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The paper aims to fabricate shape memory composites using polylactic acid (PLA) matrix and graphite. Shape memory polymers are a promising family of materials for biomedical applications because of their favourable mechanical properties, fast reactions and good biocompatibility. For most SMPs, however, achieving controllable sequential shape change is challenging.

In the present work, 4D printing technology is used to fabricate shape memory composites using polylactic acid (PLA) matrix and graphite. A comparative study of pure PLA and graphite’s different weight % composition has been done.

By carefully managing the deformation state, PLA with graphite shape memory composites produced controllable sequential deformation with an amazing shape memory effect. Surface morphology, thermal properties, melt flow index and shape recovery tests have all been carried out to assess the qualities of manufactured samples.

This is a one-of-a-kind to fabricate shape memory composites using graphite and a PLA matrix. Thus, this research attempts to deliver the possible use of PLA/graphite composites fabricated using 4D printing in robotics and biomedical devices.

This study aims to investigate profoundly the protection of oil painting from deterioration using molybdenum trisulphide quantum dots (MoS3 QDs) against microbe, dirt accumulation and ultraviolet (UV) degradation.

The protection of painting against different deterioration factors necessitates the sustainable methods and advanced techniques. Scanning electron microscopy and transmission electron microscopy have been used to investigate the morphological structure of the painting and MoS3 QDs, respectively, and optical microscopy was used to examine antibacterial activity of MoS3 QDs towards different types of bacteria. To investigate the protection of painting against deterioration, the Fourier transform IR spectroscopy (FTIR) was used to investigate the paintings left in open air for a year. Chemical composition and crystal structure of MoS3 QDs have been studied using X-ray diffraction and X-ray photoelectron spectroscopy analysis, respectively.

The addition of MoS3 nanoparticles into painted coatings enhances the durability of linseed oil-based paintings toward UV ageing regarding the change in colour which confirmed by FTIR analysis. The protection of oil painting opposed to various deterioration factors was developed by involving of MoS3 QDs in the coating of the painting. Antibacterial effect of MoS3 QDs was tested against different types of bacteria such as Pseudomonas aeruginosa confirming that the MoS3 QDs involved in the coatings of oil paintings produces a high protection layer for the paintings against several microbial attacks. In addition, coatings containing MoS3 QDs reduce the accumulation of dirt on oil paintings when subjected to open air for a year.

The novel MoS3 QDs was used to form a protective and transparent coating layer for the oil painting to overcome the deterioration, displays the promising protection and can be applied for different oil paintings.

This study aims to investigate whether and how artificial intelligence (AI) awareness affects work withdrawal.

This survey garners participation from a total of 305 hotel employees in China. The proposed hypotheses are examined using Hayes’s PROCESS macro.

The results indicate that AI awareness could positively affect work withdrawal. Negative work-related rumination and emotional exhaustion respectively mediate this relationship. Furthermore, negative work-related rumination and emotional exhaustion act as chain mediators between AI awareness and work withdrawal.

Given the growing adoption of AI technology in the hospitality industry, it is imperative that managers intensify their scrutiny of the psychological changes experienced by frontline service employees and allocate more resources to mitigating the impact of AI on their work withdrawal.

This study contributes to the burgeoning literature on AI by elucidating the chain mediating roles of negative work-related rumination and emotional exhaustion. It also makes a significant forward in examining mediating mechanisms, notably the chain-mediated mechanism, through which AI awareness impacts employee outcomes.

Mobile robots with independent wheel control face challenges in steering precision, motion stability and robustness across various wheel and steering system types. This paper aims to propose a coordinated torque distribution control approach that compensates for tracking deviations using the longitudinal moment generated by active steering.

Building upon a two-degree-of-freedom robot model, an adaptive robust controller is used to compute the total longitudinal moment, while the robot actuator is regulated based on the difference between autonomous steering and the longitudinal moment. An adaptive robust control scheme is developed to achieve accurate and stable generation of the desired total moment value. Furthermore, quadratic programming is used for torque allocation, optimizing maneuverability and tracking precision by considering the robot’s dynamic model, tire load rate and maximum motor torque output.

Comparative evaluations with autonomous steering Ackermann speed control and the average torque method validate the superior performance of the proposed control strategy, demonstrating improved tracking accuracy and robot stability under diverse driving conditions.

When designing adaptive algorithms, using models with higher degrees of freedom can enhance accuracy. Furthermore, incorporating additional objective functions in moment distribution can be explored to enhance adaptability, particularly in extreme environments.

