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Abnormal vibrations often occur in the liquid oxygen kerosene transmission pipelines of rocket engines, which seriously threaten their safety. Improper handling can result in failed rocket launches and significant economic losses. Therefore, this paper aims to examine vibrations in transmission pipelines.

In this study, a three-dimensional high-pressure pipeline model composed of corrugated pipes, multi-section bent pipes, and other auxiliary structures was established. The fluid–solid coupling method was used to analyse vibration characteristics of the pipeline under various external excitations. The simulation results were visualised using MATLAB, and their validity was verified via a thermal test.

In this study, the vibration mechanism of a complex high-pressure pipeline was examined via a visualisation method. The results showed that the low-frequency vibration of the pipe was caused by fluid self-excited pressure pulsation, whereas the vibration of the engine system caused a high-frequency vibration of the pipeline. The excitation of external pressure pulses did not significantly affect the vibrations of the pipelines. The visualisation results indicated that the severe vibration position of the pipeline thermal test is mainly concentrated between the inlet and outlet and between the two bellows.

The results of this study aid in understanding the causes of abnormal vibrations in rocket engine pipelines.

The causes of different vibration frequencies in the complex pipelines of rocket engines and the propagation characteristics of external vibration excitation were obtained.

Established in 2010, Mellower Coffee has 40 exquisite chain stores and three branches, namely Mellower Coffee Sales, Mellower Business Management and Shanghai Mellower Roasting Factory. Positioned as a premium coffee brand in China, Mellower Coffee has realized the integrated operation and management of the whole industrial chain from raw coffee trade, roasting factory, coffee retail products, specialty coffee chain, office coffee to coffee academy. It has a vision to attract and cultivate more and more coffee lovers by constant innovation coffee culture promotion.

This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s embeddedness in the global value chain (GVC) and the influence of environmental law, operational costs and corporate social responsibility (CSR). The insights gleaned bridge a gap in the literature surrounding GVCs and corporate carbon transfer.

The methodology comprised a two-step research approach. First, the authors used a two-sided fixed regression to analyse the relationship between each firm’s embeddedness in the GVC and its carbon transfers. The sample consisted of 217 US firms. Next, the authors examined the influence of environmental law, operational costs and CSR on carbon transfers using a quantitative comparison analysis. These results were interpreted through the theoretical frameworks of the GVC and legitimacy theory.

The empirical results indicate positive relationships between carbon transfers and GVC embeddedness in terms of both a firm’s position and its degree. From the quantitative comparison, the authors find that the pressure of environmental law and operational costs motivate these transfers through the value chain. Furthermore, CSR does not help to mitigate transfers.

The findings offer insights for policymakers, industry and academia to understand that, with globalised production and greater value creation, transferring carbon to different parts of the GVC – largely to developing countries – will only become more common. The underdeveloped nature of environmental technology in these countries means that global emissions will likely rise instead of fall, further exacerbating global warming. Transferring carbon is not conducive to a sustainable global economy. Hence, firms should be closely regulated and given economic incentives to reduce emissions, not simply shunt them off to the developing world.

Carbon transfer is a major obstacle to effectively reducing carbon emissions. The responsibilities of carbon transfer via GVCs are difficult to define despite firms being a major consideration in such transfers. Understanding how and why corporations engage in carbon transfers can facilitate global cooperation among communities. This knowledge could pave the way to establishing a global carbon transfer monitoring network aimed at preventing corporate carbon transfer and, instead, encouraging emissions reduction.

This study extends the literature by investigating carbon transfers and the GVC at the firm level. The authors used two-step research approach including panel data and quantitative comparison analysis to address this important question. The authors are the primary study to explore the motivation and pathways by which firms transfer carbon through the GVC.

A time-varying grey Fourier model (TVGFM(1,1,N)) is proposed for the simulation of variable amplitude seasonal fluctuation time series, as the performance of traditional grey models can't catch the time-varying trend well.

The proposed model couples Fourier series and linear time-varying terms as the grey action, to describe the characteristics of variable amplitude and seasonality. The truncated Fourier order N is preselected from the alternative order set by Nyquist-Shannon sampling theorem and the principle of simplicity, then the optimal Fourier order is determined by hold-out method to improve the robustness of the proposed model. Initial value correction and the multiple transformation are also studied to improve the precision.

