An extensive assessment index system was developed to evaluate the integration of industry and education in higher vocational education. The system was designed using panel data collected from 31 provinces in China between 2016 and 2022. The study utilized the entropy approach and coupled coordination degree model to examine the temporal and spatial changes in the level of growth of the integration of industry and education in higher vocational education, as well as the factors that impact it. In order to examine how the integration of industry and education in higher vocational education develops over time and space, as well as the factors that affect it, we utilized spatial phasic analysis, Tobit regression model, and Dagum’s Gini coefficient. The study’s findings suggest that between 2016 and 2022, the integration of industry and education in higher vocational education showed a consistent improvement in overall development. Nevertheless, there are still significant regional differences, with certain areas showing limited levels of integration, while the bulk of regions are either in a state of low integration with high clustering or low integration with low clustering. Most locations showed either a “low-high” or “low-low” level of agglomeration, indicating a significant degree of spatial concentration, with a clear trend of higher concentration in the east and lower concentration in the west. The progress of industrial structure and the degree of regional economic development have a substantial impact on the amount of integration of industry and education in higher vocational education. There is a notable increase in the amount of integration between industry and education in higher vocational education, which has a favorable effect. Conversely, the local employment rate has a substantial negative effect on this integration. Moreover, the direct influence of industrial structure optimization is restricted. The Gini coefficient of the development level of integration of industry and education in higher vocational education exhibits a slight rising trend. Simultaneously, there is a varying increase in the Gini coefficient inside the group and a decrease in the Gini coefficient between the groups. The disparities in the level of integration between Industry and Education in the provincial area primarily stem from inter-group variations across the locations. To promote the integration of industry and education in higher vocational education, it is recommended to strengthen policy support and resource allocation, address regional disparities, improve professional configuration, and increase investment in scientific and technological innovation and talent development.

The Akit tribe fishermen on Rupat Island, Riau, Indonesia, are a remote indigenous community with a low level of education. They have experienced cultural acculturation after the influx of outsiders and the government built road infrastructure to break the isolation. The government also provides internet facilities to speed up the process of modernizing communications between them. The research aim is to analyze the role of government support as a mediator in the influence of education and acculturation on communication modernization among Akit fishermen. The research used a survey method, involving 165 of the 763 Akit fishermen as respondents. This number determine used the Sample Size Calculator technique. Respondents were selected using a purposive random sampling technique. The variables studied consisted of education, acculturation, government support (as mediator), and communication modernization. Data collection was carried out through a closed questionnaire containing statements, which were measured with a 5-point Likert scale. The data were analyzed using the Structural Equation Modeling method with the help of SmartPLS 4 software. The research results show that acculturation and government support have a positive and significant influence on communication modernization, while education plays a negative influence. Government support as a mediator plays a positive and significant role in the influence of education on communication modernization, while it does not play any role in the influence of acculturation. The most implication of this research is that the government must further increase its role in organizing the acculturation process for Akit fishermen to accelerate the communication modernization process.

Credit policies for clean and renewable energy businesses play a crucial role in supporting carbon neutrality efforts to combat climate change. Clustering the credit capacity of these companies to prioritize lending is essential given the limited capital available. Support Vector Machine (SVM) and Artificial Neural Network (ANN) are two robust machine learning algorithms for addressing complex clustering problems. Additionally, hyperparameter selection within these models is effectively enhanced through the support of a robust heuristic optimization algorithm, Particle Swarm Optimization (PSO). To leverage the strength of these advanced machine learning techniques, this paper aims to develop SVM and ANN models, optimized with the PSO, for the clustering problem of green credit capacity in the renewable energy industry. The results show low Mean Square Error (MSE) values for both models, indicating high clustering accuracy. The credit capabilities of wind energy, clean fuel, and biomass pellet companies are illustrated in quadrant charts, providing stakeholders with a clear view to adjust their credit strategies. This helps ensure the efficient operation of banking green credit policies.

The proportion of national logistics costs to Gross Domestic Product (NLC/GDP) serve as a valuable indicator for estimating a country’s overall macro-level logistics costs. In some developing nations, policies aimed at reducing the NLC/GDP ratio have been elevated to the national agenda. Nevertheless, there is a paucity of research examining the variables that can determine this ratio. The purpose of this paper is to offer a scientific approach for investigating the primary determinants of the NLC/GDP and to advice policy for the reduction of macro-level logistics costs. This paper presents a systematic framework for identifying the essential criteria for lowering the NLC/GDP score and employs co-integration analysis and error correction models to evaluate the impact of industrial structure, logistics commodity value, and logistics supply scale on NLC/GDP using time series data from 1991 to 2022 in China. The findings suggest that the industrial structure is the primary factor influencing logistics demand and a significant determinant of the value of NLC/GDP. Whether assessing long-term or short-term effects, the industrial structure has a substantial impact on NLC/GDP compared to logistics supply scale and logistics commodity value. The research offers two policy implications: firstly, the goals of reducing NLC/GDP and boosting the logistics industry’s GDP are inherently incompatible; it is not feasible to simultaneously enhance the logistics industry’s GDP and decrease the macro logistics cost. Secondly, if China aims to lower its macro-level logistics costs, it must make corresponding adjustments to its industrial structure.

In the process of constructing and building the industry English curriculum system in the new era, higher education institutions should clarify the corresponding curriculum teaching focus and direction, analyze, optimize, and improve the defects and deficiencies in the English curriculum teaching system. They should also combine refined and beneficial teaching ideas and strategies, innovate existing teaching methods, and integrate more ideological and political elements into curriculum teaching, to achieve more efficient teaching guidance for students. This article briefly analyzes and explores the strategies for constructing the English course system for waterway transportation and maritime management majors at present.

With the characteristics of resisting business cycle, mitigating cash flow, and improving portfolio resilience, special assets usually enter a highly active period in the economic downturn cycle, and gradually become an effective asset allocation means in the transition phase of the business cycle. This article aims to analyze the importance of the development of China's special asset investment industry in the context of high-quality economic development, and explore how to introduce market-oriented mechanisms to build primary and secondary markets for special assets, in order to improve the effective allocation of market resources and maximize returns.