector machine (SVM) has the highest statistic power. This research founded basis in all facets for exploring the optimal forecasting models of social situation’s more deeply, further more, it is the first time methods of meta-analysis and power analysis were immersed into the assessments of such forecasting models.