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The water-lubricated hydrodynamic herringbone groove journal bearing (HGJB) is capable of running at high speed. However, when running at a low speed, it suffers from a low load-carrying capacity due to the weak hydrodynamic effect. To overcome this problem, this study proposes a hybrid water-lubricated HGJB and aims to investigate its dynamic characteristics.

A hybrid lubrication model applicable to the hybrid water-lubricated HGJB is established based on the boundary fitted coordinate system, which considers the turbulent, thermal and tilting effects, and the finite difference method is used to calculate the dynamic characteristics of the hybrid water-lubricated HGJB.

The result shows that the hybrid HGJB has larger dynamic coefficients and better system stability compared with the hydrodynamic HGJB when running at low speed. Furthermore, the stiffness of hybrid HGJB are mainly governed by the hydrodynamic effect rather than the hydrostatic effect when running at high speed.

The proposed hybrid water-lubricated HGJB shows excellent dynamic characteristics at either low speed or high speed; and the hybrid water-lubricated HGJB has a large load-carrying capacity when running at low speed and has a good dynamic stability when running at high speed.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0233/

This study aims to investigate the effects of environmental risk perception on the evaluation of socioeconomic development and subjective well-being in China.

A questionnaire survey was conducted, and data were collected from 408 participants of four major universities and government organizations in Changsha, China. Structural equation modeling (SEM) was used to analyze the collected data and to test the hypotheses with regard to the relationship among latent variables. Bayesian method was used as the statistical inference procedure.

Results show that environmental risk perception has a direct negative influence on perceived socioeconomic development and on subjective total well-being (i.e. both hedonic and eudaimonic well-being). The perceived socioeconomic development has a direct positive effect on the subjective total well-being; thus, it plays a partial mediation role between environmental risk perception and subjective total well-being.

Findings suggest that the environment protection act of the government and their contribution to socioeconomic development will significantly affect the total well-being of people. The empirical analysis is based on survey data; thus, this study may suffer the common problems of questionnaire survey.

Promoting pro-environment and health behaviors is important in developing a happy society.

This study demonstrates a significant negative effect of environmental risk perception on the total well-being of people according to SEM approach. This study determines two independent paths for government and policy makers to increase the total well-being of people in China, namely, increasing socioeconomic value to people and controlling and reducing environmental threats.

Automatic interpretation of Nominal Compounds is a crucial issue for many applications, for example, sentence understanding, machine translation, question-answering system and so forth. Many automatic interpretation models of Nominal Compounds use the strategies based on verbs or rules to obtain the interpretation of compounds. However, the performances of these models are still limited. The purpose of this paper is to propose an effective approach for automatic interpretation of Chinese nominal compounds.

The authors propose a top-down and bottom-up model based on rules and large-scale corpus for automatic interpretation of Nominal Compounds.

Experimental results demonstrate that the proposed model outperforms the state-of-the-art automatic interpretation model.

The paper is an up-to-date study of automatic interpretation for Nominal Compounds. It can help people understand the meaning of Nominal Compounds in reading. With a better understanding of Nominal Compounds, we can discover more hidden knowledge in them.

Power‐electronic systems have been playing a significant role in the integration of large‐scale wind turbines into power systems due to the fact that during the past three decades power‐electronic technology has experienced a dramatic evolution. This second part of the paper aims to focus on a comprehensive survey of power converters and their associated control systems for high‐power wind energy generation applications.

Advanced control strategies, i.e. field‐oriented vector control and direct power control, are initially reviewed for wind‐turbine driven doubly fed induction generator (DFIG) systems. Various topologies of power converters, comprising back‐to‐back (BTB) connected two‐ and multi‐level voltage source converters (VSCs), BTB current source converters (CSCs) and matrix converters, are identified for high‐power wind‐turbine driven PMSG systems, with their respective features and challenges outlined. Finally, several control issues, viz., basic control targets, active damping control and sensorless control schemes, are elaborated for the machine‐ and grid‐side converters of PMSG wind generation systems.

