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The coal-based synthetic natural gas slag (CSNGS) is a solid waste remaining from the incomplete combustion of raw coal to produce gas. With the continuous promotion of efficient and clean utilization of coal in recent years, the stockpiling of CSNGS would increase gradually, and it would have significant social and environmental benefits with reasonable utilization of CSNGS. This study prepared a new geopolymer by mixing CSNGS with PC42.5 cement in a certain mass ratio as the precursor, with sodium hydroxide and sodium silicate solution as the alkali activators.

The formulation of coal-based synthetic natural gas slag geopolymer (CSNGSG) was determined by an orthogonal test, and then the strength mechanism and microstructure of CSNGSG were characterized by multi-scale tests.

The results show that the optimum ratio of CSNGSG was a sodium silicate modulus of 1.3, an alkali dosage of 21% and a water cement ratio of 0.36 and the maximum unconfined compressive strength of CSNGSG at 7 d was 26.88 MPa. The increase of curing temperature could significantly improve the compressive strength of CSNGSG, and the curing humidity had little effect on the compressive strength of CSNGSG. The development of the internal strength of CSNSG at high temperatures consumed SiO₂, Al₂O₃ and CaO and the intensity of corresponding crystalline peaks decreased.

Moreover, the vibration of chemical bonds in different wavenumbers also revealed the reaction mechanism of CSNSG from another perspective. Finally, the relevant test results indicated that CSNGS had practical application value as a raw material for the preparation of geopolymer cementing materials.

Digital transformation and innovation-driven development have become an international consensus. The purpose of this paper is to examine the effects of relationships, mechanisms and economic consequences between digital transformation and enterprise innovation quality in order to provide a benchmark for developing countries to implement digital transformation strategies and innovation-driven strategies and provide a major support for economic recovery in the post-coronavirus disease 2019 (COVID-19) era.

Using microdata from A-share listed enterprises in Shanghai and Shenzhen from 2010 to 2021, this study examines the relationship between digital transformation and enterprise innovation quality and further reveals the internal logic and economic consequences of digital transformation to improve enterprise innovation quality through the mediating effect and moderating effect models.

The results demonstrate that digital transformation is beneficial for improving enterprise innovation quality. The heterogeneity test demonstrates that digital transformation has a larger effect on improving enterprise innovation quality in non-state-owned enterprises and eastern enterprises in China. The mechanism test demonstrates that digital transformation can improve enterprise innovation quality by improving internal control quality and analyst attention. Furthermore, with the increase in enterprise innovation inputs, digital transformation plays a significantly stronger role in improving enterprise innovation quality. The extended analysis demonstrates that digital transformation can significantly improve enterprise financial performance by improving innovation quality.

First, the construction of the core explanatory variable digital transformation index in this study is based on the Python data analysis software, which calculates the frequency of digital transformation in the text of the business situation analysis portion of the annual report of the listed companies and then obtains the degree of digital transformation of the company in this year. There may be some deviation from the degree of digital transformation in the actual production and operation of enterprises. Second, in addition to internal control quality and analyst attention, are there other mediating mechanisms for the impact of digital transformation on the quality of enterprise innovation? Third, whether the moderating effect of innovation input on digital transformation and innovation quality is related to human capital factors of the research and development (R&D) team, such as the technical background of R&D personnel, etc.

This study enriches the relevant theories of digital transformation and broadens the research boundaries of digital transformation and enterprise innovation. This study's result provides an empirical basis for enterprises to improve enterprise innovation quality and financial performance from the perspective of digital transformation at the micro level and points out specific practical directions, combining theory with practice.

This study aimed to develop a method to calculate the mattress indentation for further estimating spinal alignment.

A universal indentation calculation model is derived based on the system theory, and the deformation characteristics of each component are analyzed by the finite element (FE) model of a partial air-spring mattress under the initial air pressure of 0.01–0.025 MPa. Finally, the calculation error of the model is verified.

