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The purpose of this paper is to show how shape analysis and quantitative characterization of fiber cross sections, with the aid of image analysis techniques, provide a quick, powerful approach to automated profiled fiber identification.

In this paper, an effective method of cross‐sectional shape characterization for profiled fiber identification is reported with extraction of the distance fluctuation curve of fiber cross‐sectional boundary to the centroid. By calculating their cross‐correlations using signal processing techniques, the authors tackle the problem of calibrating the starting points of fiber objects orientated arbitrarily in image successfully, which are difficult to deal with by means of image processing, to finish the normalization of distance fluctuation curves. For two fiber cross‐sections, the similarity degree of their boundary fluctuation curves normalized can effectively reflect the similarity degree of themselves.

Based on this, the method presented extracts the curves of all fiber cross‐sections in one sample, compares the similarity degrees between each other, and creates clusters to identify profiled fiber.

Experimental results validate that this curve can effectively characterize profiled fiber cross‐sectional contour for profiled fiber identification and the normalization method is feasible.

This paper seeks to propose a novel bearingless switched reluctance motor (BSRM).

The operating principle and structure characteristics of the proposed three‐phase 12/8‐pole BSRM is analyzed in detail. Finite element method‐based calculations are applied to a prototype and some important characteristics are obtained, including radial force, static torque, air‐gap magnetic flux density, and effect of control winding current on the torque, where magnetic saturation is taken into account by using a nonlinear B‐H curve.

On the basis of the simulated results, it can be concluded that the proposed BSRM presents an excellent performance in the suspending force and in the torque. The analyzed results show that the two control‐winding currents can effectively control the radial suspending forces and produce negligible effect on the motor torque, which is mainly produced by the main‐winding currents.

In this paper, a novel BSRM is proposed. Instead of the six sets of radial suspending control windings required by conventional three‐phases BSRM, the proposed structure requires only two sets of suspending control windings, regardless of the phase number, leading to a simpler power converter with less power switches, thus lowering the overall system cost.

Service robots are increasingly prevalent in the hospitality industry. While studies have explored the concept of service robot risk awareness (SRRA) – an employee’s perception of service robots posing a threat to human labor – the impact of SRRA on robot abuse and its emotional mechanism through which it affects employees remains unclear. This research leverages emotional appraisal theory to investigate the mediating role of fear of robots in the relationship between SRRA and robot abuse. Additionally, considering the influential role of leadership in shaping emotional appraisal, this study aims to examine the moderating impact of transformational leadership.

To test the proposed model, time-lagged survey data were collected from 283 employees working under 54 leaders in 18 hotels in China. The model was analyzed using multilevel modeling in Mplus 7.3.

At the individual level, SRRA indirectly increases robot abuse through the mediation of fear of robots. However, there is a cross-level moderation: the indirect relationship is alleviated when leaders exhibit high levels of transformational leadership.

This study pioneers the concept of robot abuse in hospitality and tourism settings. It extends emotional appraisal theory by highlighting the significant mediating role played by fear of robots. Furthermore, demonstrating how transformational leadership can mitigate the effects of SRRA offers valuable insights for leadership selection and training to facilitate the successful implementation of service robots.

服务机器人在酒店业中日益普及。虽然研究已探讨了服务机器人风险意识（SRRA）的概念——即员工对服务机器人构成对人力劳动的威胁感知, 但SRRA对辱虐机器人及其对员工的情绪机制的影响仍不清楚。本研究利用情绪评估理论调查了恐惧对SRRA与机器人滥用之间关系的中介作用。此外, 考虑到领导在塑造情绪评估中的重要作用, 本研究还考察了变革型领导力的调节影响。

为了测试提出的模型, 收集了来自中国18家酒店中54位领导下的283名员工的时滞调查数据。该模型使用Mplus 7.3中的多层建模进行分析。

在个体水平上, SRRA通过恐惧对机器人的中介作用间接增加了辱虐机器人。然而, 研究发现跨层次调节变量：当领导展现出较高水平的变革型领导力时, 间接关系得到缓解。

本研究首创了服务在酒店和旅游领域的辱虐机器人行为概念。它通过突出恐惧对机器人的重要中介作用, 扩展了情绪评估理论。此外, 展示了变革型领导如何缓解SRRA的影响, 为领导选聘和培训提供了有价值的见解, 促进了服务机器人的成功实施。

The purpose of this paper is to introduce the Futures Triangle 2.0, a methodological advancement of the Futures Triangle method (Inayatullah, 2008), which better integrates the original method with Scenario Planning by visually representing scenarios against the three dimensions of the Triangle, i.e. pulls, pushes and weights.

