Flexible Informed Trees (FIT*): Adaptive Batch-Size Approach for Informed Sampling-Based Planner

In modern approaches to path planning and robot motion planning, anytime almost-surely asymptotically optimal planners dominate the benchmark of sample-based planners. A notable example is Batch Informed Trees (BIT*), where planners iteratively determine paths to groups of vertices within the exploration area. However, maintaining a consistent batch size is crucial for initial pathfinding and optimal performance, relying on effective task allocation. This paper introduces Flexible Informed Tree (FIT*), a novel planner integrating an adaptive batch-size method to enhance task scheduling in various environments. FIT* employs a flexible approach in adjusting batch sizes dynamically based on the inherent complexity of the planning domain and the current n-dimensional hyperellipsoid of the system. By constantly optimizing batch sizes, FIT* achieves improved computational efficiency and scalability while maintaining solution quality. This adaptive batch-size method significantly enhances the planner's ability to handle diverse and evolving problem domains. FIT* outperforms existing single-query, sampling-based planners on the tested problems in R^2 to R^8, and was demonstrated in real-world environments with KI-Fabrik/DARKO-Project Europe.Comment: 8 pages,6 figure

A Semi-supervised Sensing Rate Learning based CMAB Scheme to Combat COVID-19 by Trustful Data Collection in the Crowd

Mobile CrowdSensing (MCS), through employing considerable workers to sense and collect data in a participatory manner, has been recognized as a promising paradigm for building many large-scale applications in a cost-effective way, such as combating COVID-19. The recruitment of trustworthy and high-quality workers is an important research issue for MCS. Previous studies assume that the qualities of workers are known in advance, or the platform knows the qualities of workers once it receives their collected data. In reality, to reduce their costs and thus maximize revenue, many strategic workers do not perform their sensing tasks honestly and report fake data to the platform. So, it is very hard for the platform to evaluate the authenticity of the received data. In this paper, an incentive mechanism named Semi-supervision based Combinatorial Multi-Armed Bandit reverse Auction (SCMABA) is proposed to solve the recruitment problem of multiple unknown and strategic workers in MCS. First, we model the worker recruitment as a multi-armed bandit reverse auction problem, and design an UCB-based algorithm to separate the exploration and exploitation, considering the Sensing Rates (SRs) of recruited workers as the gain of the bandit. Next, a Semi-supervised Sensing Rate Learning (SSRL) approach is proposed to quickly and accurately obtain the workers' SRs, which consists of two phases, supervision and self-supervision. Last, SCMABA is designed organically combining the SRs acquisition mechanism with multi-armed bandit reverse auction, where supervised SR learning is used in the exploration, and the self-supervised one is used in the exploitation. We prove that our SCMABA achieves truthfulness and individual rationality. Additionally, we exhibit outstanding performances of the SCMABA mechanism through in-depth simulations of real-world data traces.Comment: 18 pages, 14 figure

Permeability Reduction and Electrochemical Impedance of Fractured Rock Grouted by Microbial-Induced Calcite Precipitation

The poor impermeability of fractured rock induced by excavation and construction is improved through the application of microbial-induced calcite precipitation (MICP), but it is difficult to monitor and evaluate the permeability reduction under a confining pressure and fracture aperture. For this, the grouting ratio, permeability, and electrochemical impedance of fractured rock with MICP grouting were experimented with, considering the effects of fracture aperture and confining pressure. The equivalent circuit model of grouting-fractured rock is presented, and the corresponding ratio of the electrical resistivity and cross-sectional area of the grouted fracture (ρ/S) is indicated by an electrochemical impedance spectroscope (EIS). The relationships of the permeability coefficient, the ρ/S, and the grouting ratio are analysed. The experimental results show that the Darcy permeability coefficient of fractured rock with MICP grouting is reduced by an order of magnitude of 3 to 4. As fracture aperture ranged from 1.28 to 2.56 mm and grouting rate was 0.003 ml/s, the Darcy permeability coefficient decreased with an increase in confining pressure. The grouting ratio and fracture aperture also decreased with a reduction in ρ/S. The results also showed that the permeability reduction of MICP correspondingly increased in these conditions. What is more, the Darcy permeability coefficient of fractured rock grouted by MICP and its permeability reduction may be well predicted by confining pressure and ρ/S. This study provides a new EIS method for predicting the reduction in permeability of MICP grouting-fractured rock and further enriches the application of MICP and EIS techniques in impermeable rock engineering

Investigation on cement-improved phyllite based on the vertical vibration compaction method.

