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This paper explores how the existence of a second-hand market can affect remanufacturing decisions for durable goods in the presence of patent protection.

The authors construct a dynamic decision model between a durable goods original manufacturer and a durable goods remanufacturer considering the characteristics of the multi-cycle uses of new durable goods and remanufactured durable goods.

The results show that (1) the second-hand market compresses the cost space of a durable goods original manufacturer and a remanufacturer; (2) when the second-hand market exists, the optimal pricing of new durable goods is reduced, the optimal pricing of remanufactured durable goods is increased and the patent cost of each unit of durable goods increases and (3) the presence of the second-hand market will increase the original manufacturer's and remanufacturer's profits.

The research conclusion has certain reference value for the production strategy selection of each enterprise in the process of patented product remanufacturing and the government's fiscal policy formulation at each stage of the remanufacturing industry's development.

This paper aims to report on a study that used the practice theory lens to understand how Chinese ethnic culture influences restaurant workers' learning through engagement in everyday work practices.

A multiple case study approach was used. Data were collected from semi-structured interviews and site observations. Thematic analysis was conducted to identify how workers learnt the sayings, doings and relatings in their workplaces.

The findings show that the ethnic culture of the participants influences and enriches their learning in practice settings such as small Chinese restaurants.

The understandings presented here need to be verified through more research in different regions and nations. In addition, cross-cultural studies on other ethnic restaurants may contribute to deeper understandings of the influences of ethnic culture on practice-based learning.

The research contributes to understanding the influence of ethnic culture on practice-based learning.

The understandings gained from the findings of this study form a useful basis for curriculum development and instructional design of training programmes for practice-based as well as work-integrated-learning components of vocational curriculum. Furthermore, awareness of the strengths of the ethnic culture is of interest to owner/managers of small Chinese restaurants to afford supportive learning environments for workers.

The purpose of this study was to bring a new structural hybrid design approach to improve the mechanical and biological properties of the bone scaffolds fabricated by laser powder bed fusion, selective laser melting (SLM).

In designing the hybrid scaffolds, different unit cells were used such as dodecahedron (DCH), grid (G), octet-truss (OCT) with partially dense (PDsl) and fully dense (FDsl) surface layers. After fabrication of scaffolds on SLM machine, compression test and cell viability test were applied to observe the effect of hybrid design on mechanical and biological properties of the scaffolds.

It has been observed that designing the scaffold with partially dense or FDsl surfaces did not have a critical effect on the cell viability. On the contrary, the compression strength of scaffold increased from 56  to 100 MPa when the surface layer of the scaffold was designed as FDsl surface instead of partially dense surface. It has also been observed that the scaffold having the highest hybridity (PDsl+G+DCH+OCT) delivered the highest cell viability performance and had a compressive strength slightly higher than that of the scaffolds with single unit cell, PDsl+OCT.

This study brings a new approach to designing femur bone scaffold for fabricating with SLM. This hybrid design approach, including different unit cells in a single scaffold, covers many requirements of femur bone in terms of mechanical and biological properties.

This study compares the fatigue performance and biocompatibility of as-built and chemically etched Ti-6Al-4V alloys in TPMS-gyroid and stochastic structures fabricated via Powder Bed Fusion Laser Beam (PBF-LB). This study aims to understand how complex lattice structures and post-manufacturing treatment, particularly chemical etching, affect the mechanical properties, surface morphology, fatigue resistance and biocompatibility of these metamaterials for biomedical applications.

Selective Laser Melting (SLM) technology was used to fabricate TPMS-gyroid and Voronoi stochastic designs with three different relative densities (0.2, 0.3 and 0.4) in Ti-6Al-4V ELI alloy. The as-built samples underwent a chemical etching process to enhance surface quality. Mechanical characterization included static compression and dynamic fatigue testing, complemented by scanning electron microscopy (SEM) for surface and failure analysis. The biocompatibility of the samples was assessed through in-vitro cell viability assays using the Alamar Blue assay and cell proliferation studies.

Chemical etching significantly improves the surface morphology, mechanical properties and fatigue resistance of both TPMS-gyroid and stochastic structures. Gyroid structures demonstrated superior mechanical performance and fatigue resistance compared to stochastic structures, with etching providing more pronounced benefits in these aspects. In-vitro biocompatibility tests showed high cytocompatibility for both as-built and etched samples, with etched samples exhibiting notably improved cell viability. The study also highlights the importance of design and post-processing in optimizing the performance of Ti64 components for biomedical applications.

The comparative analysis between as-built and etched conditions, alongside considering different lattice designs, provides valuable information for developing advanced biomedical implants. The demonstration of enhanced fatigue resistance and biocompatibility through etching adds significant value to the field of additive manufacturing, suggesting new avenues for designing and post-processing implantable devices.

The purpose of this paper is to propose a pre-defined performance robust control method for pre-assembly configuration establishment of in-space assembly missions, and collision avoidance is considered during the configuration establishment process.

First, six-degrees-of-freedom error kinematic and dynamic models of relative translational and rotational motion between transportation systems are developed. Second, the prescribed transient-state performance bounds of tracking errors are designed. In addition, based on the backstepping, combining the pre-defined performance control method with a robust control method, a pre-defined performance robust controller is designed.

