FDI, Geographic Location and Their Impacts on the Pattern of Regional Economic Development in China

This paper states how the reciprocal matching of foreign direct investment （FDI） and geographic location generally determine the pattern of regional economic development in China by analyzing the co-relations among geographic location, FDI and regional economic development. Among various factors that affect FDI inflow into specific regions of China, it is believed that geographic location might be one of the most essential factors in shaping the overall trend of diversification in regional economic development in China. Examinations are followed for identifying the above judgment both with econometric models and data analysis.

China＇s geographical regionalization in Chinese secondary school curriculum （1902-2012）

AS geographic literacy training is an education, national geographical education is essential content for Chinese citizens＇ literacy one of the indispensable key aspects of that training. Because of China＇s vast land area and the significance of the regional differences, it is difficult for students to receive a solid education regarding China＇s geography. In 1902, the government established the geography curriculum and began to incorporate the concept of geographical regionalization to facilitate the teaching of China＇s geography by publishing the first syllabi, which was modified later and put into use in 1904. Since 1904, numerous geog raphy textbooks have attempted to find an appropriate way to present China＇s geographical regionalization, as it is important for secondary students to have a clear understanding and appreciation for the different regional characteristics. Accordingly, the geographical region alization content is divided into four main phases： 1902 to 1927; 1928 to 1948; 1949 to 1986; and 1986 to the present. During these phases, the content related to China＇s geographical regionalization in secondary middle school geography textbooks has been gradually simplified and has adopted a more scientific foundation, thus leading to the present time where there are now four geographical regional areas. From this historical study, we find that while China＇s geographical regionalization has gradually matured, there are still some problems. For example, dividing the study into four regions to describe the panorama of China is too simplified, and the learning therefore becomes too scattered and haphazard, particularly qiven the new curriculum reform.

ANALYSIS ON SPATIAL DIFFERENCE OF LAND USECHANGE BASED ON PHYSICAL AND CULTURALLANDSCAPE ATTRIBUTES──A Case Study at Mongolian AutonomousCounty of Qian Gorlos, Jilin Province

Land use changes are regarded as landscape pattern change driven by many interactive natural and social-economic factors. Different combination of physical geographical elements induced the difference of spatio-temporal pattern of land use change. There are four physical geographical regions in Mongolian Autonomou County of Qian Gorlos of Jilin Province. Based on spatial analysis and statistical analysis, we conclude that the primary pattern of land use and the tendency of land use changes are all different in four physical geographical regions. During 1987 – 1996, the dominant land use change processes were from grassland or forest to arableland, from unused land to paddy and grassland to unused land. Though land use change is mainly affected by social and economic condition in short period, the composite characters of physical geographical elements controls land use dynamic process. The relationship between land use dynamic process and the character of physical geographical units differ in different regions. Possible human impacts on land use change are explored with application of buffer areas of series distance along main roads and radius around main settlements. A few models are built to describe the relationship between land use spatial change rates and distance to road and settlements. According to our result, the relationship with the proximity to roads was a negative liner function, with the change rate decreasing rapidly when moving away from roads. Within a distance of less 7.5km from main traffic lines, land use changes occur red more. The bulk of grassland was apt to be opened up for cultivation around the settlements and the transformation from dryland to paddy occurred within the distance of 1km away from settlements.

The Homogeneity of Distributional Patterns of the Global Terrestrial Animal,Plant and Microorganism under the Influence of Ecological Conditions

