scholarly journals Measuring and Spatio-Temporal Evolution for the Late-Development Advantage in China’s Provinces

2018 ◽  
Vol 10 (8) ◽  
pp. 2773 ◽  
Author(s):  
Fei Ma ◽  
Fei Liu ◽  
Qipeng Sun ◽  
Wenlin Wang ◽  
Xiaodan Li

The coordinated development of regional economies is a major economic goal of many countries around the world. To that end, China has actively carried out a series of strategies to expedite the development of its late-developing regions. This study explores the issues raised by this coordinated development from the perspective of late-development advantages, which refer to a region’s late-development advantages compared with the early-developing regions in the country. The 15 indicators applied for evaluating the late-development advantages fall into five categories including capital, technology, industrial structure, institutions and human resources. Then, the model of entropy-weighted technique for order preference by similarity to an ideal solution (EW-TOPSIS) is applied to evaluate the late-development advantages of China’s provinces. Following this, ArcGIS and GeoDa are used to analyze the spatio-temporal evolution pattern of the late-development advantages of China’s provinces, and to compare the spatio-temporal effect of these advantages between the provinces. The results show that the overall late-development advantages of China’s provinces had a downward trend from 2006 to 2015, with the Eastern Region falling by 8.07%, the Central Region falling by 14.37% and the Western Region falling by 8.05%, indicating that the development gap between China’s Eastern and Western Regions is still large. The temporal effect analysis shows the temporal autocorrelation changes from positive status to negative status with the increase of lagging order, which means the trend of late-development advantage will reverse over time. The spatial effect analysis shows there were only significant Low-Low and Low-High aggregation in 2006 and 2010, but significant High-High and High-Low aggregations emerge in 2012 and 2015, implying that the development environment has effectively promoted the use of the provincial late-development advantage. The research results could provide theoretical basis for the policy making of the accelerating development of late-developing regions in China.

2021 ◽  
Vol 13 (19) ◽  
pp. 11089
Author(s):  
Zhen Xu ◽  
Xiang Zhu ◽  
Guoen Wei ◽  
Xiao Ouyang

Improving regional innovation efficiency is the key to developing an innovative country. Exploring the spatio-temporal evolution characteristics of regional innovation efficiency is crucial in the formulation of regional policies and the choice of innovation models. This study used the superdata envelopment analysis method with undesirable outputs in evaluating the innovation efficiency of Chinese provinces. To assess the spatial spillover effects of innovation factors, the spatial autocorrelation and spatial Durbin model were adopted to characterize the spatio-temporal evolution, spatial correlation, and mechanisms of innovation efficiency. The highlights of the results are as follows: (1) The time-series changes in innovation efficiency showed a general trend from declining to increasing. (2) There were pronounced regional differences in innovation efficiency. The innovation efficiencies at the provincial level evolved from being decentralized to concentrated. The innovation efficiency was relatively stable in the eastern region and increased significantly in the central and western regions. The east–center–west evolution pattern gradually weakened. (3) The innovative efficiency exhibited spatial dependence, and the spatial agglomeration continued to increase. The extent of hot spots expanded, while cold spots shrunk slightly. (4) The scientific research environment, entrepreneurial environment, labor quality, and market environment were the essential elements that improved innovation efficiency. The impact of the different factors on innovation efficiency at different periods exhibited significant spatial heterogeneity.


2013 ◽  
Vol 798-799 ◽  
pp. 998-1003
Author(s):  
Jian She Li ◽  
Qian Song

Central plains economic zone is the significant strategic concept to reduce the economic gap with eastern region, and realize the rise of central China. Based on members positioned, economic integrated development mechanism of the central plains economic zone is the vital drivers of optimizing the resources configuration, accelerating industrial structure adjustment and realizing the coordinated development of the area. From the division mechanism, cooperative mechanism and cluster mechanism, the article analyses the necessity of operating mechanism by the game model, and puts forward some proposal for the economy integrated development mechanism on government, industry and society.


2019 ◽  
Vol 8 (4) ◽  
pp. 9461-9464

Current quantum computer simulation strategies are inefficient in simulation and their realizations are also failed to minimize those impacts of the exponential complexity for simulated quantum computations. We proposed a Quantum computer simulator model in this paper which is a coordinated Development Environment – QuIDE (Quantum Integrated Development Environment) to support the improvement of algorithm for future quantum computers. The development environment provides the circuit diagram of graphical building and flexibility of source code. Analyze the complexity of algorithms shows the performance results of the simulator and used for simulation as well as result of its deployment during simulation


2021 ◽  
Vol 217 ◽  
pp. 103605
Author(s):  
Xianzhi Cao ◽  
Nicolas Flament ◽  
Sanzhong Li ◽  
R. Dietmar Müller

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jinlong Shi ◽  
Xing Gao ◽  
Shuyan Xue ◽  
Fengqing Li ◽  
Qifan Nie ◽  
...  

