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The safety and reliability of high-speed trains rely on the structural integrity of their components and the dynamic performance of the entire vehicle system. This paper aims to define and substantiate the assessment of the structural integrity and dynamical integrity of high-speed trains in both theory and practice. The key principles and approaches will be proposed, and their applications to high-speed trains in China will be presented.

First, the structural integrity and dynamical integrity of high-speed trains are defined, and their relationship is introduced. Then, the principles for assessing the structural integrity of structural and dynamical components are presented and practical examples of gearboxes and dampers are provided. Finally, the principles and approaches for assessing the dynamical integrity of high-speed trains are presented and a novel operational assessment method is further presented.

Vehicle system dynamics is the core of the proposed framework that provides the loads and vibrations on train components and the dynamic performance of the entire vehicle system. For assessing the structural integrity of structural components, an open-loop analysis considering both normal and abnormal vehicle conditions is needed. For assessing the structural integrity of dynamical components, a closed-loop analysis involving the influence of wear and degradation on vehicle system dynamics is needed. The analysis of vehicle system dynamics should follow the principles of complete objects, conditions and indices. Numerical, experimental and operational approaches should be combined to achieve effective assessments.

The practical applications demonstrate that assessing the structural integrity and dynamical integrity of high-speed trains can support better control of critical defects, better lifespan management of train components and better maintenance decision-making for high-speed trains.

One increasingly popular financing option for entrepreneurial ventures is to attract corporate venture capital (CVC) investments. Prior research tends to take a CVC-centric perspective assessing the benefits and contingencies for incumbent firms or corporate investors to engage with entrepreneurial ventures. Few studies have taken the opposite perspective of investigating factors that entrepreneurial ventures need to take into account when engaging with CVC investments. As such, this study aims to investigate pre- and post-IPO entrepreneurial venture performance that partners with CVC providers or corporate investors, as well as to assess organizational and environmental contingencies.

This study draws on a sample of 631 entrepreneurial ventures from the CSMAR database ranging from 2009 to 2019, along with CVC financing data from the CVSource database and financial data in entrepreneurial ventures’ annual reports from the Juchao Network. This study applies multiple linear regression modelling and fixed effect panel data analyses to test the proposed hypotheses.

The results show that CVC investment contributes to entrepreneurial ventures’ financial performance, both pre- and post-IPO. However, while research and development (R&D) intensity and geographic proximity strengthen the positive relationship between CVC investment and entrepreneurial ventures’ performance pre-IPO, R&D intensity has a negative moderating effect on the relationship between CVC investment and entrepreneurial ventures’ performance post-IPO.

First, in emerging economies, adopting a CVC financing strategy is an important strategic choice for entrepreneurial ventures that have a great demand for external capital, resources and technology support. Second, leveraging the relationship between external financing and internal R&D investment is essential for them to maintain their core competitiveness and sustainable growth. Moreover, entrepreneurial ventures should deal with the coopetitive relationship with incumbent companies and manage their dependency on other market participants in the external environment.

This study focuses on the performance implications for entrepreneurial ventures engaging with CVC investments pre- and post-IPO. First, this study broadens and expands prior research on the mechanism of the relationship between CVC and entrepreneurial ventures’ financial performance. Second, the research conducts a comparative study of the moderating effects of different timings. Third, this study applies learning theory to the field of CVC in emerging economies.

Crack sensor based on RFID tag has become a research hotspot in the field of metal structural health monitoring for its significant benefit of passive wireless transmission. While in practice, crack location will impact the performance of crack depth-sensing tag. The purpose of this paper is to provide a method for reducing disturbance of crack location on crack depth-sensing tag.

The effect analysis of crack location on crack depth-sensing tag is presented first to find disturbance reason and disturbance law. On the basis of that, a miniaturized tag is proposed to improve the current distribution and reduce the disturbance introduced by crack location.

The degree of crack location disturbance is closely related to the current distribution in the coverage area of tag. Because sensing tag performs better when crack locates in the high current density area, miniaturization of sensing tag is exploited to expand the high current density area and make the area more symmetrical. The simulated and experimental results demonstrate that tag miniaturization can enhance the performance of crack depth-sensing tag.

