To clarify the mechanism of molecular recognition and discrimination in aqueous solutions, thermodynamic functions were investigated in the past systematically for the molecular inclusion of alcohols into α- and β-Cyclodextrin(CD) cavities in aqueous solutions by the present authors. In this paper, various molecular surface areas of monohydric alcohols were determined. The correlation of the molecular surface area of monohydric alcohols with the thermodynamics functions of molecular inclusion into cyclodextrin was examined. The enthalpies of inclusion of monohydric alcohols with CD increased in proportion to the hydrophobic surface of monohydric alcohols
This paper reports various kinds of visualization (isosurfaces, pseudo-three-dimensional representations, contour map, and cross sections) on the atomic orbitals of a hydrogen atom using multimedia techniques (animation and still image), and relation to visualization of the wave character by the oscillating circular membrane. These visualizations are very important, because they are suitable methods to understand the character of the atomic orbital wavefunctions. Interactive visualization methods on the wave character of the atomic orbitals of a hydrogen atom were investigated using large capacity and random accessible recording media, i.e., CD-R (Compact Disk Recordable). The wave character of atomic orbitals, such as a node or a nodal surface, was represented by using their classical oscillator in contrast to the atomic orbitals of a hydrogen atom through the interactive operations on a computer.
We developed a neural network simulator for structure-activity correlation of molecules: Neco. A self-organized network model for high-speed learning was included in Neco, a perceptron type with three layers. In the hidden layer the neurons are self-organized by using Mahalanobis generalized distance. This report proposes an improved training algorithm to the network. A self-organizing module decides the number of neurons in the hidden layer, at first. Then, a neuron in the hidden layer has two informations which describe a characteristic of the neuron. In this way, the network can evaluate stochastic characteristics from input data better. Using this simulator, the hydrophobic parameter, logP, of perillartine derivatives was predicted. We used for inputs a set of six parameters: five STERIMOL (L, Wl, Wu, Wr, and Wd) and the sweet/bitter activity. The 22 sampled data are used for training. Our neural network can accurately predict hydrophobic parameter, logP. Compared with a normal perceptron network, the learning ability of our network is somewhat higher and its convergence speed is greatly much larger. This simulator doesn't depend on the machine environment because it codes by the Java programming language.
We attempted to extract chemical parameter characterizing the upper, middle and lower stream by the principal component and the analysis of differential coefficients of input parameter for perceptron type neural network with three layers. The analysis of differential coefficients of input parameter for perceptron type neural network was developed by Aoyama  and was newly equipped into a neural network simulator Neco. The data used are 12 chemical parameters at 17 points along the main stream of the Tamagawa river in Tokyo, Japan, for 1997-1999 . The K-L plot of the first and second principal components (Figure 4) well divides 17 points into three groups corresponding to the three regions: upper, middle and lower streams, respectively. From results of the analysis of differential coefficients of input parameter for perceptron type neural network, Cl-, COND and NH4-N have relatively large differential coefficients and divide middle and lower streams. DO and pH are large in upper stream of Tamagawa river (Figure 5). The first principal component classifies well two groups: upper and middle-lower streams on the K-L plots. This result suggests that the water contamination is more drastic in the midstream of Tamagawa river than downstream. The water contamination in midstream should be decreased for keeping Tamagawa river clean.
The graph digitizer “GetValue" which assists in electrochemical analysis was programmed in Visual Basic language. The program has two subroutines of electrochemical analyses. One is for the estimation of diffusion coefficient using Cottrell's equation. The other is for the battery analysis using the plot of current vs. voltage. After digitizing a chart, the user can analyze obtained data by each method. The program can also be used as the standard graph digitizer that assists in obtaining numerical data from a chart on paper. A function that makes two specific points horizontal is equipped with the program to correct the inclination of the image. Specified points can be obtained in seven series. Numerical data are displayed in a table, and can be transferred to the clipboard. Either specified or interpolated methods can be selected, which enabled the efficient obtaining of numerical data.