By combining this method with the path-tracking algorithm, the robot’s structural path-tracking capabilities and ability to navigate a variety of difficult terrains can be optimized and improved.

Drawing on the tenets of institutional theory, the purpose of this study is to examine the impact of Confucianism on technology for social good, while also considering the moderating influence of extrinsic informal institutions (foreign culture) and intrinsic formal institutions (property rights).

This study constructs a comprehensive database comprising 9,759 firm-year observations in China by using a sample of Chinese A-share listed firms from 2016 to 2020. Subsequently, the hypotheses are examined and confirmed, with the validity of the results being upheld even after conducting endogenous and robustness tests.

The findings of this study offer robust and consistent evidence supporting the notion that Confucianism positively affects technology for social good through both incentive effect and normative effect. Moreover, this positive influence is particularly prominent in organizations with limited exposure to foreign culture and in nonstate-owned enterprises.

The findings contribute to the literature by fostering a deep understanding of technology for social good and Confucianism research, and further provide a nuanced picture of the role of foreign culture and property rights in the process of technology for social good in China.

The silicone modifications of two-component epoxy resin coatings are commonly built on epoxy resins rather than on epoxy curing agents. The silicone-modified epoxy curing agent system is rarely reported yet. This study aims to prepare the polysiloxane (PS)-modified waterborne epoxy coatings based on aqueous curing agents technology.

Waterborne epoxy curing agents with different contents of terminal epoxy PS were synthesized by reacting with triethylenetetramine, followed by incorporating of epoxy resin (NPEL-128) and polyethylene glycol diglycidyl ether. The waterborne epoxy coatings were prepared with the above curing agents, and their performance was investigated through thermogravimetric analysis, scanning electron microscopy, mechanical characterization, gloss measurement, chemical resistance test and ultraviolet (UV) aging experiment.

The results showed that the epoxy coating prepared by silicon-modified curing agent has higher gloss, better chemical resistance and UV resistance than the coating from unmodified curing agent with terminal epoxy PS and commercially available waterborne epoxy curing agent (Aradur 3986), as well as the competitive mechanical properties and heat resistance. Reduced water absorption on fibrous paper was also obtained with the help of silicon-modified curing agent.

These findings will be valuable for resin researchers in addressing the modification issues about waterborne epoxy resin and curing agent.

As the demand for human–robot collaboration in manufacturing applications grows, the necessity for collision detection functions in robots becomes increasingly paramount for safety. Hence, this paper aims to improve the existing method to achieve efficient, accurate and sensitive robot collision detection.

The external torque is estimated by momentum observers based on the robot dynamics model. Because the state of the joints is more accessible to distinguish under the action of the suppression operator proposed in this paper, the mutated external torque caused by joint reversal can be accurately attenuated. Finally, time series analysis (TSA) methods can continuously generate dynamic thresholds based on external torques.

Compared with the collision detection method based only on TSA, the invalid time of the proposed method is less during joint reversal. Although the soft-collision detection accuracy of this method is lower than that of the symmetric threshold method, it is superior in terms of detection delay and has a higher hard-collision detection accuracy.

Owing to the mutated external torque caused by joint reversal, which seriously affects the stability of time series models, the collision detection method based only on TSA cannot detect continuously. The consequences are disastrous if the robot collides with people or the environment during joint reversal. After multiple experimental verifications, the proposed method still exhibits detection capabilities during joint reversal and can implement real-time collision detection. Therefore, it is suitable for various engineering applications.

In recent years, augmented reality (AR) has shown its potential to assist various construction activities. Its use commonly requires additional refinement to be integrated into the building information modeling (BIM) process. Nevertheless, few studies have investigated AR implementation in BIM-enabled projects because of numerous challenges related to its implementation. This study aims to investigate the implementation of AR in construction and identify the critical mechanisms for implementing BIM-AR successfully.

A mixed methodology was adopted for this study. First, this work presents a bibliometric analysis covering articles obtained from Scopus database published between 2000 and 2022. A sample size of 65 research papers pertinent to AR in construction was analyzed using VOSviewer software. Second, a participatory case study was conducted for a BIM-enabled project in China to gain insight into how BIM-AR implementation in construction is achieved.

The findings from the bibliometric analysis show an increasing interest in AR research within construction. The results indicate that AR research focuses on four clusters: real-time communication, project management, construction activities and education. Findings from the case study provide an empirical experience of AR application scenarios in a BIM-enabled project. Concomitantly, 15 critical success factors that influence BIM-AR implementation were finally identified and demonstrated.

