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This book focuses on the systematic change in the global economy accompanying the rise of China. Once China has the same huge and advanced economy as the U.S., the global economy's current one-center system will have a chance to change: China will represent an alternative center. If it can satisfy essential criteria for the global economy such as a stable foreign exchange system, healthy international trade environment and strong support for economic development etc., China will be able to offer a viable alternative. In this constellation the two centers of the global economy and financial system, the U.S. and China, would ideally cooperate, and the global economy could benefit from having two economic and financial centers

China's trade surplus: a whole view -- What promotes China's trade surplus -- Why China's trade deficit should not appear -- To reduce trade frictions -- The U.S. trade deficit with China: an excuse

Alexander Wilhelm Freiherr Stael von Holstein is a famous orientalist, buddhist, linguist and social activist. He has served as Professor of Sanskrit at Peking University, Professor of Chinese Literature at Harbin University and Institute of China-India Research (Beijing) successively, and his academic achievements are profound and profound. This article is hoped that this research will increase the audience for this famous scholar.

AbstractWe propose a nonparametric Bayesian lifetime data analysis method using the Dirichlet process mixture model with a lognormal kernel. A simulation‐based algorithm that implements the Gibbs sampling is developed to fit the Dirichlet process lognormal mixture (DPLNM) model using rightly censored failure time data. Five examples are used to illustrate the proposed method, and the DPLNM model is compared to the Dirichlet process Weibull mixture (DPWM) model. Results indicate that the DPLNM model is capable of estimating different lifetime distributions. The DPLNM model outperforms the DPWM model in all the examples, and the DPLNM model shows promising potential to be applied to analyze failure time data when an appropriate parametric model for the data cannot be specified. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013