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This paper aims to provide top-level design and basic platform for intelligent application in China high-speed railway.

Based on the analysis for the future development trends of world railway, combined with the actual development needs in China high-speed railway, The definition and scientific connotation of intelligent high-speed railway (IHSR) are given at first, and then the system architecture of IHSR are outlined, including 1 basic platform, 3 business sectors, 10 business fields, and 18 innovative applications. At last, a basic platform with cloud edge integration for IHSR is designed.

The rationality, feasibility and implementability of the system architecture of IHSR have been verified on and applied to the Beijing–Zhangjiakou high-speed railway, providing important support for the construction and operation of the world’s first IHSR.

This paper systematically gives the definition and connotation of the IHSR and put forward the system architecture of IHSR for first time. It will play the most important role in the design, construction and operation of IHSR.

The purpose of this paper is to investigate the effects of political connections on the association between firms' business strategy and their tax aggressiveness in an emerging economy such as China.

The authors study a large sample of Chinese public firms from 2011 to 2017 using a panel regression model. In addition, a change analysis, an instrument variable test and alternative measures/samples are implemented as robustness tests.

Firms adopting innovative business strategy are more tax aggressive overall. However, innovative firms with political connections are less tax aggressive compared to those without political connections.

This paper contributes to the understanding of firms' tax behaviors in an emerging economy setting. It suggests that there are costs associated with political connections, such as foregone tax saving opportunities, which are understudies in the prior literature.

The purpose of this study is to investigate the structure and dynamics of academic articles relating to public procurement (PP) in the period 1984–2022 (up to May). The researchers also intend to analyse how this knowledge domain has grown since 1984.

A bibliometric analysis was carried out to examine the existing state of PP research. Based on 640 journal articles indexed in the Scopus database and written by 1,247 authors over nearly four decades, a bibliometric analysis was conducted to reveal the intellectual structure of academic works pertaining to PP.

Findings reveal that PP research from Scopus has significantly increased in the past decade. Major journals publishing PP research are International Journal of Procurement Management, Journal of Cleaner Production, Journal of Purchasing and Supply Management and Public Money and Management. Results also indicate that authors’ cooperation network is fragmented, showing limited collaboration among PP researchers. In addition, results suggest that the institutional collaboration network in PP research mirrors what is commonly referred to as the North–South divide, signifying insufficient research collaboration between developed and developing countries’ institutions. According to the co-occurrence keyword network and topic modelling, PP revolves around five main themes, including innovation, corruption, sustainable and green PP, PP contracts and small and medium enterprises. Based on these results, several directions for future research are suggested.

This paper provides an increased understanding of the entire PP field and the potential research directions.

To the best of the authors’ knowledge, this study is the first-ever application of bibliometric techniques and topic modelling to examine the development of PP research since 1984 based on scholarly publications extracted from the Scopus database.

The research approach is based on the concept that a failure event is rarely random and is often generated by a chain of previous events connected by a sort of domino effect. Thus, the purpose of this study is the optimal selection of the components to predictively maintain on the basis of their failure probability, under budget and time constraints.

Assets maintenance is a major challenge for any process industry. Thanks to the development of Big Data Analytics techniques and tools, data produced by such systems can be analyzed in order to predict their behavior. Considering the asset as a social system composed of several interacting components, in this work, a framework is developed to identify the relationships between component failures and to avoid them through the predictive replacement of critical ones: such relationships are identified through the Association Rule Mining (ARM), while their interaction is studied through the Social Network Analysis (SNA).

A case example of a process industry is presented to explain and test the proposed model and to discuss its applicability. The proposed framework provides an approach to expand upon previous work in the areas of prediction of fault events and monitoring strategy of critical components.

The novel combined adoption of ARM and SNA is proposed to identify the hidden interaction among events and to define the nature of such interactions and communities of nodes in order to analyze local and global paths and define the most influential entities.

The construction of cement asphalt (CA) emulsified mortar can obviously disturb the slab status after the fine adjustment. To decrease or eliminate the influence of CA mortar grouting on track slab geometry status, the effects of grouting funnel, slab pressing method, mortar expansion ratio, seepage ratio and grouting area on China Railway Track System Type (CRTS I) track slab geometry status were discussed in this paper.

Combined with engineering practice, this paper studied the expansion law of filling layer mortar, the liquid level height of the filling funnel, the pressure plate device and the amount of exudation water and systematically analyzed the influence of filling layer mortar construction on the state of track slab. Relevant precautions and countermeasures were put forward.

