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The purpose of this study is to show how gradual strength degradation of metal beams under cyclic bending up to fatigue failure is simulated based on a new elastoplasticity model free of any yield criterion.

A new approach is proposed toward accurately and explicitly prescribing evolution of non-uniform stress distribution on beam cross-section under cyclic bending and, as such, gradual degradation of the bending strength can be directly determined.

Explicit results for the bending response in a whole cyclic process up to fatigue failure are obtained and the fatigue characteristic curve is for the first time simulated directly between the curvature amplitude and the cycle number to failure.

First, explicit and accurate determination of the non-uniform stress distribution on beam cross-section is achieved with asymptotic softening effects. Second, degradation of the bending strength can be directly deduced cycle by cycle. Finally, the relationship between the bending moment and the curvature is calculated using new and efficient numerical algorithms, thus bypassing usual time-consuming calculations with finite element procedures. Numerical results are presented and in good agreement with experimental data.

A new approach is proposed toward accurately matching any given realistic hardening and softening data from uniaxial tensile test up to failure and moreover, toward bypassing usual tedious implicit trial-and-error iterative procedures in identifying numerous unknown parameters.

Finite strain response features of metals with realistic hardening-to-softening transition effects up to eventual failure are studied for the first time based on the self-consistent elastoplastic J₂-flow model with the logarithmic stress rate. As contrasted with usual approximate and incomplete treatments merely considering certain particular types of hardening effects such as power type hardening, here a novel and explicit approach is proposed to obtain a complete form of the plastic-work-dependent yield strength over the whole hardening and softening range.

A new multi-axial evolution equation for both hardening and softening effects is established in an explicit form. Complete results for the purpose of model validation and prediction are presented for the finite strain responses of monotonic uniaxial stretching up to failure.

New finite strain elastoplastic equations are established with a new history-dependent variable equivalently in place of the usual plastic work. With these equations, a unified and accurate simulation of both gardening and softening effects up to failure is achieved for the first time in an explicit sense without involving usual tedious implicit trial-and-error iterative procedures.

The purpose of this paper is to find how leader humility affects employees’ constructive voice behavior toward supervisor (speaking up) and coworkers (speaking out) from an identification-based perspective, and seeks to verify the effectiveness of leader humility in the Chinese context.

Data were collected from 325 employees in four Chinese companies with two phases. In the first phase, the participants were asked to report the leader humility, their identification of their relations with the supervisor, and their identification with their organization. In the second phase, they were asked to report their voice behaviors toward their supervisors and coworkers.

The results indicate that leader humility strongly predicts both employees’ voice behaviors of speaking up and speaking out. Results further suggest that relational identification with the supervisor explains why leader humility promotes employees speaking up, while organizational identification explains why leader humility promotes employees speaking up and speaking out.

Managers with humility can successfully shape employees’ relational and organizational identifications, which in turn encourage their voice behaviors toward supervisors and coworkers. Hence, behaving humbly in working places could be an effective way for managers to promote organizational cohesion and creativity.

Although leader humility attracts much attention in both academia and practice, researchers have been primarily focusing on conceptual development and measurement issues, and empirical studies are rare. This is the first research connecting leader humility and employee proactive behaviors. Moreover, it takes an in-depth analysis of the constructive voice behaviors by differentiating them based on their targets.

Although green logistics has become a new focus of cooperation between government and enterprises under environmental constraints, how local governments formulate subsidy policies to effectively guide the green transformation of regional logistics and how to facilitate the reasonable cost-sharing are rather critical. This paper will deeply explore the dynamic process of the tripartite participation (government, platform, and logistics enterprises) in the selection of regional green logistics strategy, and reveal the evolutionary game relationship of the three parties.

To explore the dynamics involving the government, platform and logistics enterprises for the green logistic transformation, and reveal the evolutionary gaming among the three parties, based on the bounded rationality premise, this study constructs the tripartite asymmetric evolutionary game models, uses the stability theorem of differential equation to explore the evolution and stability strategy of the system in different cases and explicates the paths of influence on the tripartite behaviors via simulations.

Results of this study indicate that there exist stable equilibrium strategies among the three parties regarding the regional green logistics, and they are affected by different factors. The government's subsidy, subsidy intensity and the platform's cost-sharing proportion can generate positive effects, but the latter two can also impact negatively beyond the effective ranges. The findings provide a theoretical basis for local governments, platforms and logistics enterprises to formulate justifiable subsidy intensity and determine reasonable sharing proportion.

Firstly, considering the significant relevance of local government, it is included in the evolution model, and the tripartite game (among government, platform and enterprises) is explored; Secondly, by comparing the equilibrium results under different game conditions, this paper analyzes the evolution of each party's game strategy to achieve the optimal return under bounded rationality and the important factors determining the strategic selection; Finally, the key factor of platform cost sharing is involved, and to what extent the change of platform cost sharing ratio will influence the systematic stability is explored.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

This study is designed to address how rising individualism in emerging Asia changes consumer values and subsequent consumer behavior toward foreign brands. For this, we investigate consumer animosity (CA) and consumer cosmopolitanism (COS) in China and their impacts on consumer dispositions toward Japanese brands.

The study hypothesizes that CA and COS mediate the effects of consumer individualism and age on brand attitudes and purchase intentions. Online surveys were conducted with 421 consumers in China.

The results indicate that consumers with individualistic values show favorable dispositions toward Japanese brands because of weak CA and strong COS values. In addition, the study found that younger consumers also harbor weak CA and do not avoid Japanese brands because of it. However, younger consumers were not found to be more cosmopolitan than their older counterparts.

