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This paper aims to explore the potential of implementing an action competence teaching model as a framework for achieving sustainable development goals (SDGs) in higher education. The paper seeks to draw insights from the students on the potential of this teaching model.

The study adopted a quantitative research design in exploring the potential of an action competence teaching model. This study used self-report measures to obtain insights into the objective of the study.

The action competence teaching model was seen as useful in equipping students with knowledge about a problem, confidence and willingness to act. However, some issues like the design of the projects, teamwork and instructional practices were identified and discussed.

To the best of the authors’ knowledge, this study is the first to implement an action competence teaching model to help draw insights from students on its potential. This paper documents certain aspects of action competence that require attention before being implemented in higher education. This information so far lacking in scientific literature contributes to ongoing discussions on SDGs while unveiling strengths and weaknesses to be considered.

A series of environmental pollution issues and economic improvement go hand in hand. Since financial listed companies contribute significantly to the national economic development, China has been paying increasing attention to the development of the financial industry. The purpose of this paper is to explore the relationship among the development level of the financial industry, over-investment of the listed companies and environmental pollution through a macro-level and micro-level mechanism.

In this study, we adopt the 2011–2017 panel data of listed companies in the manufacturing industry to study the impacts of the financial industry on environmental pollution. Meanwhile, the paper uses a mediator model, and over-investment is introduced to the econometric model as a mediator to explore whether the development of the financial industry can affect the environmental pollution through over-investment.

A U-shaped relationship between financial industry development and environmental pollution was observed through a macro-perspective; additionally, over-investment of the listed companies significantly increased environmental pollution, along with a significant mediator effect of over-investment. A significant positive correlation was observed between financial industry development and environmental pollution in the East region of China, while the correlation was negative in the Central and West regions. The mitigation effect of financial industry development on environmental pollution was more significant in the low-end manufacturing industry, compared with basic and high-end manufacturing industries.

Strengthening the incentives and supervision toward company managers, reducing over-investment behaviors, encouraging suitable financial industry development to reduce financial risks, improving environmental conservation laws and regulations, and implementing stringent penalty mechanisms for environmental conservation are necessary.

The purpose of this paper is to explore the task design and assignment of full-text generation on mass Chinese historical archives (CHAs) by crowdsourcing, with special attention paid to how to best divide full-text generation tasks into smaller ones assigned to crowdsourced volunteers and to improve the digitization of mass CHAs and the data-oriented processing of the digital humanities.

This paper starts from the complexities of character recognition of mass CHAs, takes Sheng Xuanhuai archives crowdsourcing project of Shanghai Library as a case study, and makes use of the theories of archival science, including diplomatics of Chinese archival documents, and the historical approach of Chinese archival traditions as the theoretical basis and analysis methods. The results are generated through the comprehensive research.

This paper points out that volunteer tasks of full-text generation include transcription, punctuation, proofreading, metadata description, segmentation, and attribute annotation in digital humanities and provides a metadata element set for volunteers to use in creating or revising metadata descriptions and also provides an attribute tag set. The two sets can be used across the humanities to construct overall observations about texts and the archives of which they are a part. Along these lines, this paper presents significant insights for application in outlining the principles, methods, activities, and procedures of crowdsourced full-text generation for mass CHAs.

This study is the first to explore and identify the effective design and allocation of tasks for crowdsourced volunteers completing full-text generation on CHAs in digital humanities.

This paper aims to characterize the relationship between the interelectrode capacitance (C) of metal-oxide-semiconductor field-effect transistors (MOSFETs) and the applied bias voltage (V) by a fractional-order equivalent model.

A Riemann–Liouville-type fractional-order equivalent model is proposed for the C–V characteristic of MOSFETs, which is based on the mathematical relationship between fractional calculus and the semiconductor physical model for the interelectrode capacitance of metal oxide semiconductor structure. The C–V characteristic data of an N-channel MOSFET are obtained by Silvaco TCAD simulation. A differential evolution-based offline scheme is exploited for the parameter identification of the proposed model.

According to the results of theoretical analysis, mathematical derivation, simulation and comparison, this paper illustrates that, along with the variation of bias voltage applied, the interelectrode capacitance (C) of MOSFETs performs a fractional-order characteristic.

This work uncovers the fractional-order characteristic of MOSFETs’ interelectrode capacitance. By the proposed model, the influence of doping concentration on the gate leakage parasitic capacitance of MOSFETs can be revealed. In the pre-defined doping concentration range, the relative error of the proposed model is less than 5% for the description of C–V characteristics of metal-oxide-semiconductor field-effect transistors (MOSFETs). Compared to some existing models, the proposed model has advantages in both model accuracy and model complexity, and the variation of model parameters can directly reflect the relationship between the characteristics of MOSFETs and the doping concentration of materials. Accordingly, the proposed model can be used for the microcosmic mechanism analysis of MOSFETs. The results of the analysis produce evidence for the widespread existence of fractional-order characteristics in the physical world.

This study aims to explore the influencing factors on college students’ behaviours of spreading Internet public opinion on emergencies in colleges and universities. This study provides a reference for these institutions to cope with and reduce the influence of Internet public opinion on emergencies and maintain their normal teaching order.

In this study, a research model by using motivation theory and design a questionnaire on the basis of relevant literature are constructed. This paper surveys college students and collects a total of 317 valid questionnaires. On the basis of the reliability and validity of the questionnaire, this study verifies the proposed model by using Smart PLS.

The results show that social motivation and information source preference have significant positive influences on college students’ willingness to spread Internet public opinion on emergencies in colleges and universities. Moreover, information source preference has a significant moderating effect on the relationship between social motivation and dissemination willingness. If college students’ information source preference is high, then the moderating effect is significant. The extent of college students’ interaction and involvement has a significantly positive influence on their trust in the dissemination platform for Internet public opinion on emergencies in colleges and universities. Egoism has a significantly positive influence on the social motivation of college students to spread Internet public opinion on emergencies in colleges and universities. Involvement degree has a significant moderating effect on the relationship between social motivation and trust. If college students’ involvement degree is low, then the moderating effect is significant. Thus, when the involvement of college students in Internet public opinion on emergencies in colleges and universities is low, the influence of social motivation on trust is great.

This study increases the influencing factors in the literature on Internet public opinion, enriches the research theory of Internet public opinion on emergencies in colleges and universities and expands the application scope of the theory of social motivation. The conclusion provides guidance for colleges and students to govern Internet public opinion on emergencies and improve the ability of these institutions in dealing with Internet public opinion on emergencies.

This paper aims to analyze the impact of the relations between the US oil prices, carbon emissions and GDP through the analysis of data between 1987 and 2017.

ARIMA, VAR and VEC models are used to establish synthesis integration model. Furthermore, the stability test, cointegration test and Granger causality test of the model were carried out.

The results indicate that, in both short and long term, change in oil prices is the reason for change in carbon emissions, while GDP is not the reason for the growth of carbon emissions.

Increase of oil prices would have a negative impact on carbon emissions, and GDP growth does not lead to an increase in carbon emissions.