The results showed that the track slab floating values of four corners were different with the CA mortar grouting and the track slab corner near CA mortar grouting hole had the maximum floating values. The anti-floating effect of “7” shaped slab pressing device was more efficient than fixed-joint angle iron, and the slab floating value could be further decreased by increasing the amount of “7” shaped slab pressing devices. After CA mortar grouting, the track slab floating pattern had a close correlation with the expansion rate and water seepage rate of CA mortar over time and the expansion and water seepage rate of the mortar were faster when the temperature was high. Furthermore, the use of strip CA mortar filling under the rail bearing platform on both sides could effectively reduce the float under the track slab, and it could also save mortar consumption and reduce costs.

This study plays an important role in controlling the floating values, CA mortar dosage and the building cost of projects by grouting CA mortar at two flanks of filling space. The research results have guiding significance for the design and construction of China's CRTS I, CRTS II and CRTS III track slab.

During the construction process of the China Railway Track System (CRTS) I type filling layer, the nonwoven fabric bags have been used as grouting templates for cement asphalt (CA) emulsified mortar. The porous structure of nonwoven fabrics endowed the templates with breathability and water permeability. The standard requires that the volume expansion rate of CA mortar must be controlled within 1%–3%, which can generate expansion pressure to ensure that the cavities under track slabs are filled fully. However, the expansion pressure caused some of the water to seep out from the periphery of the filling bag, and it would affect the actual mix proportion of CA mortar. The differences in physical and mechanical properties between the CA mortar under track slabs and the CA mortar formed in the laboratory were studied in this paper. The relevant results could provide important methods for the research of filling layer materials for CRTS I type and other types of ballastless tracks in China.

During the inspection of filling layer, the samples of CA mortar from different working conditions and raw materials were taken by uncovering the track slabs and drilling cores. The physical and mechanical properties of CA mortar under the filling layer of the slab were systematically analyzed by testing the electrical flux, compressive strength and density of mortar in different parts of the filling layer.

In this paper, the electric flux, the physical properties and mechanical properties of different parts of CA mortar under the track slab were investigated. The results showed that the density, electric flux and compressive strength of CA mortar were affected by the composition of raw materials for dry powders and different parts of the filling layer. In addition, the electrical flux of CA mortar gradually decreased within 90 days’ age. The electrical flux of samples with the thickness of 54 mm was lower than 500 C. Therefore, the impermeability and durability of CA mortar could be improved by increasing the thickness of filling layer. Besides, the results showed that the compressive strength of CA mortar increased, while the density and electric flux decreased gradually, with the prolongation of hardening time.

During 90 days' age, the electrical flux of the CA mortar gradually decreased with the increase of specimen thickness and the electrical flux of the specimens with the thickness of 54 mm was lower than 500 C. The impermeability and durability of the CA mortar could be improved by increasing the thickness of filling layer. The proposed method can provide reference for the further development and improvement of CRTS I and CRTS II type ballastless track in China.

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.

The purpose of this paper is to analyze the micro-motion of the cylinder block.

Based on the elasto-hydrodynamic lubrication, a numerical model for the cylinder block/valve plate interface is proposed, with consideration of the elastic deformations, the pressure-viscosity effect and asperity contacts. The influence-function method is applied to calculating the actual deformations of the cylinder block and the valve plate. The asperity contact model simplified from Greenwood assumption is introduced into the numerical model. Furthermore, the relationship between the micro-motion and the operating condition, the sealing belt width is discussed, respectively.

The results show an increase in the discharge pressure causes the tilt state and the vibrating motion getting worse, which can be eased by improving the rotational speed, the sealing belt width and the ratio of external and internal sealing belt width.

The proposed research can provide a theoretical reference for the optimizing design of cylinder block/valve plate pair.

With the growing economic impact of e-commerce and the increasing trend of omnichannel mode, more considerate services can be provided to customers. This paper aims to explore the optimal practice of business strategies and enrich the research content of marine tourism omnichannel.

This paper studies the optimal practice of bundling pricing and service effort strategies between two tourism suppliers (TSs) and a travel agent (TA) who distributes complementary products in marine tourism omnichannel considering joint efforts of both sides. This study develops five models by Stackelberg and Nash game and introduces the revenue-sharing contract. All outcomes/results are analyzed and the corresponding numerical and sensitivity analyses are conducted to derive more managerial implications and business insights.

The main findings show that bundling price is directly proportional to inter-channel integration coefficient and service effort level coefficient, and inversely proportional to the price elasticity coefficient. TA tends to provide a higher level of service effort than TSs when TA plays a dominant role. Improving the service effort level unduly leads to a decline in profits. Moreover, TSs and TA can reach a win-win situation under the coordination mechanism and the marine tourism omnichannel can achieve the best performance.

A novel and useful approach towards joint equilibrium decisions of bundle pricing and service efforts in marine tourism omnichannel with complementary tourism products under different operational strategies is proposed.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.