The paper explains the theoretical rationale behind the creation of the method, outlines the steps required to use it in a futures workshop or in a futures research project with a step-by-step procedure and reports a case study of its application in practice.

The Futures Triangle 2.0 encourages a deliberate and systematic discussion on the three dimensions of the Futures Triangle in each scenario and on whether scenarios differ in these attributes. The method allows the foresight researcher/practitioner to capture the valuable tensions between weights on the past on one hand and pushes of the present/pulls of the futures on the other hand, and to make sure that the scenarios differ substantially in these three attributes.

The method integrates the Futures Triangle and Scenario Planning in an intuitive, easily reproducible and visually pleasant graphical procedure.

In today’s digital age, news and social media are abuzz with ChatGPT and a myriad of advanced AI tools. Experts from disciplines like computer science and socioeconomics have discussed the profound transformations AI can bring. While certain industries have embraced AI, its penetration across all sectors remains uneven. Yet, even with this limited adoption, the psychological ramifications it presents for workplace employees are profound. Our study integrated social information processing and transactional stress theories to analyze the effect of automation brought by AI on job insecurity. Our study also considers whether moderating factors like supervisor–subordinate relationships and social media engagement can alleviate the adverse consequences of automation.

We empirically test our research hypotheses with longitudinal data from the US General Social Survey (GSS).

Using US General Social Survey data, our findings indicate that employees in industries with high automation potential are more susceptible to job insecurity. Interestingly, social media engagement appears to dampen this relationship, while the quality of the supervisor–subordinate relationship shows negligible impact.

This study provides valuable insights into the effects of automation potential and the role of social media engagement in coping with it, making a meaningful contribution to the existing literature in this area.

There has been a dramatic increase in the adoption of service robots in hotels, potentially replacing the human workforce. Drawing on Social Amplification of Risk Framework, this study aims to examine the moderating effect of transformational leadership on the indirect relationships between Gen Z employees’ tech-savviness and social skills on industry turnover intention via service robot risk awareness (SRRA).

This study collected two-wave time-lagged multilevel data of 281 frontline Gen Z hotel employees from 54 departments in China. Participants were asked to rate their tech-savviness, social skills and SRRA in the first survey. They rated their supervisor’s transformational leadership and industry turnover intention one week later.

Multilevel path analysis results showed SRRA mediates the negative indirect relationship of Gen Z employee’s tech-savviness and social skills on industry turnover intention. Transformational leadership weakened the positive effect of SRRA on industry turnover intention.

This study contributes to the growing literature on service robots by investigating the antecedents and outcomes of employees’ SRRA. To the best of the authors’ knowledge, it is one of the first empirical studies investigating the role of leadership to mitigate the negative consequences of employee’s SRRA. Managers can use the results of this study to implement training programs and ensure that employees and service robots successfully coexist in the workplace.

This study aims to explore why marine development and maritime security in Pakistan are significant and what the Chinese concerns are. Therefore, the objective of this research is to analyse a growing Pak–China bilateral interests, particularly at Gwadar, to achieve the geostrategic objectives of China–Pakistan Economic Corridor (CPEC).

The study adopts a qualitative means to discuss the significance of China’s ambitions towards the CPEC project concerning strategic deep-sea management and maritime regulations in the region, with a particular focus on the Gwadar Port.

The paper concludes that the Gwadar Port is a critical element for maritime security in the whole region. The study also provides an analysis of national and international, security and legal challenges associated with CPEC.

Most of the potential outcomes have already been discussed in public, though a limited academic discussion is available on the legal aspects. It is particularly so with regard to the development and capacity building in the maritime sector of Pakistan under this project. This study aims to explore why marine development and maritime security in Pakistan is significant and what the Chinese concerns are.

