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The developed plasto-elastohydrodynamic lubrication (PEHL) model is used to demonstrate the permanent change of macro morphology by critical high local stress at micro asperities in contact, which may further affect the fluid-film characteristics.

Geometric morphology is integrated into the PEHL model to elucidate the fluid-film properties governed by both macro- and micromorphologies.

Results show the model, accounting for combination of elastic and plastic deformations, realistically reveals fluid film distribution affected by the significant pressure highly concentrated within surface micro roughness interaction. The designed macroscopic textured surface mitigates the fluid film rupture phenomenon and prevents accumulated wear degradation from plastic deformation.

The PEHL model takes into account both elastic and plastic deformations and realistically reveals the fluid film distribution affected by large pressures that are highly concentrated in surface micro-roughness interactions. The macro-textured surfaces are designed to mitigate fluid film rupture phenomena and prevent cumulative wear caused by plastic deformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0170/

Gunung Mulu National Park (GMNP) is one of the two protected areas with UNESCO World Heritage Site (WHS) status in Malaysia. Until now, this area can only be accessed by tourists via air and water transportation only. Recently, the government has proposed the construction of a road connecting GMNP to several areas, including Miri City through a high-impact infrastructure project. However, this project might instigate the potential benefits and challenges in terms of tourism development and community well-being. As custodians of the park, their support for this initiative needs to be dismantled so that the management of the national park can still be implemented holistically and does not jeopardise the current UNESCO status of WHS. WHS is UNESCO-designated area of cultural, historical, scientific, or other significant value, legally safeguarded by international agreements, and preserved for the benefit of future generations due to its exceptional value to humanity. Thus, this study aims to examine challenges and socioeconomic impacts of the proposed road among key informants' perspectives at Long Terawan Village, Long Iman Village, Batu Bungan Village and GMNP Headquarters. The study was conducted via in-depth interviews with 10 community members residing in the settlement, including a tribal chief, boatman, lodging operator, park guide and farmer, all of whom are professionals and representatives of the local community. They were designated as key informants on account of their extensive engagement and development within the community. Through a thematic analysis, their perspectives on the proposed roads to be built in the area were elucidated. The study offers pragmatic understanding of socioeconomic impact assessment, which could inform strategic decision-making by incorporating information regarding potential benefits and challenges of the proposed road construction to an isolated protected area.

The paper follows Jason Cope's (2011) vision of a holistic perspective on the failure-based learning process. By analyzing the research since Cope's first attempt, which is often fragmentary in nature, and providing novel empirical insights, the paper aims to draw a new comprehensive picture of all five phases of entrepreneurial learning and their interplay.

The study features an interpretative phenomenological analysis of in-depth interviews with 18 failed entrepreneurs. Findings are presented and discussed in line with experiential learning theory and Cope's conceptual framework of five interrelated learning timeframes spanning from the descent into failure until re-emergence.

The study reveals different patterns of how entrepreneurs experience failure, ranging from abrupt to gradual descent paths, different management and coping behaviors, and varying learning effects depending on the new professional setting (entrepreneurial vs non-entrepreneurial). Analyzing the entrepreneurs' experiences throughout the process shows different paths and connections between individual phases. Findings indicate that the learning timeframes may overlap, appear in different orders, loop, or (partly) stay absent, indicating that the individual learning process is even more dynamic and heterogeneous than hitherto known.

The paper contributes to the field of entrepreneurial learning from failure, advancing Cope's seminal work on the learning process and -contents by providing novel empirical insights and discussing them in the light of recent scientific findings. Since entrepreneurial learning from failure is a complex and dynamic process, using a holistic lens in the analysis contributes to a better understanding of this phenomenon as an integrated whole.

This study aims to investigate the integration of blockchain technology into the food supply chain within the restaurant industry. It focuses on how blockchain can be applied to enhance transparency and trust in tracking food sources, ultimately impacting customer satisfaction.

A service design workshop (Study 1) and three between-subjects experiments (Studies 2–4) were conducted.

Results indicate that blockchain adoption significantly improves traceability and trust in the food supply chain. This improvement in turn enhances customer satisfaction through perceived improvements in food safety, quality and naturalness. This study also notes that the effects of blockchain technology vary depending on the type of restaurant (casual or fine dining) and its location (tourist destinations or residential areas).

The findings offer practical insights for restaurant owners, technology developers and policymakers. Emphasizing the benefits of blockchain adoption, this study guides decision-making regarding technology investments for enhancing customer service and satisfaction in the hospitality sector.

This research contributes novel insights to the field of technology innovation in the hospitality industry. It extends the understanding of signaling theory by exploring how blockchain technology can serve as a tool for signal transmission in restaurant food supply chains.

Recently, there has been a shift toward the embodied energy assessment of buildings. However, the impact of material service life on the life-cycle embodied energy has received little attention. We aimed to address this knowledge gap, particularly in the context of the UAE and investigated the embodied energy associated with the use of concrete and other materials commonly used in residential buildings in the hot desert climate of the UAE.

