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Autonomous underwater vehicle (AUV) is widely used in resource prospection and underwater detection due to its excellent performance. This study considers input saturation, nonlinear model uncertainties and external ocean current disturbances. The containment errors can be limited to a small neighborhood of zero in finite time by employing control strategy. The control strategy can keep errors within a certain range between the trajectory followed by AUVs and their intended targets. This can mitigate the issues of collisions and disruptions in communication which may arise from AUVs being in close proximity or excessively distant from each other.

The tracking errors are constrained. Based on the directed communication topology, a cooperative formation control algorithm for multi-AUV systems with constrained errors is designed. By using the saturation function, state observers are designed to estimate the AUV’s velocity in six degrees of freedom. A new virtual control algorithm is designed through combining backstepping technique and the tan-type barrier Lyapunov function. Neural networks are used to estimate and compensate for the nonlinear model uncertainties and external ocean current disturbances. A neural network adaptive law is designed.

The containment errors can be limited to a small neighborhood of zero in finite time so that follower AUVs can arrive at the convex hull consisting of leader AUVs within finite time. The validity of the results is indicated by simulations.

The state observers are designed to approximate the speed of the AUV and improve the accuracy of the control method. The anti-saturation function and neural network adaptive law are designed to deal with input saturation and general disturbances, respectively. It can ensure the safety and reliability of the multiple AUV systems.

This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.

This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.

The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.

This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

This chapter critically evaluates whether football can attain recognition as a national sport in China. Article No. 11, released by the Chinese government in 2015, aimed to develop a new national strategy centralised on the sport of football to foster consumption and enhance national soft power. Consequently, this also means encouraging Chinese football fans to support the national football team. Comparing the significance of local football clubs and the national football team to Chinese football fans is deemed meaningless and unable to generate useful information to comprehend Chinese people's attitudes towards local and national communities. Through literature comparisons with established Chinese national sports such as Chinese martial arts, badminton and table tennis, the discussion reveals that football currently falls short of meeting the general criteria of invention and popularity to be considered a Chinese national sport. In the specific Chinese context, it also proves that football fails to meet the criterion of politics, hindering its identification as a national sport. Consequently, the chapter rebuts the assumption and advocates for the validity of comparing how fans assess their fandom for local and national football teams.

This study aims to explore the influence of science fiction on innovators and present a comprehensive model using the theory of planned behavior and social support theory to discuss the impact of science fiction on the intention of becoming an innovation worker.

Partial least squares structural equation modeling (PLS-SEM) was adopted in this study and responses were obtained from 244 Chinese innovators.

The results revealed the adequacy of the proposed model and the above-mentioned constructs in explaining innovation intention. Science fiction perception was found to influence the intention of becoming an innovation worker directly. Subjective norm, perceived behavioral control, and attitude directly influence the intention of becoming an innovation worker. Additionally, attitude is a mediator between science fiction perception and the intention of becoming an innovation worker. Moreover, social support network moderates the relationship between attitude and intention.

These results shed light on the mechanism by which science fiction influence innovators as well as provide critical managerial implications for policymakers and practitioners.

The study seeks to shed light on the estimates of the carbon shadow price in the literature relying on frontier techniques. The shadow price of undesirable outputs, such as greenhouse gas emissions, assists policymakers in determining the most cost-effective methods for reducing emissions.

The study relies on the PSALSAR and PRISMA approaches for a systematic literature review. The Web of Science and Scopus databases were used for the references.

Both parametric and nonparametric methods have been employed in the literature to estimate the shadow prices of undesirable outputs. Also, results were discussed according to the methodological and application aspects, and broad conclusions on obtained results were provided, bridging climate change mitigation policies and the shadow price of undesirable outputs.

The present study applies an integrated method, PSALSAR, to conduct a systematic review of 53 studies published between 2014 and 2023 in which efficiency models were applied to estimate the shadow price of undesirable outputs, especially CO₂. After presenting the most applicable parametric and nonparametric estimation models, a systematic summary of included articles was provided, highlighting the key features of publications.

By harnessing technology developments such as Internet-of-Things (IoT)-enabled intelligent sensors and immersive virtual reality (VR) experiences, facility managers can access real-time, precise information on thermal comfort-related indicators through virtual facility models. While prior research studies have developed key technologies for improving the understanding of thermal comfort and its impact on the occupants’ well-being and productivity, there remain areas yet to be explored, especially in relation to integrating both real-time data from multimodal IoT-enabled smart sensors and VR technologies. Hence, this study demonstrates the potential of integrating IoT and VR technologies for real-time thermal comfort assessment and visualization as well as user interaction with HVAC systems to enhance thermal comfort.

To develop the proposed integrated analytical framework in this paper, various steps were implemented. First, four multimodal IoT-enabled sensing stations were created and installed to collect real-time thermal comfort-related data (i.e. temperature and relative humidity). Second, a VR environment was developed using the Unity engine to offer an immersive experience. Third, the real-time data from the IoT-enabled sensing stations was integrated into the VR environment by transmitting it to the cloud via the MQTT protocol server, and various programming scripts were developed to provide multiple functionalities to the users, including visualizing the thermal comfort along the entire indoor space as well as interacting with and controlling the cooling and heating HVAC systems. Fourth, the applicability and effectiveness of the developed framework was validated and evaluated by 92 participants using a survey questionnaire.

