Search

The rapid development of big data technology has attracted a variety of sectors, including tertiary education. The purpose of this paper is to construct a precision teaching mode based on big data technology in order to improve teaching quality and further promote education and teaching reform. The proposed mode, based on the theory of precision teaching in colleges and universities as well as the intrinsic properties of big data teaching activities, describes five procedures for analyzing learning situations, determining teaching goals, preparing teachers, and evaluating teachers. When the big data-based precision teaching mode is applied to the "Python Language Programming" course, the results show that students are more satisfied with the design of the teaching and more efficient in learning. It is believed that this mode will significantly improve students' academic performance and their ability to work independently and collaboratively as a result of more frequently online and offline interactions between teachers and students.

Reasonable determination of the water pressure on the shaft linings is the key to the optimization design of the vertical shaft of mining. The traditional water pressure calculation model is not suitable for the stratum conditions in western China. A new shaft-surrounding rock seepage model is proposed based on the coordinated seepage conditions of surrounding rock and shaft linings. In the model, the seepage within the shaft depth is assumed happening in a unit thickness confined aquifer. Thereby, the water pressure on the shaft linings is derived by the steady seepage theory, and the water pressure reduction coefficient is defined by normalizing the hydrostatic pressure. The influences of shaft diameter and shaft depth, the permeability coefficient of the surrounding rock, and the seepage flow on the water pressure reduction coefficient are analyzed. After that, the mechanism of reducing water pressure by grouting the surrounding rock is studied by considering the stratum conditions in western China. Finally, a practical equation, which only relating to the depth of the shaft, is fitted on account of the averaged water pressure reduction coefficient from the theoretical model. The effectiveness of the theoretical model and the fitted equation are verified by the measured data and data in the literature.

This research demonstrated the impact of human resource management bundles on employee performance, both direct and mediated by human capital and organizational commitment. The ability-enhancing, motivation-enhancing and empowerment-enhancing HRM bundles have significant direct impacts on employee performance and organizational commitment. However, only the motivation-enhancing HRM bundle has a significant direct impact on human capital. There are also significant impacts from human capital to employee performance, organizational commitment to human capital, organizational capital to social capital and social capital to human capital. Finally, human capital has a significant relationship with employee performance. Most of the hypothesized mediated effects were also found, except that their effects were smaller than those of the direct effects. Implications of the research findings and proposals for future research are discussed.

Calculation of the electrostatic double layer force (EDL force) between clay particles is relevant as it is closely related to important macroscopic mechanical behaviors of clays. The popular method to calculate the EDL force is to integrate the electric potential and Maxwell stress along the boundary enclosing a simply connected domain within which a clay particle resides. The EDL force has also been calculated by the integration of the electrostatic force density over the preceding domain. However, the subtle relation of the EDL forces calculated by the different existing methods has not yet been investigated. By means of theoretical analysis and finite element simulation, it was shown that the force calculated by the integration of Maxwell stress along the complete boundary enclosing a multiply connected domain in which the clay particle is excluded, and that along the partial boundary enclosing the preceding simply connected domain represents the electrical attractive force and osmotic repulsive force, respectively, while the integration of the potential along both the same complete and partial boundary denotes the osmotic force. Numerical results showed that the calculated EDL force deviates from its actual value significantly with the decrease in distance between the chosen integral boundary and particle surface, and the deviation varies with surface potential and angle between particles. Moreover, the recommended minimum distance was proposed to be 10 times the thickness of the particle based on the present simulation results.

China is the largest producer and exporter of royal jelly in the world. The high production of royal jelly in China is mainly attributed to a high royal jelly-producing lineage of honeybees (Apis mellifera) (HRJB). However, few studies have been conducted on the genetic characterization of HRJB. In this study, the mitochondrial DNA intergenic region between cytochrome oxidase I and II (COI-COII) and the mitochondrial NADH dehydrogenase subunit 2 sequences (ND2) were determined for 90 HRJB colonies, collected from the regions of China where HRJB originated, and 25 unimproved A. m. ligustica colonies from China. COI-COII sequence analysis revealed two mitotypes (C1 and C2d) in HRJB colonies and one mitotype (C1) in unimproved A. m. ligustica colonies. The main mitotype (C1) in HRJB accounted for 93% of the colonies. Based on ND2 sequences, four and two mitotypes were found in HRJB and unimproved A. m. ligustica colonies, respectively. Sequence alignment showed that nucleotides in three positions of the ND2 sequence were different between the main mitotype of HRJB and that of unimproved A. m. ligustica. Our study suggested that HRJB was bred from A. m. ligustica and possibly had genetic characteristics different from unimproved A. m. ligustica.