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This study summarizes the overall situation of the resources of the national science and technology innovation platform in the railway industry, including the distribution of platform types, supporting institutions, construction sites, professional fields, etc., to provide a reference for the further improvement and optimization of the national science and technology innovation platform system in the railway industry.

Through literature review, field investigation, expert consultation and other methods, this paper systematically investigates and analyzes the development status of the national science and technology innovation platform in the railway industry.

Taking the national science and technology innovation platform of the railway industry as the research object, this paper investigates and analyzes the construction, development and distribution of the national science and technology innovation platform of railway industry over the years. And the National Engineering Research Center of High-speed Railway and Urban Rail Transit System Technology was taken as an example to introduce its operation effect.

China Railway has made great development achievements, with the construction and development of national science and technology innovation platform in the railway industry. In recent years, a large number of national science and technology innovation platforms have been built in the railway industry, which play an important role in railway technological innovation, standard setting and commodification, and provide strong support for railway technology development.

The safe operation of the metro power transformer directly relates to the safety and efficiency of the entire metro system. Through voiceprint technology, the sounds emitted by the transformer can be monitored in real-time, thereby achieving real-time monitoring of the transformer’s operational status. However, the environment surrounding power transformers is filled with various interfering sounds that intertwine with both the normal operational voiceprints and faulty voiceprints of the transformer, severely impacting the accuracy and reliability of voiceprint identification. Therefore, effective preprocessing steps are required to identify and separate the sound signals of transformer operation, which is a prerequisite for subsequent analysis.

This paper proposes an Adaptive Threshold Repeating Pattern Extraction Technique (REPET) algorithm to separate and denoise the transformer operation sound signals. By analyzing the Short-Time Fourier Transform (STFT) amplitude spectrum, the algorithm identifies and utilizes the repeating periodic structures within the signal to automatically adjust the threshold, effectively distinguishing and extracting stable background signals from transient foreground events. The REPET algorithm first calculates the autocorrelation matrix of the signal to determine the repeating period, then constructs a repeating segment model. Through comparison with the amplitude spectrum of the original signal, repeating patterns are extracted and a soft time-frequency mask is generated.

After adaptive thresholding processing, the target signal is separated. Experiments conducted on mixed sounds to separate background sounds from foreground sounds using this algorithm and comparing the results with those obtained using the FastICA algorithm demonstrate that the Adaptive Threshold REPET method achieves good separation effects.

A REPET method with adaptive threshold is proposed, which adopts the dynamic threshold adjustment mechanism, adaptively calculates the threshold for blind source separation and improves the adaptability and robustness of the algorithm to the statistical characteristics of the signal. It also lays the foundation for transformer fault detection based on acoustic fingerprinting.

The China–Europe Railway Express (CR Express) in Chongqing has operated regularly and undergone large-scale development. Its impact on Chongqing’s economic growth has become increasingly evident, necessitating further research in this field.

This study employs the opening of CR Express as a quasi-natural experiment, designating Chongqing, which inaugurated the CR Express in 2011, as the treatment group. 13 provinces and cities that had not yet opened the CR Express until 2017 were selected as the control group. Utilizing panel data from 14 provinces across China spanning from 2006 to 2017, the synthetic control method (SCM) is employed to synthetically construct Chongqing. To quantify the difference in economic development levels between Chongqing with the operation of the CR express and Chongqing without its operation. Key metrics such as gross domestic product (GDP), per capita GDP, total retail sales of consumer goods, import and export value and the proportions of the secondary and tertiary industries are employed to measure urban economic development capabilities. Chongqing is designated as the experimental group, and a double-difference model is constructed to regress the operation of the CR Express against economic development capabilities. Robustness tests are conducted to validate the analytical results.

The results indicate that, compared to provinces without the operation of the CR Express, the initiation of the CR Express in Chongqing significantly enhances the economic development level of the city. The opening of the CR Express exhibits a pronounced positive impact on Chongqing’s economic development, and these findings remain robust and effective even after parallel trend tests and placebo tests.

The study represents an expansion of the theoretical framework. In contrast to previous studies that relied on a single indicator such as GDP, this study selects six indicators from the dimensions of economy, trade and industry to measure regional economic development capabilities. Furthermore, employing the grey relational analysis method, the study screens these indicators, thereby providing a theoretical basis for the selection of indicators for measuring regional economic development capabilities.

This exploratory study examines and comprehends the relative importance of mobile app attributes from a consumer perspective. Both quantitative and qualitative analysis approaches explore users' behavior and attitudes toward the priorities of mobile app attributes and preferences, identifying correlations between attributes and aggregating individual attributes into groups.

