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Cross-regional technology transfer is an important driving force for achieving the coordinated development of technology resources and breaking down China's provincial technical barriers. Due to the imbalance in China's technology development level, it is difficult to achieve comprehensive revitalization policies. Therefore, improving the efficiency of technology transfer is an effective way to solve this problem. This paper selects the relevant data of 31 provinces and regions in China in 2019 for analysis, uses factor analysis to measure the efficiency of technology transfer, and then proposes a technology transfer improvement path through QCA clear set configuration analysis. The study found that the development of technology transfer efficiency in 31 provinces and regions in China is extremely unbalanced. The improvement paths that effectively break this unbalanced development status can be summarized into 4 types, namely, the "intermediary-environment" leading path, weak "intermediary-R&D-environment" leading path, strong "intermediary-R&D-environment" leading path and "intermediary-economic" leading path. [ABSTRACT FROM AUTHOR]

With the continuous improvement of agricultural mechanization, soil compaction becomes more and more serious. Serious soil compaction has been considered as an important negative factor affecting crop growth and yield. The measurement of soil compactness is a common method to measure the soil compaction level. In order to solve the problems of discontinuous sampling, time-consuming and poor real-time soil compactness measurement, a real-time measurement method of soil compactness based on fertilizing shovel was proposed, and the mathematical model between fertilizing shovel arm deformation and soil compactness was established. Based on the interaction mechanism between fertilizing shovel and soil, through the force analysis of fertilizing shovel, it was found that the deformation of fertilizing shovel arm was positively correlated with the sum of soil compactness (SSC) within the range of tillage depth. In order to verify the theoretical analysis results and the detection accuracy of strain gauge, the static bench test was carried out. The test results showed that the strain gauge signal for measuring the deformation of the fertilizing shovel arm was significantly correlated with the applied force. The fitting curve of the linear correlation coefficient was 0.999, the maximum detection error was 0.68 kg, and the detecting accuracy was within the tolerance of 0.57%. Through field orthogonal experiments with four working depths and four compaction levels, a mathematical model of the strain gauge signal and the SSC within the range of tillage depth was established. The experiment showed that compared with the other three depths, the linear correlation coefficient at the tillage depth of 5 cm (TD5) was the lowest, and the slope of the fitting curve was obviously different from the other three depths, so the 5 cm data were excluded when modeling. The model between mean signal value and mean SSC within the range of tillage depth was established based on the data of sampling points with tillage depths of 7.5 cm (TD7.5), 10 cm (TD10), and 12.5 cm (TD12.5). The linear correlation coefficient (R²) of the model between mean signal value and mean SSC which eliminated 5 cm data was 0.980 and the root mean square error (RMSE) was 143.57 kPa. Compared with the linear model before averaging, the R² was improved by 8.65%, and the RMSE was reduced by 52.39%. This system can realize the real-time and continuous measurement of soil compactness and provide data support for follow-up intelligent agricultural operations. [ABSTRACT FROM AUTHOR]