We consider two systems of active swimmers moving close to a solid surface, one being a living population of wild-type E. coli and the other being an assembly of self-propelled Au-Pt rods. In both situations, we have identified two different types of motion at the surface and evaluated the fraction of the population that displayed ballistic trajectories (active swimmers) with respect to those showing randomlike behavior. We studied the effect of this complex swimming activity on the diffusivity of passive tracers also present at the surface. We found that the tracer diffusivity is enhanced with respect to standard Brownian motion and increases linearly with the activity of the fluid, defined as the product of the fraction of active swimmers and their mean velocity. This result can be understood in terms of series of elementary encounters between the active swimmers and the tracers.

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Abstract:Controlling floor heave plays an important role in the stability of mining roadways that is pivotal to the sustainable, safe, and efficient development of coal resources in underground coal mines. In order to propose highly efficient and economical methods of controlling floor heave, numerical simulation, laboratory physical simulation, and engineering practice were carried out to reveal the mechanism of reinforcing roof and sidewalls to control the floor heave of the mining roadway, return airway 15208, in the Xinjing Coal Mine in the Yanquan mining area of China. The numerical simulation demonstrated that the surrounding rock of the roadway underwent expansion and deformation, accompanied by redistribution of the surrounding rock stress due to the reinforcement of the roof and two sidewalls. The laboratory physical simulation revealed that the reinforcing roof and sidewalls decreased the bed separation of the floor and reduced the quantity of the displacement of the floor in Coal Seam 15. Engineering practice showed that the floor heave in the roadway, the roof, and the sidewalls, which was reinforced by intensive bolts combined with steel belt, wire mesh, and cable, was significantly reduced compared with that with lower supporting intensity of roof and sidewalls. The floor heave could be successfully controlled.

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Real-time traffic accident forecasting is increasingly important for public safety and urban management (e.g., real-time safe route planning and emergency response deployment). Previous works on accident forecasting are often performed on hour levels, utilizing existed neural networks with static region-wise correlations taken into account. However, it is still challenging when the granularity of forecasting step improves as the highly dynamic nature of road network and inherent rareness of accident records in one training sample, which leads to biased results and zero-inflated issue. In this work, we propose a novel framework RiskOracle, to improve the prediction granularity to minute levels. Specifically, we first transform the zero-risk values in labels to fit the training network. Then, we propose the Differential Time-varying Graph neural network (DTGN) to capture the immediate changes of traffic status and dynamic inter-subregion correlations. Furthermore, we adopt multi-task and region selection schemes to highlight citywide most-likely accident subregions, bridging the gap between biased risk values and sporadic accident distribution. Extensive experiments on two real-world datasets demonstrate the effectiveness and scalability of our RiskOracle framework.

For large underground coal mines producing 10 million tons a year, rapid excavation and stability of deep roadways are pivotal to ensure sustainable, safe, and efficient production. This paper provides a case study of Hulusu Coal Mine in Inner Mongolia, where roadway excavation speed was insufficient to meet production needs. Moreover, deformation in the roofs of the roadways was severe. To achieve rapid excavation and control the stability of deep roadways, a new support system was proposed and constructed in a roadway at a depth of 640 m. The system consisted of long flexible bolts pretensioned to high levels and spaced at large intervals. Roadway excavation and construction of a support system were conducted simultaneously. Field measurements indicated that the new support system effectively controlled deformation and fracture development during excavation and mining. Maximum displacements of the roof during excavation and mining were 10 and 30 mm, respectively. The axial load on bolts surged during excavation as a result of slight deformations caused by excavation operations. This active response of the bolts is beneficial to the prevention of roof deformation during excavation and mining. During mining, fissures propagated up to only a depth of 1.4 m into the surrounding rock mass. The new support system formed a thick reinforced anchorage zone, which greatly improved the bearing capacity of the roof. Compared with the previous support system, the new system allowed the maximum excavation speed (31.5 m/day) to increase by 85.3%. This successful case provides a practical reference for similar roadway projects.

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