Journal of Computer Chemistry, Japan(JCCJ) is now celebrating 20 years of publication. Our academic journal has its origins in 1992 as an irregular publication of The Journal of Chemical Software(JCS). Within five years it had become a quarterly journal and in 2002 the title was changed to the above mentioned JCCJ with the merging of The Chemical Software Society of Japan into a new organization: Society of Computer Chemistry, Japan. JCS and JCCJ are peer-reviewed scientific journals. Electronic publishing in the form of website has been achieved since 1997. In 2010, the archive titles were also open to the public on web. Web-based journal submission and review system has been running since 2007.
The author first diagnosed the reason for waned interest in the industrial application of fullerenes as being the failure in determining the mechanism of formation of C60 under unusual conditions in time. Recently, the Irle-Morokuma group solved the mechanism by performing combined quantum mechanics and molecular dynamics calculations on random assemblies of C2 molecules at 2000 to 3000 K. They proposed a shrinking hot giant road mechanism, which fits Prigogine's irreversible thermodynamic theory. Still the last steps of this mechanism leading to significant yields of C60 could not be satisfactorily reproduced. The author suggests carbon mono-oxide as a critical catalyst for giant fullerenes to close to C60.
For the past 30 years, together with the Chemical Software Society of Japan and the Society of Computer Chemistry, Japan, we have conducted scientific activities related to the interdisciplinary aspects of chemistry and computers at the Chemistry PC Workshop. From the early development of computers to their widespread use in all fields, we have witnessed the 2,300,000-fold improvement of computer performance. We are managing our Society at a time when such activities are greatly needed. We explained our footprints until now at the 10th anniversary symposium.
In our previous study, the performances of various QSAR models were examined to predict carcinogenicities of diverse chemicals from their structures as a method alternative to animal tests. We found that the parallel model combining support vector machine (SVM) models constructed for twenty substructure groups predict the carcinogenicities of a wide variety of chemicals with a satisfactory overall accuracy of approximately 80%. In this study, in order to improve the performance of this model by raising the accuracy for N-nitroso-, nitroso- and nitroaromatic group (89 chemicals) which showed the lowest accuracy (70.8%) among twenty substructure groups, we tested the methods of variable selection in SVM modeling. The accuracy of the SVM model trained with descriptors which were selected by using the correlation coefficient method, the F-score method and the sensitivity analysis method was examined. It was found that the sensitivity analysis method improves the accuracy of the N-nitroso-, nitroso- and nitroaromatic group from 70.8% to 77.5%. Thus, it is the most appropriate for constructing the model to predict the carcinogenicity of chemicals among these variable selection methods.
Regions of explanatory variables X need to be selected in many fields such as spectral analysis and process control. Genetic algorithm-based wavelength selection (GAWLS) method is one of the methods that is used to select combinations of important variables from X-variables using regions as a unit of measurement. However, a partial least-squares method is used as a regression method; hence, a GAWLS method cannot handle a nonlinear relationship between X and an objective variable y. We therefore proposed a region selection method based on GAWLS and support vector regression (SVR), one of the nonlinear regression methods, for achieving both appropriate selection of variable regions and construction of a high predictive model when there is a nonlinear relationship between X and y(Figure 1). The proposed method is named GAWLS-SVR. The q2 value of a SVR model, which is calculated using a cross-validation method, is used as a fitness value of the chromosome. In order to verify the effectiveness of the GAWLS-SVR method, we applied it to simulation data in which correlation between close pairs of X-variables was high and the relationship between X and y was nonlinear. The GAWLS-SVR method could select regions of variables appropriately, while considering the nonlinearity and could construct a predictive model with high accuracy (Table 2, Figure 6).
Membrane bioreactors (MBRs) have been widely used to purify wastewater for reuse. However, MBRs are subject to fouling, which is the phenomenon whereby foulants absorb or deposit on the membrane. When MBR filtration is operated at a constant permeate flow rate, the transmembrane pressure (TMP) and the energy required to maintain the permeate rate increase with time. To enable chemical cleaning to be performed at an appropriate time, one must be able to predict membrane fouling in the long-term. There has been research on correlations among fouling phenomena, water quality variables, and operating conditions. Therefore, in this paper, we aimed to construct a statistical model between the increase in TMP and MBR parameters such as water quality variables and operating conditions and to use this model to predict TMP (Figure 1). In our study, two methods are used to construct regression models. One is a partial least-squares method and the other is a support vector regression method. We analyzed two data sets measured in a real industrial MBR plant and then confirmed that the constructed model could predict TMP over time with high accuracy (Figures 4, 5).
The online manuscript submission and peer-reviewing system at J-stage2 has been used for the editorial management from the submission of a manuscript to its publication of the Journal of Computer Chemistry, Japan (JCCJ) on Web. Recently, because the publication on XML format has been demanded in the world and because the XML format will be supported on the J-stage3, the XML workflow must be developed for the journal publication by the JCCJ. Japanese XML workflow was realized for the first time in the world by utilizing eXtyles, Indesign, and Typefi for the rendering and conversion software. Web publication management system for JCCJ is also developed by using PHP/XSLT processor, Apache/RewriteEngine directive, and CCS definition.
HeH+ is the simplest heteronuclear diatomic molecule. Two molecular orbital energy level maps of HeH+ are shown in this note by using HF/6-311++G**. One is a covalent bond type map shown as He+ + H →HeH+. Another is a coordinate bond type map shown as He + H+→HeH+. The latter is stable. In the covalent bond type map, the orbital energy of HeH+ 1σ (-1.6288a.u.) is lower than that of H 1s (-0.4998a.u.) but higher than that of He+ 1s (-1.9983a.u.) because of destabilizing by electron repulsion. In the coordinate bond type map, the orbital energy of HeH+ 1σis lower than those of both H+ 1s (-0.4998a.u.) and He 1s (-0.9176a.u.) because of stabilization thanks to decreasing of the electron repulsion in He 1s.