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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.

It is of a great significance for the health monitoring of a liquid rocket engine to build an accurate and reliable fault prediction model. The thrust of a liquid rocket engine is an important indicator for its health monitoring. By predicting the changing value of the thrust, it can be judged whether the engine will fail at a certain time. However, the thrust is affected by various factors, and it is difficult to establish an accurate mathematical model. Thus, this study uses a mixture non-parametric regression prediction model to establish the model of the thrust for the health monitoring of a liquid rocket engine.

This study analyzes the characteristics of the least squares support vector regression (LS-SVR) machine . LS-SVR is suitable to model on the small samples and high dimensional data, but the performance of LS-SVR is greatly affected by its key parameters. Thus, this study implements the advanced intelligent algorithm, the real double-chain coding target gradient quantum genetic algorithm (DCQGA), to optimize these parameters, and the regression prediction model LSSVRDCQGA is proposed. Then the proposed model is used to model the thrust of a liquid rocket engine.

The simulation results show that: the average relative error (ARE) on the test samples is 0.37% when using LS-SVR, but it is 0.3186% when using LSSVRDCQGA on the same samples.

The proposed model of LSSVRDCQGA in this study is effective to the fault prediction on the small sample and multidimensional data, and has a certain promotion.

The original contribution of this study is to establish a mixture non-parametric regression prediction model of LSSVRDCQGA and properly resolve the problem of the health monitoring of a liquid rocket engine along with modeling the thrust of the engine by using LSSVRDCQGA.

This study aims to explore how institutional quality impacts private capital participation in large-scale infrastructure development, particularly in public–private partnership (PPP) projects, aiming to enhance incentives for private sector involvement.

Building on new institutional theory, a triangular theoretical framework was constructed to analyze the high participation of private capital in PPP projects, focusing on seven key institutional factors. Data from 1,319 PPP projects across 36 Belt and Road Initiative (BRI) countries from 2015 to 2020 were then analyzed using a combination of necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis (fsQCA) to evaluate the combined impact and interactions of these factors.

Results indicate that high private capital participation does not hinge on a single institutional quality factor but results from the synergistic influence of multiple factors. The paths leading to high private capital participation can be categorized as regulatory-led, normative-cognitive synergistic, regulatory-normative synergistic and institutional failure-led. Among these, regulatory quality plays a central role in the regulatory-led; the synergy between political stability and voice and accountability is pivotal in the normative-cognitive synergistic, and the rule of law, in combination with voice and accountability, is essential to the regulatory-normative synergistic.

This research systematically examines the multidimensional impact of institutional quality, revealing how different institutional factors interact to influence private capital’s willingness to participate and behavior. It enriches applied research in institutional economics within PPP projects and provides a new theoretical perspective and methodological framework to the scholarly community.

Project portfolio benefit (PPB) evaluation is crucial for project portfolio management decisions. However, PPB is complex in composition and affected by synergy and ambidexterity. Ignoring these characteristics can result in inaccurate assessments, impeding the management and optimization of benefit. Considering the above complexity of PPB evaluation, this study aims to propose a refined PPB evaluation model to provide decision support for organizations.

A back propagation neural network optimized via genetic algorithm and pruning algorithm (P-GA-BPNN) is constructed for PPB evaluation. First, the benefit evaluation criteria are established. Second, the inputs and expected outputs for model training and testing are determined. Then, based on the optimization of BPNN via genetic algorithm and pruning algorithm, a PPB evaluation model is constructed considering the impacts of ambidexterity and synergy on PPB. Finally, a numerical example was applied to validate the model.

The results indicate that the proposed model can be used for effective PPB evaluation. Moreover, it shows superiority in terms of MSE and fitting effect through extensive comparative experiments with BPNN, GA-BPNN, and SVM models. The robustness of the model is also demonstrated via data random disturbance experiment and 10-cross-validation. Therefore, the proposed model could serve as a valuable decision-making tool for PPB management.

