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This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

This study aims to investigate whether firms purchase directors' and officers' liability (D&O) insurance when the country-level economic policy uncertainty (EPU) is high.

This study uses D&O insurance data from Chinese listed firms between 2003 and 2019 to conduct regression analyses to examine the association between D&O insurance and EPU.

The results show that government EPU, despite being an exogenous factor, increases the likelihood of firms' purchasing D&O insurance, and this effect is more pronounced when firms are exposed to great share price crash risk and high litigation risk, suggesting that firms intend to purchase D&O insurance possibly due to the accentuated stock price crash risk and litigation risk associated with EPU. In addition, the results indicate that the effect of EPU on the D&O insurance purchase decision is moderated by the provincial capital market development and internal control quality.

The study highlights the role of uncertain economic policies in shareholder approval of D&O insurance purchases.

The study enriches the literature on the determinants of D&O insurance purchases by documenting novel evidence that country-level EPU is a key institutional factor shaping firms' decisions to purchase D&O insurance.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

To optimize train operations, dispatchers currently rely on experience for quick adjustments when delays occur. However, delay predictions often involve imprecise shifts based on known delay times. Real-time and accurate train delay predictions, facilitated by data-driven neural network models, can significantly reduce dispatcher stress and improve adjustment plans. Leveraging current train operation data, these models enable swift and precise predictions, addressing challenges posed by train delays in high-speed rail networks during unforeseen events.

This paper proposes CBLA-net, a neural network architecture for predicting late arrival times. It combines CNN, Bi-LSTM, and attention mechanisms to extract features, handle time series data, and enhance information utilization. Trained on operational data from the Beijing-Tianjin line, it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.

This study evaluates our model's predictive performance using two data approaches: one considering full data and another focusing only on late arrivals. Results show precise and rapid predictions. Training with full data achieves a MAE of approximately 0.54 minutes and a RMSE of 0.65 minutes, surpassing the model trained solely on delay data (MAE: is about 1.02 min, RMSE: is about 1.52 min). Despite superior overall performance with full data, the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals. For enhanced adaptability to real-world train operations, training with full data is recommended.

This paper introduces a novel neural network model, CBLA-net, for predicting train delay times. It innovatively compares and analyzes the model's performance using both full data and delay data formats. Additionally, the evaluation of the network's predictive capabilities considers different scenarios, providing a comprehensive demonstration of the model's predictive performance.

This study aims to examine the effect of game newness and game interactivity on players’ brand recall and brand attitude using contrast effect, mind-engagement and transfer effect theories.

A 2 (newness: congruent or incongruent) × 2 (game interactivity: high or low) between-subjects measures design was conducted. A total of 224 undergraduate management students participated in the study. A 2 × 2 between-subjects measures multivariate analysis of variance was used to test the hypotheses.

Findings show that incongruent-newness results in higher brand recall but less favorable brand attitude. Under incongruent-newness condition, high interactivity results in higher brand recall. However, under congruent-newness condition, both high- and low-interactivity conditions result in similar brand recall. Under congruent-newness condition, high interactivity results in more favorable brand attitude, whereas under incongruent-newness condition, both high- and low-interactivity conditions result in similar brand attitude.

Developing high brand recall rates and attitudes are the prime goals of advertisers for selecting a medium to promote their brands. This experimental study adds to the knowledge of online media advertising, especially in-game advertising (IGA) as a media-strategy to advertise brands taking newness and game-interactivity factors into consideration.

From the perspectives of attention, cognitive elaboration, engagement and transportation of experience, this study adds to the literature of IGA by examining the impact of newness and game interactivity.

Se analiza el efecto de la congruencia de la novedad del juego y su interactividad en el recuerdo y la actitud hacia la marca de los jugadores utilizando las teorías de contrast effect, mind-engagement y transfer effect.

Se desarrolló un diseño de 2 (novedad: congruente o incongruente) x 2 (interactividad de juego: alta o baja) de medidas entre sujetos. 224 estudiantes de administración participaron en el estudio. Para contrastar las hipótesis se utilizó un MANOVA de medidas entre sujetos de 2 x 2.

Los hallazgos muestran que cuando la novedad es incongruente es mayor el recuerdo de la marca, pero la actitud es menos favorable. Bajo la condición de novedad incongruente, la alta interactividad motiva mayor recuerdo de la marca. Sin embargo, en la condición de novedad congruente, tanto las condiciones de alta como las de baja interactividad resultan en el mismo nivel de recuerdo de marca. Si la novedad es congruente, la alta interactividad conduce a una actitud de marca más favorable, mientras que, en condiciones de novedad incongruente, tanto la alta como baja interactividad conducen a una actitud hacia la marca similar.

Lograr altos índices de recuerdo y actitudes positivas hacia la marca son los objetivos principales de los anunciantes al seleccionar un medio para anunciar sus marcas. Este estudio avanza en el conocimiento de la publicidad online, especialmente la publicidad en juegos como estrategia de medios para anunciar marcas teniendo en cuenta la novedad e interactividad de los juegos.

Desde las perspectivas de la atención, la elaboración cognitiva, el compromiso y la experiencia, este estudio contribuye a la literatura de la publicidad en juegos al examinar el impacto de la novedad y la interactividad de los juegos.