The results indicate that the indentation calculation model could describe the stain of a mattress given the load and the constitutive model of each element. In addition, the FE model of a partial air-spring mattress can be used for further simulation analysis with an error of 1.47–3.42 mm. Furthermore, the deformation of the series system is mainly contributed by the air spring and the components directly in contact with it, while the top component is mainly deflection deformation. In addition, the error of the calculation model is 2.17–5.59 mm on the condition of 0.01–0.025 MPa, satisfying the engineering application. Finally, the supine spinal alignment is successfully extracted from the mattress indentation.

The limitation of this study is that it needs to verify the practicality of the indentation calculation model for the Bonnier spiral spring mattress. The main feature of the Bonnier spring mattress is that all springs are connected, so the mattress deflection and neighborhood effect are more significant than those of the air-spring mattress. Therefore, the applicability of the model needs to be tested. Moreover, it is worth further research to reduce the deformation error of each component.

As part of the series of studies on the intelligent air-spring mattress, the indentation-based evaluation method of spinal alignment in sleep postures will be studied for hardness and intelligent regulation based on this study.

The results of this research are ultimately used for the intelligent adjustment of air-spring mattresses, which automatically adjusts the hardness according to the user's sleep postures and spinal alignment, thus maintaining optimal spinal biomechanics. The successful application of this result could improve the sleep health of the general public.

Based on the series system theory, an indentation calculation model for mattresses with arbitrary structure is proposed, overcoming the dependence of parameters on materials and their combinations when fitting the Burgers model. Further, the spinal alignment in supine posture is extracted from the indentation, laying a theoretical foundation for further recognition and adjustment of the spinal alignment of the intelligent mattress.

The purpose of this study is to compare self-reported antisocial (SRA) behaviour of 10-year-old boys in China (in Zhuhai) and the USA (in Pittsburgh).

In Pittsburgh, 868 boys were given a SRA behaviour questionnaire in 1987–1988. In Zhuhai, 1,154 boys were given the same questionnaire in 2017.

The prevalence of 23 acts in the two countries was significantly correlated (r = 0.69), showing that the acts that were admitted by most boys in one country also tended to be admitted by most boys in the other country. Also, the mean prevalence in the two countries was very similar, at about 13%. However, several acts (e.g. stealing) were more prevalent in Zhuhai, while violent acts were more prevalent in Pittsburgh. The frequencies of the acts in the two countries were also significantly correlated (r = 0.51), although frequency was usually greater in Pittsburgh.

While most theories and research in criminology and psychology are based on Western industrialised countries, it is important to carry out more cross-cultural comparisons of antisocial behaviour in other countries. These results show encouraging generalizability and replicability, despite differences in time and place.

To the best of the authors’ knowledge, this study presents the first comparison of age-matched Chinese and American children on the prevalence and frequency of specific antisocial acts.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.

This study aims to investigate the neurocognitive status of people with different moods (depressed and non-depressed) both in a typical urban environment (TUE) and in an urban green environment (UGE).

The study was conducted with the participation of 210 individuals in a real environment. Heart rates of the participants were measured together with EEG and eye-tracking measurements while they were walking in a real urban environment (TUE and UGE). The participants were divided into depressed and non-depressed groups according to different moods. Movements within the city based on these two distinctions and different cognitive moods were investigated, together with the effects of the city plan on these people.

As a result, the green urban fabric was found to have a positive effect even on people with depression. Yet, it was found that the non-depressed group also spent more time in a green urban environment.

The study shows that urban planners and designers should assume an important role in the design of green spaces, which have a more intense visual and cognitive impact than structures.

This study discusses the tracking trajectory issue of the exoskeleton under the bounded disturbance and designs an useful tracking trajectory control method to solve it. By using the proposed control method, the tracking error can be successfully convergence to the assigned boundary. Meanwhile, the chattering effect caused by the actuators is already reduced, and the tracking performance of the pneumatic artificial muscles (PAMs) elbow exoskeleton is improved effectively.

