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Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural network (PINN), which was proposed to encode physical laws into neural networks, is a less data-demanding approach for flow field reconstruction. However, when the fluid physics is complex, it is tricky to obtain accurate solutions under the PINN framework. This study aims to propose a physics-based data-driven approach for time-averaged flow field reconstruction which can overcome the hurdles of the above methods.

A multifidelity strategy leveraging PINN and a nonlinear information fusion (NIF) algorithm is proposed. Plentiful low-fidelity data are generated from the predictions of a PINN which is constructed purely using Reynold-averaged Navier–Stokes equations, while sparse high-fidelity data are obtained by field or experimental measurements. The NIF algorithm is performed to elicit a multifidelity model, which blends the nonlinear cross-correlation information between low- and high-fidelity data.

Two experimental cases are used to verify the capability and efficacy of the proposed strategy through comparison with other widely used strategies. It is revealed that the missing flow information within the whole computational domain can be favorably recovered by the proposed multifidelity strategy with use of sparse measurement/experimental data. The elicited multifidelity model inherits the underlying physics inherent in low-fidelity PINN predictions and rectifies the low-fidelity predictions over the whole computational domain. The proposed strategy is much superior to other contrastive strategies in terms of the accuracy of reconstruction.

In this study, a physics-informed data-driven strategy for time-averaged flow field reconstruction is proposed which extends the applicability of the PINN framework. In addition, embedding physical laws when training the multifidelity model leads to less data demand for model development compared to purely data-driven methods for flow field reconstruction.

This paper attempts to explain the phenomenon that Macau has a parliament (Legislative Assembly) and mass suffrage but no political parties.

This paper reviews the development process of “parliament – mass suffrage – political party” in Hong Kong and Macau and tries to explain why Macau does not have a party using comparative research methods.

The political party development of Hong Kong and Macau was influenced by both the (former) colonial power and China, and whether there were political parties in these two regions was the result of the game between China and the (former) colonial power. China hoped to limit the development of party politics in the two regions. Since Britain felt reluctant to cooperate with China, political parties in Hong Kong developed. At the same time, Portugal chose to defer to China, which led Macau not to have a political party.

Existing studies have yet to explain why there are no political parties in Macau, and this paper is the first attempt to do so.

Weber's hypothesis about China is the hypothesis forwarded by Weber that why capitalist production did not appear in eastern countries such as China in the first place. Weber considered that the reason may be Chinese Confucianism and Taoism lack protestant ethic like Western countries.

The clarification has aroused wide discussion, meanwhile, East Asian capitalism belonging to the Chinese cultural circle has successfully refuted Weber's proposition. Chinese scholars have a broad debate around this topic while no agreement has been reached. This paper tries to explain Weber's hypothesis by Marx's theory of capital origin, which can be explained that the landlord economy caused by China's federal society under centralism leads to the result that the commodity of labor cannot exist in that environment.

The answer from Marxist economics has not only solved an enormous theoretical problem, but also it has vital practical significance. It easily clarifies the fact that the commodity of labor in full sense still cannot emerge in China nowadays, which is an important reason causing China to enter the New Normal and New Era.

Therefore, it leaves China the only way of the socialist road with Chinese characteristics and revitalizing China's rural economy, which means China can only promote rural industrialization and urbanization under the principle of adhering to rural collective ownership, while implementing various forms of integrated agricultural and industrial business models based on local conditions.

Aiding employment is an important poverty reduction strategy in many countries’ social welfare systems, as this strategy can help empower the recipients with a better living standard, development and social inclusion. The purpose of this paper is to identify the most significant individual and systematic variables for the employment status of low-income groups in urban China.

The data of this study are drawn from “Social Policy Support System for Poverty-stricken Families in Urban and Rural China 2015” report. The Ministry of Civil Affairs of the People’s Republic of China appointed and funded the Institute of Social Science Survey (ISSS) at Peking University to deliver the related project and organize a research team to write the report. Multiple binary logistic regression analysis is adopted to identify both individual and systematic factors that affect the employment status among low-income groups in urban China.

According to the results of the binary logistic regression model, individual factors, including: gender; householder status; education; and self-rated health status, play a significant role in determining the employment status of low-income groups in urban China. Clearly, the impacts of individual factors are more influential to marginal families than to families entitled to receive Basic Living Allowance. In contrast, compared with marginal families, systematic factors are more influential to families entitled to receive Basic Living Allowance.

This study highlights the importance of precise poverty reduction strategy and the issue of “welfare dependence” among low-income groups in urban China. Policy recommendations derived from the findings are hence given, including: the promotion of family-friendly policies; the introduction of a smart healthcare system; the establishment of a Basic Living Allowance adjustment mechanism; and the provision of related social services.

This study aims to propose a speed guidance model of the CV environment to alleviate traffic congestion at intersections and improve traffic efficiency. By introducing the theory of moving block section for high-speed train control, a speed guidance model based on the quasi-moving block speed guidance (QMBSG) is proposed to direct platoon including human-driven vehicles and connected vehicles (CV) through the intersection coordinately.

