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The purpose of this paper is to propose an new online path planning method for porcine belly cutting. With the proliferation in demand for the automatic systems of pork production, the development of efficient and robust meat cutting algorithms are hot issues. The uncertain and dynamic nature of the online porcine belly cutting imposes a challenge for the robot to identify and cut efficiently and accurately. Based on the above challenges, an online porcine belly cutting method using 3D laser point cloud is proposed.

The robotic cutting system is composed of an industrial robotic manipulator, customized tools, a laser sensor and a PC.

Analysis of experimental results shows that by comparing with machine vision, laser sensor-based robot cutting has more advantages, and it can handle different carcass sizes.

An image pyramid method is used for dimensionality reduction of the 3D laser point cloud. From a detailed analysis of the outward and inward cutting errors, the outward cutting error is the limiting condition for reducing the segments by segmentation algorithm.

Consumers and businesses are becoming increasingly conscious of sustainable business practices and are often willing to pay a premium for responsibly sourced and manufactured products. Many countries and organizations have implemented regulations and standards for sustainability and companies face penalties or are barred from exporting for not meeting the requirements. Rooted in the resource-based view theory, this study aims to test a moderated mediation model to improve the sustainability performance of exporting firms.

Textile firms generating more than 25% of export revenues were targeted for this research. The data collected from 245 middle management-level employees were tested for reliability and validity. The structural equation modelling in AMOS 26 was used to test hypotheses.

Organizational readiness for green innovation (ORGI) has a direct positive effect on sustainability performance. The mediation analysis implies that ORGI translates into sustainability performance through improvement in green innovation performance. The moderating effect of knowledge integration highlights the importance of being prepared internally and actively seeking and incorporating external knowledge to improve green innovation performance.

The findings offer a solid foundation for informed decision-making, policy development and strategies to improve sustainability performance while aligning with the global nature of the textile industry and its inherent challenges. The proposed model and practical implications guide policymakers and managers of exporting firms to foster a culture of green innovation to leverage the effect of their readiness for green innovation on sustainability performance.

This paper aims to solve the problem of the inability to apply learning methods for robot motion skills based on dynamic movement primitives (DMPs) in tasks with explicit environmental constraints, while ensuring the reliability of the robot system.

The authors propose a novel DMP that takes into account environmental constraints to enhance the generality of the robot motion skill learning method. First, based on the real-time state of the robot and environmental constraints, the task space is divided into different regions and different control strategies are used in each region. Second, to ensure the effectiveness of the generalized skills (trajectories), the control barrier function is extended to DMP to enforce constraint conditions. Finally, a skill modeling and learning algorithm flow is proposed that takes into account environmental constraints within DMPs.

By designing numerical simulation and prototype demonstration experiments to study skill learning and generalization under constrained environments. The experimental results demonstrate that the proposed method is capable of generating motion skills that satisfy environmental constraints. It ensures that robots remain in a safe position throughout the execution of generation skills, thereby avoiding any adverse impact on the surrounding environment.

This paper explores further applications of generalized motion skill learning methods on robots, enhancing the efficiency of robot operations in constrained environments, particularly in non-point-constrained environments. The improved methods are applicable to different types of robots.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.

First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.

(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.

The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.

The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.

The purpose of this paper is to explore and disseminate knowledge about quantum-inspired computing technology's potential to solve complex challenges faced by the operational agility capability in Industry 4.0 manufacturing and logistics operations.

A multi-case study approach is used to determine the impact of quantum-inspired computing technology in manufacturing and logistics processes from the supplier perspective. A literature review provides the basis for a framework to identify a set of flexibility and agility operational capabilities enabled by Industry 4.0 Information and Digital Technologies. The use cases are analyzed in depth, first individually and then jointly.

Study results suggest that quantum-inspired computing technology has the potential to harness and boost companies' operational flexibility to enhance operational agility in manufacturing and logistics operations management, particularly in the Industry 4.0 context. An exploratory model is proposed to explain the relationships between quantum-inspired computing technology and the deployment of operational agility capabilities.