Our findings suggest that the modernization and individualization of a society can have impacts on consumer values in emerging Asia and that changes in consumer values among young and individualistic consumers can lead to increased preferences for foreign brands, especially brands from a country with historical animosity.

The purpose of this paper is to develop a statistical-based model to forecast future domestic water demand in the context of climate change, population growth and technological development in Yellow River.

The model is developed through the analysis of the effects of climate variables and population on domestic water use in eight sub-basins of the Yellow River. The model is then used to forecast water demand under different environment change scenarios.

The model projected an increase in domestic water demand in the Yellow River basin in the range of 67.85 × 10⁸ to 62.20 × 10⁸ m³ in year 2020 and between 73.32 × 10⁸ and 89.27 × 10⁸ m³ in year 2030. The general circulation model Beijing Normal University-Earth System Model (BNU-ESM) predicted the highest increase in water demand in both 2020 and 2030, while Centre National de Recherches Meteorologiques Climate Model v.5 (CNRM-CM5) and Model for Interdisciplinary Research on Climate- Earth System (MIROC-ESM) projected the lowest increase in demand in 2020 and 2030, respectively. The fastest growth in water demand is found in the region where water demand is already very high, which may cause serious water shortage and conflicts among water users.

The simple regression-based domestic water demand model proposed in the study can be used for rapid evaluation of possible changes in domestic water demand due to environmental changes to aid in adaptation and mitigation planning.

This paper aims to examine a large-scale typhoon response coordination, focusing on the emergency collaborative network (ECN) configuration and structural properties that characterized the 2018 Typhoon Mangkhut response operations in Shenzhen, China.

The response coordination of Typhoon Mangkhut was operationalized as a Shenzhen-based ECN established upon a six-week observation. A systematic content analysis of publicly available government documents and newspaper articles was conducted to identify participating organizations and interorganizational relationships built and sustained during and immediately after the disaster. Social network metrics at levels of the node, subgroup of nodes and whole network were utilized to examine network capacity, network homophily and network performance, respectively.

Results of the centrality analysis demonstrate that government agencies at municipal and district/county levels took central network positions while private and non-profit organizations were mostly positioned at the network periphery. The blocking analysis points to a salient homophily effect that participating organizations sharing similar attributes were more likely to connect with each other. A further investigation of whole network metrics and the small-world index reveals the highly fragmented and discontinued features of ECN, which may result in unsystematic coordination among organizational actors.

This paper is distinctive in examining the coordination structure among response organizations embedded in a centralized and monocentric governance system and, more importantly, how the structural characteristics can differ from that evidenced in a more decentralized and polycentric system.

This study aims to provide a solution of the power flow calculation for the low-voltage ditrect current power grid. The direct current (DC) power grid is becoming a reliable and economic alternative to millions of residential loads. The power flow (PF) in the DC network has some similarities with the alternative current case, but there are important differences that deserve to be further concerned. Moreover, the dispatchable distributed generators (DGs) in DC network can realize the flexible voltage control based on droop-control or virtual impedance-based methods. Thus, DC PF problems are still required to further study, such as hosting all load types and different DGs.

The DC power analysis was explored in this paper, and an improved Newton–Raphson based linear PF method has been proposed. Considering that constant impedance (CR), constant current (CI) and constant power (CP) (ZIP) loads can get close to the practical load level, ZIP load has been merged into the linear PF method. Moreover, DGs are much common and can be easily connected to the DC grid, so V nodes and the dispatchable DG units with droop control have been further taken into account in the proposed method.

The performance and advantages of the proposed method are investigated based on the results of the various test systems. The two existing linear models were used to compare with the proposed linear method. The numerical results demonstrate enough accuracy, strong robustness and high computational efficiency of the proposed linear method even in the heavily-loaded conditions and with 10 times the line resistances.

The conductance corresponding to each constant resistance load and the equivalent conductance for the dispatchable unit can be directly merged into the self-conductance (diagonal component) of the conductance matrix. The constant current loads and the injection powers from dispatchable DG units can be treated as the current sources in the proposed method. All of those make the PF model much clear and simple. It is capable of offering enough accuracy level, and it is suitable for applications in DC networks that require a large number of repeated PF calculations to optimize the energy flows under different scenarios.

Employees’ bootlegging innovation behavior is common and plays an important role in enterprise management. Based on the resource conservation theory and self-regulation theory, the purpose of this study is to explore the influence mechanism of leaders’ abusive supervision on employees’ bootlegging innovation behavior, with psychological safety as a mediator and mindfulness at workplace as a moderator.

Survey data were gathered from 591 employees’ self-assessment questionnaires in China. Hierarchical regression analysis was used to test the research model through SPSS and AMOS.

This study found that the leaders’ abusive supervision negatively affects employees’ bootlegging innovation behavior; employees’ psychological safety completely mediates the negative effect of leaders’ abusive supervision on employees’ bootlegging innovation behavior; and mindfulness at work moderates the influence of leaders’ abusive supervision on employee’ bootlegging innovation behavior, as well as the influence of leaders’ abusive supervision on employees’ psychological safety.

This study has significant implications in passive leadership that affect employees’ innovation. Authors found that leaders’ abusive supervise, mindfulness at workplace play a crucial role in employees’ bootleg innovation through psychological safety.

Theoretically, this study has enriched the antecedent research on employees’ bootlegging innovation behavior from the perspective of negative leadership behavior and employee psychology. And this study considered mindfulness at workplace as a boundary condition.