Search results

This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.

First, taking the Liuyuan Tunnel of Huanggang-Huangmei High-Speed Railway as an example and taking deflection of the third principal stress of the surrounding rock at a vault after tunnel excavation as the criterion, the critical buried depth of the large section tunnel was determined. Then, the strength reduction method was employed to calculate the tunnel safety factor under different rock classes and thickness-span ratios, and mathematical statistics was conducted to identify the relationships of the tunnel safety factor with the thickness-span ratio and the basic quality (BQ) index of the rock for different rock classes. Finally, the influences of thickness-span ratio, groundwater, initial stress of rock and structural attitude factors were considered to obtain the corrected BQ, based on which the stability of a large cross-section tunnel with a depth of more than 100 m during mechanized operation was analyzed. This evaluation method was then applied to Liuyuan Tunnel and Cimushan No. 2 Tunnel of Chongqing Urban Expressway for verification.

This study shows that under different rock classes, the tunnel safety factor is a strict power function of the thickness-span ratio, while a linear function of the BQ to some extent. It is more suitable to use the corrected BQ as a quantitative index to evaluate tunnel stability according to the actual conditions of the site.

The existing industry standards do not consider the influence of buried depth and span in the evaluation of tunnel stability. The stability evaluation method of large section tunnel considering the correction of overburden span ratio proposed in this paper achieves higher accuracy for the stability evaluation of surrounding rock in a full or large-section mechanized excavation of double line high-speed railway tunnels.

Intermediate short food supply chains (SFSC) have been presented as a possible solution to unsustainable global food supply chains. There is currently a knowledge gap about intermediate SFSC. Thus, this review synthesizes the available literature to identify prominent themes and their main considerations.

This research is based on a systematic literature review including peer-reviewed journal articles until December 2021. Inductive data coding resulted in the identification of four themes related to intermediate SFSC.

The identified themes illustrate the complex landscape intermediate SFSCs operate in and focus on the key relationships within these supply chains. The established relationships have implications for the governance of intermediate SFSCs. The organization of intermediate SFSCs affects numerous sustainability indicators.

Future research should focus on the position intermediate SFSCs have in food systems and the roles intermediaries have in intermediate SFSCs. There is furthermore an opportunity for researchers to investigate different types of intermediaries and explore the factors influencing them.

Creating sustainable food supply chains is one of the major societal challenges of today. The current state of the art suggests that intermediate SFSCs could play an important role in achieving this. So far, this area is underdeveloped and this review highlights knowledge gaps in the literature and suggestions for a future research agenda are proposed.

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.

Global climate change is a serious threat to the survival and development of mankind. Reducing carbon emissions and achieving carbon neutrality are the keys to reducing greenhouse gas emissions and promoting sustainable human development. For many countries, taking China as an example, the electric power sector is the main contributor to the country’s carbon emissions, as well as a key sector for reducing carbon emissions and achieving carbon neutrality. The low-carbon transition of the power sector is of great significance to the long-term low-carbon development of the economy. Therefore, on the one hand, it is necessary to improve the energy supply structure on the supply side and increase the proportion of new energy in the total power supply. On the other hand, it is necessary to improve energy utilization efficiency on the demand side and control the total primary energy consumption by improving energy efficiency, which is the most direct and effective way to reduce emissions. Improving the utilization efficiency of electric energy and realizing the low-carbon transition of the electric power industry requires synergies between the government and the market. The purpose of this study is to investigate the individual and synergistic effects of China’s low-carbon policy and the opening of urban high-speed railways (HSRs) on the urban electricity consumption efficiency, measured as electricity consumption per unit of gross domestic product (GDP).

This study uses a panel of 289 Chinese prefecture-level cities from the years 1999–2019 as the sample and uses the time-varying difference-in-difference method to test the relationship between HSR, low-carbon pilot cities and urban electricity consumption efficiency. In addition, the instrumental variable method is adopted to make a robustness check.

Empirical results show that the low-carbon pilot policy and the HSR operation in cities would reduce the energy consumption per unit of GDP, and synergies occur in both HSR operated and low-carbon pilot cities.

This study has limitations that would provide possible starting points for future studies. The first limitation is the choice of the proxy variable of government and market factors. The second limitation is that the existing data is only about whether the high-speed rail is opened or not and whether it is a low-carbon pilot city, and there is no more informative data to combine the two aspects.

The findings of this study can inform policymakers and regulators about the effects of low-carbon pilot city policies. In addition, the government should consider market-level factors in addition to policy factors. Only by combining various influencing factors can the efficient use of energy be more effectively achieved so as to achieve the goal of carbon neutrality.

From the social perspective, the findings indicate that improving energy utilization is dependent on the joint efforts of the government and market.

