The main sources of regional innovation investment in China are government direct investment and indirect grant. The positive relationship between innovation investment and regional innovation performance has been recognized by scholars, but the relationship between direct investment, indirect grant, and innovation performance and the mechanism of their impact on innovation performance need to be clarified. This study uses 5‐year data from China regional innovation, using multiple regression analysis, found that government grant and actor's investment can facilitate performance, but the government grant for innovation investment has a crowding‐out effect, absorptive capacity positively moderated the relationship between Research and Development (R&D) and innovation performance but play a negative moderate role between government grant and innovation performance. On the basis of the empirical result, China's regional governments need to focus on institutional and environmental development in the future, pay more attention to the structural problems of innovation input, promote flow of talents orderly, and rationally build regional knowledge chain, so as to enhance efficiency of innovation more effectively.

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Multithreaded operating system (OS) is essential to be used for many wireless sensor network (WSN) applications. However, the RAM consumption of the multithreaded OS is high. Thus, it is infeasible to apply the multithreaded OS on many high RAM constrained wireless sensor nodes (WNs). To address this challenge, several memory optimization strategies are investigated in this paper. On one hand, the subfunctiongranularity thread switch and hybrid OS scheduling model are proposed to decrease the RAM consumption of the thread stacks. On the other hand, different dynamic memory allocation mechanisms are presented to reduce the heap memory size. With the implementation of these optimization techniques, the total RAM consumption of the multithreaded WSN OSs can be brought down greatly. In result, the multithreaded WSN OSs become suitable to be used even on the high RAM constrained WNs.

Soil total nitrogen (TN) plays a major role in agriculture, geochemical cycles and terrestrial ecosystem functions. Knowledge regarding the TN distribution is crucial for the sustainable use of soil resources. This paper therefore aims to characterize the spatiotemporal distribution of soil TN and improve the current understanding of how various factors influence changes in TN. Natural characteristics and remote sensing (RS) variables were used in conjunction with the random forest (RF) model to map the TN distribution in a low hilly region of southeastern China in 1979, 2004 and 2014. The means and changes of TN in different geographic regions and farmland protection regions were also analyzed. The results showed that: (1) the TN showed an increasing trend in the early periods and exhibited a decreasing trend from 2004 to 2014; (2) the geographic and RS variables played more important roles in predicting TN distribution than did the other variables; and (3) changes in the fertilization and crop planting structure caused by soil testing and formulated fertilization techniques (STFFT—Soil Testing and Formulated Fertilization Techniques) as well as farmland protection policies influenced the spatiotemporal variability of TN. Evidently, more attention should be focused on improving the quality and soil fertility in the surrounding low mountainous areas.

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