As people’s awareness of the special functions of selenium continues to deepen, the development of selenium-rich food continues to develop, and selenium-rich places have been vigorously developing this resource-based industry. The development of selenium-rich agriculture is of great significance to improve people’s quality of life and promote agricultural, rural and regional economic development. This paper analyzes the factors affecting consumers’ willingness to purchase selenium-rich agricultural products in detail through questionnaire survey data of some consumers in Jiangxi, Ensh, Hubei and Ankang, Shaanxi, using three analytical methods of descriptive statistical analysis, factor analysis and logistic regression analysis with SPSS software. The research results show that consumers’ attitude toward selenium-rich agricultural products, price concerns, consumers’ family characteristics, health and environmental protection motives, gender and other factors have certain influence on consumers’ willingness to purchase selenium-rich agricultural products, among which the attitude factor and family characteristics have the greatest influence. Finally, the market prospect of selenium-rich agricultural products in China is analyzed and prospected, and the measures and suggestions for developing selenium-rich food are proposed in response to the problems of developing selenium-rich food in China.

This study investigates robust control strategies for Intelligent Connected Electric Vehicles (ICEVs) under cybersecurity threats, with the objective of enhancing both operational safety and energy efficiency in electrified vehicular systems. The proposed framework integrates three key innovations: (1) A hierarchical control architecture combining H ∞ robust control for actuator-level resilience with adaptive Kalman filter to mitigate sensor anomalies caused by cyberattacks; (2) An energy-aware distributed control algorithm that optimizes torque distribution in heterogeneous platoons while maintaining cybersecurity constraints; (3) A novel pre-post filter mechanism for safety-critical systems that provides additional protection layers against false data injection and ECU intrusions. This study combines H ∞ control with blockchain verification for the first time to solve the problem of dynamic delay attacks in V2X communication, and proposes a distributed collaborative control architecture to address the coupling problem between malicious node identification and energy allocation in heterogeneous fleets. The response speed is 40% faster than centralized control. Experimental validation demonstrates significant improvements: Cybersecurity performance 18.7% higher penetration test scores compared to conventional systems.Energy efficiency 12.2% reduction in energy consumption for electric vehicles in mixed platoons through coordinated control. Control robustness Maintains 98.3% trajectory tracking accuracy under simulated GNSS spoofing attacks.The results establish that the proposed strategy simultaneously addresses cybersecurity vulnerabilities and operational optimization in ICEVs, providing a unified solution for next-generation vehicle safety and sustainability.

Digital technology has changed how rural households allocate factors and the environment they make decisions in. Yet, we do not fully understand how digital adoption can lead to a household energy transition. The micro survey data utilized in this study are from the Hundred Villages and Thousand Households project, Jiangxi Province, China. It utilizes ordered probit models and propensity score matching to study the link between digital technology adoption and the intensity of rural households' clean energy consumption. The estimates show a positive and statistically significant association, and the matching results remain consistent after adjusting for observable differences between adopters and non-adopters. Mechanism analyses suggest two pathways. Digital adoption is associated with a higher non-farm employment share, consistent with higher time opportunity costs of collecting traditional fuels and improved budget capacity, and with stronger social capital, consistent with stronger peer influence and lower transaction frictions in adopting clean energy. The association is strongest for cooking energy, followed by space heating, and weakest for water heating. In addition, information acquisition use is more strongly associated with clean energy consumption than social entertainment use. These findings suggest that narrowing gaps in digital access and effective use may complement efforts to accelerate rural household clean energy transitions in China.

Agriculture faces the dual challenges of climate change mitigation and food security, and reducing agricultural carbon-emission intensity has become an important pathway toward a low-carbon agricultural transformation. Against the backdrop of rapid digitalization in rural areas, whether digital agriculture development can effectively reduce agricultural carbon emission intensity remains an important empirical question. Using panel data for 30 provincial-level regions in China from 2012 to 2023, this study constructs a Digital Agriculture Development Index from three dimensions: digital human capital and application capacity, digital infrastructure and production conditions, and digital industry and service environment. Agricultural carbon emission intensity is measured based on carbon emissions from major crop production inputs and operations. The results show that digital agriculture development significantly reduces agricultural carbon emission intensity, and this finding remains robust after a series of robustness and endogeneity tests. Mechanism analysis indicates that digital agriculture development is significantly and negatively associated with capital misallocation, while capital misallocation is significantly and positively associated with agricultural carbon emission intensity. For labor and land misallocation, the two estimated relationships are not both statistically significant. Spatial econometric results indicate a significant spatial association between digital agriculture development and agricultural carbon emission intensity. In the heterogeneity analysis, the digital-agriculture coefficient is significantly negative in major grain-producing areas and eastern China and statistically insignificant in non-major grain-producing areas and central and western China. Improvements in capital allocation may partly explain how digital agriculture supports the low-carbon transition of agriculture. The findings offer policy implications for advancing green agricultural development in emerging economies.