The study provides quantitative evidence to assess the synergic effect between government and the market in the low-carbon transition of the electric power industry. Particularly, to the best of the authors’ knowledge, it is the first to comprehend the role of the city low-carbon pilot policy and the construction of HSR in improving electricity efficiency.

The authors examine psychologically informed coaching approaches for evidence-based work-applied management through a meta-analysis. This analysis synthesized previous empirical coaching research evidence on cognitive behavioral and positive psychology frameworks regarding a range of workplace outcomes, including learning, performance and psychological well-being.

The authors undertook a systematic literature search to identify primary studies (k = 20, n = 957), then conducted a meta-analysis with robust variance estimates (RVEs) to test the overall effect size and the effects of each moderator.

The results confirm that psychologically informed coaching approaches facilitated effective work-related outcomes, particularly on goal attainment (g = 1.29) and self-efficacy (g = 0.59). Besides, these identified coaching frameworks generated a greater impact on objective work performance rated by others (e.g. 360 feedback) than on coachees' self-reported performance. Moreover, a cognitive behavioral-oriented coaching process stimulated individuals' internal self-regulation and awareness to promote work satisfaction and facilitated sustainable changes. Yet, there was no statistically significant difference between popular and commonly used coaching approaches. Instead, an integrative coaching approach that combines different frameworks facilitated better outcomes (g = 0.71), including coachees' psychological well-being.

Effective coaching activities should integrate cognitive coping (e.g. combining cognitive behavioral and solution-focused technique), positive individual traits (i.e. strength-based approach) and contextual factors for an integrative approach to address the full range of coachees' values, motivators and organizational resources for yielding positive outcomes.

Building on previous meta-analyses and reviews of coaching, this synthesis offers a new insight into effective mechanisms to facilitate desired coaching results. Frameworks grounded in psychotherapy and positive appear most prominent in the literature, yet an integrative approach appears most effective.

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.

This paper focuses on governance in higher education in China. It sees that governance as distinctive on the world scale and the potential source of distinctiveness in other domains of higher education. By taking an historical approach, reviewing relevant literature and drawing on empirical research on governance at one leading research university, the paper discusses system organisation, government–university relations and the role of the Communist Party (CCP), centralisation and devolution, institutional leadership, interior governance, academic freedom and responsibility, and the relevance of collegial norms. It concludes that the party-state and Chinese higher education will need to find a Way in governance that leads into a fuller space for plural knowledges, ideas and approaches. This would advance both indigenous and global knowledge, so helping global society to also find its Way.

Library intelligence institutions, which are a kind of traditional knowledge management organization, are at the frontline of the big data revolution, in which the use of unstructured data has become a modern knowledge management resource. The paper aims to discuss this issue.

This research combined theme logic structure (TLS), artificial neural network (ANN), and ensemble empirical mode decomposition (EEMD) to transform unstructured data into a signal-wave to examine the research characteristics.

Research characteristics have a vital effect on knowledge management activities and management behavior through concentration and relaxation, and ultimately form a quasi-periodic evolution. Knowledge management should actively control the evolution of the research characteristics because the natural development of six to nine years was found to be difficult to plot.

Periodic evaluation using TLS-ANN-EEMD gives insights into journal evolution and allows journal managers and contributors to follow the intrinsic mode functions and predict the journal research characteristics tendencies.

The purpose of this study is to develop a cylindrical capacitive sensor that has the advantages of high resolution, small size and designability and can be easily installed on lubricant pipeline to monitor lubricant oil debris.

A theoretical model of the cylindrical capacitive sensor is presented to analyze several parameters’ effectiveness on the performance of sensor. Numerical simulations are then conducted to determine the optimal parameters for preliminary experiments. Experiments are finally carried out to demonstrate the detectability of developed capacitive sensors.

It is clear from experimental results that the developed capacitive sensor can monitor the debris in lubricant oil well, and the capacitance values increase almost linearly when the number and size of debris increase.

There is lot of further work to do to apply the presented method into the application. Especially, it is necessary to consider several factors’ influence on monitoring results. These factors include the flow rate of the lubricant oil, the temperature, the debris distribution and the vibration. Moreover, future work should consider the influence of the oil degradation to the capacitance change and other contaminations (e.g. water and dust).

This work conducts a feasibility study on application of capacitive sensing principle for detecting debris in aero engine lubricant oil.

The novelty of the presented capacitance sensor can be summarized into two aspects. One is that the sensor structure is simple and characterized by two coaxial cylinders as electrodes, while conventional capacitive sensors are composed of two parallel plates as electrodes. The other is that sensing mechanism and physical model of the presented sensor is verified and validated by the simulation and experiment.