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The shield tunnels closely constructed near the foundations have an inevitable influence on the structures, even results in the large settlement or uplift of the structures.

The comparison of structural deformation of three different foundations is presented based on the field monitoring data.

Shield tunnelling parameters vary for the different types of foundations. For the long pile foundations, the recommended speed is 3 to 4 cm/min, the grouting pressure is about 0.3 MPa and the grouting rate ranges from 150 to 180.

The study based on the field monitoring data is rarely reported, especially the topic about the structural deformation of different types of the foundations.

This study aims to conduct a dynamic analysis of consumer attitudes towards domestic brands under the influence of multiple-period opinion events, providing methodological guidance for the overall development of fast-fashion clothing brands.

This study takes the Xinjiang cotton event and ERKE donation event in 2021 as the samples and Weibo comments on the hot topic of the fact that ANTA’s total turnover exceeded NIKE’s on the 2021 Double 11 as the first and explores the process and influencing factors of consumer domestic brand attitude change through latent Dirichlet allocation (LDA) model.

Under the influence of multiple public opinion events, consumers’ attitudes towards domestic brands experienced changes from brand awareness and brand identification to brand loyalty. First of all, patriotism and the awareness of Chinese goods lead to consumers’ brand awareness. The social responsibility and perceived quality of the later stage will stimulate consumers’ brand identification. Finally, the matching of national pride and perceived products will promote consumers’ brand loyalty.

This study establishes a model of the evolution of consumer attitudes towards domestic brands, revealing for the first time from a dynamic perspective the factors influencing these attitudes. This study offers a novel perspective on the processes and structures of the relationship between consumers and domestic brands.

Conducting innovation in low-carbon technology is vital to boost the low-carbon economy. Collaborative innovation among industry-university-research (IUR) is an effective mode of developing low-carbon technologies. There is a lack of visualization and analysis of the spatial-temporal of such collaboration among the IUR. This paper aims to serve as insights to guide IUR’s collaborative innovation in Chinese universities to promote low-carbon technologies.

This paper uses IncoPat to collect patent data. Collaborative patent output on low-carbon technologies was selected as the indicator to measure the effectiveness of IUR collaboration. The temporal evolution trend of the collaborative patent output in Chinese universities is analyzed.

The collaborative patent output of the Chinese IUR varies greatly among the regions, evolving from stronger in the east and weaker in the west, to stronger in the south and weaker in the north region. The triple helix (TH) innovation system in China’s low-carbon sector is dominated by intraregional collaborative innovation, while there is a weak bilateral synergy between universities and research institutions.

This paper innovatively developed a novel TH model that characterize the regional differences of the IUR collaboration in low-carbon technology innovation of Chinese universities. A new attempt focuses on the spatial-temporal evolution of the collaborative innovation of IUR to promote low-carbon technologies.

In China, more than 80,000 people have been diagnosed with COVID-19, and more than 3,000 people have lost their lives. It seems that there will be more deaths since the epidemic is not over. All the Chinese provinces have reported the COVID-19 cases. This chapter aims to explore the trend of COVID-19 treatment efficiency in Chinese provinces using the data released daily by China Center for Disease Control and Prevention. Since China Center for Disease Control and Prevention began to release data daily from January 24 to March 12, we have more than 40 groups of daily data for 31 provinces in China mainland. In the calculation, we take the daily data of each province as a sample and then we have more than 1,200 samples in this study.

We use additive two-stage data envelopment analysis as an efficiency evaluation tool to calculate the COVID-19 treatment efficiency. In our framework, the first stage is to understand the infection rate and the second stage is to evaluate the treatment efficiency. In the first stage for the tth day, we use total population (p) and number of people infected in the previous day (inf_t−1) as the inputs and cumulative number of people infected in the current day (inf_t) as the output. In the second stage for the tth day, we use cumulative number of people infected in the current day (inf_t) as the input and cumulative death in the current day (death_t) and cumulative recovery in the current day (recov_t) as the outputs. Some techniques on how to deal with undesirable outputs such as inf_t and death_t are employed in this study.

