Network Capacity Optimization for Cellular-Assisted Vehicular Systems by Online Learning-Based mmWave Beam Selection

Directional communication is helpful to improve the performance of millimeter Wave (mmWave) links. However, the dynamic nature of vehicular scenarios raises the complexity of directional mmWave vehicular communications. Also, a mmWave link is susceptible to blockages. Therefore, a mmWave vehicular communication system requires high environmental adaptability and context-awareness. Due to inadequate context information and insufficient beam settings in the existing related algorithm, it is difficult to pick out the set of beams with more reasonable widths and directions, which hinders the further promotion of network capacity in vehicular networks. Therefore, we propose an improved fast machine learning (IFML) algorithm to overcome this shortcoming. In order to improve network capacity while suppressing the additional beam search overhead, a partitioned search method is designed in the IFML. Also, in order to be robust to occasional fluctuations and timely adapt to significant changes in communication environments, the IFML adopts a flexible beam performance update approach based on adjustable weight coefficient. The simulation results show that the IFML significantly outperforms the existing related algorithm in terms of aggregate received data after a certain number of online learning time periods.

A new weighted fraction Monte Carlo method for particle coagulation

Purpose The purpose of this study is to investigate the aerosol dynamics of the particle coagulation process using a newly developed weighted fraction Monte Carlo (WFMC) method. Design/methodology/approach The weighted numerical particles are adopted in a similar manner to the multi-Monte Carlo (MMC) method, with the addition of a new fraction function (α). Probabilistic removal is also introduced to maintain a constant number scheme. Findings Three typical cases with constant kernel, free-molecular coagulation kernel and different initial distributions for particle coagulation are simulated and validated. The results show an excellent agreement between the Monte Carlo (MC) method and the corresponding analytical solutions or sectional method results. Further numerical results show that the critical stochastic error in the newly proposed WFMC method is significantly reduced when compared with the traditional MMC method for higher-order moments with only a slight increase in computational cost. The particle size distribution is also found to extend for the larger size regime with the WFMC method, which is traditionally insufficient in the classical direct simulation MC and MMC methods. The effects of different fraction functions on the weight function are also investigated. Originality Value Stochastic error is inevitable in MC simulations of aerosol dynamics. To minimize this critical stochastic error, many algorithms, such as MMC method, have been proposed. However, the weight of the numerical particles is not adjustable. This newly developed algorithm with an adjustable weight of the numerical particles can provide improved stochastic error reduction.

Development of a 3D human osteoblast cell culture model for studying mechanobiology in orthodontics

Summary Objectives Mechanobiology phenomena constitute a major element of the cellular and tissue response during orthodontic treatment and the implantation of a biomaterial. Better understanding these phenomena will improve the effectiveness of our treatments. The objective of this work is to validate a model of three-dimensional (3D) culture of osteoblasts to study mechanobiology. Materials and methods The hFOB 1.19 cell line was cultured either traditionally on a flat surface or in aggregates called spheroids. They were embedded in 0.8% low-melting agarose type VII and placed in a polyethylene terephthalate transwell insert. Compressive forces of 1 and 4 g/cm2 were applied with an adjustable weight. Proliferation was evaluated by measuring diameters, monitoring glucose levels, and conducting Hoechst/propidium iodide staining. Enzyme-linked immunosorbent assays focusing on the pro-inflammatory mediators interleukin (IL)-6 and IL-8 and bone remodelling factor osteoprotegerin were performed to evaluate soluble factor synthesis. quantitative reverse transcription-polymerase chain reaction was performed to evaluate bone marker transcription. Results The 3D model shows good cell viability and permits IL dosing. Additionally, three gene expression profiles are analysable. Limitations The model allows analysis of conventional markers; larger exploration is needed for better understanding osteoblast mechanobiology. However, it only allows an analysis over 3 days. Conclusion The results obtained by applying constant compressive forces to 3D osteoblastic cultures validate this model system for exploring biomolecule release and analysing gene transcription. In particular, it highlights a disturbance in the expression of markers of osteogenesis.

Abnormal dynamics of cascading edge failures with congestion effect

Considering congestion effects in realistic network environments, we give a new method to adjust dynamically adjust the weight of the congested edge. We calculate the load on an edge based on the revised betweenness method and propose a novel model with three states of edges to investigate the dynamics of cascading failures in the ring network, the BA scale-free network, and the real traffic networks in London. By two robust metrics, we surprisingly observe the abnormal dynamics of cascading propagation, especially compared with that in the unadjustable weight, the curves of cascading dynamics in the adjustable weight are more irregular, which means that enhancing the capacity of each edge is not always better to avoid the cascading propagation. In addition, our simulation results show that the dynamical change of the edge’s weight makes the heterogeneous BA networks more vulnerable.

Optimization of the target profile for asymmetrical rail grinding in sharp-radius curves for high-speed railways

Asymmetrical rail grinding in sharp-radius curves could reduce the side wear of railheads and enhance curve capacity of rail vehicles. The wheel/rail contact performance and curve capacity could be further improved by the optimization of the asymmetrical rail grinding target profile. In order to modify the target profile smoothly, the nonuniform rational B-spline curve with adjustable weight factors is used to establish a parameterized model of railhead curves in the asymmetrical grinding region. The indices of contact performance and curve capacity for different weight factors are obtained using experiment design and service performance simulation. Two Kriging surrogate models are proposed, in which the design variables are the adjustable weight factors, and the response parameters are the indices of contact performance and curve capacity, respectively. The multi-objective optimization model of the target profile is established, in which the objective functions are the two Kriging surrogate models of contact performance and curve capacity. The optimized weight factors are sought using a nondominated sorting genetic algorithm II, and the corresponding optimal target profile is obtained. The wheel/rail service performance simulation before and after optimization indicates that the contact performance and curve capacity are improved significantly.