By designing prescribed transient-state performance bounds of tracking errors to guarantee that there is no overshoot, collision-avoidance can be achieved. Combining the pre-defined performance control method with a robust control method, robustness to disturbance is guaranteed.

This paper proposed a pre-defined performance robust control method. Simulation results demonstrate that the proposed controller can achieve a pre-assembly configuration establishment with collision avoidance in the existence of external disturbances.

The purpose of this paper is to analyze supply chain practices, and supply chain food quality performance indicator in the Australian beef processing industry.

A conceptual model was developed to test how supply chain practices: strategic alliance, customer focus, information sharing, information quality, Lean system and antecedent cooperative behavior: trust and commitment impact on food quality. A survey questionnaire to 600 Australian beef processors was conducted to collect the empirical data for testing of the formulated hypotheses. The stepwise multiple regression analysis was performed to test the hypothesized relationships.

Strategic alliance, information quality and trust and commitment are significantly related to food quality. In particular, the standardized coefficient shows that information quality has a significant positive relationship with food quality.

As Lean principles have been widely adopted in the red meat industry, strategic alliance becomes even critical for maintaining cost and operation effectiveness in the beef supply chain. A various approaches in terms of innovative technologies can improve information quality and promote information sharing in the beef supply chain. To build trust and commitment among supply chain partners requires perception of mutual long-term goals.

Australian Meat Manufacturers face greater regulatory challenges and restraints (product labeling, food safety and carbon tax) over the next five years. Therefore, to tackle the challenges, the findings of this research have significant practical implications.

This study intends to fill the research gap and explore how advanced supply chain systems have a potential to provide contributions to Australian beef processing industry performance. Vertical integration between livestock producers, meat processors, wholesalers and retailers provides the opportunities for greater economies of scale in production and distribution.

The purpose of this paper is to find solutions to improve the red meat sector in an emerging economy, Turkey, from the circular economy point of view, and taking sustainability approach. The need for circular management within the red meat sector in Turkey is emphasized by using Grey method. As theoretical contribution of this study, the investigation of the causes of losses at the slaughter stages of the red meat supply chain leads to proposals for sustainable and circular solutions.

Grey method is used to predict the number of slaughtered cattle and the amount of bone and blood waste in the slaughtering process between 2018 and 2020.

It is revealed that according to Grey prediction calculations, although the amount of slaughtered cattle, bone and blood waste seem have decreased between 2018 and 2020, there are still significant losses in Turkish red meat sector. For bone waste, this is expected to be 56,581,200 kg in 2018, 48,235,840 kg in 2019 and 41,121,380 kg in 2020. For blood waste, it is expected to be 24,754,275 kg in 2018, 21,103,180 kg in 2019 and 17,990,604 kg in 2020.

The proposed model in the study will contribute on sector revitalization, increase in product safety, quality and hygiene, development in the management of training and education centers for farmers/labors and increase in employment.

This paper represents policymakers with a proposal for triple bottom line (TBL) based circular and central slaughterhouse model, based on TBL, which brings social, economic and environmental benefits for the red meat sector in Turkey.

To ensure the motion attitude and stable contact force of massage robot working on unknown human tissue environment, this study aims to propose a robotic system for autonomous massage path planning and stable interaction control.

First, back region extraction and acupoint recognition based on deep learning is proposed, which provides a basis for determining the working area and path points of the robot. Second, to realize the standard approach and movement trajectory of the expert massage, 3D reconstruction and path planning of the massage area are performed, and normal vectors are calculated to control the normal orientation of robot-end. Finally, to cope with the soft and hard changes of human tissue state and body movement, an adaptive force tracking control strategy is presented to compensate the uncertainty of environmental position and tissue hardness online.

Improved network model can accomplish the acupoint recognition task with a large accuracy and integrate the point cloud to generate massage trajectories adapted to the shape of the human body. Experimental results show that the adaptive force tracking control can obtain a relatively smooth force, and the error is basically within ± 0.2 N during the online experiment.

This paper incorporates deep learning, 3D reconstruction and impedance control, the robot can understand the shape features of the massage area and adapt its planning massage path to carry out a stable and safe force tracking control during dynamic robot–human contact.

The color painting of ancient buildings has high historical and artistic value but is prone to aging due to long-term outdoor exposure. The purpose of this study is to develop a new type of sealing coating to mitigate the impact of ultraviolet (UV) light on color painting.

The new coating was subjected to a 500-h UV-aging test. Compared with the existing acrylic resin Primal AC33, the UV aging behavior of the new coating, such as color difference and gloss, was studied with aging time. The Fourier infrared spectra of the coatings were analyzed after the UV-aging test.

Compared with AC33, the antiaging performance of SF8 was substantially improved. SF8 has a lower color difference value and better light retention and hydrophobicity. The Fourier transform infrared spectroscopy results showed that the C-F bond and Si-O bonds in the resin of the optimized sealing coating protected the main chain C-C structure from degradation during the aging process; thus, the resin maintained good stability. The hindered amine light stabilizer TN292 added to the coating inhibited the antiaging process by trapping active free radicals.

To address the problem of UV aging of oil-decorated colored paintings, a new type of sealing coating with excellent antiaging properties was developed, laying the foundation for its demonstration application on the surface of ancient buildings.

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.