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This paper aims to investigate the friction and wear properties of Cr-Ni-Mo-V steel against 440C stainless steel under both water and water–silica mixture lubricant.

The Cr-Ni-Mo-V steel specimens were taken from a forged steel brake disc with the process of quenching at 900°C and tempering at 600°C. The tribological testing was performed using a contact configuration of ball-on-flat with a liquid cell according to the ASTM standard. Detailed examinations on the worn surface were analyzed using a scanning electron microscope.

The results indicate that the friction coefficient and friction damage of the steel sliding under water–silica mixture are higher than those under water. The friction coefficient decreases with increasing load and increases with the sliding speed for the two lubricants. The mass wear rate presents a rising trend with both sliding load and speed. The wear mechanisms of the Cr-Ni-Mo-V steel sliding under the two lubricants are oxidation wear, abrasive wear and fatigue wear.

Because of the chosen tribological testing approach, the research results could not describe the tribological performance of the brake disc accurately during actual braking process of the high-speed train. Therefore, researchers are encouraged to test the proposed propositions further.

This study shows that the tribology behavior of the Cr-Ni-Mo-V steel with water or water–silica mixture lubrications helps the industrial firms and academicians to work on the wear of the brake disc in rainwater or wet environment.

This paper aims to investigate how digital orientation affects digital process innovation from the dual perspectives of knowledge and capability. It also stresses the mediating effects of digital knowledge creation and strategic flexibility on this relationship, as well as the moderating effect of strategic flexibility on the relationship between digital knowledge creation and digital process innovation.

This paper adopted knowledge- and capability-based views to develop the theoretical model. A total of 193 samples from China were collected to test the model and hypotheses by the partial least squares structural equation modeling method.

The results indicate that digital orientation promotes knowledge creation and strategic flexibility respectively, which in turn facilitates digital process innovation. Also, the effect of digital knowledge creation on digital process innovation is moderated by strategic flexibility.

This study adopts the dual perspectives of knowledge and capability to deepen the relationship between digital orientation and digital process innovation by introducing digital knowledge creation and strategic flexibility as the crucial links, which responds to the call for attaching importance to digital process innovation.

Understandings of house prices and their interrelationships have undoubtedly drawn a great amount of attention from various market participants. This study aims to investigate the monthly newly-built residential house price indices of seventy Chinese cities during a 10-year period spanning January 2011–December 2020 for understandings of issues related to their interdependence and synchronizations.

Analysis here is facilitated through network analysis together with topological and hierarchical characterizations of price comovements.

This study determines eight sectoral groups of cities whose house price indices are directly connected and the price synchronization within each group is higher than that at the national level, although each shows rather idiosyncratic patterns. Degrees of house price comovements are generally lower starting from 2018 at the national level and for the eight sectoral groups. Similarly, this study finds that the synchronization intensity associated with the house price index of each city generally switches to a lower level starting from early 2019.

Results here should be of use to policy design and analysis aiming at housing market evaluations and monitoring.

Power loss is an important index to evaluate the transmission performance of a gear pair. In some cases, the starved lubrication exists on the gear contact interface. The purpose of this paper is to reveal the mechanical power loss of a helical gear pair under starved lubrication.

A starved thermal-elastohydrodynamic lubrication (EHL) model is proposed to evaluate the tribological properties of a helical gear pair. The numerical result has been validated against the published simulation data. Based on the proposed model, the influence of thermal effect, working conditions, inlet oil-supply layer and surface roughness on the mechanical power loss and lubrication performance has been discussed.

Results show that the thermal effect has a significant effect on the tribological properties of helical gear pair, especially on mechanical power loss. For a specified working condition, there is an optimal oil supply for gear lubrication to obtain the state of full film lubrication. Meanwhile, it reveals that the mechanical power loss increases with the increase of the surface roughness amplitude.

In this paper, a starved thermal-EHL model has been developed for the helical gear pair based on the finite line contact theory. This model can be used to analyze the tribological properties of gear pair from full film lubrication to mixed lubrication. The results can provide the tribological guidance for design of a helical gear pair.

As one of its major strategies, China has made a new plan to further expand High Standard Farmland (HSF) to all permanent basic farmland (80% of total farmland) for grain security over the next decade. Yet, what will be the impact of farmland infrastructure investment on agrifood systems? The paper aims to systematically evaluate the multiple effects (food security, economy, nutrition and environment) of expanding HSF construction under the context of the “Big Food vision” using an interdisciplinary model.

An interdisciplinary model – AgriFood Systems Model, which links the China CGE model to diet and carbon emission modules, is applied to assess the multiple effects of HSF construction on agrifood systems, such as food security and economic development, residents’ diet quality and carbon emissions. Several policy scenarios are designed to capture these effects of the past HSF investment based on counterfactual analysis and compare the effects of HSF future investment at the national level under the conditions of different land use policies – restricting to grain crops or allowing diversification (like vegetables, and fruit).

The investments in HSF offer a promising solution for addressing the challenges of food and nutrition security, economic development and environmental sustainability. Without HSF construction, grain production and self-sufficiency would decline significantly, while the agricultural and agrifood systems’ GDP would decrease. The future investment in the HSF construction will further increase both grain production and GDP, improve dietary quality and reduce carbon emissions. Compared with the policy of limiting HSF to planting grains, diversified planting can provide a more profitable economic return, improve dietary quality and reduce carbon emissions.

This study contributes to better informing the impact of land infrastructure expanding investment on the agrifood systems from multiple dimensions based on an interdisciplinary model. We suggest that the government consider applying diversified planting in the future HSF investment to meet nutritional and health demands, increase household income and reduce carbon emissions.