This study extends prior research by integrating the impacts of synergy and ambidexterity on PPB when conducting PPB evaluation, which facilitates to manage and enhance PPB. Besides, the structural redundancy of existing assessment methods is solved through the dynamic optimization of the network structure via the pruning algorithm, enhancing the effectiveness of PPB decision-making tools.

This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s embeddedness in the global value chain (GVC) and the influence of environmental law, operational costs and corporate social responsibility (CSR). The insights gleaned bridge a gap in the literature surrounding GVCs and corporate carbon transfer.

The methodology comprised a two-step research approach. First, the authors used a two-sided fixed regression to analyse the relationship between each firm’s embeddedness in the GVC and its carbon transfers. The sample consisted of 217 US firms. Next, the authors examined the influence of environmental law, operational costs and CSR on carbon transfers using a quantitative comparison analysis. These results were interpreted through the theoretical frameworks of the GVC and legitimacy theory.

The empirical results indicate positive relationships between carbon transfers and GVC embeddedness in terms of both a firm’s position and its degree. From the quantitative comparison, the authors find that the pressure of environmental law and operational costs motivate these transfers through the value chain. Furthermore, CSR does not help to mitigate transfers.

The findings offer insights for policymakers, industry and academia to understand that, with globalised production and greater value creation, transferring carbon to different parts of the GVC – largely to developing countries – will only become more common. The underdeveloped nature of environmental technology in these countries means that global emissions will likely rise instead of fall, further exacerbating global warming. Transferring carbon is not conducive to a sustainable global economy. Hence, firms should be closely regulated and given economic incentives to reduce emissions, not simply shunt them off to the developing world.

Carbon transfer is a major obstacle to effectively reducing carbon emissions. The responsibilities of carbon transfer via GVCs are difficult to define despite firms being a major consideration in such transfers. Understanding how and why corporations engage in carbon transfers can facilitate global cooperation among communities. This knowledge could pave the way to establishing a global carbon transfer monitoring network aimed at preventing corporate carbon transfer and, instead, encouraging emissions reduction.

This study extends the literature by investigating carbon transfers and the GVC at the firm level. The authors used two-step research approach including panel data and quantitative comparison analysis to address this important question. The authors are the primary study to explore the motivation and pathways by which firms transfer carbon through the GVC.

The aim was not to perform a systematic review but firstly to search in PubMed, Science Direct, Scopus and Web of Science databases on the papers published in the last five years using tools for reviewing the statement of preferred information item for systematic reviews without focusing on a randomized analysis and secondly to perform a bibliometric analysis on the properties of films and coatings added of tocopherol for food packaging.

On January 24, 2022, information was sought on the properties of films and coatings added of tocopherol for use as food packaging published in PubMed, Science Direct, Scopus and Web of Science databases. Further analysis was performed using bibliometric indicators with the VOSviewer tool.

The searches returned 33 studies concerning the properties of films and coatings added of tocopherol for food packaging, which were analyzed together for a better understanding of the results. Data analysis using the VOSviewer tool allowed a better visualization and exploration of these words and the development of maps that showed the main links between the publications.

In the area of food science and technology, the development of polymers capable of promoting the extension of the shelf life of food products is sought, so the knowledge of the properties is vital for this research area since combining a biodegradable polymeric material with a natural antioxidant active is of great interest for modern society since they associate environmental preservation with food preservation.

Purpose of This Chapter: >The study examines the importance and effect of working over office hours and lengthy commutes on work–life balance because both consume time away from the official working hours. The study utilized perceived organizational support to measure the moderating role of working over office hours, lengthy commutes, and work–family balance.

Design / Methodology / Approach: An inferential statistics cross-sectional study collected data from 437 full-time employees of IT-BPM companies in 5 metropolitan cities in India. The study used the PLS-SEM to examine the hypotheses.

Findings: The results show a negative relationship between working over office hours and lengthy commutes on work–family balance. This study also found the moderating effect of perceived organizational support on working over office hours and lengthy commutes on the work–family balance. Also, the study revealed that half of the respondents spend three hours, and one-fourth of the respondents spend four and half hours working over office hours and lengthy commutes.

