The economic operation of battery swapping stations (BSSs) is significant for the promotion of large-scale electric vehicles. This paper develops a linear programming model to maximize the daily operation profits of a BSS by considering constraints of the battery swapping demand of users and the charging/discharging balance of batteries in the BSS. Based on the BSS configuration and data from electric taxis in Beijing, we simulate the operation situation and charging/discharging load of the BSS in nine scenarios with two ordered charging and discharging strategies. The simulation results demonstrate that the model can achieve the maximum daily profits of the BSS. According to the sensitivity analysis, the battery swapping price for batteries is the most sensitive, followed by the number of batteries in the BSS, while the operation-maintenance costs and battery depreciation costs are least sensitive. In addition, the charging and discharging of batteries in the BSS can be coordinated by increasing the battery quantity of the BSS and formulating the ladder-type battery swapping price.

In traditional Chinese Medicine (TCM), the licorice-yuanhua herbal pair is one of the most representative incompatible herbal pairs recorded in the “eighteen incompatible herbal pairs” theory. Previous studies of our research group have demonstrated several gut-related side-effects induced by the licorice-yuanhua herbal pair. In this study, we investigated whether and why this incompatible herbal pair could induce gut tissue damage. After licorice-yuanhua treatment, the duodenum, ileum, and colon and serum biomarkers of mice were examined by pathological staining, Western blot, and ELISA assays. The IEC-6 cells and LS174T cells were treated with licorice saponins, yuanhua flavonoids, and di-terpenes; iTRAQ-labeled proteomic technology was then used to explore their synergistic effects on mucosa cells, followed by verification of ZO-1 and MUC-2 protein expressions. The results showed that the licorice-yuanhua herbal pair induced ileum tissue injuries, including epithelial integrity loss, inflammation, and edema. These injuries were verified to be related to epithelial and mucous barrier weakening, such as downregulated ileum ZO-1 and MUC-2 protein expressions. Proteomic analysis also suggested that glycyrrhizic acid and genkwanin synergistically influence tight junction pathways in LS174T cells. Furthermore, licorice saponins, yuanhua flavonoids, and di-terpenes dose/structure-dependently downregulate ZO-1 and MUC-2 protein expressions in mucosa cells. Our study provides different insights into the incompatibility mechanisms and material basis of the licorice-yuanhua herbal pair, especially that besides toxic di-terpenes, licorice saponins and yuanhua flavonoids, which are commonly known to be non-toxic compounds, can also take part in the gut damage induced by the licorice-yuanhua herbal pair.

This paper develops a charge pricing model for private charging piles (PCPs) by considering the environmental and economic effects of private electric vehicle (PEV) charging energy sources and the impact of PCP charging load on the total load. This model simulates users’ responses to different combinations of peak-valley prices based on the charging power of PCPs and user charging transfer rate. According to the regional power structure, it calculates the real-time coal consumption, carbon dioxide emissions reduction, and power generation costs of PEVs on the power generation side. The empirical results demonstrate that the proposed peak-valley time-of-use charging price can not only minimize the peak-valley difference of the total load but also improve the environmental effects of PEVs and the economic income of the power system. The sensitivity analysis shows that the load-shifting effect of PCPs will be more obvious when magnifying the number of PEVs by using the proposed charging price. The case study indicates that the proposed peak, average, and valley price in Beijing should be 1.8, 1, and 0.4 yuan/kWh, which can promote the large-scale adoption of PEVs.

Urban transportation data are crucial for smart city development, enhancing traffic management’s intelligence, accuracy, and efficiency. This paper conducts a comprehensive investigation encompassing policy analysis, a literature review, concept definition, and quantitative analysis using CiteSpace from both domestic and international perspectives. Urban transportation data comprise multiple dimensions, such as infrastructure status, real-time monitoring, policy planning, and environmental assessment, which originate from various sources and stakeholders. Highly influential authors and active institutions, particularly in the USA, China, Canada, and England, contribute significantly to extensive and collaborative research. Key areas include intelligent transportation, traffic flow prediction, data fusion, and deep learning. Domestic research focuses on practical applications, while international studies delve into interdisciplinary research areas. With advancements in intelligent systems and big data technology, research has evolved from basic data collection to sophisticated methodologies, such as deep learning and spatiotemporal analysis, driving substantial progress. This paper concludes by recommending enhanced data integration, improved privacy and security, fostering big data and AI applications, facilitating policy formulation, and exploring innovative transportation modes, thereby underscoring the importance of urban transportation data in shaping the future of smart cities. The findings provide theoretical and practical guidance for the future intelligence, efficiency, and sustainability of urban transportation systems.

Farmers experience high risks of stress, depression, and suicide. Risk factors are well-established, but protective factors are less studied. Social connectedness encompasses organizational participation, resource sharing, and social support. Although social connectedness is protective of mental health among the general population, its impact on farmers is unclear. It is unknown whether resources offered by farmer-owned cooperatives and other organizations influence farmers’ mental health. Furthermore, social support reduces psychological distress more among younger farmers than older farmers, but more research is needed to examine its impacts. In-depth interviews were conducted to characterize farmers’ cooperative experiences and perceptions of cooperatives in promoting mental health. A survey was used to examine whether having cooperative resources and social support impacted dairy farmers’ symptoms of depression. A second survey was administered to investigate whether program use, program satisfaction, and social support impacted perceived stress and symptoms of depression among cooperative and non-cooperative farmers. Interview findings revealed that cooperatives create support networks and a sense of control for farmers. In addition, cooperative leaders are a source of support for distressed farmers. Results from both surveys indicated that organizational resources and social support were associated with decreased perceived stress and symptoms of depression. Program satisfaction was more strongly associated with perceived stress and symptoms of depression than program use. Interview and survey findings suggest that social connectedness may be protective of farmers’ mental health. Future research and interventions should consider the roles of organizational resources and social support in influencing farmers’ mental health.

Data products play an important role in driving the digital transformation of enterprises, establishing the market of data elements, and fostering the sustainable development of the economy. Based on the research on data products in Chinese academic circles, this paper summarizes and defines the concept of data products, systematically collects Chinese policies related to data elements, and forms a literature review of data products. With the CiteSpace bibliometric analysis software, it conducts an analysis of authoritative literature on data products both domestically and internationally up to 2023 by using the relevant research literature from CNKI and Web of Science databases as data sources. It delves into the author institution, topic evolution and research trend within the realm of data product research. The results demonstrate that data products are multi-dimensional and complex, with their evolution significantly influenced by policy and legal frameworks. Since 2010, both domestic and international research on data products has seen rapid growth. The Chinese academia has gradually expanded from focusing on data market expansion and service system to meteorology and earth sciences, while the international research has involved the application of data products in soil moisture, UV scattering, precipitation monitoring, remote sensing technology, geoclimate and other fields. The research recommends strengthening interdisciplinary, cross-field, cross-team and industry-academia-research-application cooperation and international exchanges. With the development of new technologies such as artificial intelligence, it should pay more attention to the quality and performance evaluation of data products, data security and privacy protection, and the value co-creation and income distribution of data products. This paper is aimed to promote the application of data products in social management and business fields, and maximizing the value and potential of data products.