AbstractThe novel coronavirus pneumonia (COVID-19) outbreak that emerged in late 2019 has posed a severe threat to human health and social and economic development, and thus has become a major public health crisis affecting the world. The spread of COVID-19 in population and regions is a typical geographical process, which is worth discussing from the geographical perspective. This paper focuses on Shandong province, which has a high incidence, though the first Chinese confirmed case was reported from Hubei province. Based on the data of reported confirmed cases and the detailed information of cases collected manually, we used text analysis, mathematical statistics and spatial analysis to reveal the demographic characteristics of confirmed cases and the spatio-temporal evolution process of the epidemic, and to explore the comprehensive mechanism of epidemic evolution and prevention and control. The results show that: (1) the incidence rate of COVID-19 in Shandong is 0.76/100,000. The majority of confirmed cases are old and middle-aged people who are infected by the intra-province diffusion, followed by young and middle-aged people who are infected outside the province. (2) Up to February 5, the number of daily confirmed cases shows a trend of “rapid increase before slowing down”, among which, the changes of age and gender are closely related to population migration, epidemic characteristics and intervention measures. (3) Affected by the regional economy and population, the spatial distribution of the confirmed cases is obviously unbalanced, with the cluster pattern of “high–low” and “low–high”. (4) The evolution of the migration pattern, affected by the geographical location of Wuhan and Chinese traditional culture, is dominated by “cross-provincial” and “intra-provincial” direct flow, and generally shows the trend of “southwest → northeast”. Finally, combined with the targeted countermeasures of “source-flow-sink”, the comprehensive mechanism of COVID-19 epidemic evolution and prevention and control in Shandong is revealed. External and internal prevention and control measures are also figured out.


2021 ◽  
Vol 13 (10) ◽  
pp. 5439
Author(s):  
Chenggang Li ◽  
Tao Lin ◽  
Zhenci Xu ◽  
Yuzhu Chen

With the development of economic globalization, some local environmental pollution has become a global environmental problem through international trade and transnational investment. This paper selects the annual data of 30 provinces in China from 2000 to 2017 and adopts exploratory spatial data analysis methods to explore the spatial agglomeration characteristics of haze pollution in China’s provinces. Furthermore, this paper constructs a spatial econometric model to test the impact of foreign direct investment (FDI) and industrial structure transformation on haze pollution. The research results show that the high-high concentration area of haze pollution in China has shifted from the central and western regions to the eastern region and from inland regions to coastal regions. When FDI increases by 1%, haze pollution in local and neighboring areas will be reduced by 0.066% and 0.3538%, respectively. However, the impact of FDI on haze pollution is heterogeneous in different stages of economic development. FDI can improve the rationalization level of industrial structure, and then inhibit the haze pollution. However, FDI inhibits the upgrading level of industrial structure to a certain extent, and then aggravates the haze pollution. The research in this paper provides an important decision-making basis for coordinating the relationship between FDI and environmental pollution and realizing green development.


2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Masayuki Kano ◽  
Shin’ichi Miyazaki ◽  
Yoichi Ishikawa ◽  
Kazuro Hirahara

Abstract Postseismic Global Navigation Satellite System (GNSS) time series followed by megathrust earthquakes can be interpreted as a result of afterslip on the plate interface, especially in its early phase. Afterslip is a stress release process accumulated by adjacent coseismic slip and can be considered a recovery process for future events during earthquake cycles. Spatio-temporal evolution of afterslip often triggers subsequent earthquakes through stress perturbation. Therefore, it is important to quantitatively capture the spatio-temporal evolution of afterslip and related postseismic crustal deformation and to predict their future evolution with a physics-based simulation. We developed an adjoint data assimilation method, which directly assimilates GNSS time series into a physics-based model to optimize the frictional parameters that control the slip behavior on the fault. The developed method was validated with synthetic data. Through the optimization of frictional parameters, the spatial distributions of afterslip could roughly (but not in detail) be reproduced if the observation noise was included. The optimization of frictional parameters reproduced not only the postseismic displacements used for the assimilation, but also improved the prediction skill of the following time series. Then, we applied the developed method to the observed GNSS time series for the first 15 days following the 2003 Tokachi-oki earthquake. The frictional parameters in the afterslip regions were optimized to A–B ~ O(10 kPa), A ~ O(100 kPa), and L ~ O(10 mm). A large afterslip is inferred on the shallower side of the coseismic slip area. The optimized frictional parameters quantitatively predicted the postseismic GNSS time series for the following 15 days. These characteristics can also be detected if the simulation variables can be simultaneously optimized. The developed data assimilation method, which can be directly applied to GNSS time series following megathrust earthquakes, is an effective quantitative evaluation method for assessing risks of subsequent earthquakes and for monitoring the recovery process of megathrust earthquakes.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3099
Author(s):  
V. Javier Traver ◽  
Judith Zorío ◽  
Luis A. Leiva

Temporal salience considers how visual attention varies over time. Although visual salience has been widely studied from a spatial perspective, its temporal dimension has been mostly ignored, despite arguably being of utmost importance to understand the temporal evolution of attention on dynamic contents. To address this gap, we proposed Glimpse, a novel measure to compute temporal salience based on the observer-spatio-temporal consistency of raw gaze data. The measure is conceptually simple, training free, and provides a semantically meaningful quantification of visual attention over time. As an extension, we explored scoring algorithms to estimate temporal salience from spatial salience maps predicted with existing computational models. However, these approaches generally fall short when compared with our proposed gaze-based measure. Glimpse could serve as the basis for several downstream tasks such as segmentation or summarization of videos. Glimpse’s software and data are publicly available.


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