The novel bearingless switched reluctance motor (BSRM) is proposed recently, which is different from the conventional BSRM in the stator structure and suspension winding arrangement. The reduced number of suspension windings makes the novel BSRM much simpler, so that the control circuit and algorithm are greatly simplified when compared to those of the conventional BSRM. This paper for the first time proposes the novel BSRM's analytic model, including the mathematical relationships among the winding currents, rotor angle, radial forces, and motor torque, to further achieve the suspending forces and torque control. The paper aims to discuss these issues.

The magnetic equivalent circuit method is employed to obtain the self-inductances and mutual-inductances of the motor torque windings (main windings) and suspension windings (control windings). The straight flux paths are combined with the elliptical fringing flux paths to calculate the air-gap permeances, and the stored magnetic energy. Then, the mathematical expressions of radial forces and torque are derived. A novel BSRM prototype is analyzed through using the proposed analytical model and the finite element model. The results of both methods are compared to verify the proposed mathematical model.

The proposed mathematical model of the novel BSRM considering unsaturated magnetic circuits is verified by finite-element analysis results.

The mathematical model represents the situation of magnetic circuit unsaturated and is not suitable for the magnetic circuit saturation. It cannot be used to control the motor which is working in the deep magnetic circuit saturation region.

Building mathematical model is a necessary step for the motor's suspension and rotating control. The built model provides the fundamental for the preliminary control algorithm and experimental study of this novel BSRM.

For the first time, the novel BSRM's mathematical model is proposed. It provides necessary fundamental for the motor's further analysis, design, and suspending and rotating controls.

The purpose of this study is to investigate the application of non-destructive testing methods in measuring bearing oil film thickness to ensure that bearings are in a normal lubrication state. The oil film thickness is a crucial parameter reflecting the lubrication status of bearings, directly influencing the operational state of bearing transmission systems. However, it is challenging to accurately measure the oil film thickness under traditional disassembly conditions due to factors such as bearing structure and working conditions. Therefore, there is an urgent need for a nondestructive testing method to measure the oil film thickness and its status.

This paper introduces methods for optically, electrically and acoustically measuring the oil film thickness and status of bearings. It discusses the adaptability and measurement accuracy of different bearing oil film measurement methods and the impact of varying measurement conditions on accuracy. In addition, it compares the application scenarios of other techniques and the influence of the environment on detection results.

Ultrasonic measurement stands out due to its widespread adaptability, making it suitable for oil film thickness detection in various states and monitoring continuous changes in oil film thickness. Different methods can be selected depending on the measurement environment to compensate for measurement accuracy and enhance detection effectiveness.

This paper reviews the basic principles and latest applications of optical, electrical and acoustic measurement of oil film thickness and status. It analyzes applicable measurement methods for oil film under different conditions. It discusses the future trends of detection methods, providing possible solutions for bearing oil film thickness detection in complex engineering environments.

This paper aims to empirically investigate the dynamic interlinkages among globalization, digitalization and economic development in the top 75 most globalized countries from 2000 to 2019. The selection of the 75 most globalized developing countries is based on the overall scores of the KOF Globalization Index (2021).

The research design is based on secondary data collected from the World Bank (2021), the International Telecommunication Union (2021) and the KOF Globalization Index (2021). The study uses panel unit root tests followed by the panel cointegration techniques. Further, the estimation uses panel fully modified ordinary least squares and panel dynamic ordinary least squares methods.

The empirical results reveal that the effect of globalization on economic development is sensitive to different estimation procedures; in some cases, but not in every case, the effect is positive and significant. However, the positive and significant effect of digitalization on economic development is robust across all estimated models. Long-run equilibrium relationships and bidirectional causalities strongly affirm the nexus among globalization, digitalization and economic development, substantiating the interconnectedness among 75 developing economies.

The study reinstates that the forces of globalization and digitalization will be instrumental in shaping the selected most globalized economies in the long run. Adopting various econometric methodologies takes care of the time-specific and cross-sectional dynamics, as evident in the panel framework considered in this study. The empirical findings truly ascertain the theoretical synergy among the forces of globalization leading to more digitalization and economic development. This makes the empirical interplay highly conducive to framing long-term policies to expand the information communication network in terms of its access and reach.