Computer Management of Quantitative Analysis Chemistry Experiment

The application of computer in the quantitative analysis chemistry experiment is a chemistry experiment teaching applications software, developed by Visual Basic （6.0）, based on the content of quantitative analysis chemistry experiment of chemistry major in higher institute. This software has the function of the automatic processing the experimental data, the automatic generation of test report copies, and the automatic evaluation of students＇ experimental results, which solve the reliability, objectivity and accuracy problems of the students＇ experiment data processing and evaluation, and avoid interference with human factors. The software has the characteristic of the easy installation, the easy operation, the strong practicability, pertinence, the systematicness and the running stability, so it provides a platform in the quantitative analysis chemistry experiment for the students＇ assessment system of automatic processing, and it has a high popularization value. The project＇s technical route design is reasonable, the research method is correct, and the experimental data processing results are reliable, which has reached the leading domestic level in the quantitative analysis chemistry experiment teaching field of computer data processing. And this project has been through the achievements appraisal of Gansu Provincial Sci. ＆ Tech. Department.

SOME PROBLEMS IN THE Z-C-X SPACE

The new concepts of the Z-C-X space and excellent cone are introduced. Some problems of random semiclosed 1-set-contractive operator are investigated in the Z-C-X space. At first, an important inequality is proved. Secondly, several new conclusions are proved by means of random fixed point index in the theory of random topological degree. A random solution of a class of random operator equations under conditions of imitating the parallelogram law is obtained, famous Altman's theorem is generalized in partially ordered Z-C-X space. Therefore, some new results are obtained.

Relationship between air temperature oscillations and solar variability on short and medium time scales

The contemporary science of climate change is increasingly focusing on the temporal and spatial characteristics of temperature oscillations and determining possible underlying causes.In particular,the effect of variations in solar irradiance on the variability of the climate remains a hot topic of debate.Most studies focus on the effects of solar variation on the Earth's climate on long time scales.This study presents the responses of regional climates to solar variations on shorter time scales using two datasets:one for the air temperature in Nanjing and the Greenwich sunspot number,and the other for the air temperature in Shijiazhuang and the United States sunspot number.Employing empirical mode decomposition,both the 11-year quasi-period of the sunspot number and similar periods including approximately 5.5-and 10.5-year cycles of the air temperature in Nanjing and Shijiazhuang are obtained.However,correlation analysis of similar periodic components for the sunspot number and air temperature indicates that changes in the air temperature on short and medium time scales are not linked to solar variations.This is further confirmed by a test of whether a mode component is a stochastic noise signal.Many shorter periods are also found at the 95% confidence level;in particular,the 3.1-year period of the Nanjing air temperature coincides with a previously obtained empirical result.Moreover,no temperature variations on shorter time scales correlate with solar variability.

On Using Physico-Chemical Properties of Amino Acids in String Kernels for Protein Classification via Support Vector Machines

String kernels are popular tools for analyzing protein sequence data and they have been successfully applied to many computational biology problems. The traditional string kernels assume that different substrings are independent. However, substrings can be highly correlated due to their substructure relationship or common physico-chemical properties. This paper proposes two kinds of weighted spectrum kernels： The correlation spectrum kernel and the AA spectrum kernel. We evMuate their performances by predicting glycan-binding proteins of 12 glycans. The results show that the correlation spectrum kernel and the AA spectrum kernel perform significantly better than the spectrum kernel for nearly all the 12 glycans. By comparing the predictive power of AA spectrum kernels constructed by different physico-chemical properties, the authors can also identify the physico- chemical properties which contributes the most to the glycan-protein binding. The results indicate that physico-chemical properties of amino acids in proteins play an important role in the mechanism of glycamprotein binding.

General H-matrices and their Schur complements

The definitions of θ-ray pattern proposed to establish some new results matrix and θ-ray matrix are firstly on nonsingularity/singularity and convergence of general H-matrices. Then some conditions on the matrix A ∈ C^n×n and nonempty α （n） = {1,2,... ,n} are proposed such that A is an invertible H-matrix if A（α） and A/α are both invertible H-matrices. Furthermore, the important results on Schur complement for general H-matrices are presented to give the different necessary and sufficient conditions for the matrix A E HM and the subset α C （n） such that the Schur complement matrix A/α∈ HI^n-｜α｜ or A/α ∈ Hn-｜α｜^M or A/α ∈ H^n-｜ α｜^S.

Discrete Global Optimization Problems with a Modified Discrete Filled Function

This paper considers discrete global optimization problems.The traditional definition of the discrete filled function is modified in this paper.Based on the modified definition,a new discrete filled function is presented and an algorithm for discrete global optimization is developed from the discrete filled function.Numerical experiments reported in this paper on several test problems with up to 200 variables have demonstrated the efficiency of the algorithm.