The new model has a broader applicability range as a result of the new grey action, attaining higher fitting and forecasting accuracy. The numerical experiment of a generated monthly time series indicates the proposed model can accurately fit the variable amplitude seasonal sequence, in which the mean absolute percentage error (MAPE) is only 0.01%, and the complex simulations based on Monte-Carlo method testify the validity of the proposed model. The results of monthly electricity consumption in China's primary industry, demonstrate the proposed model catches the time-varying trend and has good performances, where MAPE_F and MAPE_T are below 5%. Moreover, the proposed TVGFM(1,1,N) model is superior to the benchmark models, grey polynomial model (GMP(1,1,N)), grey Fourier model (GFM(1,1,N)), seasonal grey model (SGM(1,1)), seasonal ARIMA model seasonal autoregressive integrated moving average model (SARIMA) and support vector regression (SVR).

The parameter estimates and forecasting of the new proposed TVGFM are studied, and the good fitting and forecasting accuracy of time-varying amplitude seasonal fluctuation series are testified by numerical simulations and a case study.

This paper aims to determine the adaptability of China’s legal system in recognizing and enforcing foreign judgements in China.

Academic articles, case law and books are examined as are relevant reports by various regulatory authorities and organizations.

Historically, Chinese courts have strictly adhered to “de facto reciprocity”, which made it difficult for foreign judgements to be recognized and enforced in China. Fortunately, Chinese courts have since abandoned their rigid adherence to de facto reciprocity, and have instead, used flexible tests of reciprocity such as de jure reciprocity, reciprocal commitment and reciprocal understand/consensus. Accordingly, this would facilitate the recovery of stolen assets, as there is a lower threshold for the recognition and enforcement of a foreign judgement.

There are limited data available in relation to the recognition and enforcement of foreign judgements pertaining to the recovery of stolen assets. Any discussions within this paper are based on the impressionistic observations of this author, which may not reflect the true state of affairs within the Belt and Road Initiative.

Those who are interested in examining the viability in recognizing and enforcing foreign judgements relating to stolen assets will have an interest in this topic.

The value of the paper is to demonstrate the difficulties in recognizing and enforcing foreign judgements in China in relation to stolen assets.

To solve the instability problem of Zhangjiayao landslide caused by rainfall, the internal mechanism of slope instability and the supporting effect of anti-slide piles are studied. The research results can provide theoretical basis for the prevention and control of loess landslides.

A three-dimensional finite element model of Zhangjiayao landslide is established by field geological survey, laboratory test and numerical simulation.

The results show that Zhangjiayao landslide is a loess-mudstone contact surface landslide, and rainfall leads to slope instability and traction landslide. The greater the rainfall intensity, the faster the pore water pressure of the slope increases and the faster the matrix suction decreases. The longer the rainfall duration, the greater the pore water pressure of the slope and the smaller the matrix suction. Anti-slide pile treatment can significantly improve slope stability. The slope safety factor increases with the increase of embedded depth of anti-slide pile and decreases with the increase of pile spacing.

Based on the unsaturated soil seepage theory and finite element strength reduction method, the failure mechanism of Zhangjiayao landslide was revealed, and the anti-slide pile structure was optimized and designed based on the pile-soil interaction principle. The research results can provide theoretical basis for the treatment of loess landslides.

1. A three-dimensional finite element model of Zhangjiayao landslide is established.

2. Zhangjiayao landslide is a loess-mudstone contact surface landslide.

3. The toe of Zhangjiayao slope is first damaged by heavy rainfall, resulting in traction landslide.

4. The deformation of Zhangjiayao slope is highly dependent on rainfall intensity and duration.

5. The anti-slide pile can effectively control the continuous sliding of Zhangjiayao slope.

A three-dimensional finite element model of Zhangjiayao landslide is established.

Zhangjiayao landslide is a loess-mudstone contact surface landslide.

The toe of Zhangjiayao slope is first damaged by heavy rainfall, resulting in traction landslide.

The deformation of Zhangjiayao slope is highly dependent on rainfall intensity and duration.

The anti-slide pile can effectively control the continuous sliding of Zhangjiayao slope.

This paper intends to construct a new adaptive grey seasonal model (AGSM) to promote the application of the grey forecasting model in quarterly GDP.

Firstly, this paper constructs a new accumulation operation that embodies the new information priority by using a hyperparameter. Then, a new AGSM is constructed by using a new grey action quantity, nonlinear Bernoulli operator, discretization operation, moving average trend elimination method and the proposed new accumulation operation. Subsequently, the marine predators algorithm is used to quickly obtain the hyperparameters used to build the AGSM. Finally, comparative analysis experiments and ablation experiments based on China's quarterly GDP confirm the validity of the proposed model.