The operating wagon records were produced from distinct railway information systems, which resulted in the wagon routing record with the same oriental destination (OD) was different. This phenomenon has brought considerable difficulties to the railway wagon flow forecast. Some were because of poor data quality, which misled the actual prediction, while others were because of the existence of another actual wagon routings. This paper aims at finding all the wagon routing locus patterns from the history records, and thus puts forward an intelligent recognition method for the actual routing locus pattern of railway wagon flow based on SST algorithm.

Based on the big data of railway wagon flow records, the routing metadata model is constructed, and the historical data and real-time data are fused to improve the reliability of the path forecast results in the work of railway wagon flow forecast. Based on the division of spatial characteristics and the reduction of dimension in the distributary station, the improved Simhash algorithm is used to calculate the routing fingerprint. Combined with Squared Error Adjacency Matrix Clustering algorithm and Tarjan algorithm, the fingerprint similarity is calculated, the spatial characteristics are clustering and identified, the routing locus mode is formed and then the intelligent recognition of the actual wagon flow routing locus is realized.

This paper puts forward a more realistic method of railway wagon routing pattern recognition algorithm. The problem of traditional railway wagon routing planning is converted into the routing locus pattern recognition problem, and the wagon routing pattern of all OD streams is excavated from the historical data results. The analysis is carried out from three aspects: routing metadata, routing locus fingerprint and routing locus pattern. Then, the intelligent recognition SST-based algorithm of railway wagon routing locus pattern is proposed, which combines the history data and instant data to improve the reliability of the wagon routing selection result. Finally, railway wagon routing locus could be found out accurately, and the case study tests the validity of the algorithm.

Before the forecasting work of railway wagon flow, it needs to know how many kinds of wagon routing locus exist in a certain OD. Mining all the OD routing locus patterns from the railway wagon operating records is helpful to forecast the future routing combined with the wagon characteristics. The work of this paper is the basis of the railway wagon routing forecast.

As the basis of the railway wagon routing forecast, this research not only improves the accuracy and efficiency for the railway wagon routing forecast but also provides the further support of decision-making for the railway freight transportation organization.

The purpose of this paper is to study the drivers of service provider switching intention other than satisfaction and, additionally, analyse the moderating role of the type of service (utilitarian vs hedonic). Specifically, the authors study the effects of alternative attractiveness, post-purchase regret, anticipated regret and past switching behaviour.

A representative survey with 800 consumers of mobile phone services (utilitarian) and holiday destinations (hedonic) was carried out.

Satisfaction is not a significant antecedent of switching intention in the hedonic service and its effect is marginal in the utilitarian service. In the utilitarian service, the main predictor of switching intention is post-purchase regret, whereas in the hedonic service, the main determinants of switching intention are past switching behaviour and anticipated regret.

The main contribution of this study is the analysis of the determinants of provider switching behaviour that may explain abandonment by satisfied customers, to see if their influence is greater or smaller than that of satisfaction itself, which has been the most analysed variable. Furthermore, there are expected to be differences between utilitarian and hedonic services, an aspect which is also studied in this work.

This study examines the information literacy practices of young video bloggers, focusing on the ways in which they construct their cognitive authority through a health-related information creation process.

This study draws upon socially oriented information literacy research and nexus analysis as its methodological framework. Data, including YouTube videos, theme interviews and video diaries, were collected with three Finnish video bloggers and qualitatively analysed using nexus analytical concepts to describe the central elements of social action.

The study shows that video bloggers employ several information practices during the information creation process, including planning, information-seeking, organization, editing and presentation of information. They construct their cognitive authority in relation to their anticipated audience by grounding it on different types of information: experience-based, embodied and scientific. Trustworthiness, emphasized with authenticity and genuineness, and competence, based on experience, expertise and second-hand information, were recognized as key components of credibility in this context.

This study increases the understanding of the complex ways in which young people create information on social media and influence their audiences. The study contributes to information literacy research by offering insights into the under-researched area of information creation. It is among the few studies to examine cognitive authority construction in the information creation process. The notion of authority as constructed through trustworthiness and competence and grounded on different types of information, can be taken into account in practice by information professionals and educators when planning information literacy instruction.

The purpose of this article is to investigate the interrelationships between innovation climate and human capital in the development of dynamic capabilities related to innovation. The study presents a set of concepts about variables involved in the innovation process and their interrelationship, addressing the analysis of international scientific production related to the antecedents of the innovation climate, human capital and dynamic capabilities.

A review of the literature from 1998 to 2018 was carried out, using descriptive statistical methods, at first, and qualitative analysis of the results in order to visualize the current configuration of the field of study of innovation background.

The results demonstrate a significant number of studies relating human capital and dynamic capabilities and little quantitative significance in studies relating to a climate of innovation and dynamic capabilities. The research describes how the dynamic capabilities of innovation have been approached in a conceptual model based on the perspective of human capital and innovation climate.

The study did not contemplate the analysis of the interrelationship between the resource configuration construct and the dynamic innovation capacities (part of the gap pointed out by Tuzovic, Wirtz and Heracleous (2018), constituting a perceptible limitation of the analyzes carried out in this article.

The influence of the innovation climate construct and its relationship with dynamic innovation capabilities deserves greater attention in research with an empirical approach, constituting a field to be explored by scientific research in organizations.

The research sought to investigate the gap involving the interrelations between innovation climate and human capital in the development of dynamic capabilities related to innovation, indicating the need for further empirical studies on the subject.