INFLUENCE OF CROSSING WEAR ON ROLLING CONTACT FATIGUE DAMAGE OF FROG RAIL

The damage of the frog rail significantly affects the wear of the crossing rail and restricts the passing speed of the train. A geometric 3D modeling of the vehicle passing through the crossing center is particularly concerned with the cumulative wheel-rail contact of the traffic volume. The frog rail wear is simulated to obtain the dynamic change of the impact force of the wheel on the frog rail as the rail wears. By summarizing the existing experimental results of other scholars, it is clear that the important factors, that cause the damage of the frog rail, are vehicle load, friction coefficient, slip roll ratio and shear stress.  This paper combines the theoretical analysis of mechanics and 3D simulation to obtain the position change of the wheel-rail contact point with the wear of the frog rail, and finally compares it with the actual measurement results. It can more accurately predict the area where the maximum damage occurs after a certain amount of traffic for a certain fixed model, the change of wheel-rail contact point at frog rail is simulated with the wear of each component. Through theoretical analysis, the main factors determining frog rail damage were determined. Then evaluate the possible damage area of the frog track and control the prediction range to 5-10 cm, which reduces the detection time and cost. The worst state of distraction will be detected in time to facilitate replacement or polishing. Through further research in this area, the service life of the frog rail can be predicted

Watermarking protocol of secure verification

The secure verification is important for watermarking protocols. A malicious arbitrator is able to remove an original watermark from an unauthorized copy of the digital content as a result of a security breach in the phase of arbitration and resell multiple copies of it with impunity. We propose a novel buyer-seller watermarking protocol of secure verification. In this scheme, a seller permutes an original watermark provided by a trusted Watermarking Certification Authority (WCA) and embeds it into digital content in an encrypted domain. In case an unauthorized copy is found, the seller can recover the original watermark from the watermark extracted from the copy and sends it to an arbitrator. Without the knowledge of permutations applied by the seller, the arbitrator is unable to remove the permuted watermark from the digital content. Hence, verification is secured. As an additional advantage of the proposed protocol, arbitration can be conducted without the need for the cooperation of the WCA or the buyer

A survey on the development status and application prospects of knowledge graph in smart grids

With the advent of the electric power big data era, semantic interoperability and interconnection of power data have received extensive attention. Knowledge graph technology is a new method describing the complex relationships between concepts and entities in the objective world, which is widely concerned because of its robust knowledge inference ability. Especially with the proliferation of measurement devices and exponential growth of electric power data empowers, electric power knowledge graph provides new opportunities to solve the contradictions between the massive power resources and the continuously increasing demands for intelligent applications. In an attempt to fulfil the potential of knowledge graph and deal with the various challenges faced, as well as to obtain insights to achieve business applications of smart grids, this work first presents a holistic study of knowledge-driven intelligent application integration. Specifically, a detailed overview of electric power knowledge mining is provided. Then, the overview of the knowledge graph in smart grids is introduced. Moreover, the architecture of the big knowledge graph platform for smart grids and critical technologies are described. Furthermore, this paper comprehensively elaborates on the application prospects leveraged by knowledge graph oriented to smart grids, power consumer service, decision-making in dispatching, and operation and maintenance of power equipment. Finally, issues and challenges are summarised.Comment: IET Generation, Transmission & Distributio

Combat Network Synchronization of UCAV Formation Based on RTBA Model

The paper aims at developing an efficient method to acquire a proper UCAV formation structure with robust and synchronized features. Here we introduce the RTBA (Route Temporary Blindness Avoidance) model to keep the structure stable and the HPSO (hybrid particle swarm optimization) method is given to find an optimal synchronized formation. The major contributions include the following: (1) setting up the dynamic hierarchy topologic structure of UCAV formation; (2) the RTB phenomenon is described and the RTBA model is put forward; (3) the node choosing rules are used to keep the invulnerability of the formation and the detective information quantifying method is given to measure the effectiveness of the connected nodes; and (4) the hybrid particle swarm optimization method is given to find an optimal synchronized topologic structure. According to the related principles and models, the simulations are given in the end, and the results show that the simplification of the model is available in engineering, and the RTBA model is useful to solve the real problems in combat in some degree