This study provides a rich insight into the understanding and awareness of implementing AR. First, the findings are beneficial to construction practitioners and researchers because they provide a concentrated perspective of AR for emerging activities in the construction industry. Second, the results obtained from the case study could provide a useful guide for effectively implementing AR in a BIM-enabled construction project. Overall, this study may stimulate further research on AR-related studies in construction, such as BIM integration, factor analysis and construction education.

Over the last 2 decades, supply chain sustainability research has become a highly dynamic and fruitful study area. This field has garnered significant attention due to its potential to reshape decision-making processes within supply chains. At the same time, the practical side of supply chain operations remains intensely competitive in today’s business landscape. Furthermore, the current academic research aims to outline effective strategies for achieving sustainability across supply chains, particularly in the manufacturing sector. In response to these challenges, this research has conducted an integrated multi-criteria decision-making approach to evaluate sustainable supply chain performance from the triple bottom line perspective, including financial, environmental, and social performance.

The initial stage involves selecting the crucial criteria (short-term and long-term) and alternatives for sustainable supply chain performance (SSCP) from experts and conducting an in-depth literature review. Initially, there were 17 criteria, but after a pilot test with co-authors and online discussions with experts, the number of criteria was subsequently reduced to 9. In the second phase, the Best-Worst Method (BWM) was applied to rank and prioritize the criteria. The third and final stage examined the causal relationship between the identified criteria, utilizing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique.

Based on BWM analysis results, the top three criteria in terms of prominence are: (1) return on investment (ROI), (2) product quality, and (3) manufacturing lead time. Out of the three alternatives, financial performance (FP) is the most crucial dimension for SSCP, followed by environmental performance (ENP) and social performance (SP). On the other hand, the DEMATEL approach showed that work health and safety (short-term criterion), asset utilization (long-term criterion), energy consumption (long-term criterion), waste disposal (long-term criterion), manufacturing lead time (short-term criterion), and on-time delivery (short-term criterion) are categorized within the cause group, while criteria such as return on investment (ROI) (long-term criterion), customer-service level (short-term criterion), and product quality (long-term criterion) fall into the effect group.

The proposed study has certain drawbacks that pave the way for future research directions. First, it is worth noting the need for a larger sample size to ensure the reliability of results, the potential inclusion of additional criteria to enhance the assessment of sustainability performance, and the consideration of a qualitative approach to gain deeper insights into the outcomes. In addition, fuzziness in qualitative subjective perception could be imperative when collecting data to ensure its reliability, as translating experts’ perceptions into exact numerical values can be challenging because human perceptions often carry elements of uncertainty or vagueness. Therefore, fuzzy integrated MCDM frameworks are better suited for future research to handle the uncertainties involved in human perceptions, making it a more appropriate approach for decision-making in scenarios where traditional MCDM methods may prove insufficient.

The proposed framework will enable decision-makers to gain deeper insights into how various decision criteria impact SSCP, thus providing a comprehensive evaluation of SSCP that considers multiple dimensions, such as financial, environmental, and social performance within the manufacturing sector.

The proposed study is the first empirical study to integrate both BWM and DEMATEL approaches to evaluate sustainable supply chain performance in the manufacturing context.

This study aims to explore the determinants of digital technology adoption within micro, small and medium enterprises (MSMEs) operating in a developing economy. Grounded in the theoretical frameworks of fit-viability and task-technology fit models, this study investigates the impact of environmental fit, task-technology fit and viability on the intention to adopt digital technologies among MSMEs.

This study validates the theoretical model using structural equation modeling, using data collected from 280 experienced respondents employed in the MSMEs in India.

The results indicate that both functional and symbolic benefits positively impact managers’ intention to adopt digital technology. However, subgroup analysis reveals that in the case of service enterprises, only functional benefits have a positive influence on managers’ intention to adopt digital technology. In addition, the findings underscore the crucial role of viability in shaping the intention to adopt digital technologies among MSMEs. This study highlights how functional and symbolic benefits motivate digital technology adoption in MSMEs.

There is a dearth of empirical studies investigating the factors influencing the adoption of digital technology by MSME firms, especially within the context of developing economies and specifically within the MSME domain. This study contributes to the theoretical discussion surrounding digital technology adoption among MSMEs in India. Through empirical research, it expands on the fit-viability model and formulates a technology adoption model within the MSME context.