An Empirical Study on the International Competitiveness of Chinese Commercial Banks

According to the Chinese government’ commitments while entering the WTO, now China has cancelled many restrictions for foreign banks including the restriction of foreign exchange business, the geographic restriction of RMB business and the restriction of the establishment form of foreign banks. Foreign banks are now permitted to offer services to all Chinese clients and to set up the same city services points to make cross‐region business. It means that nowadays foreign commercial banks and Chinese commercial banks are standing at the same start line to compete with each other. The innovation of this paper is mainly reflected in the following three aspects. First, we made a complete and systematic summary about the latest achievements on the competitiveness of commercial banks, including the foreign and domestic authoritative method of the evaluation of international competitiveness of commercial banks, in order to build a solid theoretical foundation for the empirical analysis. The second is the multilevel empirical method. In addition to the innovation on the selected indicators of the traditional factor analysis, we also made a cointegration analysis on the macro‐level variables which further strengthened the content of the international competitiveness of commercial banks. Thirdly, the data used in the empirical analysis are the latest ones released by the official website of the commercial banks, statistical agencies, regulatory bodies and related database by 2010, in order to ensure the validity and the timeliness of the empirical results

Systematic mutational analysis of the cation-independent mannose 6-phosphate/insulin-like growth factor II receptor cytoplasmic domain - An acidic cluster containing a key aspartate is important for function in lysosomal enzyme sorting

We have used systematic mutational analysis to identify signals in the 166-residue murine cation-independent mannose 6-phosphate/insulin-like growth factor II receptor cytoplasmic domain required for efficient sorting of lysosomal enzymes. Alanine cluster mutagenesis on all conserved residues apart from the endocytosis signal demonstrates that the major sorting determinant is a conserved casein kinase II site followed by a dileucine motif (157DDSDEDLL164). Small deletions or additions outside this region have severe to mild effects, indicating that context is important. Single residue mutagenesis indicates that cycles of serine phosphorylation/dephosphorylation are not obligatory for sorting. In addition, the two leucine residues and four of the five negatively charged residues can readily tolerate conservative substitutions. In contrast, aspartate 160 could not tolerate isoelectric or isosteric substitutions, implicating it as a critical component of the sorting signal

Analysis of the Chinese provincial air transportation network

The air transportation system is of a great impact on the economy and globalization of a country. In this paper, we analyze the Chinese air transportation network (ATN) from a provincial perspective via the complex network framework, where all airports located in one province are abstracted as a single node and flights between two provinces are denoted by a link. The results show that the network exhibits small-world property, homogeneous structure and disassortative mixing. The variation of the flight flow within 24 h is investigated and an obvious tide phenomenon is found in the dynamics of Chinese provincial ATN for high output level of tertiary industry. Our work will offer a novel approach for understanding the characteristic of the Chinese air transportation network.Peer ReviewedPostprint (author's final draft

Semisupervised Soft Mumford-Shah Model for MRI Brain Image Segmentation

One challenge of unsupervised MRI brain image segmentation is the central gray matter due to the faint contrast with respect to the surrounding white matter. In this paper, the necessity of supervised image segmentation is addressed, and a soft Mumford-Shah model is introduced. Then, a framework of semisupervised image segmentation based on soft Mumford-Shah model is developed. The main contribution of this paper lies in the development a framework of a semisupervised soft image segmentation using both Bayesian principle and the principle of soft image segmentation. The developed framework classifies pixels using a semisupervised and interactive way, where the class of a pixel is not only determined by its features but also determined by its distance from those known regions. The developed semisupervised soft segmentation model turns out to be an extension of the unsupervised soft Mumford-Shah model. The framework is then applied to MRI brain image segmentation. Experimental results demonstrate that the developed framework outperforms the state-of-the-art methods of unsupervised segmentation. The new method can produce segmentation as precise as required