AGSM can be degraded to some classical grey prediction models by replacing its own structural parameters. The proposed accumulation operation satisfies the new information priority rule. In the comparative analysis experiments, AGSM shows better prediction performance than other competitive algorithms, and the proposed accumulation operation is also better than the existing accumulation operations. Ablation experiments show that each component in the AGSM is effective in enhancing the predictive performance of the model.

A new AGSM with new information priority accumulation operation is proposed.

During the past decade, the necessity to integrate manufacturing and sustainability has increased mainly to reduce the adverse effect on the manufacturing industry, transforming traditional manufacturing into smart manufacturing by adopting the latest manufacturing technology as part of the Industry 4.0 revolution. Smart manufacturing has piqued the interest of both academics and industry. Manufacturing is a foundation of products and services required for human health, safety, and well-being in modern society and from an organizational standpoint. This paper uses bibliometric analysis better to understand the relationship between smart manufacturing and sustainability scholarship and provide an up-to-date account of current industry practices.

This paper used the bibliometric analysis method to analyze and draw conclusions from 839 articles retrieved from the Scopus database from 1994 to February 2022. The methodology is divided into four steps: data collection, analysis, visualization, and interpretation. The current study aims to comprehend smart manufacturing and sustainability scholarship using the bibliometric R-package and VOSviewer software.

The study provides fascinating insights that may assist scholars, industry professionals, and top management in conceptualizing smart manufacturing and sustainability in their organizations. The results show that the number of publications has significantly increased from 2015 onwards, reaching a maximum of 317 journals in 2021 with an increasing publication annual growth rate of 21.9%. The United Kingdom, India, the United States of America, Italy, France, Brazil and China were the most productive countries in terms of the total number of publications. Technological Forecasting and Social Change, Journal of Cleaner Production, International Journal of Production Research, Production Planning and Control, Business Strategy and the Environment Technology in Society, and Benchmarking: An International Journal emerged as the top outlets.

The research in the area of smart manufacturing and sustainability is underpinned by this study, which aims to understand the trends in this field over the last two decades in terms of prolific authors, most influential journals, key themes, and the field's intellectual and social structure. However, according to the research, this field is still in its early stages of development. As a result, a more in-depth analysis is required to aid in the development of a better understanding of this new field.

The paper focuses on integrating smart manufacturing and sustainability through increased interest from 2015 onwards through the literature review. Specific policies should be formulated to improve the manufacturing sector's competence. Furthermore, these findings can guide researchers who want to delve deeper into smart manufacturing and sustainability.

This study investigates the impact of network positions on inter-team conflicts and project success in megaprojects.

Network position is measured with centrality and structural holes. Substantive conflict and affective conflict reflect inter-team conflicts. A questionnaire survey was implemented in Chinese megaprojects, and 309 valid questionnaires were collected. The data were analyzed using structural equation modeling and bootstrapping methods.

The results show that centrality negatively impacts project success, while the presence of a team in a structural hole has no significant impact on project success. Centrality is negatively related to substantive conflict and is positively related to affective conflict. The team in a structural hole has a positive effect on substantive conflict and a negative effect on affective conflict. Substantive conflict and affective conflict have positive and negative effects on project success, respectively. The effect of network position on project success is mediated by inter-team conflict.

This research provides a reference for megaproject managers to better conduct network governance, manage inter-team conflict, and successfully manage projects. The study did not investigate the effects of changes in teams' network positions on project success. Future research should explore this facet of megaprojects.

This research adds to existing research on network position, and reveals that project network governance is important for megaproject success. This provides a new direction for megaproject management. Furthermore, the results validate constructive and non-constructive roles and the mediating role of inter-team conflict. This complements the literature on conflict management, providing a reference for megaproject managers when managing inter-team conflict.

The proliferation of health misinformation on social media has increasingly engaged scholarly interest. This research examines the determinants influencing users’ proactive correction of health misinformation, a crucial strategy in combatting health misbeliefs. Grounded in the elaboration likelihood model (ELM), this research investigates how factors including issue involvement, information literacy and active social media use impact health misinformation recognition and intention to correct it.

A total of 413 social media users finished a national online questionnaire. SPSS 26.0, AMOS 21.0 and PROCESS Macro 4.1 were used to address the research hypotheses and questions.

Results indicated that issue involvement and information literacy both contribute to health misinformation correction intention (HMCI), while misinformation recognition acts as a mediator between information literacy and HMCI. Moreover, active social media use moderated the influence of information literacy on HMCI.

This study not only extends the ELM into the research domain of correcting health misinformation on social media but also enriches the perspective of individual fact-checking intention research by incorporating dimensions of users’ motivation, capability and behavioral patterns.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2023-0505