In this article, the effect of the deformed interface on the hydro-viscous drive characteristics was investigated through a three-dimensional fluid simulation and experiments. The main parameters such as pressure field, velocity field, and torque transferred by the oil film were simulated in FLUENT software in the light of the principle of the computational fluid dynamics. The results found that the dynamic pressure and velocity of the oil film goes up gradually along the radial direction, and the dynamic pressure at zone with groove is much higher than that without groove due to the hydrodynamic effect. After the interface deforming, the dynamic pressure decreases; while the torque transferred by the oil film increases slightly. Furthermore, a special hydro-viscous drive test-bed was developed to verify the correctness and validity of the theoretical results.

For the purpose of reducing the number of conventional seed-metering devices and high demand for vacuums, this study designed a vacuum central drum seed-metering device, that is intended to replace multiple seed-metering devices with one, which is comprised of the inner and outer drum. This can be replaced with different diameters of suction holes, ventilation housing, seeding tube, agitating devices, seed box, and seed-cleaning devices, etc. A hybrid rice seed Jingliangyou1212 was applied as an experimental material, and a JPS-12 computer vision metering device test bench was used to test singular-factor and multi-factor seeding performance of the seed-metering device. The singular-factor performance test of the metering device was conducted under negative pressure of seed suction in the range of 1~1.5 kPa, at the metering device rotation speed of 10~60 rpm, with diameters of inlet holes being 2 mm (chamfer: 45°), 2, and 1.5 mm, respectively. The number of seeds was counted by a sucking hole under different factor combinations. The multi-factor test was carried out by rotation rate, negative pressure, and types of sucking holes. A rate of 2 ± 1 rice seed per sucking hole is regarded as the qualified standard. It shows that the qualification rate (2 ± 1 rice seed per sucking hole) of seed suction can reach 97.4% under a combination of metering device rotation speed of 30 r/min, negative pressure of 1.0 kPa, and suction hole diameters of 1.5 mm. High-speed photography was used to study the trajectory of seed-metering at different rotation rates, a locomotive axis was applied to fit the motion curve, and 3D-printing was used to make the seed-metering tube so that the seed collisions could be reduced. This study provides evidence for further optimizing the performance of the vacuum central drum direct-seeding machine for hybrid rice.

Possible mechanisms to achieve high mobility in zinc oxynitride (ZnON) have been investigated by comparison with other thin film semiconductors. Integrated processes to fabricate ZnON TFTs have been developed. Issues and challenges encountered at current stage will be discussed.

The use of social media data provided powerful data support to reveal the spatiotemporal characteristics and mechanisms of human activity, as it integrated rich spatiotemporal and textual semantic information. However, previous research has not fully utilized its semantic and spatiotemporal information, due to its technical and algorithmic limitations. The efficiency of the deep mining of textual semantic resources was also low. In this research, a multi-classification of text model, based on natural language processing technology and the Bidirectional Encoder Representations from Transformers (BERT) framework is constructed. The residents’ activities in Beijing were then classified using the Sina Weibo data in 2019. The results showed that the accuracy of the classifications was more than 90%. The types and distribution of residents’ activities were closely related to the characteristics of the activities and holiday arrangements. From the perspective of a short timescale, the activity rhythm on weekends was delayed by one hour as compared to that on weekdays. There was a significant agglomeration of residents’ activities that presented a spatial co-location cluster pattern, but the proportion of balanced co-location cluster areas was small. The research demonstrated that location conditions, especially the microlocation condition (the distance to the nearest subway station), were the driving factors that affected the resident activity cluster patterns. In this research, the proposed framework integrates textual semantic analysis, statistical method, and spatial techniques, broadens the application areas of social media data, especially text data, and provides a new paradigm for the research of residents’ activities and spatiotemporal behavior.

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