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Traditional visual simultaneous localization and mapping (SLAM) systems are primarily based on the assumption that the environment is static, which makes them struggle with the interference caused by dynamic objects in complex industrial production environments. This paper aims to improve the stability of visual SLAM in complex dynamic environments through semantic segmentation and its optimization.

This paper proposes a real-time visual SLAM system for complex dynamic environments based on YOLOv5s semantic segmentation, named YLS-SLAM. The system combines semantic segmentation results and the boundary semantic enhancement algorithm. By recognizing and completing the semantic masks of dynamic objects from coarse to fine, it effectively eliminates the interference of dynamic feature points on the pose estimation and enhances the retention and extraction of prominent features in the background, thereby achieving stable operation of the system in complex dynamic environments.

Experiments on the Technische Universität München and Bonn data sets show that, under monocular and Red, Green, Blue - Depth modes, the localization accuracy of YLS-SLAM is significantly better than existing advanced dynamic SLAM methods, effectively improving the robustness of visual SLAM. Additionally, the authors also conducted tests using a monocular camera in a real industrial production environment, successfully validating its effectiveness and application potential in complex dynamic environment.

This paper combines semantic segmentation algorithms with boundary semantic enhancement algorithms to effectively achieve precise removal of dynamic objects and their edges, while ensuring the system's real-time performance, offering significant application value.

The study of mindfulness is still shown to be of interest in different aspects of organisations and/or businesses. Therefore, this study aims to present an integrative, multi-level model of mindfulness based on a holistic approach that can contribute to better governance practices and lead to competitive advantages.

To fulfil this aim, an extensive integrative review of the literature, from the main articles about this topic, was made.

This study shows that the concept of mindfulness, a conscious presence or full attention and its relation with organisations or firms’ personal, behavioural and social characteristics, in the current context of great adversity, uncertainty and unpredictability, is of interest at the individual, organisational and social level.

This conceptual study has important implications for both practice and theory. It demonstrates that mindfulness significantly impacts the manager/business person’s ecosystem at the individual, organisational and social levels, particularly in relation to Sustainable Development Goals.

This study introduces a comprehensive theoretical model that explains this relationship and organises information from a multi-level perspective. This approach can contribute to the advancement of theory by clarifying and discussing the role of mindfulness at the individual, organisational and societal levels. It also identifies opportunities and outlines future research directions, aiming to promote more sustainable development.

This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.

The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.

First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.

This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.

The purpose of this study is to examine how the implementation of edge computing can enhance the progress of the circular economy within supply chains and to address the challenges and best practices associated with this emerging technology.

This study utilized a streamlined evaluation technique that employed Latent Dirichlet Allocation modeling for thorough content analysis. Extensive searches were conducted among prominent publishers, including IEEE, Elsevier, Springer, Wiley, MDPI and Hindawi, utilizing pertinent keywords associated with edge computing, circular economy, sustainability and supply chain. The search process yielded a total of 103 articles, with the keywords being searched specifically within the titles or abstracts of these articles.

There has been a notable rise in the volume of scholarly articles dedicated to edge computing in the circular economy and supply chain management. After conducting a thorough examination of the published papers, three main research themes were identified, focused on technology, optimization and circular economy and sustainability. Edge computing adoption in supply chains results in a more responsive, efficient and agile supply chain, leading to enhanced decision-making capabilities and improved customer satisfaction. However, the adoption also poses challenges, such as data integration, security concerns, device management, connectivity and cost.

This paper offers valuable insights into the research trends of edge computing in the circular economy and supply chains, highlighting its significant role in optimizing supply chain operations and advancing the circular economy by processing and analyzing real time data generated by the internet of Things, sensors and other state-of-the-art tools and devices.

Wine is a complicated and difficult product to know, which makes it extremely difficult for people with little knowledge to choose the wine they want. This study aims to analyze whether the vocabulary used in reviews on wine written by experts and amateurs on the specialized website is useful for those consumers who wish to search for information on this website to choose a wine.

The analysis combines text mining, Natural Language Processing and the Biterm Topic model applied to 25,847 reviews, evaluating a total of 13,263 Spanish wines made by 17 selected users of a specialized wine website.

The results show that wine consumers and users of the specialized wine website who write reviews can be divided into expert users and amateur users. Both experts and amateurs use a specific vocabulary related to the wines they review. Unlike amateurs, experts have a broader and more precise vocabulary, and greater consistency in the use of words with the aspects of the wine. For the revised wines, they address fewer and more specific aspects of wine (such as vintages), but they do so with more depth and rigor.

The originality and value of this research work lie in addressing two aspects that have hardly been analyzed: the reviews of experienced consumers and amateur consumers, and the textual information referring to the Spanish language, which distinguishes this analysis from other similar analyses carried out on the English language.