The electoral campaign that led Trump to win the presidential election focused on attacking the elites and using nationalist rhetoric, highlighting issues such as illegal immigration and economic globalization. Once in power, his trade policies, based on perceptions of unfair competition with countries like China, resulted in the imposition of high tariffs on key products. These measures were justified as necessary to protect domestic industries and jobs, although they triggered trade wars at the international level. This article examines the economic consequences of the protectionist policies implemented by the United States under the Trump administration. The protection of less competitive sectors aims to reduce imports, negatively affecting production and income in exporting countries, and limiting U.S. exports to these markets. Although some countries have experienced an increase in real income due to trade diversion, overall, income fluctuations have been negative.

Objective: To promote the development of China’s crop seed industry with high quality, guarantee food security and sustainable agricultural development, scientific design of the evaluation index system for high-quality development of the seed industry and conduct of metric analysis are the keys to promoting the revitalization of the seed industry and the construction of a strong agricultural country. Methods: This paper focused on the high-quality development of China’s crop seed industry as the main research object by combining previous research findings of studies based on the connotation of high-quality development of the crop seed industry and constructed the evaluation index system of high-quality development of China’s crop seed industry which covers five dimensions, namely, innovation-driven development, green and sustained development, coordinated and comprehensive development, opening-up and strengthened development, and share-and-promote development, The Entropy method, Dagum’s Gini coefficient, Kernel’s density estimation, and panel regression methods were used to comprehensively analyze the spatial and temporal evolution, regional differences, and driving factors of the level of high-quality development of the crop seed industry in 30 provinces (municipalities and autonomous regions) of China from 2011 to 2020. Conclusions: After systematic analysis, it was concluded that (1) the overall level of high-quality development in China’s crop seed industry has stabilized, and progress has been made. (2) The overall inter-regional differences among the four major regions showed a gradual upward trend, with the inter-regional differences serving as the primary source of the differences and the contribution rate of various inter-regional differences demonstrating an upward trend. (3) Innovation capacity, the cultural and educational level of rural residents, the development of rural infrastructure, national financial support, and market-oriented approach are important factors driving the high-quality development of the crop seed industry in Chinese provinces (districts and municipalities).

Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.

The purpose of the current study is to examine the mediating role of intercultural communicative competence on the relationship between teaching of English language and learning at Chinese higher vocational colleges. The convenience sampling technique was used to collect data from 668 teachers, teaching English language subjects in different public and private Chinese higher vocational colleges. Smart partial least squares-structural equation modeling on SmartPLS software version 4 was used to test the hypotheses. The result revealed the direct effect of English language teaching (ELT) is not significant on English language learning (ELL). However, the intercultural communicative competences (ICC) have been tested and proved to be a potential mediator between English language teaching and learning. Because the indirect effect of ELT on ELL is positive and significant through mediator ICC. Therefore, based on the findings of this study, it can be concluded that the inclusion of intercultural communication ability is a crucial component in the vocational education of college students. Policymakers should be cautious about promoting and expanding the availability of cultural teaching and learning across demographic conditions (e.g., linguistic and ethnic diversity, age, and gender) and various levels of language proficiency. In accordance with the effects of teacher education and professional development programs, the implementation of ICC content necessitates a harmonization of pedagogical approaches and assessment practices across designated levels in order to effectively achieve educational objectives. To promote ICC in English language education, there must be clear guidelines and communication to school leaders, educators, and administrators regarding the necessity and goals of cultural integration.

This study sought an innovative quality management framework for Chinese Prefabricated Buildings (PB) projects. The framework combines TQM, QSP, Reconstruction Engineering, Six Sigma (6Σ), Quality Cost Management, and Quality Diagnosis Theories. A quantitative assessment of a representative sample of Chinese PB projects and advanced statistical analysis using Structural Equation Modeling supported the framework, indicating an excellent model fit (CFI = 0.92, TLI = 0.90, RMSEA = 0.06). The study significantly advances quality management and industrialized building techniques, but it also emphasizes the necessity for ongoing research, innovation, and information exchange to address the changing problems and opportunities in this dynamic area. In addition, this study’s findings and recommendations can help construction stakeholders improve quality performance, reduce construction workload and cost, minimize defects, boost customer satisfaction, boost productivity and efficiency in PB projects, and boost the Chinese construction industry’s growth and competitiveness.

While the healthcare landscape continues to evolve, rural-based hospitals face unique challenges in providing quality patient care amidst resource constraints and geographical isolation. This study evaluates the impact of big data analytics in rural-based hospitals in relation to service delivery and shaping future policies. Evaluating the impact of big data analytics in rural-based hospitals will assist in discovering the benefits and challenges pertinent to this hospital. The study employs a positivist paradigm to quantitatively analyze collected data from rural-based hospital professionals from the Information Technology (IT) departments. Through a comprehensive evaluation of big data analytics, this study seeks to provide valuable insights into the feasibility, infrastructure, policies, development, benefits and challenges associated with incorporating big data analytics into rural-based hospitals for day-to-day operations. The findings are expected to contribute to the ongoing discourse on healthcare innovation, particularly in rural-based hospitals and inform strategies for optimizing the implementation and use of big data analytics to improve patient care, decision-making, operations and healthcare sustainability in rural-based hospitals.