The obtained survey results validated the importance and effectiveness of the developed framework on various aspects including graphical satisfaction, spatial presence, involvement, experienced realism, low-to-no cybersickness and overall application satisfaction, among others. More specifically, the findings reflected that the participants’ average scores for graphical satisfaction, sense of spatial presence, involvement and experienced realism were 4.69, 4.61, 4.71 and 4.53 out of 5, respectively. Hence, the results showed that the visualization capabilities of the developed framework serve as a powerful feature that enables a comprehensive visualization of thermal comfort variations across the entire room/office space. Also, the results showed that there were no statistically significant differences between the responses of participants with prior VR experience with those from participants with limited-to-no prior VR experience, thus further highlighting the usefulness of the proposed technology not only for experienced users but also for users from different skills and background.

This research has the potential to revolutionize the way built environments are managed and interacted with, where facility managers can monitor, assess and visualize thermal comfort in real-time as well as interact with the HVAC systems and control multimodal IoT devices in the real-world from a distance through virtual facility models. The proposed framework’s ability to provide dynamic and continuously updated assessments of thermal conditions in real-time positions it as a valuable tool for prompt adjustments to optimize occupants’ comfort levels. Ultimately, the proposed framework provides an intuitive and immersive platform to manage thermal comfort, thus promoting healthier, more productive and eco-friendly indoor environments.

This research endeavors to conduct a thorough and holistic analysis of the foundational elements that empower the cultivation of dynamic capabilities in micro, small and medium-sized enterprises (MSMEs). The purpose of this study is to determine whether these capabilities have a noticeable impact on the sustainable performance of these enterprises. The study aims to support future research efforts in understanding this phenomenon by filling this knowledge gap and presenting a conceptual framework, thereby enhancing the scholarly discourse in this field.

The study consists of a systematic review of 126 articles meticulously chosen through a series of screening stages employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. This examination is conducted within the organized framework of antecedents, decisions and outcomes-theory, context and methods (ADO-TCM), ensuring a structured and comprehensive analysis.

The study uncovers significant insights, identifying four key antecedents: resource base, organizational learning, managerial expertise and external environment management. These factors are instrumental in fostering dynamic capabilities within the enterprise, leading to sustainable entrepreneurial success and a competitive advantage over rivals.

By comprehending the mechanisms by which dynamic capabilities are established within the enterprise, this study provides a valuable resource for entrepreneurs, professionals and managers, offering them practical insights to leverage.

This systematic literature review is the initial attempt to explain how dynamic capabilities can be used to enhance and accomplish sustainable performance in the context of MSMEs.

The nickel-based alloys Inconel 625 and Inconel 718 stand out due to their high strength and corrosion resistance in important industries like aerospace, aviation and automotive. Even though they are widely used, current techniques of producing materials that are difficult to cut pose several problems from a financial, ecological and even health perspective. To handle these problems and acquire improved mechanical and structural qualities, laser powder bed fusion (LPBF) has been widely used as one of the most essential additive manufacturing techniques. The purpose of this article is to focus on the state of the art on LPBF parts of Inconel 625 and Inconel 718 for microstructure, mechanical behavior and postprocessing.

The mechanical behavior of LPBF-fabricated Inconel is described, including hardness, surface morphology and wear, as well as the influence of fabrication orientation on surface quality, biocompatibility and resultant mechanical properties, particularly tensile strength, fatigue performance and tribological behaviors.

The postprocessing techniques such as thermal treatments, polishing techniques for surface enhancement, mechanical and laser-induced peening and physical operations are summarized.

The highlighted topic presents the critical aspects of the advantages and challenges of the LPBF parts produced by Inconel 718 and 625, which can be a guideline for manufacturers and academia in practical applications.

This paper introduces a formal risk interdependency framework to model cascading effects in collaborative systems. By characterizing risk causal chains and propagation chains, the framework aims to provide decision-makers with a structured tool to systematically identify, analyze, and prevent cascading risks in interconnected networks.

The framework, named the danger-risk-consequence chain, defines core components – danger, stake, risk, condition, and consequence – alongside their causal and propagation relationships, which form the basis for risk characterization. The framework is applied through a use case in the construction supply chain to demonstrate its capacity to model cascading risks.

The framework uncovers risk propagation chains that lead to cascading effects and formalizes the state evolution of these effects within collaborative systems. Through the use case, it demonstrates practical value by enabling stakeholders to visualize interrelated risks, detect vulnerabilities early, and implement targeted mitigation measures to enhance resilience against cascading disruptions.

This study presents a novel approach to modeling cascading effects by integrating risk causality and propagation into a formalized framework. In contrast to previous research, which offers static risk definitions for risk characterization, this framework contributes to risk management theory by providing a structured method for understanding and modeling interdependencies.

This study aims to analyse the influence of the pillars (hard and soft skills) of digital academic entrepreneurship on students' entrepreneurial intention.

This was done by adopting a quantitative methodology involving empirical research with a sample of 761 university students from two countries and adopting structural equation analysis to validate the theoretical model proposed.

The results indicate a direct influence between hard and soft skills and entrepreneurial intention, and a positive, indirect influence between these and entrepreneurial intention mediated by the dimensions of the theory of planned behaviour (TPB) – entrepreneurial attitude, subjective norms and perceived behavioural control. Therefore, the pillars of digital academic entrepreneurship have a direct and indirect influence on university students' entrepreneurial intention.

This study also contributes to better operationalization of entrepreneurial education in university environments, since the development of hard and soft skills can be planned better based on the model proposed here. Considering the relations between the dimensions of hard and soft skills and those of TPB, this study shows there can be an influence on students' entrepreneurial intention.

In this study, a new and innovative construct is inserted in the model of entrepreneurial intention: “structural pillars of digital academic entrepreneurship” through structural equation modelling, to determine the degree of influence of these pillars (hard and soft skills) constructs on HEI students' entrepreneurial intention.