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Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

A new type of variable damping viscous damper is developed to meet the settings of different damping parameter values at different working stages. Its main principle and design structure are introduced, and the two-stage and multi-stage controllable damping methods are proposed.

The theoretical calculation formulas of the damping force of power-law fluid variable damping viscous damper at elongated holes are derived, aiming to provide a theoretical basis for the development and application of variable damping viscous dampers. For the newly developed variable damping viscous damper, the dynamic equations for the seismic reduction system with variable damping viscous dampers under a multi-degree-of-freedom system are established. A feasible calculation and analysis method is proposed to derive the solution process of time history analysis. At the same time, a program is also developed using Matlab. The dynamic full-scale test of a two-stage variable damping viscous damper was conducted, demonstrating that the hysteresis curve is complete and the working condition is stable.

Through the calculation and analysis of examples, the results show that the seismic reduction effect of high and flexible buildings using the seismic reduction system with variable damping viscous dampers is significant. The program developed is used to analyze the seismic response of a broadcasting tower using a variable damping TMD system under large earthquakes. The results indicate that the installation of variable damping viscous dampers can effectively control the maximum inter-story displacement response of TMD water tanks and can effectively consume seismic energy.

This method can provide a guarantee for the safe and effective operation of TMD in wind and vibration control.

The purpose of this paper is to propose a new fault feature extraction scheme for the rolling element bearing.

The generalized Stockwell transform (GST) and the singular value ratio spectrum (SVRS) methods are combined. A time-frequency distribution measurement criterion named the energy concentration measurement (ECM) is initially used to determine the parameter of the optimal GST method. Then, the optimal GST is applied to conduct a time-frequency transformation for a raw signal. Subsequently, the two-dimensional time-frequency matrix is obtained. Finally, the improved singular value decomposition (SVD) analysis is used to conduct a noise reduction of the time-frequency matrix. The SVRS is proposed to select the effective singular values. Furthermore, the time-domain feature of the impact signal is obtained by taking the inverse GST transform.

The simulated and experimental signals are used to verify the superiority of the proposed method over conventional methods. The obtained results show that the proposed method can effectively extract fault features of the rolling element bearing.

This paper mainly discusses the application of GST and SVRS methods to analyze the weak fault feature extraction problem. The next research direction is to explore the application of the Hilbert Huang transform (HHT) and variational modal decomposition (VMD) in the impact feature extraction of rolling bearing.

In the present study, a new SVRS method is proposed to select the number of effective singular values. This paper proposed an effective way to obtain the fault feature in monitoring of rotating machinery.

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

Viscous dampers are commonly used in large span cable-stayed bridges to mitigate seismic effects and have achieved great success.

However, the nonlinear analysis on damper parameters is usually computational intensive and nonobjective. To address these issues, this paper proposes a simplified method to determine the viscous damper parameters for double-tower cable-stayed bridges. An empirical formula of the equivalent damping ratio of viscous dampers is established through decoupling nonclassical damping structures and linearization of nonlinear viscous dampers. Shaking table tests are conducted to verify the feasibility of the proposed method. Moreover, this simplified method has been proved in long-span cable-stayed bridges.

The feasibility of this method is verified by the simplified model shaking table test. This simplified method for determining the parameters of viscous dampers is verified in cable-stayed bridges with different spans.

This simplified method has been validated in cable-stayed bridges with various spans.

Trust is one of the main pillars of many communication and interaction domains. Computing is no exception. Fog computing (FC) has emerged as mitigation of several cloud computing limitations. However, selecting a trustworthy node from the fog network still presents serious challenges. This paper aims to propose an algorithm intended to mitigate the trust and the security issues related to selecting a node of a fog network.

The proposed model/algorithm is based on two main concepts, namely, machine learning using fuzzy neural networks (FNNs) and the weighted weakest link (WWL) algorithm. The crux of the proposed model is to be trained, validated and used to classify the fog nodes according to their trust scores. A total of 2,482 certified computing products, in addition to a set of nodes composed of multiple items, are used to train, validate and test the proposed model. A scenario including nodes composed of multiple computing items is designed for applying and evaluating the performance of the proposed model/algorithm.

The results show a well-performing trust model with an accuracy of 0.9996. Thus, the end-users of FC services adopting the proposed approach could be more confident when selecting elected fog nodes. The trained, validated and tested model was able to classify the nodes according to their trust level. The proposed model is a novel approach to fog nodes selection in a fog network.

Certainly, all data could be collected, however, some features are very difficult to have their scores. Available techniques such as regression analysis and the use of the experts have their own limitations. Experts might be subjective, even though the author used the fuzzy group decision-making model to mitigate the subjectivity effect. A methodical evaluation by specialized bodies such as the security certification process is paramount to mitigate these issues. The author recommends the repetition of the same study when data form such bodies is available.