Using input–output based hybrid analysis, we quantified the life-cycle embodied energy of a villa in the UAE with over 50 years of building life using the average, minimum, and maximum material service life values. Mathematical calculations were performed using MS Excel, and a detailed bill of quantities with >170 building materials and components of the villa were used for investigation.

For the base case, the initial embodied energy was 57% (7390.5 GJ), whereas the recurrent embodied energy was 43% (5,690 GJ) of the life-cycle embodied energy based on average material service life values. The proportion of the recurrent embodied energy with minimum material service life values was increased to 68% of the life-cycle embodied energy, while it dropped to 15% with maximum material service life values.

The findings provide new data to guide building construction in the UAE and show that recurrent embodied energy contributes significantly to life-cycle energy demand. Further, the study of material service life variations provides deeper insights into future building material specifications and management considerations for building maintenance.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This paper aims to propose a stable and precise recognition and pose estimation method to deal with the difficulties that industrial parts often present, such as incomplete point cloud data due to surface reflections, lack of color texture features and limited availability of effective three-dimensional geometric information. These challenges lead to less-than-ideal performance of existing object recognition and pose estimation methods based on two-dimensional images or three-dimensional point cloud features.

In this paper, an image-guided depth map completion method is proposed to improve the algorithm's adaptability to noise and incomplete point cloud scenes. Furthermore, this paper also proposes a pose estimation method based on contour feature matching.

Through experimental testing on real-world and virtual scene dataset, it has been verified that the image-guided depth map completion method exhibits higher accuracy in estimating depth values for depth map hole pixels. The pose estimation method proposed in this paper was applied to conduct pose estimation experiments on various parts. The average recognition accuracy in real-world scenes was 88.17%, whereas in virtual scenes, the average recognition accuracy reached 95%.

The proposed recognition and pose estimation method can stably and precisely deal with the difficulties that industrial parts present and improve the algorithm's adaptability to noise and incomplete point cloud scenes.

In the past 10 years, the scale of running events in China has increased dramatically, and the forms of running events have also become rich and diverse. Running is not only a social phenomenon but also a historical and cultural phenomenon as an organic part of human culture with its own sociological values in China. This chapter offers insight into the development of Chinese running culture and how this has emerged from ancient and modern Chinese running cultures based on Foucault's disciplinary power theory, biopower and the technologies of the self. This chapter argues that running culture in China constructs the subjectivity of the Chinese runners under the joint action of the technologies of power and the technologies of the self. The findings acknowledge how Chinese Runners present and express themselves by showing a ‘sense of presence’. Runners illustrate the implicit or explicit meaning and value of a particular way of life through running. Runners regard running as the technology of the self for self-expression and self-creation so that individuals can control their bodies and soul, thoughts, behaviours and ways of existence. Emerging technologies of power provide possibilities for the production of running culture in China, and the current policy under the technologies of power meets the needs of runners. In Chinese running culture, power was not oppressive but productive.

The paper focuses on the issue of manual rebar-binding tasks in the construction industry, which are marked by high labor intensity, high costs and inefficient operations. The rebar-binding robots that are currently available are not fully mature. Most of them can only bind one or two nodes in one position, which leads to significant time wastage in movement. Based on a new type of rebar-binding robot, this paper aims to propose a new movement and binding control that reduces manpower and enhances efficiency.

The robot is combined with photoelectric sensors, travel switches and other sensors. It is supposed to move accurately and run in a limited area on the rebar mesh through logical judgment, speed control and position control. Machine vision is used by the robot to locate the rebar nodes and then adjusts the binding-gun position to ensure that multiple rebar nodes are bound sequentially.

By moving on the rebar mesh with accuracy, the robot meets the positioning accuracy requirements of the binding module, with experimental testing accuracy within 5 mm. Furthermore, its ability to bind four rebar nodes in one place results in a high efficiency and a binding effect that meets building standards.

The innovative design of the robot can adapt itself to the rebar mesh, move accurately to the target position and bind four nodes at that position, which reduces the number of movements on the mesh. Repetitive and heavy rebar-binding tasks can be efficiently completed by the robot, which saves human resources, reduces worker labor intensity and reduces construction overhead. It provides a more feasible and practical solution for using robots to bind rebar nodes.

This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance.

First, the working space is divided into a force control subspace and a position subspace, the force control subspace adopts the position impedance control strategy. At the same time, the contact force model between the robot and the surface is analyzed in this space. Second, based on the traditional position impedance, the model reference adaptive control is introduced to provide an accurate reference position for the impedance controller. Then, the BP neural network is used to adjust the impedance parameters online.

The experimental results show that compared with the traditional PI control method, the proposed method has a higher flexibility, the dynamic response accommodation time is reduced by 7.688 s and the steady-state error is reduced by 30.531%. The overshoot of the contact force between the end of robot and the workpiece is reduced by 34.325% comparing with the fixed impedance control method.

The proposed control method compares with a hybrid force/position based on PI control method and a position fixed impedance control method by simulation and experiment.

The adaptive variable impedance control method improves accuracy of force tracking and solves the problem of the large surfaces with robot grinding often over-polished at the protrusion and under-polished at the concave.