The vertical vibration compaction method (VVCM), heavy compaction method and static pressure method were used to form phyllite specimens with different degrees of weathering. The influence of cement content, compactness, and compaction method on the mechanical properties of phyllite was studied. The mechanical properties of phyllite was evaluated in terms of unconfined compressive strength (Rc) and modulus of resilience (Ec). Further, test roads were paved along an expressway in China to demonstrate the feasibility of the highly weathered phyllite improvement technology. Results show that unweathered phyllite can be used as subgrade filler. In spite of increasing compactness, phyllite with a higher degree of weathering cannot meet the requirements for subgrade filler. With increasing cement content, Rc and Ec of the improved phyllite increases linearly. Rc and Ec increase by at least 15% and 17%, respectively, for every 1% increase in cement content and by at least 10% and 6%, respectively, for every 1% increase in compactness. The higher the degree of weathering of phyllite, the greater the degree of improvement of its mechanical properties

Development and Application of Skid Resistance Fog Seal for Pavements

The performance of a skid resistance fog seal is studied to develop a high bond performance road skid resistance fog seal. Accordingly, a fog seal is developed based on the bond strength, permeability, and aging resistance. To develop the skid resistance fog seal herein, the skid resistance particle types and dosages are optimized according to the skid and wear resistance properties. The fog seal performance is then verified. Furthermore, the road performance of the skid resistance fog seal is studied, and the optimal amount of the skid resistance fog seal is proposed. Finally, the influence of the construction process on the skid and wear resistance is investigated. The results show that the self-made skid resistance fog seal has better bond strength, permeability, and aging resistance. The 0.6 kg/m2 skid resistance fog seal exhibits the best skid and wear resistance and water penetration performance, while the skid resistance fog seal constructed by the premix process has the best skid and wear resistance properties

Research on Mechanical Properties and Influencing Factors of Cement-Graded Crushed Stone Using Vertical Vibration Compaction

To study the mechanical properties of cement-graded crushed stone for use in the transition sections of intercity railways, the growth laws governing unconfined compressive strength, splitting strength and resilience modulus of cement-graded crushed stone and their influencing factors were studied by the vertical vibration compaction method (VVCM). The strength growth equations of cement-graded crushed stone are proposed, and strength prediction equations are established. The research shows the unconfined compressive strength, splitting strength and resilience modulus of cement-graded crushed stone with a strong interlocked skeleton density type (VGM-30) are significantly enhanced to 20, 20 and 17% higher, respectively, than those of standard cement-graded crushed stone. The growth law of mechanical properties of cement-graded crushed stone is similar, with the fastest growth occurring before 14 days, and the rate decreasing after 28 days. The strength growth tended to be stable after 90 days, increasing with the increase in curing time, compaction coefficient and cement dosage. The correlation coefficients (R2) of the strength growth prediction models were found to be 0.99, 0.97, and 0.99, respectively. These values can be used to accurately predict the strength growth curve. This paper verifies the superiority of VGM-30 gradation through laboratory tests, providing a reference for gradation selection in the construction of intercity railway transition sections

Efficient and nontoxic biological response carrier delivering TNF-α shRNA for gene silencing in a murine model of rheumatoid arthritis

Small interfering RNA (siRNA) is an effective and specific method for silencing genes. However, an efficient and nontoxic carrier is needed to deliver the siRNA into the target cells. Tumor necrosis factor α (TNF-α) plays a central role in the occurrence and progression of rheumatoid arthritis. In this study, we pre-synthetized a degradable cationic polymer (PDAPEI) from 2,6-pyridinedicarboxaldehyde and low molecular weight polyethyleneimine (PEI, Mw=1.8 kDa) as a gene vector for the delivery of TNF-α shRNA. The PDAPEI/pDNA complex showed a suitable particle size and stable zeta potential for transfection. In vitro study of the PDAPEI/pDNA complex revealed a lower cytotoxicity and higher transfection efficiency when transfecting TNF-α shRNA to macrophages by significantly down-regulating the expression of TNF-α. Moreover, the complex was extremely efficient in decreasing the severity of arthritis in mice with collagen-induced arthritis (CIA). PDAPEI delivered TNF-α shRNA has great potential in the treatment of rheumatoid arthritis