Enzyme-induced carbonate precipitation (EICP) is a new biogeotechnical ground improvement technique that uses calcium carbonate (CaCO3) formed by biochemical processes to increase soil strength and stiffness. In this paper, crude urease extracted from soybeans was employed to catalyze the precipitation of CaCO3 in sand. To optimize the urease extraction efficiency, factors affecting the soybean crude urease extraction, including the powdered soybean particle size, concentration, soaking time, and soaking temperature, were addressed. This paper also provided further insight regarding the impact of the urease activity of soybean crude extract on the chemical conversion efficiency and the biocementation performance in EICP. The findings revealed that the powdered soybean concentration and the particle size were the two most important factors affecting the urease activity of the soybean crude extract. The enzyme activity utilized in the EICP process might further lead to different reactant efficiencies of urea-CaCl2 solution, and consequently, the improvement in the physical and mechanical properties of biocemented sand. Considering the chemical conversion efficiency and the biocementation performance, 60 g/L of powdered soybean was concluded as the preferred quantity for extracting the crude urease, with an enzyme activity of 6.62 mM urea min−1. Under this condition, a chemical conversion efficiency of approximately 95% for 0.5 M urea-0.5 M CaCl2 could be obtained in merely 12 h, and the unconfined compressive strength (UCS) of the EICP-treated sand exceeded 4 MPa with a CaCO3 content of ~8%. As a high-efficient cost-effective alternative to the purified enzyme for carbonate precipitation, the soybean crude urease showed great potential for ground improvement.

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In conventional metamorphic testing, metamorphic relations (MRs) are identified as necessary properties of a computer program's intended functionality, whereby violations of MRs reveal faults in the programunder the assumption that the source and follow-up inputs (test cases used in metamorphic testing) are valid. In the present study, the authors argue that MRs can also be used to validate and assess the quality of the program's input data-under the assumption that the source or follow-up inputs can be inappropriately generated. Using this new perspective, a case study in the natural language processing domain is used to explore the different types of text messages that are difficult to interpret by (Chinese-English) machine translation. A total of 46,180 short user comments on Personal Tailor (a 2013 Chinese film), collected from Douban (a popular Chinese social media platform), has been used as the primary dataset of this study, and the analysis of results demonstrates that the proposed MR-based data validation method is useful for the automatic identification of poorly translated text messages.

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This paper uses CFD (Computational Fluid Dynamics) numerically to simulate and calculate the axial flow pumps under different guide vane rotation angle and inlet angles and to conduct a comparative analysis of the inflow field. The results show that the influence of different guide vane rotation angles and inlet angles on the performance of the axial flow pump reflects in the operating conditions of large-discharge conditions. Adjusting the different guide vane rotation angles can significantly improve the efficiency of axial flow pumps. Moreover, the high-efficiency area of pump operation conditions is expanded nearly two times with the increase of the guide vane rotation angles under large-discharge conditions. At the same time, Under the design operating conditions, when the guide vane rotation angle is -2{degree sign}, the highest efficiency of the axial flow pump is 87.69%. However, under the linear change of the inlet angle of the guide vane, the highest efficiency of the axial flow pump can reach 87.71%. Finally, the model test verifies the reliability of the numerical simulation, and the research results are beneficial for improving the efficiency of the axial flow pump.