In 2016 China began implementing a new population strategy after having maintained a one-child policy for 35 years.This paper draws on the lessons we can learn about low fertility and population aging in Japan and Sou...In 2016 China began implementing a new population strategy after having maintained a one-child policy for 35 years.This paper draws on the lessons we can learn about low fertility and population aging in Japan and South Korea to consider the implications of the newly announced'universal two-child'policy in China.Japan,Korea and China share many socio-cultural characteristics and have undergone similar processes with respect to low fertility and population aging at different periods of time.Many scholars argue that China's family planning program has greatly reduced China's fertility level,but the effects of other socioeconomic factors have,in fact,had a greater impact on the reduction of the fertility rate than the one-child policy had.Considering the effects of the fertility policy that limits the number of births in China and the lessons we can get from unsuccessful fertility boosting measures in Japan and Korea,this paper suggests that a fertility policy that puts no limits on births should be adopted in China.展开更多
Landslides are abundant in mountainous regions.They are responsible for substantial damages and losses in those areas.The A1 Highway,which is an important road in Algeria,was sometimes constructed in mountainous and/o...Landslides are abundant in mountainous regions.They are responsible for substantial damages and losses in those areas.The A1 Highway,which is an important road in Algeria,was sometimes constructed in mountainous and/or semi-mountainous areas.Previous studies of landslide susceptibility mapping conducted near this road using statistical and expert methods have yielded ordinary results.In this research,we are interested in how do machine learning techniques help in increasing accuracy of landslide susceptibility maps in the vicinity of the A1 Highway corridor.To do this,an important section at Ain Bouziane(NE,Algeria) is chosen as a case study to evaluate the landslide susceptibility using three different machine learning methods,namely,random forest(RF),support vector machine(SVM),and boosted regression tree(BRT).First,an inventory map and nine input factors were prepared for landslide susceptibility mapping(LSM) analyses.The three models were constructed to find the most susceptible areas to this phenomenon.The results were assessed by calculating the receiver operating characteristic(ROC) curve,the standard error(Std.error),and the confidence interval(CI) at 95%.The RF model reached the highest predictive accuracy(AUC=97.2%) comparatively to the other models.The outcomes of this research proved that the obtained machine learning models had the ability to predict future landslide locations in this important road section.In addition,their application gives an improvement of the accuracy of LSMs near the road corridor.The machine learning models may become an important prediction tool that will identify landslide alleviation actions.展开更多
With the novel coronavirus pandemic casting a shadow on economic growth worldwide,the first roadmap for improving the allocation of production factors outlines measures to give the market a bigger role in deciding whe...With the novel coronavirus pandemic casting a shadow on economic growth worldwide,the first roadmap for improving the allocation of production factors outlines measures to give the market a bigger role in deciding where resources should be allocated.The Communist Party of China Central Committee and the State Council,the cabinet issued a guideline on April 9 to facilitate free and orderly flow of production factors and boost market vitality.Land,labor,technological knowledge,capital and data are the major production factors.The government will make land management more flexible,encourage the flow of labor forces,boost technology and data exchanges and improve the capital market system.It will also make pricing mechanisms more marketoriented and ensure better resource allocation through digital technologies.展开更多
Guangzhou,capital of the prosperous southern province of Guangdong,recently implemented a host of policy measures aimed at boosting business entities as the world emerges from the COVID-19 pandemic.
REVITALISING PRIVATE BUSINESSES Sanlian Lifeweek 28 August On 19 July,Chinese authorities published a set of measures aimed at boosting the country’s private economy.The guidelines pledge to create a more robust and ...REVITALISING PRIVATE BUSINESSES Sanlian Lifeweek 28 August On 19 July,Chinese authorities published a set of measures aimed at boosting the country’s private economy.The guidelines pledge to create a more robust and favourable environment in which the private sector can unleash its potential amid challenges.The private economy accounts for more than 60 percent of the country’s GDP.展开更多
The COVID-19 pandemic has made severe impacts on the economy during the past three years,China adjusted its virus control in early December,relaxing the restriction measures in line with the lessening pathenogenicity ...The COVID-19 pandemic has made severe impacts on the economy during the past three years,China adjusted its virus control in early December,relaxing the restriction measures in line with the lessening pathenogenicity of the virus,Now,the priority should be boosting the economy.展开更多
基金Support System for Family Care for the Elderly in China,Japan and Korea"sponsored by Asia Research Center,Renmin University of China.
