Search Results (13,535)

Abstract: As an important carrier of sports services and the main force participating in the “short board” project of urban development, the renovation and upgrading of old stadiums have become an important trend for the sustainable development of venues in the context of urban renewal, consumption upgrading, and national fitness. However, owing to the complexity of the transformation process, the probability of safety accidents continues to increase, posing a serious threat to national property security. In order to reasonably evaluate the safety of the stadium renovation construction process and reduce the incidence of accidents in the renovation project, this study proposed a safety evaluation model for the stadium renovation construction based on the combination weighting extension model. First, according to the 5M1E theory, 27 influencing factors were selected, a safety evaluation index system for stadium reconstruction construction was constructed, and the safety evaluation grade of the index was quantified. Second, based on the analytic hierarchy process (AHP) and improved entropy weight method, the combination weight of the index was determined, and a safety evaluation model was constructed using the matter–element extension theory. Finally, the established evaluation model was applied to the example of stadium renovation, and the construction safety level of the renovation project was obtained. The research results showed that the model has strong operability, and the evaluation results are reasonable and reliable, providing a new concept for the safety control of stadium reconstruction construction. Full article

This study establishes and refines a social-landscape ecological security pattern that integrates the demand and supply of ecosystem services, providing a substantial foundation for the ecological restoration of territorial spaces. This foundation is crucial for enhancing the effectiveness of “social–ecological” systems in achieving sustainable development. Jilin Province, serving as a national ecological security buffer and experiencing rapid economic growth, exhibits a significant spatial imbalance between social and economic progress and ecological conservation. The balance of ecosystem service demand and supply is pivotal in this context, making Jilin Province an ideal study area. We employed a multifaceted approach, including MSPA, the InVEST model, landscape connectivity assessment, circuit theory, and ecological network integrity evaluation, to elucidate the spatial disparities between the demand and supply of ecosystem services. We then developed and optimized social and landscape ecological security patterns to meet human demands and safeguard ecological integrity, thereby promoting the sustainable development of “social–ecological” systems. The key findings are as follows: (1) The supply of ecosystem services shows a clear spatial gradient, with lower values in the west and higher in the east, while demand is concentrated in the central region with lower values in the east and west, indicating a pronounced spatial mismatch in Jilin Province. (2) The landscape ecological security pattern includes 18 barrier points, 33 pinch points, 166 ecological corridors, and 101 ecological sources. (3) The social–ecological security pattern comprises 119 demand sources and 150 supply–demand corridors. (4) The study introduces 14 supply–demand nodes and 47 optimization corridors, proposing zoning schemes for the eastern core protection area, the central ecological demand area, and the western core restoration area. Additionally, recommendations are concerning the optimization of the “social–ecological” system pattern. This research advances the theoretical understanding of “social–ecological” system development in Jilin Province and offers insights for more harmonized development strategies. Full article

Stakeholders in multimodal freight transport encounter significant challenges due to the multitude of unknowns and inherent risks that can adversely affect operations. The subjective nature of the information complicates the identification and assessment of these risks, making them particularly challenging in the context of multimodal transport, where the potential consequences can be substantial. This research intends to provide a comprehensive understanding of the asymmetries in risks associated with multimodal freight transport by identifying and evaluating quantitative hazards. By integrating fuzzy set theory and failure mode and effects analysis (FMEA), the study offers a structured approach to statistically forecast risks, addressing imprecision in traditional risk assessments. Qualitative interviews conducted with multimodal freight transport operators in Thailand reveal critical insights, including the identification of high-priority risks such as delays from regulatory compliance, inadequate infrastructure, and inefficiencies in stakeholder communication. The findings of this study not only highlight these pressing issues but also provide actionable strategies to mitigate risks, thereby enhancing the operational resilience of multimodal freight transport systems. Full article

