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The research on electric drive wheel technology is an important direction of the research on the new energy drive system in the future. With the increasing requirements of the electric drive wheel on the speed, the oil churning power loss has become a non-negligible part, even up to 50%-80% of the total power loss. The existing calculation method of churning loss mainly adopts simple empirical formula, which cannot be applied to complex planetary gear transmission. The splash lubrication of the two-stage planetary gear drive is simulated by computational fluid dynamics (CFD) software and C language user defined function (UDF), and the visualization of oil gas two-phase transient flow field is realized; by extracting the surface pressure and the viscous force, the churning loss of the sun gears, planet gears and planet carriers are obtained; the simulation and analysis of the 25 working conditions show that the churning loss varies with the immersion depth and speed; the results show that the oil churning power loss increases with the oil immersion depth and the speed, and there is no obvious inflection point. To achieve the minimum oil stirring loss, the minimum oil immersion depth should be taken on the premise of ensuring full lubrication.

In this paper, we first establish a locally converged bioinformatics dataset based on gradient sampling and design an optimal data mining control model to improve the accuracy of bioinformatics big data feature mining. The performance of the Compressive Tracking algorithm and Online Bosting algorithm is compared with the mining error as a test index. At the same time, we propose a social media information dissemination algorithm applicable to large-scale social network datasets, taking the degree value of each node as the node’s full influence and comparing and analyzing the dissemination influence of BP-IM, RAND and MC-CELF algorithms. Finally, taking public health big data as the research object, the least squares regression method was used to analyze the influence of the amount of public attention to bioinformatics scientific knowledge on their scientific literacy in different media. The results showed that there was a significant positive correlation between scientific literacy and willingness to engage in science participation behavior on social media when the amount of public attention to scientific information was β =0225, p

Objective: This study aimed to compare the effects of different sterilization on the quality of fermented jujube juice. Methods: The effects of cold plasma sterilization (CPS) and pulsed strong light sterilization (PLS) on the quality of jujube juice before and after fermentation were studied, with high pressure sterilization (SA) jujube juice as the control. Results: The contents of total sugar, reducing sugar and soluble solid in jujube juice before and after fermentation by CPS treatment were significantly higher than those of the other two sterilization methods, and the contents of total sugar, reducing sugar and soluble solid in jujube juice after fermentation were 1.7 mg/L, 1.64 mg/L and 12.4%, respectively. With SA treatment, the total phenol content of jujube juice before and after fermentation was the lowest, and the total phenol content of jujube juice after fermentation was only 2.19 mg/L. The color of jujube juice treated by PLS changed minimally before and after fermentation. The viable count of Lactobacillus plantarum in jujube juice treated by CPS, PLS and SA were more than 6.48 lg（CFU/mL） after 48 h fermentation by L. plantarum, and the viable count of L. plantarum in jujube juice was the highest 6.63 lg(CFU/mL) after PLS treatment. Conclusion: Non-thermal sterilization (especially PLS) has little effect on the quality of fermented jujube juice and could be applied in the processing of fermented jujube juice.

Abstract Mechanical precision corn seed-metering planter has a compact structure, missed and repeated seeding advantages during high-speed operation. In this regard, the current research study focuses on the development of a corn seed planter that features an inclined seed-metering device. The spatial layout of the seed-metering device is optimized to change the seed-filling mode to meet the needs of high-speed operation. Firstly, the mechanical characteristics and seeds in the metering device chamber were analyzed, and then the seed-filling stress model was established. Secondly, a mechanical model for corn seed particles was developed for virtual simulation tests and numerical analysis using the discrete element method (DEM) and EDEM software. Moreover, a quadratic rotating orthogonal center combination test was implemented by setting the inclination angle of seed-metering device θ(A), machine ground speed v(B), and rotation speed of metering disc n(C) as the influence factors, with the missed seeding rate M and the seed-filling stress S as the evaluation indices. The results indicated that the most significant factors affecting the missed seeding rate, seed-filling stress, S, were the rotation speed of the metering disc (n) > machine ground speed (v) > inclination angle of the metering disc (θ) and inclination angle of the metering device (θ) > rotation speed of the metering disc (n) > machine ground speed (v), respectively. However, the field verification test shows that the optimized corn seed-metering planter achieved mean values of M = 4.33, Q(qualified seeding rate) = 92.83%, and R(repeated seeding rate) = 2.84%, with average relative errors of 1.17% compared to the simulation tests and the accuracy and effectiveness of the DEM simulation model was verified. Therefore, the developed corn seed-metering device meets the industry standards and operation requirements for precise corn sowing, and technical support can be given for future studies of similar precision seeding equipment.