文摘In 2016 China began implementing a new population strategy after having maintained a one-child policy for 35 years.This paper draws on the lessons we can learn about low fertility and population aging in Japan and South Korea to consider the implications of the newly announced'universal two-child'policy in China.Japan,Korea and China share many socio-cultural characteristics and have undergone similar processes with respect to low fertility and population aging at different periods of time.Many scholars argue that China's family planning program has greatly reduced China's fertility level,but the effects of other socioeconomic factors have,in fact,had a greater impact on the reduction of the fertility rate than the one-child policy had.Considering the effects of the fertility policy that limits the number of births in China and the lessons we can get from unsuccessful fertility boosting measures in Japan and Korea,this paper suggests that a fertility policy that puts no limits on births should be adopted in China.
文摘Landslides are abundant in mountainous regions.They are responsible for substantial damages and losses in those areas.The A1 Highway,which is an important road in Algeria,was sometimes constructed in mountainous and/or semi-mountainous areas.Previous studies of landslide susceptibility mapping conducted near this road using statistical and expert methods have yielded ordinary results.In this research,we are interested in how do machine learning techniques help in increasing accuracy of landslide susceptibility maps in the vicinity of the A1 Highway corridor.To do this,an important section at Ain Bouziane(NE,Algeria) is chosen as a case study to evaluate the landslide susceptibility using three different machine learning methods,namely,random forest(RF),support vector machine(SVM),and boosted regression tree(BRT).First,an inventory map and nine input factors were prepared for landslide susceptibility mapping(LSM) analyses.The three models were constructed to find the most susceptible areas to this phenomenon.The results were assessed by calculating the receiver operating characteristic(ROC) curve,the standard error(Std.error),and the confidence interval(CI) at 95%.The RF model reached the highest predictive accuracy(AUC=97.2%) comparatively to the other models.The outcomes of this research proved that the obtained machine learning models had the ability to predict future landslide locations in this important road section.In addition,their application gives an improvement of the accuracy of LSMs near the road corridor.The machine learning models may become an important prediction tool that will identify landslide alleviation actions.
文摘With the novel coronavirus pandemic casting a shadow on economic growth worldwide,the first roadmap for improving the allocation of production factors outlines measures to give the market a bigger role in deciding where resources should be allocated.The Communist Party of China Central Committee and the State Council,the cabinet issued a guideline on April 9 to facilitate free and orderly flow of production factors and boost market vitality.Land,labor,technological knowledge,capital and data are the major production factors.The government will make land management more flexible,encourage the flow of labor forces,boost technology and data exchanges and improve the capital market system.It will also make pricing mechanisms more marketoriented and ensure better resource allocation through digital technologies.
文摘Guangzhou,capital of the prosperous southern province of Guangdong,recently implemented a host of policy measures aimed at boosting business entities as the world emerges from the COVID-19 pandemic.
文摘REVITALISING PRIVATE BUSINESSES Sanlian Lifeweek 28 August On 19 July,Chinese authorities published a set of measures aimed at boosting the country’s private economy.The guidelines pledge to create a more robust and favourable environment in which the private sector can unleash its potential amid challenges.The private economy accounts for more than 60 percent of the country’s GDP.
文摘The COVID-19 pandemic has made severe impacts on the economy during the past three years,China adjusted its virus control in early December,relaxing the restriction measures in line with the lessening pathenogenicity of the virus,Now,the priority should be boosting the economy.