This paper provides a method to enhance the performance of crack depth-sensing tag.

How to use a simple and classical topology to provide a high-efficiency excitation voltage for dielectric barrier discharge (DBD) loads is one of the primary problems to be solved for DBD application fields.

To address the issue, a set of modes that can generate a high-efficiency pulse excitation voltage in a full-bridge inverter are adopted. With the set of modes, the unique equivalent circuit of DBD loads and the parasitic parameter of the step-up transformer can be fully used. Based on the set of modes, a control strategy for the full-bridge inverter is designed. To test the performance of the power supply, a simulation model is established and an experimental prototype is made with a DBD excimer lamp.

The simulation and experimental results show that not only a high-efficiency excitation voltage can be generated for the DBD load, but also the soft switching of all power switch is realized. Besides this, with the set of modes and the proposed control strategy, the inverter can operate in a high frequency. Compared with other types of power supplies, the power supply used in the paper can fully take advantage of the potential of the excimer lamp at the same input power.

This work considers that how to use a simple and classical topology to provide a high-efficiency excitation voltage for DBD loads is one of the primary problems to be solved for DBD application fields.

The purpose of this paper is to obtain analytic solutions of telegraph equation by the homotopy Padé method.

The authors used Maple Package to calculate the solutions obtained from the homotopy Padé method.

The obtained approximation by using homotopy method contains an auxiliary parameter which is a simple way to control and adjust the convergence region and rate of solution series. The approximation solutions by [m, m] homotopy Padé technique are often independent of auxiliary parameter h and this technique accelerates the convergence of the related series. Finally, numerical results for some test problems with known solutions are presented and the numerical results are given to show the efficiency of the proposed techniques.

The paper is shown that homotopy Padé technique is a promising tool with accelerated convergence for complicated nonlinear differential equations.

With the rapid development and stable operated application of lithium-ion batteries used in uninterruptible power supply (UPS), the prediction of remaining useful life (RUL) for lithium-ion battery played an important role. More and more researchers paid more attentions on the reliability and safety for lithium-ion batteries based on prediction of RUL. The purpose of this paper is to predict the life of lithium-ion battery based on auto regression and particle filter method.

In this paper, a simple and effective RUL prediction method based on the combination method of auto-regression (AR) time-series model and particle filter (PF) was proposed for lithium-ion battery. The proposed method deformed the double-exponential empirical degradation model and reduced the number of parameters for such model to improve the efficiency of training. By using the PF algorithm to track the process of lithium-ion battery capacity decline and modified observations of the state space equations, the proposed PF + AR model fully considered the declined process of batteries to meet more accurate prediction of RUL.

Experiments on CALCE dataset have fully compared the conventional PF algorithm and the AR + PF algorithm both on original exponential empirical degradation model and the deformed double-exponential one. Experimental results have shown that the proposed PF + AR method improved the prediction accuracy, decreases the error rate and reduces the uncertainty ranges of RUL, which was more suitable for the deformed double-exponential empirical degradation model.

In the running of UPS device based on lithium-ion battery, the proposed AR + PF combination algorithm will quickly, accurately and robustly predict the RUL of lithium-ion batteries, which had a strong application value in the stable operation of laboratory and other application scenarios.

The purpose of this paper is to discuss the relationships between person–job fit and job satisfaction, the mediating role of career self-management and the moderating role of job demands.

In this paper, 947 employees were surveyed using questionnaires, and hypothesis testing was conducted using structural equation modeling in Mplus.

Person–job fit was found to be positively related to career self-management, and career self-management plays a mediating role in the positive relationship between person–job fit and job satisfaction. Statistical analysis also confirmed that job demands moderate both the relationship between person–job fit and career self-management, as well as the relationship between person–job fit and job satisfaction via career self-management.

The results of a single study offer limited generalizability and should thus be applied with caution. More cross-industry and cross-company studies should be conducted to verify the applicability of the findings to other industries, cultures and geographical contexts.

Managers should try to enhance employees' person–job fit and help or encourage them to engage in career self-management to increase job satisfaction. Additionally, managers should be aware of the negative influence of job demands and try to keep them at low levels.

