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This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).

Using the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.

The results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.

Firstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

Under the high-speed operating conditions, the effects of wheelset elastic deformation on the wheel rail dynamic forces will become more notable compared to the low-speed condition. In order to meet different analysis requirements and selecting appropriate models to analyzing the wheel rail interaction, it is crucial to understand the influence of wheelset flexibility on the wheel-rail dynamics under different speeds and track excitations condition.

The wheel rail contact points solving method and vehicle dynamics equations considering wheelset flexibility in the trajectory body coordinate system were investigated in this paper. As for the wheel-rail contact forces, which is a particular force element in vehicle multibody system, a method for calculating the Jacobian matrix of the wheel-rail contact force is proposed to better couple the wheel-rail contact force calculation with the vehicle dynamics response calculation. Based on the flexible wheelset modeling approach in this paper, two vehicle dynamic models considering the wheelset as both elastic and rigid bodies are established, two kinds of track excitations, namely normal measured track irregularities and short-wave irregularities are used, wheel-rail geometric contact characteristic and wheel-rail contact forces in both time and frequency domains are compared with the two models in order to study the influence of flexible wheelset rotation effect on wheel rail contact force.

Under normal track irregularity excitations, the amplitudes of vertical, longitudinal and lateral forces computed by the flexible wheelset model are smaller than those of the rigid wheelset model, and the virtual penetration and equivalent contact patch are also slightly smaller. For the flexible wheelset model, the wheel rail longitudinal and lateral creepages will also decrease. The higher the vehicle speed, the larger the differences in wheel-rail forces computed by the flexible and rigid wheelset model. Under track short-wave irregularity excitations, the vertical force amplitude computed by the flexible wheelset is also smaller than that of the rigid wheelset. However, unlike the excitation case of measured track irregularity, under short-wave excitations, for the speed within the range of 200 to 350 km/h, the difference in the amplitude of the vertical force between the flexible and rigid wheelset models gradually decreases as the speed increase. This is partly due to the contribution of wheelset’s elastic vibration under short-wave excitations. For low-frequency wheel-rail force analysis problems at speeds of 350 km/h and above, as well as high-frequency wheel-rail interaction analysis problems under various speed conditions, the flexible wheelset model will give results agrees better with the reality.

This study provides reference for the modeling method of the flexible wheelset and the coupling method of wheel-rail contact force to the vehicle multibody dynamics system. Furthermore, by comparative research, the influence of wheelset flexibility and rotation on wheel-rail dynamic behavior are obtained, which is useful to the application scope of rigid and flexible wheelset models.

The precast concrete slab track (PST) has advantages of fewer maintenance frequencies, better smooth rides and structural stability, which has been widely applied in urban rail transit. Precise positioning of precast concrete slab (PCS) is vital for keeping the initial track regularity. However, the cast-in-place process of the self-compacting concrete (SCC) filling layer generally causes a large deformation of PCS due to the water-hammer effect of flowing SCC, even cracking of PCS. Currently, the buoyancy characteristic and influencing factors of PCS during the SCC casting process have not been thoroughly studied in urban rail transit.

In this work, a Computational Fluid Dynamics (CFD) model is established to calculate the buoyancy of PCS caused by the flowing SCC. The main influencing factors, including the inlet speed and flowability of SCC, have been analyzed and discussed. A new structural optimization scheme has been proposed for PST to reduce the buoyancy caused by the flowing SCC.

The simulation and field test results showed that the buoyancy and deformation of PCS decreased obviously after adopting the new scheme.

The findings of this study can provide guidance for the control of the deformation of PCS during the SCC construction process.

Textile production is a very complex industrial process, whose planning still depends on experts' knowledge and experience. With traditional techniques, a great many process parameters have to be repeatedly computed and the optimization of process parameters is also getting more and more difficult. However the proliferation of a huge mass of data from real production has been creating many new opportunities for those working in textile science, engineering and business. The field of data mining (DM) and knowledge discovery from database (KDD) has emerged as a new discipline in engineering and computer science. This paper investigates data mining methods from the industrial database, and presents a novel DM-based intelligent model (DMIM) for worsted process decisions through an integral application of case-based reasoning (CBR) and artificial neural network (ANN) techniques. First, from the rich existing process database, CBR is able to retrieve and recommend a similar process case as a process template; then, by means of modification on these parameters in the existing cases, ANN model is used to predict the yarn quality and make the best process decision. The basic concept and system modeling are presented in this paper. An applied case with DMIM is also given to demonstrate that the best process decision can be made and important process parameters such as those for raw materials can be optimized.

Social media is becoming a hub of fake content, be it political news, product reviews, business promotion or any other sociocultural event. This study aims to provide a comprehensive review of the emerging literature to advance an understanding of misinformation on social media platforms, which is a growing concern these days.

The authors curate and synthesize the dispersed knowledge about misinformation on social media by conducting a systematic literature review based on the preferred reporting items for systematic reviews and meta-analyses framework. The search strategy resulted in 446 research articles, out of which 33 relevant articles were identified for this research.

Misinformation on social media spreads swiftly and may result in negative consequences. This review identifies 13 intrinsic predictors of the dissemination, 11 detection approaches and 10 ways to combat misinformation on social media.

The study adds to the present knowledge of spread and detection of misinformation on social media. The results of this study will be beneficial for researchers and practitioners and help them in mitigating the harmful consequences of the spread of misinformation.

