中国古典舞钢琴伴奏中的求变性研究

为了提高中国古典舞教学水平,文章针对钢琴伴奏在中国古典舞教学中的求变性展开分析。首先介绍中国古典舞钢琴伴奏的必要性,主要阐述钢琴伴奏的价值与作用。其次介绍中国古典舞及其对钢琴伴奏的要求,总结求变性的形成原因以及应对思路。最后则围绕钢琴伴奏求变性,提出了教师自身需要深刻认知中国古典舞与钢琴伴奏、教师结合古典舞教学实际改编伴奏钢琴曲目、优化钢琴伴奏教材内容三点建议。通过多元化方法,改编钢琴变奏曲目,为中国古典舞钢琴教学提供辅助,以期能够真正提高中国古典舞钢琴伴奏的水平。

Supply-demand Evolution about Main Characters of Wheat Varieties in China

Using the data of wheat varieties with year-sown area of 6 666.7 hm^2 or more from 1982 to 2006 in China, the evolution of wheat varieties was studied from both supply and demand. Results showed that although various characters of wheat varieties grown by peasants in production were improved obviously in China, the demand for variety yield was still the main demand by peasants; there was no significant difference between the supply and demand of crude protein content by peasants; the demand for disease resistance has been lower than the supply recently; the demand for full growth stage at every stage was less than the supply; and while there was a larger demand for plant height by peasants.

Impact analysis of supplier relationship on supply chain resilience using biological cellular resilience theory

A supply chain resilience model is established based on the biological cellular resilience theory to analyze the impact of the supplier relationship on supply chain resilience. A scenario where the market demand is changed suddenly by some undesired events is considered. The results reveal that enhancing collaboration with a more resilient supplier can significantly improve supply chain resilience and reduce supply chain losses. It is also found that enhancing the supplier relationship can significantly benefit supply chain resilience if the collaborative intensity is relatively low, and it has less effect if supply chain members have already collaborated closely. Thus, enhancing the supplier relationship to a limited intensity is a relatively effective and economic method to strengthen supply chain resilience.

Discrete logistics network design model under interval hierarchical OD demand based on interval genetic algorithm

Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.

Invariant Sets and Exact Solutions to Nonlinear Diffusion Equations with x-Dependent Convection and Absorption

In this paper, we introduce a new invariant set Eo={u：ux=f＇（x）F（u）＋ε[g＇（x）-f＇（x）g（x）]F（u）×exp（-∫^u1/F（z）dz）}where f and g are some smooth functions of x, ε is a constant, and F is a smooth function to be determined. The invariant sets and exact sohltions to nonlinear diffusion equation ut = （ D（u）ux）x ＋ Q（x, u）ux ＋ P（x, u）, are discussed. It is shown that there exist several classes of solutions to the equation that belong to the invariant set Eo.

Microscopic Fuzzy Urban Traffic Simulation with Variable Demand

Some microscopic traffic simulations on urban road network are developed up to now. However, the effect of urban transport policy in the local city is influenced with the complex interaction of automobile traffic and public transport traffic. Particularly, behaviours of vehicles should be described with the fuzziness of the subjective recognition and operation. On the other hand, the trip makers are influenced by various transport policies in terms of mode choice behaviour. The change in mode choice behaviour and number of public transport mode users would eventually affect traffic flow conditions on road network. Modal spilt and traffic conditions of a network are interrelated. Therefore, the present study mainly aims to integrate mode choice model and microscopic traffic simulation model based on fuzzy logic. In the study, the fuzzy logic based mode choice model is proposed. The proposed mode choice model and the existing microscopic traffic simulation model are combined. The developed model has been applied on real urban network to demonstrate the effectiveness of the installation of LRT system. Finally, it is helpful for evaluation of transport policy that the fuzzy logic based microscopic traffic simulation with modal choice model has been constructed.

Evaluation of C02 Reduction and Primary Energy Savings for Collective Housing with Fuel Cells Considering Variability in Demand

In Japan, residential FCs （fuel cells） are being introduced not only in detached houses but also in collective housing. In this context, the effects of FC introduction （e.g., primary energy savings） should be quantitatively evaluated, but this has not been done sufficiently for collective housing, particularly with regard to demand variability. Here, the authors propose a method taking into account demand variability to evaluate the effects of FC introduction into collective housing, based on a finite set of observational demand data. The method provides a new viewpoint for evaluating the effects of FC introduction. Numerical simulation results based on real-world data indicate the validity of these effects in terms of primary energy savings and CO2 reduction considering demand variability.

A Descent Method for Mixed Variational Inequalities

A new descent method for solving mixed variational inequalities is developed based on the auxiliary principle problem. Convergence of the proposed method is also demonstrated.

The effect of learning on the evolution of new courtship behavior： A simulation model

The fact that individuals learn can change the relationship between genotype and phenotype in the population, and thus affect the evolutionary response to selection. Here we ask how male ability to learn from female response affects the evolu- tion of a novel male behavioral courtship trait trader pre-existing female preference （sensory drive）. We assume a courtship trait which has both a genetic and a learned component, and a two-level female response to males. With individual-based simulations we show that, under this scenario, learning generally increases the strength of selection on the genetic component of the courtship trait, at least when the population genetic mean is still low. As a consequence, learning not only accelerates the evolution of the courtship trait, but also enables it when the trait is costly, which in the absence of learning results in an adaptive valley. Further- more, learning can enable the evolution of the novel trait in the face of gene flow mediated by immigration of males that show superior attractiveness to females based on another, non-heritable trait. However, rather than increasing monotonically with the speed of learning, the effect of learning on evolution is maximized at intermediate learning rates. This model shows that, at least under some scenarios, the ability to learn can drive the evolution of mating behaviors through a process equivalent to Wadding- ton＇s genetic assimilation .