This study extends and enriches the understanding of the positive influence of person–job fit on work outcomes, explores the mechanism of person–job fit on job satisfaction from a new perspective, namely career self-management, and explores the boundary condition (i.e. job demands) of the relationship between person–job fit and career self-management in the Chinese context.

This paper aims to systematically demonstrate a methodology to determine the relative and absolute encapsulation efficiencies (α_Re and α_Ab) for thermally- and chemically-robust inorganic pigments, typically like ZrSiO₄-based pigments, thereby enhancing their coloring performance.

The authors designed a route, surplus alkali-decomposition and subsequently strong-acid dissolution (SAD2) to completely decompose three classic zircon pigments (Pr–ZrSiO₄, Fe₂O₃@ZrSiO₄ and CdS@ZrSiO₄) into clear solutions and preferably used inductively coupled plasma-optical emission spectrometry (ICP-OES) to determine the concentrations of host elements and chromophores, thereby deriving the numeric data and interrelation of α_Re and α_Ab.

Zircon pigments can be thoroughly decomposed into some dissoluble zirconate–silicate resultants by SAD2 at a ratio of the fluxing agent to pigment over 6. ICP-OES is proved more suitable than some other quantification techniques in deriving the compositional concentrations, thereby the values of α_Re and α_Ab, and their transformation coefficient K_RA, which maintains stably within 0.8–0.9 in Fe₂O₃@ZrSiO₄ and CdS@ZrSiO₄ and is slightly reduced to 0.67–0.85 in Pr–ZrSiO₄.

The SAD2 method and encapsulation efficiencies are well applicable for both zircon pigments and the other pigmental or non-pigmental inhomogeneous systems in characterizing their accurate composition.

The authors herein first proposed strict definitions for the relative and absolute encapsulation efficiencies for inorganic pigments, developed a relatively stringent methodology to determine their accurate values and interrelation.

This paper aims to introduce a new fault protection scheme for microgrid DC networks with ring buses.

It is well recognized that the protection scheme in a DC ring bus microgrid becomes very complicated due to the bidirectional power flow. To provide reliable protection, the differential current signal is decomposed into several basic modes using adaptive variational mode decomposition (VMD). In this method, the mode number and the penalty factor are chosen optimally by using arithmetic optimization algorithm, yielding satisfactory decomposition results than the conventional VMD. Weighted Kurtosis index is used as the measurement index to select the sensitive mode, which is used to evaluate the discrete Teager energy (DTE) that indicates the occurrence of DC faults. For localizing cable faults, the current signals from the two ends are used on a sample-to-sample basis to formulate the state space matrix, which is solved by using generalized least squares approach. The proposed protection method is validated in MATLAB/SIMULINK by considering various test cases.

DTE is used to detect pole-pole and pole-ground fault and other disturbances such as high-impedance faults and series arc faults with a reduced detection time (10 ms) compared to some existing techniques.

Verification of this method is performed considering various test cases in MATLAB/SIMULINK platform yielding fast detection timings and accurate fault location.

Embroidery as a textile embellishment technique plays an important role in people's daily life. Esthetic embroidery artworks possess cultural values. With the development of robotics and artificial intelligence (AI), these technologies have been studied and applied in the embroidery process. This study aims to survey how these technologies facilitate embroidery from different aspects.

This paper surveys how the technologies of robotics and AI are applied in the embroidery field. The applications are mainly reviewed from three aspects: computerized robotic embroidery systems has been widely used for the mass production of embroidered textiles, the advanced technological systems and techniques have greatly facilitated the development of smart textiles and the artificial intelligence plays an important role in the inheritance, innovation and protection of traditional handicraft artwork of embroidery.

The programmable robotic embroidery machines have greatly improved the production efficiency of embroidered textiles and promoted the development of electronic textiles. The AI, mainly the deep learning technology, brings significant benefits to esthetic embroidery creation. Technology-based embroidery has become a hot research topic in the field of textiles.

This paper summarizes the application of robotics and AI technologies in the field of embroidery, which provides readers a comprehensive and systematic understanding about the research progress of modern technology-oriented embroidery. This helps readers gain inspiration from the technology perspectives.