Based on the growth rates of population, Gross Domestic Products (GDP) and agriculture productivity, the areas of deforestation were predicted in Jutp ani village, Chitwan district, Nepal by Area Production Model (AP...Based on the growth rates of population, Gross Domestic Products (GDP) and agriculture productivity, the areas of deforestation were predicted in Jutp ani village, Chitwan district, Nepal by Area Production Model (APM). Through the APM simulation in this study, all of forestland will be transferred into agricu ltural land in 2030 at the rate of 24% per year on the current productivity. And if the productivity of subsistence food crop is assumed to increase at the rate of 1%, the productivity of market crop and export crop increase at the rate of 2% annually, deforestation rate will decrease to 17% per year, but only 124 hm2 forest land will be left till 2038. The agriculture productivity is a very impor tant factor for the deforestation, so intensification of agriculture management is more important.展开更多
To reveal the quantitative relationship between research and development (R&D) investment and gross domestic product (GDP) in China, we have demonstrated and analyzed the relationship between R&D investment an...To reveal the quantitative relationship between research and development (R&D) investment and gross domestic product (GDP) in China, we have demonstrated and analyzed the relationship between R&D investment and science and technology (S&T) progress, and based on a mount of S&T statistical data, have proceeded demonstration research of the relationship between R&D investment and GDP in China with Solow and vector auto regression (VAR) models. Cubic curve fitting and cross-correlation analysis of them with SPSS have shown that there is a strong synchronic relationship between R&D investment and GDP.展开更多
This paper first estimated the infectious capacity of COVID-19 based on the time series evolution data of confirmed cases in multiple countries. Then, a method to infer the cross-regional spread speed of COVID-19 was ...This paper first estimated the infectious capacity of COVID-19 based on the time series evolution data of confirmed cases in multiple countries. Then, a method to infer the cross-regional spread speed of COVID-19 was introduced in this paper, which took the gross domestic product(GDP) of each region as one of the factors that affect the spread speed of COVID-19 and studied the relationship between the GDP and the infection density of each region(China's Mainland, the United States, and EU countries). In addition, the geographic distance between regions was also considered in this method and the effect of geographic distance on the spread speed of COVID-19 was studied. Studies have shown that the probability of mutual infection of these two regions decreases with increasing geographic distance. Therefore, this paper proposed an epidemic disease spread index based on GDP and geographic distance to quantify the spread speed of COVID-19 in a region. The analysis results showed a strong correlation between the epidemic disease spread index in a region and the number of confirmed cases. This finding provides reasonable suggestions for the control of epidemics. Strengthening the control measures in regions with higher epidemic disease spread index can effectively control the spread of epidemics.展开更多
文摘Based on the growth rates of population, Gross Domestic Products (GDP) and agriculture productivity, the areas of deforestation were predicted in Jutp ani village, Chitwan district, Nepal by Area Production Model (APM). Through the APM simulation in this study, all of forestland will be transferred into agricu ltural land in 2030 at the rate of 24% per year on the current productivity. And if the productivity of subsistence food crop is assumed to increase at the rate of 1%, the productivity of market crop and export crop increase at the rate of 2% annually, deforestation rate will decrease to 17% per year, but only 124 hm2 forest land will be left till 2038. The agriculture productivity is a very impor tant factor for the deforestation, so intensification of agriculture management is more important.
文摘To reveal the quantitative relationship between research and development (R&D) investment and gross domestic product (GDP) in China, we have demonstrated and analyzed the relationship between R&D investment and science and technology (S&T) progress, and based on a mount of S&T statistical data, have proceeded demonstration research of the relationship between R&D investment and GDP in China with Solow and vector auto regression (VAR) models. Cubic curve fitting and cross-correlation analysis of them with SPSS have shown that there is a strong synchronic relationship between R&D investment and GDP.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.62266030 and 61863025)International S & T Cooperation Projects of Gansu province (Grant No.144WCGA166)Longyuan Young Innovation Talents and the Doctoral Foundation of LUT。
文摘This paper first estimated the infectious capacity of COVID-19 based on the time series evolution data of confirmed cases in multiple countries. Then, a method to infer the cross-regional spread speed of COVID-19 was introduced in this paper, which took the gross domestic product(GDP) of each region as one of the factors that affect the spread speed of COVID-19 and studied the relationship between the GDP and the infection density of each region(China's Mainland, the United States, and EU countries). In addition, the geographic distance between regions was also considered in this method and the effect of geographic distance on the spread speed of COVID-19 was studied. Studies have shown that the probability of mutual infection of these two regions decreases with increasing geographic distance. Therefore, this paper proposed an epidemic disease spread index based on GDP and geographic distance to quantify the spread speed of COVID-19 in a region. The analysis results showed a strong correlation between the epidemic disease spread index in a region and the number of confirmed cases. This finding provides reasonable suggestions for the control of epidemics. Strengthening the control measures in regions with higher epidemic disease spread index can effectively control the spread of epidemics.