The Fourth Industrial Revolution, also known as Industry 4.0, which is the intensified digitalization and automation in industry, embraces cyber–physical systems, the Internet of Things (IoT), and artificial intelligence, among others. This study utilizes Fuzzy Integration–Rough Set Theory (FI-RST) analysis to quantify the impacts of the imperative Industry 4.0 technologies for manufacturing firms located in Fujian Province, China, namely, Manufacturing Execution Systems (MES), the Industrial Internet of Things (IIoT), and Additive Manufacturing (AM), on the sustainable development performance of firms. The findings of the study indicate that these technologies greatly improve the effectiveness of the utilization of resources, reduce the costs of operations, and reduce the impact on the environment. In addition, they have a favorable influence on social considerations, such as preserving the well-being of employees and the outcome of training programs. This research work has convincingly provided an underlying strategic adoption of these technologies for sustainability production by raising important insights that could be valuable for industry managers and policymakers, especially those seeking sustainability at the global level. Full article

This study investigates the mechanisms by which service-oriented transformation affects employee satisfaction with performance evaluation systems within the context of China’s electricity market reform. Using CGN New Energy’s Guangxi Branch as a case study and applying the grounded theory method, the research systematically analyzes employees’ perceptions of fairness, transparency, and career development during the transition from a product-oriented to a service-oriented model, based on in-depth interviews and surveys. The findings reveal that while servitization enhances employee skill development and career satisfaction, it also introduces challenges, such as increased work pressure and the demand for more transparent performance evaluation systems. This study provides valuable insights into optimizing management practices and performance evaluation systems in renewable energy companies, contributing both theoretically and practically to the literature on organizational transformation in the energy sector. These conclusions are not only significant for Chinese enterprises but also offer important reference points for global energy companies undergoing similar transitions. Full article

This article examines the process of creating and researching a virtual laboratory for training students in coding theory. General information about the virtual laboratories is presented. A methodology for conducting comprehensive scientific research is presented, as well as a specialized method for designing and developing the virtual laboratory, including the system’s architecture. The article also presents brief information about the developed system. The results of the experimental research, including a pedagogical experiment aimed at evaluating the influence of the virtual laboratory on the students’ success rate, as well as an analysis of the statistical data on their activity, are discussed in detail. In addition, a survey was conducted to assess the satisfaction of students with the use of the laboratory. Full article

Aiming at the problem of system controller performance failure caused by improperly setting the value of each weighting coefficient of the model predictive control (MPC), a fractional-order MPC strategy with Takagi–Sugeno fuzzy optimization (T–SFO MPC) is proposed for a vehicle active suspension system. Firstly, the fractional-order model predictive control framework for active suspension systems is designed based on a 1/4 vehicle model. Then, we analyze the influence of different weighting coefficients on the suspension performance and introduce the Takagi–Sugeno fuzzy optimization theory to adaptively adjust the weighting coefficients of the fractional-order MPC controller. Finally, the system responses of the T–SFO MPC, traditional MPC, linear quadratic regulator (LQR), and passive suspension control are numerically analyzed under various road conditions. Simulation results show that suspension response with the T–SFO MPC is significantly improved compared with passive suspension control, traditional MPC control, and LQR control, and the weight coefficients of the T–SFO MPC can be adaptively adjusted according to the dynamic changes of suspension response. Compared with passive suspension, the root mean square (RMS) value of the vertical acceleration of the T–SFO MPC under various roads decreased by a maximum of 37.97%, and the RMS value of suspension dynamic deflection and tire dynamic load decreased by a maximum of 32.94% and 37.8%, respectively. These results validate that the proposed control method can achieve coordinated optimization of vehicle comfort and handling stability. Full article

We introduce fuzzy enriched contraction, which extends the classical notion of fuzzy Banach contraction and encompasses specific fuzzy non-expansive mappings. Our investigation establishes both the presence and uniqueness of fixed points considering this broad category of operators using a Krasnoselskij iterative scheme for their approximation. We also show the graphical representation of fuzzy enriched contraction and analyze its graph for different values of beta. The implications of these findings extend to significant results within fuzzy fixed-point theory, enriching the understanding of iterative processes in fuzzy metric spaces. To demonstrate the versatility of our innovative concepts and the associated fixed-point theorems, we provide illustrative examples that showcase their applicability across diverse domains, including the generation of fractals. This demonstrates the relevance of fuzzy enriched contraction to iterated function systems, enabling the study of fractal structures under various contractive conditions. Additionally, we explore practical applications of fuzzy enriched contraction in dynamic market equilibrium, offering new insights into stability and convergence in economic models. Through this unified framework, we open new avenues for both theoretical advancements and real world applications in fuzzy systems. Full article