Fault Diagnosis for Power Electronics Converters based on Deep Feedforward Network and Wavelet Compression

A fault diagnosis method for power electronics converters based on deep feedforward network and wavelet compression is proposed in this paper. The transient historical data after wavelet compression are used to realize the training of fault diagnosis classifier. Firstly, the correlation analysis of the voltage or current data running in various fault states is performed to remove the redundant features and the sampling point. Secondly, the wavelet transform is used to remove the redundant data of the features, and then the training sample data is greatly compressed. The deep feedforward network is trained by the low frequency component of the features, while the training speed is greatly accelerated. The average accuracy of fault diagnosis classifier can reach over 97%. Finally, the fault diagnosis classifier is tested, and final diagnosis result is determined by multiple-groups transient data, by which the reliability of diagnosis results is improved. The experimental result proves that the classifier has strong generalization ability and can accurately locate the open-circuit faults in IGBTs.Comment: Electric Power Systems Researc

A novel role for IGF-1R in p53-mediated apoptosis through translational modulation of the p53-Mdm2 feedback loop

Insulin-like growth factor 1 receptor (IGF-1R) is important in cancer cell growth and survival and has been implicated in cancer pathophysiology and treatment. Here we report a novel function for IGF-1R in p53-dependent apoptotic response. We show that inhibition or loss of IGF-1R activity reduces translational synthesis of p53 and Mdm2 protein. Notably, IGF-1R inhibition increases p53 protein stability by reducing p53 ubiquitination and maintains p53 at low levels by decreasing p53 synthesis, thus rendering p53 insensitive to stabilization after DNA damage. The accumulation and apoptosis of DNA-damage–induced p53 is therefore reduced in Igf-1r−/− mouse embryonic fibroblasts or tumor cells treated with the IGF-1R inhibitor. Furthermore, we find that inhibition of IGF-1R reduces p53 and Mdm2 translation through a gene-specific mechanism mediated by the respective 5′ untranslated region of p53 and mdm2 messenger RNA. The eukaryotic translation initiation factor 4F complex is also involved in this translational inhibition. These results demonstrate an unexpected role for translational control by IGF-1R in p53-mediated apoptosis

Is Model Attention Aligned with Human Attention? An Empirical Study on Large Language Models for Code Generation

Large Language Models (LLMs) have been demonstrated effective for code generation. Due to the complexity and opacity of LLMs, little is known about how these models generate code. To deepen our understanding, we investigate whether LLMs attend to the same parts of a natural language description as human programmers during code generation. An analysis of five LLMs on a popular benchmark, HumanEval, revealed a consistent misalignment between LLMs' and programmers' attention. Furthermore, we found that there is no correlation between the code generation accuracy of LLMs and their alignment with human programmers. Through a quantitative experiment and a user study, we confirmed that, among twelve different attention computation methods, attention computed by the perturbation-based method is most aligned with human attention and is constantly favored by human programmers. Our findings highlight the need for human-aligned LLMs for better interpretability and programmer trust.Comment: 13 pages, 8 figures, 7 table

Dynamic characteristics of the railway ballast bed under water-rich and low-temperature environments

Studying the dynamic characteristics and evolution laws of the ballast bed under low-temperature, rain and snow environments has practical significance for the driving stability of railways in alpine. In this paper, a full-scale ballasted track model was constructed in a programmable temperature control laboratory, and the frequency response function (FRF) curves of the ballast bed under different temperature and humidity conditions were measured. Then the vibration characteristics and the evolution laws of the ballast bed under different conditions were analyzed. The longitudinal transfer behavior and the dissipation of the vibration energy in the ballast bed under different humidity and temperature environments were discussed combined with the finite element method. The results show that the influence of temperature on the vibration characteristics of the ballast bed is not significant in the dry and water-rich environments, but the vibration characteristics of the ballast bed in the frozen environment change dramatically with the decrease of temperature. The vibration energy is harder to dissipate in the frozen ballast bed than in the dry and water-rich ballast beds, and the frozen ballast bed is more prone to be sudden damaged when a train passes due to the significant increase in its stiffness. Thus, the performance monitoring and emergency maintenance of the ballast bed in those environments should be strengthened