In this study, an amorphous Al-Ti-Ni coating was fabricated on S355 steel using an arc spraying, and its corrosion behavior immersed in 3.5 per cent NaCl solution for 720 h was discussed, which provided an experimental basis for the application of arc sprayed Al-Ti-Ni coating on S355 steel on marine platform.

An amorphous Al-Ti-Ni coating was sprayed on S355 structural steel using an arc spraying. The surface-interface morphologies, chemical element compositions and phases of the obtained Al-Ti-Ni coating were analyzed using a scanning electron microscope, energy dispersive spectrometer and X-ray diffractometer, respectively. The distributions of chemical elements on the coating surface and interface were analyzed using an energy spectrum scanning; the bonding mechanism between the coating and the substrate was also discussed.

Financial support for this research by the Key Research and Development Project of Jiangsu Province (BE2016052).

In this study, an amorphous Al-Ti-Ni coating was fabricated on S355 steel using an arc spraying, its corrosion behavior immersed in 3.5 per cent 25 NaCl solution for 720 h was discussed.

The COVID-19 pandemic has profoundly impacted small and medium-sized enterprises (SMEs), inherently vulnerable entities, prompting a pivotal question of how to enhance SMEs’ organizational resilience (OR) to withstand discontinuous crises. Although digital innovation (DI) is widely acknowledged as a critical antecedent to OR, limited studies have analyzed the configurational effects of DI on OR, particularly stage-based analysis.

Underpinned by the dynamic capabilities view, this study introduces a multi-stage dynamic capabilities framework for OR. Employing Latent Dirichlet Allocation (LDA), digital product innovation (DPI), digital services innovation (DSI) and digital process innovation (DCI) are further deconstructed into six dimensions. Furthermore, we utilized fuzzy-set qualitative comparative analysis (fsQCA) to explore the configuration effects of six DI on OR at different stages, using data from 94 Chinese SMEs.

First, OR improvement hinges not on a singular DI but on the interactions among various DIs. Second, multiple equivalent configurations emerge at different stages. Before the crisis, absorptive capability primarily advanced through iterative DPI and predictive DSI. During the crisis, response capability is principally augmented by the iterative DPI, distributed DCI, and integrated DCI. After the crisis, recovery capability is predominantly fortified by the iterative DPI, expanded DPI and experiential DSI. Third, iterative DPI consistently assumes a supportive role in fortifying OR.

This study contributes to the extant literature on DI and OR, offering practical guidance for SMEs to systematically enhance OR by configuring DI across distinct stages.

Presents over sixty abstracts summarising the 1999 Employment Research Unit annual conference held at the University of Cardiff. Explores the multiple impacts of globalization on work and employment in contemporary organizations. Covers the human resource management implications of organizational responses to globalization. Examines the theoretical, methodological, empirical and comparative issues pertaining to competitiveness and the management of human resources, the impact of organisational strategies and international production on the workplace, the organization of labour markets, human resource development, cultural change in organisations, trade union responses, and trans‐national corporations. Cites many case studies showing how globalization has brought a lot of opportunities together with much change both to the employee and the employer. Considers the threats to existing cultures, structures and systems.

The purpose of this article is to analysis of the effects of green innovation ecosystem coopetition (cooperation and competition), environmental management practices (EMPs) and digital innovation (DI) on carbon footprint reduction.

To conduct the study, a questionnaire was administered to hotel managers from different regions of Brazil. Data were collected from 197 hotels and analyzed via partial least squares structural equation modeling.

The results show that green innovation ecosystem cooperation positively and significantly affects EMPs and DI. Green innovation ecosystem competition interactions also benefit the adoption of EMPs. However, they do not significantly influence the use of DI. The results indicate that hotels that are in a scenario of simultaneous competition and collaboration (coopetition) within the green innovation ecosystem can reduce carbon emissions when EMPs and DI are used.

The authors contribute to the literature by showing different pathways for reducing the carbon footprint of hotels. The results expand the authors’ knowledge by showing evidence that cooperation and competition interactions can produce distinct effects, especially on DI. Thus, this study has important practical implications for hotel managers seeking to improve their environmental practices and DI with the help of external multiagent resources and knowledge.

This research contributes to the literature by examining how cooperation and competition interactions in the green innovation ecosystem help in the adoption of environmental management and DI practices.

The purpose of this paper is to present results of a study that operationalizes the construct of disruptive innovation activities (DIA) at managerial level and to examine its validity.

A sequential mixed method approach is adopted in this study where a Likert-type scale to measure DIA is developed basing on the interviews of thirteen managers and conceptualization of disruptive innovation at manager level. Later, the scale validity and reliability are examined through quantitative data from 390 managers. The data are analyzed using IBM SPSS 23 and AMOS 21.

The findings of the study indicate that managers' DIA are spread across four phases of the disruptive innovation process, i.e. initiation, introduction, evolution and convergence. Furthermore, the reliability measures, exploratory factor analyses, confirmatory factor analysis and subsequent convergent and discriminant validity tests support the DIA scale. Nomological validity of DIA is also presented which demonstrates its predictive validity.

Limitations include research methods used in this study, such as cross-sectional design and nonprobabilistic sampling technique. Implications for future research are also provided.

Despite highlighting the importance of managers regarding disruptive innovation outcomes, prior research lacked to provide empirical foundations to understand the phenomenon from managerial perspective. This study fills this gap in the literature by providing a measure of DIA at manager level and distinguishing it from similar constructs. The construct validity of DIA can help measure an organization's disruptive potential in terms of its key human resource. Moreover, the DIA scale can be used to substantiate the alignment of the managerial activities with the innovation roles in organizational settings and to develop more relevant incentive plans.