In this paper, a distributed algorithm for reaching average consensus is proposed for multi-agent systems with tree communication graph, when the edge weight distribution is unbalanced. First, the problem is introduced as a key topic of core algorithms for several modern scenarios. Then, the relative solution is proposed as a finite-time algorithm, which can be included in any application as a preliminary setup routine, and it is well-suited to be integrated with other adaptive setup routines, thus making the proposed solution useful in several practical applications. A special focus is devoted to the integration of the proposed method with a recent Laplacian eigenvalue allocation algorithm, and the implementation of the overall approach in a wireless sensor network framework. Finally, a worked example is provided, showing the significance of this approach for reaching a more precise average consensus in uncertain scenarios. Full article

This research introduces a fractional high-order sliding mode control (FHOSMC) method that utilises an inverse integral fractional order, $0<\beta <1$, as the high order on the FHOSMC reaching law, exhibiting a novel contribution in the related field of study. The application of the proposed approach into a bioreactor system via diffeomorphism operations demonstrates a notable improvement in the management of the bioreactor dynamics versus classic controllers. The numerical findings highlight an improved precision in tracking reference signals and an enhanced plant stability compared to proportional–integral–derivative (PID) controller implementations within challenging disturbance scenarios. The FHOSMC effectively maintains the biomass concentration at desired levels, reducing the wear of the system as well as implementation expenses. Furthermore, the theoretical analysis of the convergence within time indicates substantial potential for further enhancements. Subsequent studies might focus on extending this control approach to bioreactor systems that integrate sensor technologies and the formulation of adaptive algorithms for real-time adjustments of $\beta$-type fractional-orders. Full article

The generalized theory of the double reduction of systems of partial differential equations (PDEs) based on the association of conservation laws with Lie–Bäcklund symmetries is one of the most effective algorithms for performing symmetry reductions of PDEs. In this article, we apply the theory to a (1 + 1)-dimensional Broer–Kaup (BK) system, which is a pair of nonlinear PDEs that arise in the modeling of the propagation of long waves in shallow water. We find symmetries and construct six local conservation laws of the BK system arising from low-order multipliers. We establish associations between the Lie point symmetries and conservation laws and exploit the association to perform double reductions of the system, reducing it to first-order ordinary differential equations or algebraic equations. Our paper contributes to the broader understanding and application of the generalized double reduction method in the analysis of nonlinear PDEs. Full article

Background/Objectives: Sport persistence is the embodiment of sports performance and mental toughness. It refers to our attempts concerning the performance plateau, failures, injuries, or even the resolution and processing of stressful situations associated with success and positive events. In our research, we used qualitative methods based on Bronfenbrenner’s socio-ecological model to investigate the factors influencing sport persistence among high school and university athletes. Methods: The research was based on semi-structured interviews with 133 athletes. ATLAS.ti software and the grounded theory methodology were applied for data analysis. Our analysis grouped the responses according to Bronfenbrenner’s categorisation system, highlighting motivational factors at the microsystem level. Our research question was as follows: What kind of factors dominate the development of sport persistence among adolescent (high school) and young adult (university) athletes along Bronfenbrenner’s dimension of the microsystem? Results: Regarding the microsystem, family, peers, and coaches were mentioned as influential factors. Concerning the family, general, person-specific, family value-related, future-oriented, introjected, and disadvantage-compensating motivational components were identified. General, individual, community and relational factors were identified concerning peers. Concerning the coach, general, individual, community, and coach personality-driven motivational segments were detected. Conclusions: By recognising the complex interplay of systemic factors, we can design interventions targeting these factors at various socio-ecological levels, promoting youth sports and increasing physical activity among young people. These findings instil hope and motivation for the future of sports and physical activity. Full article