Research Limitations: This research is limited to IT-BPM companies in India. Nevertheless, the findings highlight the factors associated with IT-BPM employee work–family balance, and only two factors were identified.

Practical Implications: This study enhances the work–family balance’s theoretical and practical effects. The results provide a competitive benchmark for IT-BPM managers, administrators, and governing bodies of employee well-being.

Originality: To the best of the author’s knowledge, this study is the first to adopt extrinsic variables in work–family border theory to measure the work–family balance of IT-BPM employees.

Dynamically tracking the target by unmanned ground vehicles (UGVs) plays a critical role in mobile drone recovery. This study aims to solve this challenge under diverse random disturbances, proposing a dynamic target tracking framework for UGVs based on target state estimation, trajectory prediction, and UGV control.

To mitigate the adverse effects of noise contamination in target detection, the authors use the extended Kalman filter (EKF) to improve the accuracy of locating unmanned aerial vehicles (UAVs). Furthermore, a robust motion prediction algorithm based on polynomial fitting is developed to reduce the impact of trajectory jitter caused by crosswinds, enhancing the stability of drone trajectory prediction. Regarding UGV control, a dynamic vehicle model featuring independent front and rear wheel steering is derived. Additionally, a linear time-varying model predictive control algorithm is proposed to minimize tracking errors for the UGV.

To validate the feasibility of the framework, the algorithms were deployed on the designed UGV. Experimental results demonstrate the effectiveness of the proposed dynamic tracking algorithm of UGV under random disturbances.

This paper proposes a tracking framework of UGV based on target state estimation, trajectory prediction and UGV predictive control, enabling the system to achieve dynamic tracking to the UAV under multiple disturbance conditions.

With the rapid low-carbon transformation in China, the industrial approach and labor structure of mining enterprises are undergoing constant changes, leading to an increasing psychological dilemma faced by coal miners. This study aims to reveal the relationship and mechanism of factors influencing the psychological dilemma of miners, and to provide optimal intervention strategies for the safety and sustainable development of employees and enterprises.

To effectively address the complex issue of the psychological dilemma faced by miners, this study identifies and constructs five-dimensional elements, comprising 20 indicators, that influence psychological dilemmas. The relational mechanism of action of factors influencing psychological dilemma was then elucidated using an integration of interpretive structural modeling and cross-impact matrix multiplication.

Industry dilemma perception is a “direct” factor with dependent attributes. The perceptions of management response and relationship dilemmas are “root” factors with driving attributes. Change adaptation dilemma perception is a “susceptibility” factor with linkage attributes. Work dilemma perception is a “blunt” factor with both dependent and autonomous attributes.

The aforementioned findings offer a critical theoretical and practical foundation for developing systematic and cascading intervention strategies to address the psychological dilemma mining enterprises face, which contributes to advancing a high-quality coal industry and efficient energy development.

Given that a prerequisite for COVID-19 transmission is the interaction between individuals, it is reasonable to suspect that transportation networks may have contributed to the spread of COVID-19. This study uses the air transportation network to quantify the risk of COVID-19 spread in the United States. The proposed model is applied at the county level and identifies the risk of importing COVID-19-infected passengers into a given county. We also undertake an examination of the factors influencing the spread of COVID-19 in relation to air travel. Utilizing an extensive dataset encompassing various socioeconomic, demographic, and healthcare-related variables, our results indicate a positive relationship between these factors and the relative risk of COVID-19 spread, highlighting the pronounced impact of population density, air travel volume, and larger household sizes on increasing travel-related risk. Conversely, greater healthcare capacity, particularly in terms of hospital and intensive care unit (ICU) beds, is associated with reduced risk. We provide estimates of expected relative risk for each county and a ranking that can be useful for informing public health policies to stem the spread of the virus by devoting resources such as screening and enhanced travel protocols to airports located in at-risk counties.