This paper aims to adopt the knowledge-based view and social network theory to investigate the relationship between network capability ambidexterity and knowledge creation (KC) in the context of open innovation. It also examines the moderating effects of innovation climate on this relationship.

This paper developed a model including network capability ambidexterity, innovation climate and KC. A total of 463 samples were collected from China to test the model and hypotheses by SEM.

The empirical results indicate that network capability ambidexterity is the crucial antecedent of KC. Specifically, network capability ambidexterity consists of the balanced and combined dimensions that both have significant and positive effects on KC. More importantly, the balanced dimension has a stronger effect on KC than the combined. In addition, an innovation climate positively moderates the effects of network capability ambidexterity and KC.

This study advances a new understanding of how network capability ambidexterity influences KC. Moreover, investigating the relationships should provide fresh insights into network capabilities and KC for practitioners in the open innovation context.

This study aims to provide a new method of multiscale directional Lyapunov exponents (MSDLE) calculated based on the state space reconstruction for the nonstationary time series, which can be applied to detect the small target covered by sea clutter.

Reconstructed state space is divided into non-overlapping submatrices whose columns are equal to a predetermined scale. The authors compute eigenvalues and eigenvectors of the covariance matrix of each submatrix and extract the principal components σ_ip and their corresponding eigenvectors. Then, the angles ψ_ip of eigenvectors between two successive submatrices were calculated. The curves of (σ_ip, ψ_ip) reflect the nonlinear dynamics both in kinetic and directional and form a spectrum with multiscale. The fluctuations of (σ_ip, ψ_ip), which are sensitive to the differences of backscatter between sea wave and target, are taken out as the features for the target detection.

The proposed method can reflect the local dynamics of sea clutter and the small target within sea clutter is easily detected. The test on the ice multiparameter imaging X-ban radar data and the comparison to K distribution based method illustrate the effectiveness of the proposed method.

The detection of a small target in sea clutter is a compelling issue, as the conventional statistical models cannot well describe the sea clutter on a larger timescale, and the methods based on statistics usually require the stationary sea clutter. It has been proven that sea clutter is nonlinear, nonstationary or cyclostationary and chaotic. The new method of MSDLE proposed in the paper can effectively and efficiently detect the small target covered by sea clutter, which can be also introduced and applied to military, aerospace and maritime fields.

The study adopts congruence theory to explore the structure of inter-organizational compatibility and its structural effects on knowledge transfer in cross-border merger and acquisitions (M&As).

This paper built a moderated-mediation model that presented the relationship between inter-organizational compatibility and knowledge transfer. Regression analysis was conducted with 182 samples from China to examine the model and hypotheses.

The results indicate that inter-organizational compatibility is a four-dimensional construct comprising culture, strategy, routine and knowledge. Additionally, inter-organizational compatibility has structural effects on knowledge transfer. Specifically, routine compatibility mediates the relationships between cultural compatibility and knowledge transfer and between strategic compatibility and knowledge transfer. Moreover, the mediating roles are moderated by knowledge compatibility.

This study updates the construct and provides a comprehensive and fresh understanding of inter-organizational compatibility. Additionally, it presents the structural effects of inter-organizational compatibility on knowledge transfer.

This study aims to investigate the acoustic roughness of rails on China’s high-speed railways, with a focus on short-wavelength irregularities (less than 80 cm), which are known to significantly contribute to noise. The goal is to develop a specific acoustic roughness spectrum tailored for China’s high-speed railway system, as no such spectrum currently exists.

A long-term tracking study was conducted on major railway lines in China, monitoring rail roughness throughout the initial operational period and the rails’ service life. Data preprocessing techniques such as peak removal and curvature correction were applied for acoustic adjustments. A spatial-wavelength domain transformation was performed, providing the distribution patterns and statistical characteristics of acoustic roughness on China’s high-speed rails. Based on these analyses, a model for constructing the acoustic roughness spectrum was developed.

The study found that the acoustic roughness of China’s high-speed railway rails follows a χ² distribution with six degrees of freedom. For wavelengths greater than 8 cm, the acoustic roughness spectrum remains below the ISO specified limits. In the wavelength range of 3.2 cm to 6.3 cm, the roughness is comparable to or within the limits specified by ISO 3095:2005 and ISO 3095:2013. However, for wavelengths shorter than 2.5 cm, the roughness exceeds ISO limits.

This research fills the gap in the lack of a specific acoustic roughness spectrum for China’s high-speed railways. By establishing a tailored spectrum based on long-term data analysis, the findings provide valuable insights for noise control and rail maintenance in the context of China’s high-speed rail system.

Intelligent and connected vehicle technology is in the ascendant. High-level autonomous driving places more stringent requirements on the accuracy and reliability of environmental perception. Existing research works on multitarget tracking based on multisensor fusion mostly focuses on the vehicle perspective, but limited by the principal defects of the vehicle sensor platform, it is difficult to comprehensively and accurately describe the surrounding environment information.

In this paper, a multitarget tracking method based on roadside multisensor fusion is proposed, including a multisensor fusion method based on measurement noise adaptive Kalman filtering, a global nearest neighbor data association method based on adaptive tracking gate, and a Track life cycle management method based on M/N logic rules.

Compared with fixed-size tracking gates, the adaptive tracking gates proposed in this paper can comprehensively improve the data association performance in the multitarget tracking process. Compared with single sensor measurement, the proposed method improves the position estimation accuracy by 13.5% and the velocity estimation accuracy by 22.2%. Compared with the control method, the proposed method improves the position estimation accuracy by 23.8% and the velocity estimation accuracy by 8.9%.

A multisensor fusion method with adaptive Kalman filtering of measurement noise is proposed to realize the adaptive adjustment of measurement noise. A global nearest neighbor data association method based on adaptive tracking gate is proposed to realize the adaptive adjustment of the tracking gate.