Artificial intelligence, industrial structure optimization, and CO2 emissions.

The carbon-reducing effects of artificial intelligence (AI) will be a critical means of achieving carbon peak and carbon neutrality in China. However, in order to efficiently harness the power of AI, the relationship between AI and carbon reduction needs to be fully understood. In this study, we systematically investigated the impacts and mechanisms of action of AI on CO2 emissions by constructing econometric models using dynamic panel data from 30 provinces in mainland China from 2006 to 2019. The empirical results show that AI significantly reduces CO2 emissions. Further mediation effect tests found that in the western region, there are mediation effects of the quantity and quality of industrial structure advancedization and industrial structure ecology, while the mediation effect of industrial structure rationalization is not significant. In the eastern and central regions, the mediating effect of the quantity of industrial structure advanced is not significant, while the mediating effect of the quality of industrial structure advanced, industrial structure rationalization, and industrial structure ecology all exist. Our work provides evidence to support that AI reduces CO2 emissions in various regions of China. This can help regions formulate appropriate policies to promote the synergistic development of AI and the "dual-carbon" goal.

The Influence of Network Location on Knowledge Hiding from the Perspective of Lifelong Education.

Inhibiting negative knowledge behavior is one of the ways to improve the effective circulation of knowledge within the organization. This study puts employees' knowledge hiding behavior in the organizational relationship network situation and discusses the influence of network location on knowledge hiding, exploring the moderating role of knowledge acquisition in the relationship between network location and knowledge hiding. From the perspective of social network, 232 knowledge-based employees were used to obtain the data, and we used literature analysis, social network analysis, multiple regression analysis, UCINET, SPSS, and other software packages. Research shows that employees in the central network are less willing to do knowledge hiding behavior, and those in the structural hole network tend to do knowledge hiding behavior. Knowledge acquisition as the supply way of knowledge resources plays a positive role on the negative relationship between centrality and knowledge hiding and on the positive relationship between structure hole and knowledge hiding. The research results have positive significance for understanding and mastering the hiding behavior law of individual knowledge in the organizational relationship network and also provide certain theoretical basis and data support for organizational knowledge governance.

Spatial and Temporal Evolution and Driving Factors of Urban Ecological Well-Being Performance in China.

Extensive development leads to the decline of ecological well-being, and it is necessary to improve the urban ecological well-being performance (EWP). This paper adopted the Super-slack-based measure (Super-SBM) model to evaluate the EWP of 285 Chinese prefecture level cities from 2011 to 2017. The exploratory spatial data analysis method (ESDA) was used to explore the spatial and temporal evolution characteristics of the EWP, and then the spatial Durbin model (SDM) was adopted to analyze the driving factors of the EWP. The results show that the trend of the overall average EWP has experienced a stage evolution process of "upward → downward → upward". The urban EWPs have significant spatial agglomeration and path dependence. The economic development level and technological progress had the positive impacts on the EWP, and the urbanization level, economic extroversion and industrial structure had the negative impacts on the EWP. The result reveals that there was a "U-shaped" relationship existing between urbanization level and the EWP. The negative spatial spillover effect of urbanization level on the EWP was significant. The corresponding policy implications were put forward. This study will provide strategic guidance for policy makers to optimize and enhance the urban EWP.

Rhizosphere iron and manganese-oxidizing bacteria stimulate root iron plaque formation and regulate Cd uptake of rice plants (Oryza sativa L.).

Iron plaque is the amorphous and/or crystalline layer of Fe and Mn (hydr)oxides formed on the root surface of wetland plants. It could adsorb and co-precipitate metal(loid)s at the rhizosphere, thus modulating the uptake and accumulation of metal elements in plants. In this study, the Fe(II)/Mn(II)-oxidizing bacteria Burkholderia sp. D416 (D416) and Pseudomonas sp. YGL (YGL) were isolated from Cd-contaminated rice field, both hydroponic experiment and pot experiment were performed to assess the impact of bacterial inoculation on iron plaque formation, elemental content of the plaque, plant dry mass, antioxidant enzyme activity and Cd content in rice plants. The results revealed that inoculation with D416, YGL, and D416+YGL stimulated iron plaque formation on the root surface of the hydroponic rice. The content of C, N, O, Na, Mg, Al, Si, P, S, Cl, K, Fe and Ca in the root plaque were affected by the bacterial inoculation and varied among different plant growth stages. The pot experiment indicated that inoculation with D416 increased the root dry biomass by 58.89%, and the combined inoculation of D416 and YGL increased the dry biomass of root, shoot and grain by 16.89%, 21.66% and 23.26%, respectively. Importantly, YGL inoculation decreased the Cd translocation from root to shoot and from glume to brown rice grain by 50.00% and 50.27%, respectively, and the Cd content in shoot and brown rice grain were decreased by 20.00% and 34.48%, respectively. Taken together, the elemental content of the iron plaque and Cd content in rice plants varied among different plant growth stages and when plants were inoculated with different bacterial strains. YGL dramatically reduced the Cd content in brown rice grain, thus it could potentially be used to reduce Cd content in rice crop grown in Cd-contaminated soils.