For high‐power PMSG‐based wind turbines ranging from 3 MW to 5 MW, parallel‐connected 2‐level LV BTB VSCs are the most cost‐effective converter topology with mature commercial products, particularly for dual 3‐phase stator‐winding PMSG generation systems. For higher‐capacity wind‐turbine driven PMSGs rated from 5 MW to 10 MW, medium voltage multi‐level converters, such as 5‐level regenerative CHB, 3‐ and 4‐level FC BTB VSC, and 3‐level BTB VSC, are preferred. Among them, 3‐level BTB NPC topology is the favorite with well‐proven technology and industrial applications, which can also be extensively applicable with open‐end winding and dual stator‐winding PMSGs so as to create even higher voltage/power wind generation systems. Sensorless control algorithms based on fundamental voltages/currents are suggested to be employed in the basic VC/DPC schemes for enhancing the robustness in the entire PMSG‐based wind power generation system, due to that the problems related with electromagnetic interferences in the position signals and the failures in the mechanical encoders can be avoided.

This second part of the paper for the first time systematically reviews the latest state of arts with regard to power converters and their associated advanced control strategies for high‐power wind energy generation applications. It summarizes a variety of converter topologies with pros and cons highlighted for different power ratings of wind turbines.

This study aims to examine the impact of intellectual capital (IC) and its three components (human, structural and relational capital) on corporation performance in the Chinese transportation industry. In addition, this study also investigates auditor characteristics (both Big-N and non-Big-N auditors) as a moderating role to examine the relationship between IC and corporate performance.

The data include 398 firm-year observations of transportation companies listed on the Shanghai and Shenzhen Stock Exchange from 2011 to 2020. Value-added intellectual coefficient (VAIC) model and its modified version (MVAIC) are applied to measure IC efficiency. Finally, the fixed effects regression analysis is used to mitigate the endogeneity issue. To investigate the moderating effect of auditor characteristics, the authors divide the samples based on the clients audited by Big-4 and non-Big-4 firms.

This study reveals that IC can enhance firm performance in China’s transportation sector. Overall, findings indicate that on the whole, IC has a positive and significant impact on corporation profitability and productivity. Human capital and physical and financial assets (capital employed) play highly important roles, but structural capital has no significant impact. The authors also found that auditor characteristics play an important moderating role in the connection between IC and corporate performance. For example, the positive association between IC and corporate performance is more pronounced when Big-4 auditors audit client firms. At the same time, the authors found a negative relationship between IC and firm performance when non-Big-4 auditors audit client firms.

Managers must understand that several components of IC have a total effect on corporate financial performance. Therefore, managers can dedicate more resources to such components based on the performance outcomes to emphasize their business strategies.

This study is the first empirical analysis of the impact of IC and its components on corporation performance in the transportation sector in China, an emerging market. Previous studies mainly focus on developed countries’ high technology and financial industries sectors but the impact of IC in transportation industry largely remains unknown. Thus, the present findings contribute to IC literature by revealing several underlying mechanisms by which the components of IC help achieve good firm performance.

The purpose of this paper is to investigate the impact of intellectual capital (IC) and its components (human, structural, relational and innovation capitals) on financial performance (FP) at different life cycle stages.

The study uses the data from Chinese manufacturing listed companies during 2014–2018. The modified value added intellectual coefficient (MVAIC) model is employed as the measurement of IC efficiency. Finally, multiple regression analysis is used to test the research hypotheses.

This study shows that the impact of IC on FP is different across life cycle stages. Specifically, at the birth stage, human capital (HC), structural capital (SC) and innovation capital (INC) have a positive impact on FP. At the growth and mature stages, all IC components contribute to FP improvement. HC and SC play an important role at the revival stage, while only HC positively affects FP at the decline stage.

The findings may help corporate managers to make optimal strategies to improve FP by effective utilization of IC resources in the complex and competitive business environment. Meanwhile, companies can invest in the core elements of IC at different stages of development, so as to maximize the contribution of IC to company value.

This is among the few studies to explore the impact of IC on FP of manufacturing listed companies in the Chinese context from the perspective of life cycle. It also makes novel contributions in measuring IC by the MVAIC model with the inclusion of relational capital and INC that are largely neglected in previous research.

