Spatial and Temporal Pattern of Urban Smart Development in China and Its Driving Mechanism

Smart urban development is an inevitable choice, and is essential to overall strength improvement. It is important to explore an urban smart development path which unites smart growth with driving shrinkage perfectly in forming scientific and sustainable development concept and responding to new normal strategic opportunities. Based on statistic data of 294 prefecture-level cities and above in China from 2000 to 2015, we analyzed spatial and temporal evolution of urban smart development in China by constructing a dynamic fitting model of urban land expansion, population growth, and economic development as well as the coefficient of variation of urban smart development(CVSD). Further efforts were then made to consider differential distribution regularity of urban smart development so as to understand the driving mechanisms of heterogeneous classification of urban smart development in China from different scales and scale variation. Our results indicate that: 1) the disordered growth tendency of urban cities in China is overall well controlled in the middle, and late research and it mainly presented a doublet coexistence of shrinkage disordered cities and smart developing cities. It is particularly obvious that Northeast China and East China have regarded shrinkage disordered cities and smart developing cities as main development tendency separately. 2) Areas with basic stability and relative variation were relatively dispersed across the time period, but the proportion was far beyond areas with significant variation. It demonstrates a relative equilibrium spatial and temporal differential evolution pattern of prefecture-level cities and above in China, except for Tongling, Lanzhou and Chaoyang. 3) prefecture-level cities and above in China are mostly characterized by shrinkage disordered and smart development classification under the background of different scale and scale variation from 2000–2015; however, the spatial resonance relation is not obvious. 4) There are many interaction factors forming an important driving mechanism in developing the spatial and temporal pattern of urban smart development in China, including natural geographical factors, industrial structure adjustment, human capital radiation, regional traffic accessibility, and government decision-making intervention.

Interactive Effect and Spatial Characteristics of Agricultural Development Level and Transport Superiority Degree in Main Grain-producing Areas of the Central Jilin Province,China

To investigate the spatial synergy between agricultural development level and transport superiority degree in grain-producing areas of the central Jilin Province and the driving mechanism between them,22 counties in the central Jilin Province were used as the research units to calculate agricultural development level and transport superiority degree using the entropy weighting method,weighted travel time and raster cost distance.The spatial econometric model was used to analyze the mechanism of the mutual influence between the two.The main conclusions are as follows.1)Agricultural development level around Changchun,the provincial capital city,and in the areas of Changchun-Jilin and Changchun-Gongzhuling is high,whereas the development level of the counties in the southwest is low.2)Transport superiority degree of each county has improved,the overall connectivity of the road networks has been optimized,and the level of transportation accessibility has shown the development trend of‘centralization’,exhibiting the characteristics of proximity diffusion.3)Locally,there is spatial heterogeneity in the mutual driving effects of the two,with six main patterns.4)The theoretical conditions of von Thunen’s agricultural location have changed under the conditions of market economy due to the improvement of the transport networks,the new model of agricultural development,and the changes of the market system.

Genetic diversity decreases as population density declines: Implications of temporal variation in mitochondrial haplotype frequencies in a natural population of Tscherskia triton

Although the spatial genetic differentiation that occurs in animal populations has been extensively studied,information on temporal variations in genetic structure and diversity is still lacking,especially for animals with oscillating populations.In the present study,we used the mtDNA D-loop sequence to assess the temporal genetic variation in samples from six successive years for the greater long-tailed hamster,Tscherskia triton.Sampling was carried out between 1998 and 2003 in cropland on the North China Plain,China.A total of 108 individuals were analyzed.The temporal samples showed a high level of genetic diversity.Substantial genetic changes in haplotype frequencies over time were detected for the hamster population.Random genetic drift and migration are likely to be the major factors responsible for the observed temporal pattern.The genetic diversity of the hamster population was higher in years with higher population density,and lower in years with lower population density.The result supports our hypothesis that genetic diversity decreases when population density declines in animals whose population oscillates greatly between years.The combined effects of inbreeding and genetic drift caused by reproduction,dispersal and population size might play important roles in the observed changes in genetic structure and diversity between years.

Design of all-optical temporal differentiator using a Moir fiber grating

We design and demonstrate an all-optical temporal differentiator based on a simple Moire fiber grating operated in reflection. The simulation results prove that a single Moire fiber grating with only one π-phase shifted point can act as the first-order temporal differentiator and that a Moire fiber grating incorporating two symmetrical π-phase shifted points can act as the second-order temporal differentiator. A practical Moire fiber grating is fabricated, thereby proving that such a grating can act as the first-order temporal differentiator. Our results verify the feasibility, flexibility, and accuracy of the proposed method.