Achieving significant breakthroughs in both the fundamental theories and technological applications of artificial intelligence is essential for fostering its long-term development. Under the guidance of Professor Qian Xuesen’s theory of technological science, exploring the internal mechanisms of knowledge evolution in artificial intelligence holds profound theoretical and practical significance for promoting sustainable technological advancement. This study draws on literature from the Web of Science (WOS) database and employs methods such as knowledge mapping, natural language processing, clustering analysis, and citation analysis to outline the knowledge structure of the field, clarify the trajectory of sustainable development, and trace the technological genealogy of VR/AR technologies.This study divides the knowledge structure within the field of technological science into “basic theoretical knowledge—applied basic knowledge—applied knowledge”, enriching Qian’s theory of technological science from within and providing strong intellectual support and technological pathways for sustainable technological development in practice. Artificial intelligence encompasses 10 distinct knowledge domains, among which machine learning and deep learning constitute the basic theoretical knowledge, data intelligence, computer vision, and swarm intelligence are the applied basic knowledge, and image processing and human-computer intelligence are the applied knowledge. The development of VR/AR technology has formed two main sustainable development paths: “machine learning—data intelligence—intelligent systems—human computer intelligence”, and “deep learning—computer vision—image processing”. Full article

One amongst many of the defining characteristics of so-called ‘late stage’ capitalism are human-animal relationships that have become acrimonious, hostile, or even monstrous in nature. A foundational premise of monster theory, and one that Jeffrey Jerome Cohen’s seminal 1996 edited collection of the same name suggests, is that the construction of the monster in popular culture is fraught with the boundaries that constitute the society that has spawned them; the monstrous body “exists only to be read” (p. 4). Bringing together the theoretical insights of the Marxist theory of reification, critical animal studies, and monster theory, this article examines the ways in which cinematic depictions of gigantic monstrosity can inform our theorizing of multispecies relationships under capitalism. Specifically, I explore how the tensions between capital and human-animal relationships serve to construct and constitute the multiform monster, Jean Jacket, in Jordan Peele’s 2022 film Nope. Through an examination of the multispecies relationalities that the film portrays, I argue that the figure of Jean Jacket is a monstrous culmination of the reified and therefore, necessarily deferred nature of human-animal relationships under capital. However, Nope’s conclusion alerts us to the radical dereifying potential of multispecies bonds of care and embodied knowledge; systems of resistance that can be forged even within our current capitalist ruins. Full article

With the development and application of artificial intelligence (AI) in the shipping industry, using AI to replace traditional draft survey methods in bulk carriers can significantly reduce manpower, lower the risks associated with visual observations, improve measurement accuracy, and minimize the impact of human subjective factors. Ultimately, the integration of software and hardware technologies will replace human visual observations with automated draft measurement calculations. A similar anti-fluctuation device described in this article has been used in ship draft observation based on AI-assisted proving, which can ease the fluctuation of the wave inside the pipe. Observers can directly read the water surface inside the pipe and compare it to the ship’s draft mark to obtain the final draft, effectively improving draft observation accuracy. However, some surveyors refuse to accept the readings obtained from this device, citing a lack of theoretical basis or the absence of accreditation from relevant technical authorities, leading to the rejection of results. To address these issues, this paper integrates wave energy attenuation theory with PaddlePaddle-OCR recognition to further validate the anti-fluctuation device for accurate ship draft observation. The experimental results are as follows: first, the pipe effectively suppresses the amplitude of external water surface fluctuations by 75%, explaining the fundamental theory that wave heights within the anti-fluctuation device are consistent with external swell heights. When taking a draft measurement, the system dynamically adjusts the position of the main tube in response to the ship’s movements, maintaining the stability of the measurement section and significantly reducing the difficulty of observations. Due to the reduction in fluctuation amplitude, there is a noticeable improvement in observation accuracy. Full article