We reviewed U.S. federal and state sexual harassment court cases involving a prior workplace romance between the plaintiff and alleged harasser. Results of our content analysis show that, unlike employees’ decisions, judges’ decisions can be predicted from legal but not ethically salient extralegal case features. Hence, when compared to prior research, our study reveals the following discrepancy: judges follow a traditional legal model, whereas employees follow an ethical model when making decisions about romance‐harassment cases. Our study also reveals that the mere presence (versus absence) of a prior romance reduces the likelihood of a plaintiff’s success in a harassment case. We discuss implications for management practice and research from the perspective of legal and ethical decision making.

The microcutting performance of the ¹⁰B/Al composite is significantly poor because of the existence of hard boron particles. The effects of cutting parameters, including uncut chip thickness and cutting speed, on the material removal mechanism and surface generation are investigated to improve the surface quality.

The 2D finite element model, which includes a rigid cutting tool, a reinforced phase, a matrix and a dense layer, is established. The effects of uncut chip thickness on material removal mechanism and surface generation are analyzed from a probabilistic perspective. The relationship between the uncut chip thickness and the probability in which the machined surface will have a better surface quality is constructed. A Gaussian distribution formula is applied to describe the machined surface quality.

Two representative particle-removal modes, namely, cutting-through and pulling-out modes, are observed. For cutting-through mode, when the relative cutting location is small, better surface quality is obtained. For pulling-out mode, the quality of the machined surface gradually improves because the further increase of the relative cutting location reduces the height of the generated pit and scratches. The microcutting at high cutting speed tends to suppress the scratch phenomenon. The best surface quality will be obtained at small uncut chip thickness and high cutting speed.

The surface quality generated in microcutting of the ¹⁰B/Al composite can be improved by optimizing the cutting parameters and controlling the particle-removal modes based on the proposed Gaussian distribution formula.

Purpose: In this technologically advanced era, it is crucial to understand how consumers adopt innovations so that producers and marketers can cater to these needs effectively. While existing technology adoption models have good explanatory power, a hybrid model must account for newer contexts.

Need for the Study: Most technology adoption papers in extant literature deal with the phenomenon’s functional, environmental and cognitive aspects. However, a mindset-oriented approach is largely absent from current studies. Mindsets are core beliefs people have about the malleability of human traits and characteristics that ultimately shape consumer behaviour. Investigating the adoption of such technologies through a deeper psychological lens will advance the field substantially.

Methodology: This conceptual paper utilised a literature review and theoretical integration to present a novel technology adoption model. The literature review of secondary data helped identify extant gaps, while academic integration of major concepts helped fill said gaps.

Findings: Based on the existing gaps in the literature, this study conceptualised a novel technology adoption model based on the foundation of Mindset Theory. Overall, relevant constructs, variables and scales have been presented along with future research propositions.

Practical Implications: From a global perspective, the findings of this chapter will enable marketers and practitioners to understand consumer adoption of new-age technologies. Producers of such technologies will also be able to cater to consumers more efficiently as a result of this study.

A densely distributed network radar system compensates for the disadvantages of sparse radars and poses a significant threat to low-altitude penetration by an unmanned combat aerial vehicle (UCAV). Unlike previous studies, this paper aims to consider radar blind areas and proposes a rapid online method for planning low-altitude penetration paths.

First, the optimization problem coupling digital elevation map (DEM), radar detection probability model and nonholonomic UCAV kinematic model is established. Second, an online solution framework of penetration path planning is constructed. An intervisibility method and map scaling are proposed to generate a detection probability map (DPM). Through completeness and consistency analysis, an adaptive hybrid A* algorithm with fast local replanning strategy is proposed to search a path that takes into account time-consuming, detection probability under nonholonomic constraints. Finally, three scenarios of multiple known, pop-up and vanished static radars are simulated using C++. The computational performance is compared and analyzed.

The results showed that the proposed online method can generate low-detection-probability penetration paths within subseconds.

This paper provides a new online method to plan UCAV penetration trajectory in military and academic contexts.