After we have the infection rate and treatment efficiency for the samples more than 1,200, we analyze the COVID-19 treatment efficiency and its development trend from January 24 to March 12 in 34 regions of China from static and dynamic aspects. The results show that, on the whole, the overall efficiency and phased efficiency of COVID-19 treatment efficiency in all regions of China are relatively high, which reflects the key factor for the Chinese government to quickly control the epidemic in the short term. Relatively speaking, the average efficiency value in the infection stage (first stage) is lower than the average efficiency value in the healing stage (second stage), which shows that the focus of anti-epidemic in China should be early detection and prevention rather than treatment process. In terms of trend, the total efficiency of COVID-19 treatment in each region shows a trend of “increasing first and then decreasing.” Our analysis indicates that in the initial stage, the continuous increase of various resources leads to the rise of the total efficiency, while in the later stage, the rapid decline of the number of infected people leads to the decrease of the total efficiency. Based on the results of the efficiency analysis, this study provides corresponding management implications and policy suggestions, hoping to provide some enlightenment and suggestions for the anti-epidemic work of other countries in the severe environment where the epidemic is spreading rapidly.

The purpose of this paper is to investigate the determinants of pork consumption in urban western China and the different consumption patterns across income strata with respect to income elasticity and price elasticity of demand.

The double-hurdle model is fit to the household data of Sichuan and Xinjiang provinces which is from the National Bureau of Statistics urban household surveys.

The paper finds that consumers’ purchasing decisions regarding pork are related to both non-economic and economic factors. The results also indicate large differences among the determinants for decision of how much pork to buy across the three income strata. Low-income households have higher income elasticity than middle-income and high-income households. High-income and middle-income households’ level of pork consumption is more sensitive to pork price. High-income households have greater cross-price elasticity.

In the previous studies, the non-economic determinants of pork consumption have not been addressed, and neither does the issue of difference pork purchasing behavior across income strata for urban households in western China. So this study uses the double-hurdle model to investigate the determinants of pork consumption in urban western China.

This paper aims to apply fractional variational iteration method using He's polynomials (FVIMHP) to obtain exact solutions for variable-coefficient fractional heat-like and wave-like equations with fractional order initial and boundary conditions.

The approach is based on FVIMHP. The authors choose as some examples to illustrate the validity and the advantages of the method.

The results reveal that the FVIMHP method provides a very effective, convenient and powerful mathematical tool for solving fractional differential equations.

The variable-coefficient fractional heat-like and wave-like equations with fractional order initial and boundary conditions are solved first. Illustrative examples are included to demonstrate the validity and applicability of the method.

The purpose of this paper is to analyze the linear and nonlinear effects of market integration on carbon emissions and explore the direct and indirect paths of market integration on carbon emissions through path analysis.

The authors first conduct a measurement and contrastive study of the market integration and carbon emissions of China’s 28 provinces from year 1995 to 2015. Then, the linear effect of market integration on carbon emissions is analyzed by using the fixed-effect model. Next, based on the path analysis method, the direct and indirect paths of market integration’s impact on carbon emissions are explored. Finally, the panel threshold regression model is used to evaluate the effect of market integration on carbon emissions under different situations of geographic distance.

The results show that first, the improvement of market integration can increase carbon emissions in the form of a linear relationship. Second, market integration not only has a direct and positive impact on the carbon emissions, but also has an indirect and positive impact on carbon emissions through the level of economic development, and a negative impact on carbon emissions through technological level. Third, an increase in market integration can reduce its positive effect on carbon emissions, but the improvement of economic growth and technology level can both enhance the positive effect of market integration on carbon emissions.

This paper focuses on the impact of market integration on carbon emissions in 30 provinces in China, while, the authors do not conduct a comparative analysis of different regions, so there are certain limitations. In addition, policy interaction between regional governments is also a key factor affecting carbon emissions, but this paper does not consider the effect of policy interaction, future follow-up research will try to incorporate it into the analytical models.

An important practical implication of this research is that market integration should be regarded highly in China’s energy conservation and emission reduction efforts. The research results have important reference value for policy authorities to formulate relevant policies. That is, the government can play a more active role in the process of integration through breaking the regional blockade and interest barriers to comprehensively improve resource utilization efficiency and technical level, and ultimately achieve regional low-carbon development.

This paper explores the effects of market integration on China’s carbon emissions based on different methods and perspectives, and confirms that market integration plays a vital role in China’s carbon emissions through economic growth and technological progress. Notably, based on the studied results, some specific and practical suggestions are proposed in this paper so as to reduce carbon emission and realize the sustainable development of economy and society in China.