This work proposes a novel concept for an intelligent and semi-autonomous human-cyber-physical system (HCPS) to operate future wind turbines in the context of Industry 5.0 technologies. The exponential increase in the complexity of next-generation wind turbines requires artificial intelligence (AI) to operate the machines efficiently and consistently. Evolving the current Industry 4.0 digital twin technology beyond a sole aid for the human decision-making process, the digital twin in the proposed system is used for highly effective training of the AI through machine learning. Human intelligence (HI) is elevated to a supervisory level, in which high-level decisions made through a human–machine interface break the autonomy, when needed. This paper also identifies and elaborates key enabling technologies (KETs) that are essential for realizing the proposed HCPS.

Although substantial studies emphasized the close relationship among land development, public infrastructure, and urban economic growth, the mediating effect of public infrastructure remains unexplored. Using panel data of 253 prefecture-level Chinese cities from 1999 to 2012, we empirically conduct a mediating effect analysis to examine how land development promotes urban economic growth. It is found that land development has a positive impact on public infrastructure, whereas the construction of public infrastructure is positively related with urban economic growth. Therefore, land development exerts a positive influence on urban economic growth through one important mediator: public infrastructure. It is also found that the mediating effect of public infrastructure is partial. The estimation results are robust to various specifications and sensitivity analysis.