In this model, the green time of the intersection is divided into multiple block intervals according to the minimal safety headway. Connected vehicles can pass through the intersection by following the block interval using the QMBSG model. The block interval is assigned dynamically according to the traveling relation of HV and CV, when entering the communication range of the intersection. To validate the comprehensive guidance effect of the proposed model, a general evaluation function (GEF) is established. Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement.

Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement. Also, compared to the single intersection speed guidance model, the GEF value of the QMBSG model improves over 17.1%. To further explore the guidance effect, the impact of sensitivity factors of the CVs’ environment, such as intersection environment, communication range and penetration rate (PR) is analyzed. When the PR reaches 75.0%, the GEF value will change suddenly and the model guidance effect will be significantly improved. This paper also analyzes the impact of the length of block interval under different PR and traffic demands. It is found that the proposed model has a better guidance effect when the length of the block section is 2 s, which facilitates traffic congestion alleviation of the intersection in practice.

Based on the aforementioned discussion, the contributions of this paper are three-fold. Based on the traveling information of HV/CV and the signal phase and timing plans, the QMBSG model is proposed to direct platoon consisting of HV and CV through the intersection coordinately, by following the block interval assigned dynamically. Considering comprehensively the indexes of mobility, safety and environment, a GEF is provided to evaluate the guidance effect of vehicles through the intersection. Sensitivity analysis is carried out on the QMBSG model. The key communication and traffic parameters of the CV environment are analyzed, such as path attenuation, PR, etc. Finally, the effect of the length of block interval is explored.

Francois Quesnay, known as the “Confucius of Europe”, was profoundly influenced by traditional Chinese culture to form his thoughts, which contained strong Chinese characteristics. This paper aims to examine economic thought of Francois Quesnay from the perspective of the construction of socialist political economics with Chinese characteristics.

Moreover, his thoughts also profoundly influenced subsequent economists, such as Adam Smith and Karl Marx. It can be said that Francois Quesnay was at the intersection of Chinese, Western and Marxist thought systems, so it is quite important to examine his thoughts critically and conduct source-tracing in China.

Hence, in the process of constructing and developing socialist political economy with Chinese characteristics, there is an urgent need to focus on exploring the value of excellent traditional Chinese culture at the theoretical level and combining the development and dissemination of the history of thoughts and the historical position of Chinese reality to realize the innovation and development of socialist political economy with Chinese characteristics.

Meanwhile, while absorbing nutrition from excellent traditional Chinese culture, it is necessary to establish scientific coordinates rather than use the discourse systems and paradigms of Western economics to interpret ancient Chinese economic thoughts. It is necessary to adhere to, inherit and develop Marxist political economy and absorb nutrition from Chinese excellent traditional culture to construct socialist political economy with Chinese characteristics.

The purpose of this study is to explore the impact of digital technology on promoting the equalization of basic regional public services based on measuring the level of digital technology and the equalization level of regional basic public services.

Based on the inter-provincial panel data from 2013 to 2021, this article utilizes the method of replacing digital technology to verify the robustness of the conclusion, evaluating the impact of digital technology on promoting the equalization of basic regional public services, while carrying out an extended analysis of government intervention, population density and regional heterogeneity.

According to our findings, digital technology has significantly promoted the equalization of basic public services in the region. According to the result of the heterogeneity test, digital technology has a better effect on promoting the equalization of public services in regions with moderate government intervention and relatively low population density. Moreover, the development of digital technology can significantly promote the equalization of public services in China’s eastern region.

This article elaborates on the impact of digital technology on the equalization of basic regional public services from three perspectives: reducing the cost of public services, increasing the degree of marketization of public services and realizing the sharing of public service resources. Thus, it enriches the empirical research literature on digital technology and the equalization of regional public services.

Climate change has aroused widespread concern around the world, which is one of the most complex challenges encountered by human beings. The underlying cause of climate change is the increase of carbon emissions. To reduce carbon emissions, the analysis of the factors affecting this type of emission is of practical significance.

This paper identified five factors affecting carbon emissions using the logarithmic mean Divisia index (LMDI) decomposition model (e.g. per capita carbon emissions, industrial structure, energy intensity, energy structure and per capita GDP). Besides, based on the projection pursuit method, this paper obtained the optimal projection directions of five influencing factors in 30 provinces (except for Tibet). Based on the data from 2000 to 2014, the authors predicted the optimal projection directions in the next six years under the Markov transfer matrix.

The results indicated that per capita GDP was the critical factor for reducing carbon emissions. The industrial structure and population intensified carbon emissions. The energy structure had seldom impacted on carbon emissions. The energy intensity obviously inhibited carbon emissions. The best optimal projection direction of each index in the next six years remained stable. Finally, this paper proposed the policy implications.

This paper provides an insight into the current state and the future changes in carbon emissions.