The novel combination of FNN and WWL in a trust model mitigates uncertainty, subjectivity and enables the trust classification of complex FC nodes. Furthermore, the combination also allowed the classification of fog nodes composed of diverse computing items, which is not possible without the WWL. The proposed algorithm will provide the required intelligence for end-users (devices) to make sound decisions when requesting fog services.

This paper aims to clarify an important nuance by proposing that people attribute human mind to brands on two distinct dimensions: think and feel.

Eight studies were conducted to first develop and validate the 14-item Brand Anthropomorphism Questionnaire, and then to investigate how the two subscales, think or feel dimensions, influence consumer moral judgment of brands.

This research developed a 14-item Brand Anthropomorphism Questionnaire with two subscales, which are psychometrically sound and show discriminant validity with regard to existing brand constructs. Furthermore, think or feel brand anthropomorphism dimensions can predict consumers’ moral judgment of brands.

The present research offers preliminary evidence about the value of distinguishing between think brand and feel brand in consumer moral judgment. Further research could investigate other potential impact of the two dimensions, and possible antecedents of think/feel dimensions.

Managers can use the scale for assessment, planning, decision-making and tracking purposes. In addition, in the event of brand scandal or brand social responsibility activities, public-relations efforts can use the findings to earn or regain the trust of consumers, as this research demonstrates that marketers can shape (tailor) the feel or think dimensions of brand perception to change consumers’ moral judgment of the brands.

This research makes theoretical contribution to the brand anthropomorphism literature by differentiating the two dimensions and exploring the influence of anthropomorphism of consumer moral judgment.

With the advent of the information age, this paper aims to apply risk analysis theories to study the risk prevention mechanism of information disclosure, thus supporting the green electricity supply.

This paper conducts a comprehensive evaluation and analysis of the impact of power market transactions, power market operations and effective government supervision, so as to figure out the core risk content of power market information disclosure. Moreover, AHP-entropy method is adopted to weigh different indicators of information disclosure risks for the participants in the electricity market.

The potential reasons for information disclosure risk in the electricity market include insufficient information disclosure, high cost of obtaining information, inaccurate information disclosure, untimely information disclosure and unfairness of information disclosure.

Some suggestions and implications on risk prevention mechanism of information disclosure in the electricity market are provided, so as to ensure the green electricity supply and promote the electricity market reform in China.

This study aims to investigate a new circuitous minichannel cold plate (MCP) design involving flow fragmentation. The overall thermal performance and the temperature uniformity analysis are performed and compared with the traditional serpentine design. The substrate thickness and its thermal conductivity are varied to analyse the effect of axial-back conduction due to the conjugate nature of heat transfer.

The traditional serpentine minichannel is modified into five new fragmented designs with two inlets and two outlets. A three-dimensional numerical model involving the effect of conjugate heat transfer with a single-phase laminar fluid flow subjected to constant heat flux is solved using a finite volume-based computational fluid dynamics solver.

The minimum and maximum temperature differences are observed for the two branch fragmented flow designs. The two-branch and middle channel fragmented design shows better temperature uniformity over other designs while the three-branch fragmented designs exhibited better hydrodynamic performance.

MCPs could be used as an indirect liquid cooling method for battery thermal management of pouch and prismatic cells. Coupling the modified cold plates with a battery module and investigating the effect of different battery parameters and environmental effects in a transient state are the prospects for further research.

The study involves several aspects of evaluation for a conclusive decision on optimum channel design by analysing the performance plot between the temperature uniformity index, average base temperature and overall thermal performance. The new fragmented channels are designed in a way to facilitate the fluid towards the outlet in the minimum possible path thereby reducing the pressure drop, also maximizing the heat transfer and temperature uniformity from the substrate due to two inlets and a reversed-flow pattern. Simplified minichannel designs are proposed in this study for practical deployment and ease of manufacturability.

This study aims to investigate the influence of CEO’s only-child status on corporate social responsibility (CSR) practices. It seeks to extend the understanding of upper echelon theory by examining unexplored CEO characteristics and their impact on CSR decisions.

The paper uses manually collected CEO family information and Chinese Stock and Market Accounting Research data as a basis to examine the influence of CEOs’ early-life experiences on their engagement in CSR activities. The study applies attachment security theory from developmental psychology and uses upper echelon theory, particularly focusing on CEOs’ only-child status. A comparative analysis of philanthropic donations between CEOs who are only children and those who have siblings is conducted. The study also examines the moderating effects of corporate slack resources and CEO shareholdings.

Preliminary findings suggest that CEOs who are only children are more likely to engage in CSR compared to their counterparts with siblings. However, the difference in donation amounts between the two groups tends to attenuate with decreased slack resources and increased CEO shareholdings.

To the best of the authors’ knowledge, this research represents the first attempt to investigate being the only child in one’s family and the CSR-related decision of CEOs, which extends the upper echelon theory by introducing the family science theory into the management domain.