A prescribed performance sliding mode control method was developed in this study to fulfill the joint position tracking trajectory task on the elbow exoskeleton driven by two PAMs. In terms of the control structure, a dynamic model was built by conforming to the adaptive law to compensate for the time variety and uncertainty exhibited by the system. Subsequently, a super-twisting algorithm-based second-order sliding mode control method was subjected to the exoskeleton under the boundedness of external disturbance. Moreover, the prescribed performance control method exhibits a smooth prescribed function with an error transformation function to ensure the tracking error can be finally convergent to the pre-designed requirement.

From the theoretical perspective, the stability of the control method was verified through Lyapunov synthesis. On that basis, the tracking performance of the proposed control method was confirmed through the simulation and the manikin model experiment.

As revealed by the results of this study, the proposed control method sufficiently applies to the PAMs elbow exoskeleton for tracking trajectory, which means it has potential application in the actual robot-assisted passive rehabilitation tasks.

The Chinese government hopes to achieve the goal of benefiting citizens by building a National Integrated Online Government Service Platform (NIOGSP). However, citizens' low adoption of the platform makes it difficult for the government to achieve its goal. Research on the influencing factors of citizen adoption of NIOGSP can help the government fully understand the concerns and needs of its citizens and take targeted measures to increase citizen adoption.

First, this research builds a model of the citizen adoption process, including attention, retention and motivation, based on an observational learning model. Next, research variables are determined based on social cognitive theory, literature review and real-world needs. Finally, based on the questionnaire survey and structural equation model, the influencing factors of each stage of the citizen adoption process model are studied and the relationship between the three stages of the model is verified.

Results show that perceived usefulness (PU) and self-efficacy (SE) positively affect attention. SE positively affects retention, while perceived privacy (PP) negatively affects retention. PU, social influence, PP and anxiety positively affect motivation.

The conclusion of this study can provide reference for governments in various countries to establish and improve online one-stop government. In addition, this study verifies the citizen adoption process model and finds that there is no obvious causal relationship between attention and retention, but both have positive effects on motivation.

The Grey System Theory (GST) is an emerging area of research within artificial intelligence. Since its founding in 1982, it has seen a lot of multidisciplinary applications. In just a short period, it has garnered some considerable strengths. Based on the 1987–2021 data collected from the Web of Science (WoS), the current study reports the advancement of the GST.

Research papers utilizing the GST in the fields of economics and education were retrieved from the Web of Science (WoS) platform using a set of predetermined keywords. In the final stage of the process, the papers that underwent analysis were manually chosen, with selection criteria based on the information presented in the titles and abstracts.

The study identifies prominent authors, institutions, publications and journals closely associated with the subject. In terms of authors, two major clusters are identified around Liu SF and Wang ZX, while the institution with the highest number of publications is Nanjing University of Aeronautics and Astronautics. Moreover, significant keywords, trends and research directions have been extracted and analyzed. Additionally, the study highlights the regions where the theory holds substantial influence.

The study is subject to certain limitations stemming from factors such as the language employed in the chosen literature, the papers included within the Web of Science (WoS) database, the designation of works categorized as “articles” in the database, the specific selection of keywords and keyword combinations, and the meticulous manual process employed for paper selection. While the manual selection process itself is not inherently limiting, it demands a greater investment of time and meticulous attention, contributing to the overall limitations of the study.

The significance of the study extends not only to scholars and practitioners but also to readers who observe the development of emerging scientific disciplines.

The analysis of trends revealed a growing emphasis on the application of GST in diverse domains, including supply chain management, manufacturing and economic development. Notably, the emergence of COVID-19 as a new research focal point among GST scholars is evident. The heightened interest in COVID-19 can be attributed to its global impact across various academic disciplines. However, it is improbable that this interest will persist in the long term, as the pandemic is gradually brought under control.