Online convenience sampling and snowball sampling resulted in 417 valid responses. The numerical data are analyzed using the relative to an identified distribution (RIDIT) scoring system and gray relational analysis (GRA), and qualitative responses are investigated using text-mining techniques.

This study finds enhanced nuances of user preferences and provides data-driven insights that might help app developers and marketers create a distinct app that will add value to consumers. The latent semantic analysis indicates relationship structure among the attributes, and text-based cluster analysis determines the subsets of attributes that represent the unique functions of the mobile app.

This study reveals the essential components of mobile apps, paying particular attention to the consumer value component, which boosts user approval and encourages prolonged use. Overall, the results demonstrate that developers must concentrate on its functional, technical and esthetic features to make an app more exciting and practical for potential users.

Most scholarly research on apps has focused on their technological merits, aesthetics and usability from the user's perspective. A post-adoption multi-attribute app analysis using both structured and unstructured data is conducted in this study.

In this paper, the C80 special coal gondola car was taken as the subject, and the load test data of the car body at the center plate, side bearing and coupler measured on the dedicated line were broken down to generate the random load component spectrums of the car body under five working conditions, namely expansion, bouncing, rolling, torsion and pitching according to the typical motion attitude of the car body.

On the basis of processing the measured load data, the random load component spectrums were equivalently converted into sinusoidal load component spectrums for bench test based on the principle of pseudo-damage equivalence of load. Relying on the fatigue and vibration test bench of the whole railway wagon, by taking each sinusoidal load component spectrum as the simulation target, the time waveform replication (TWR) iteration technology was adopted to create the drive signal of each loading actuator required for the fatigue test of car body on the bench, and the drive signal was corrected based on the equivalence principle of measured stress fatigue damage to obtain the fatigue test loads of car body under various typical working conditions.

The fatigue test results on the test bench were substantially close to the measured test results on the line. According to the results, the relative error between the fatigue damage of the car body on the test bench and the measured damage on the line was within the range of −16.03%–27.14%.

The bench test results basically reproduced the fatigue damage of the key parts of the car body on the line.

The type 120 emergency valve is an essential braking component of railway freight trains, but corresponding diaphragms consisting of natural rubber (NR) and chloroprene rubber (CR) exhibit insufficient aging resistance and low-temperature resistance, respectively. In order to develop type 120 emergency valve rubber diaphragms with long-life and high-performance, low-temperatureresistant CR and NR were processed.

The physical properties of the low-temperature-resistant CR and NR were tested by low-temperature stretching, dynamic mechanical analysis, differential scanning calorimetry and thermogravimetric analysis. Single-valve and single-vehicle tests of type 120 emergency valves were carried out for emergency diaphragms consisting of NR and CR.

The low-temperature-resistant CR and NR exhibited excellent physical properties. The elasticity and low-temperature resistance of NR were superior to those of CR, whereas the mechanical properties of the two rubbers were similar in the temperature range of 0 °C–150 °C. The NR and CR emergency diaphragms met the requirements of the single-valve test. In the low-temperature single-vehicle test, only the low-temperature sensitivity test of the NR emergency diaphragm met the requirements.

The innovation of this study is that it provides valuable data and experience for future development of type 120 valve rubber diaphragms.

Motivated by the significant role of uncertainty in affecting investment decisions and China's economic leadership in Asia, this paper investigates the predictive role of exposure to Chinese economic policy uncertainty at the individual stock level in large Asian markets.

We estimate the monthly uncertainty exposure (beta) for each stock and then employ the portfolio-level sorting analysis to investigate the relationship between the China’s uncertainty exposure and the future returns of major Asian markets over multiple trading horizons. The raw returns of the high-minus-low portfolios are then adjusted using conventional asset pricing models to investigate whether the relationship is explained by common risk factors. Finally, we check the robustness of the portfolio-level results through firm-level Fama and MacBeth (1973) regressions.

Applying portfolio-level sorting analysis, we reveal that exposure to Chinese uncertainty is negatively related to the future returns of large stocks over multiple trading horizons in Japan, Hong Kong and India. We discover this is unexplained by common risk factors, including market, size, value, profitability, investment and momentum, and is robust to the specification of stock-level Fama and MacBeth (1973) regressions.

Our analysis demonstrates the spillover effects of Chinese economic policy uncertainty across the region, provides evidence of China's emerging economic leadership, and offers trading strategies for managing uncertainty risks.

The findings of the study significantly improve our understanding of stock return predictability in Asian markets. Unlike previous studies, our results challenge the leading role of the US by providing a new intra-regional return predictor, namely, China’s uncertainty exposure. These results also evidence the continuing integration of the Asian economy and financial markets. However, contrary findings for some Asian markets point toward certain market-specific features. Compared with market-level research, our analysis provides deeper insights into the performance of individual stocks and is of particular importance to investors and other market participants.