This is study explores the use of quantum-inspired computing technology in Industry 4.0 operations management and contributes to understanding its potential to enable operational agility capability in manufacturing and logistics operations.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

The aim of this study is to examine the nature and determinants of stock market integration between India and other Asia–Pacific countries (Malaysia, Hong Kong, Singapore, South Korea, Japan, China, Indonesia, the Philippines, Thailand and Taiwan) over the period 1991–2021.

Unit root tests, the dynamic conditional correlation-Glosten Jagannathan and Runkle-generalized autoregressive conditional heteroscedasticity (DCC-GJR-GARCH), pooled ordinary least squares (OLS) regression and random effects models are employed for the analysis.

The empirical results show that the DCC between each pair of sample countries is less than 0.5, indicating weak ties between the pairs of sample countries. Also, the DCC between India and other Asia–Pacific stock markets is positive and low, implying low level of integration. The correlation between India and China stock markets is found to be the highest, implying significant level of integration. The main reason for it would be strong economic linkages and bilateral trade relationship between India and China. Moreover, gross domestic product (GDP), interest rate (IR), consumer price index (CPI)-inflation and money supply (MS) differentials are the major driver of stock market integration between India and other Asia–Pacific countries.

The findings of the study have important implications for investors, portfolio managers and policymakers. It is found that the DCC between India and other Asia–Pacific countries (considered in the study) except China is low, which indicates weak ties between the pairs of sample countries. This implies that the Indian stock market provides good investment opportunities for foreign investors. Also, investors and portfolio managers can attain more diversified benefits and can minimize country risk by investing across Asia–Pacific countries. Further, knowledge about the factors that integrate the Indian stock market with the other Asia–Pacific stock markets will help policymakers frame suitable economic and financial stabilization policies.

This study contributes to the extant literature: first, by examining the linkages of Indian stock market with other Asia–Pacific countries; second, although previous studies confirmed the existence of linkages among the various stock markets, few researchers pay attention to the factors driving the process of stock market integration. This study provides additional evidence by examining the significant macroeconomic factors driving the process of such integration in the Asia–Pacific region considered under the study.

The purpose of this study is to examine the formation of sustainable development competencies (SDCs) in future primary school teachers during English for specific purposes classes, and to assess the correlation between English proficiency and the development of SDCs, including Collaboration, Strategic thinking, Critical thinking, Modelling sustainable behaviour, Systems thinking and Future thinking.

The research experiment involved the application of content and language integrated learning and facilitation methods in three higher education institutions in Ukraine. The students’ level of English language proficiency was assessed based on the results of the online Cambridge English Language Assessment test, while the level of SDC formation was measured using research methods adapted to the Ukrainian context.

The experiment revealed positive changes in the levels of SDCs and English language proficiency through integrated learning and the application of facilitation methods.

The study established a correlation between the level of English language proficiency and the formation of competencies, such as Collaboration, Strategic thinking, Critical thinking, Modelling sustainable behaviour, Systems thinking and Future thinking, all of which are vital for sustainable development.

This study examines the use of dark humor in brand-to-brand communications on social media and its impact on consumers' brand perceptions. In particular, this study looks at roasting messages in which a brand humorously insults its peers.

The authors used a sampling method to recruit 286 participants from the United States. They employed an ANOVA and Tukey's post hoc analysis to test the hypotheses, as well as Hayes' PROCESS to test the mediation and moderation effects, including Johnson–Neyman procedure.

The authors found that not all customers find roasting messages funny. Rather, consumers' personality and age will influence their perceived humor of the messages and their brand evaluations. Customers who are young and extroverted are likely to believe roasting messages to be funny. They thus perceive the brand to be cooler and more sincere when using such a communication approach, compared to when the brand neutrally interacts with others. Meanwhile, brands may find less success with old and introverted customers.

This research sheds light on how the consumers' perception of humor in a roasting type of brand-to-brand communication has an impact on consumers' psychological perceptions of brand coolness and brand sincerity. To guide practitioners, it explored how the interaction between a consumer's personality and age moderates the aforementioned relationship.