The world animal geographical regionalization scheme and the plant geographical regionalization scheme have been formulated by zoologists and botanists respectively since the biogeography has been established.This research team initially confirmed the homogeneity of Chinese animal and plant geography.To explore the relationship between the distribution pattern of global animals,plants,and microorganisms,global 141,814 genera of terrestrial animals,17,526 genera of plants,21,321 genera of microorganisms,and their major taxa were analyzed using their proposed SGF(Similarity General Formula)and a new multivariate similarity clustering analysis method.Almost identical analytical results were obtained,meeting the requirements of statistics,geography,ecology and biology respectively.The expected consistency of their distribution pattern was achieved for the first time.We prove that the earth’s ecological conditions affect the homogeneity and accumulation of the distribution of animals,plants and microorganisms.Homogeneity determines the distribution pattern of global kinds of biological consistency,accumulation determines the impact of the evolutionary period on the breadth of distribution,microorganisms appear earliest,plants second,animals later,and their average distribution domain decreases in turn,reflecting these differences.Therefore,this study not only provides a theoretical basis and quantitative basis for the establishment of geographical regionalization scheme but also advances the development of biogeography to a new stage and raises the theory of biogeographic analysis to a new height.

Improvement of ecological geographic regionalization based on remote sensing and canonical correspondence analysis： A case study in China

Ecological geographic regions, also called eco-regions, can be used to divide a remotely sensed image, which is helpful for reducing the complexity of land cover types within eco-regions and for improving the classification accuracy of land cover. In this case study in China, we improved a method of ecological geographic regionalization that is more suitable for remote sensing mapping of regional land cover, and we obtained new eco-regions. The canonical correspondence analysis(CCA) and k-means clustering were adopted in the ecological geographic regionalization using both seasonal remotely-sensed vegetation information and environmental data including climate, elevation and soil features. Our results show that the combination of seasonal vegetation information and the CCA performed well in the selection of the dominant environmental factor of the biogeographic pattern, and it can be used as regionalization indicators of eco-regions. We found that thermal factors are the most important driving forces of the biogeographic pattern in China, which followed by moisture factors. Two global land cover products(MODIS MCD12C1 and Glob Cover) were used to assess our eco-regions. The results show that our eco-regions performed better than that of a previous study regarding the complexity of land cover types, such as in the number of types and the proportional area of the major/secondary type. These results indicate that the method of ecological geographic regionalization, which is based on environmental factors associated with seasonal vegetation features, is effective for reducing the regional complexity of land cover.

Genetic analysis of wild-type hepatitis A virus strains

Objective To clarify the distribution of hepatitis A virus (HAV) genotype in geographical regions of China Methods Seventeen representative HAV strains were isolated from the stool or serum of hepatitis A patients in different geographical regions Viral RNA was recovered from stool or serum by proteinase K digestion and phenol chloroform extraction, followed by ethanol precipitation prior to reverse transcription and polymerase chain reaction (RT PCR) amplification The nucleotide sequences of VP1/2A junction region were tested by using a direct sequencing technique Results A pairwise comparison of sequences within 168 bases at the VP1/2A junction revealed that all the sequences clustered within genotype Ⅰ About 53% of strains clustered in genotype ⅠB, with less than 6% variability; while the others clustered in genotype ⅠA, with less than 5 3% variability Sequence homology between genotype ⅠA and ⅠB varied from 88 7% to 92 3% Conclusion Epidemic or sporadic HAV strains in China may belong to HAV genotype ⅠA or ⅠB Epidemiologically related strains may be identical or closely related in sequence

Region-aware neural graph collaborative filtering for personalized recommendation

Personalized recommender systems have been widely deployed in various scenarios to enhance user experience in response to the challenge of information explosion.Especially,personalized recommendation models based on graph structure have advanced greatly in predicting user preferences.However,geographical region entities that reflect the geographical context of the items is not being utilized in previous works,leaving room for the improvement of personalized recommendation.This study proposes a region-aware neural graph collaborative filtering(RA-NGCF)model,which introduces the geographical regions for improving the prediction of user preference.The approach first characterizes the relationships between items and users with a user-item-region graph.And,a neural network model for the region-aware graph is derived to capture the higher-order interaction among users,items,and regions.Finally,the model fuses region and item vectors to infer user preferences.Experiments on real-world dataset results show that introducing region entities improves the accuracy of personalized recommendations.This study provides a new approach for optimizing personalized recommendation as well as a methodological reference for facilitating geographical regions for optimizing spatial applications.