Generally, different prevention measures should be taken according to spontaneous combustion propensities. The current methods to evaluate the propensity of coal spontaneous combustion, such as chromatographic method ...Generally, different prevention measures should be taken according to spontaneous combustion propensities. The current methods to evaluate the propensity of coal spontaneous combustion, such as chromatographic method of oxygen adsorption, oxidation kinetics method and activation energy method, are mostly affected by human factors. Their boundaries among different classes of propensities were all established by subjective judgments. A new evaluation method using catastrophe theory is introduced. This method can accurately depict the process of coal spontaneous combustion and the evaluation index, ＂catastrophe temperature＂, be obtained based on the model. In terms of catastrophe temperature, the spontaneous combustion propensity of different coals can be sequenced. Experimental data indicate that this method is appropriate to describe the spontaneous combustion process and to evaluate the propensity of coal svontaneous combustion.展开更多
The objective of social development is to construct a harmonious society.In China,the key to a harmonious society is the happiness of more than 900 million farmers living in the rural areas.This study aimed to measure...The objective of social development is to construct a harmonious society.In China,the key to a harmonious society is the happiness of more than 900 million farmers living in the rural areas.This study aimed to measure rural residents' subjective well-being(SWB) through the day reconstruction method,as well as to analyze SWB's influencing factors through a variety of statistical methods.The results showed that the average U index was 12.79%,indicating that respondents were unhappy 12.79% of the time.Twenty-seven percent of the population had a U index greater than 0,with the average value being 47%,indicating that these people were unhappy 47% of the time.The study also found that SWB varied according to the characteristics of the respondents.Logistic regression analysis showed that social and demographic factors,including age,education,county,household size,generation number,per capita income,migration status and social networking,which significantly affected rural residents' SWB.The size of the impact varied with the different factors.展开更多
By using principal component analysis, this paper selected some appropriate influencing indicators, and constructed multiple linear regression models to predict the development of energy-saving environmental protectio...By using principal component analysis, this paper selected some appropriate influencing indicators, and constructed multiple linear regression models to predict the development of energy-saving environmental protection industry（ESEPl） in Shanghai. The Influencing Factors can be categorized into comprehensive economic factors and environmental factors, and GDP of the second industries and the total industries GDP in comprehensive economic factors have the strongest correlation, while in the environmental index factors, the total discharge of waste water has the strongest correlation. On the basis of influencing factors study, the regression model shows that by the end of 2020, the industry investment will reach 89.788 billion RMB, which proves that the development of ESEPI in Shanghai would grow continuously and dramatically.展开更多
文摘Generally, different prevention measures should be taken according to spontaneous combustion propensities. The current methods to evaluate the propensity of coal spontaneous combustion, such as chromatographic method of oxygen adsorption, oxidation kinetics method and activation energy method, are mostly affected by human factors. Their boundaries among different classes of propensities were all established by subjective judgments. A new evaluation method using catastrophe theory is introduced. This method can accurately depict the process of coal spontaneous combustion and the evaluation index, ＂catastrophe temperature＂, be obtained based on the model. In terms of catastrophe temperature, the spontaneous combustion propensity of different coals can be sequenced. Experimental data indicate that this method is appropriate to describe the spontaneous combustion process and to evaluate the propensity of coal svontaneous combustion.
基金supported by Independent Inovation Foundation of Shandong Univercity,IIFSDU
文摘The objective of social development is to construct a harmonious society.In China,the key to a harmonious society is the happiness of more than 900 million farmers living in the rural areas.This study aimed to measure rural residents' subjective well-being(SWB) through the day reconstruction method,as well as to analyze SWB's influencing factors through a variety of statistical methods.The results showed that the average U index was 12.79%,indicating that respondents were unhappy 12.79% of the time.Twenty-seven percent of the population had a U index greater than 0,with the average value being 47%,indicating that these people were unhappy 47% of the time.The study also found that SWB varied according to the characteristics of the respondents.Logistic regression analysis showed that social and demographic factors,including age,education,county,household size,generation number,per capita income,migration status and social networking,which significantly affected rural residents' SWB.The size of the impact varied with the different factors.
基金This research work was financially supported by the Shanghai Board of Education （2012-SHNGE-06ZD） , China Postdoctoral Science Foundation funded project （2013M531157） , and The Ministry of Education of Youth Fund Project of Humanities and Social Sciences Research （14YJC790152）
文摘By using principal component analysis, this paper selected some appropriate influencing indicators, and constructed multiple linear regression models to predict the development of energy-saving environmental protection industry（ESEPl） in Shanghai. The Influencing Factors can be categorized into comprehensive economic factors and environmental factors, and GDP of the second industries and the total industries GDP in comprehensive economic factors have the strongest correlation, while in the environmental index factors, the total discharge of waste water has the strongest correlation. On the basis of influencing factors study, the regression model shows that by the end of 2020, the industry investment will reach 89.788 billion RMB, which proves that the development of ESEPI in Shanghai would grow continuously and dramatically.
