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This study aimed to facilitate a rapid evaluation of track service status and vehicle ride comfort based on car body acceleration. Consequently, a low-cost, data-driven approach was proposed for analyzing speed-related acceleration limits in metro systems.

A portable sensing terminal was developed to realize easy and efficient detection of car body acceleration. Further, field measurements were performed on a 51.95-km metro line. Data from 272 metro sections were tested as a case study, and a quantile regression method was proposed to fit the control limits of the car body acceleration at different speeds using the measured data.

First, the frequency statistics of the measured data in the speed-acceleration dimension indicated that the car body acceleration was primarily concentrated within the constant speed stage, particularly at speeds of 15.4, 18.3, and 20.9 m/s. Second, resampling was performed according to the probability density distribution of car body acceleration for different speed domains to achieve data balance. Finally, combined with the traditional linear relationship between speed and acceleration, the statistical relationships between the speed and car body acceleration under different quantiles were determined. We concluded the lateral/vertical quantiles of 0.8989/0.9895, 0.9942/0.997, and 0.9998/0.993 as being excellent, good, and qualified control limits, respectively, for the lateral and vertical acceleration of the car body. In addition, regression lines for the speed-related acceleration limits at other quantiles (0.5, 0.75, 2s, and 3s) were obtained.

The proposed method is expected to serve as a reference for further studies on speed-related acceleration limits in rail transit systems.

High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.

The research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

The authors examine the joint effect of the country-wide legal institutions and product market competition on stock crash risk in a large sample of international firms.

In the study, the authors examine whether the country-level institutional factors affect product market competition's impact on stock crash risk. Specifically, the authors characterize country-wide institutional quality with individual governance indices developed in earlier studies and also adopt the worldwide board reforms as a proxy for the change in firms' governance environment.

The authors find that strong institutions mitigate the positive relationship between product market competition and stock crash risk in the international setting. In addition, the authors find that institutional quality moderates the effect of product market competition on stock crash risk via the information channel, i.e. although firms in competitive industries manage and report earnings more aggressively, strong institutions or board reforms, curtail managers' incentive to do so.

The authors’ findings lend support to the dark side of product market competition with a broader sample from 35 countries. In light of this, when earlier studies consider firms from competitive (concentrated) industries as having less (more) severe agency problems, future studies should consider the agency costs associated with product market competition for both the US firms and non-US firms. Furthermore, when it is debatable that regulators are self-interested, captured, uninformed and thus the regulations and institutions may not be fully effective as a result, this study demonstrates the effectiveness of institutions in ex ante mitigating agency conflicts associated with product market competition.