This paper explores the dynamics of the collaborative innovation network of China’s agricultural biotechnology, from a spatial-topological perspective. The data pertain to a collection of patent applications jointly filed by universities, research institutes and enterprises on the mainland of China during 1985–2017. Using the logistic model, we first identify the developing phases of China’s agricultural biotechnology. By dismantling the collaborative innovation network into spatial and topological networks, the dynamics are analyzed from these two dimensions at the three levels of nodes, edges and whole network. The results indicate that with the technology developing from the introduction to the growth-to-maturity phase, the collaborative innovation network exhibits dynamics as follows: as the scale expands, collaborations in the network are concentrated core cities, while dispersing to more innovators; enterprises replace universities and become the main innovation forces; the network attributes of small-world, scale-free and core-edge structures are apparent. Multi proximity factors including geographical, cognitive and organizational, play key roles in driving the dynamics, and the main factor evolves from geographical proximity to cognitive as well as organizational proximity.
This paper deals with the leader-following synchronization of first-order, semi-linear, complex spatio-temporal networks. Firstly, two sorts of complex spatio-temporal networks based on hyperbolic partial differential equations (CSTNHPDEs) are built: one with a single weight and the other with multi-weights. Then, a new distributed controller is designed to address CSTNHPDE with a single weight. Sufficient conditions for the synchronization and exponential synchronization of CSTNHPDE are presented by showing the gain ranges. Thirdly, the proposed distributed controller addresses of CSTNHPDE with multi-weights, and gain ranges are obtained for synchronization and exponential synchronization, respectively. Finally, two examples show the effectiveness and good performance of the control methods.
This study explored the impact of government-led high-standard farmland construction (HSFC) on market-oriented farmland transfer using a unified analysis framework of HSFC and farmland transfers. We used a binary probit model based on 660 questionnaires from five counties in Shandong Province, China to empirically analyze this impact. The results show that HSFC can significantly promote farmland lease-in while inhibiting lease-out. We found that farmland fragmentation plays a significant role in moderating this impact, which is illustrated by the fact that improved farmland fragmentation does not promote HSFC in the context of farmland lease-in. Furthermore, it can effectively alleviate the inhibitory effect of HSFC on farmland lease-out. The impact of HSFC on farmland transfer has significant labor transfer heterogeneity. For households with a low degree of labor transfer, HSFC can significantly promote farmland lease-in and inhibit lease-out, while for households with a high degree of labor transfer, the above effect is not significant.
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