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Coastal water supply infrastructure systems are critical to modern society. This paper proposes a model to develop improvement strategies for the resilience of these systems to sea-level rise, incorporating both predisaster and postdisaster adaptive measures. The primary objective is to maximize the expected value of resilience. Beyond enhancing system resilience, the model accounts for proactive and reactive capacities, system deterioration, and limited resources. A numerical solution method, combining heuristic approaches and SEAWAT (a computer program) simulation, is proposed to solve the model. Its effectiveness is demonstrated through a case study in the Minhang district. Results indicate that compared to single adaptive measures, a combination of measures significantly enhances system resilience, maintaining performance within acceptable levels. Furthermore, the optimal mix of adaptive measures varies with the requirement of decision-makers for system (e.g., proactive capability, reactive capability, and consideration of deterioration) and is heavily influenced by the intensity of natural disasters and the availability of resources. The model offers guidance for selecting optimal adaptive measures under various sea-level rise scenarios. [ABSTRACT FROM AUTHOR]

In light of the carbon neutrality goals set post-Paris Climate Conference (COP21), this study delves into the relationship between green technology innovations, energy consumption, and CO2 emissions in China, spanning the period of 1990 to 2021. The objective of this paper is to creatively present the idea of a low-carbon digital economy from the viewpoint of digital technology. Utilizing the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, we scrutinize this relationship, employing unit-root testing to verify the integrative attributes of the variables, inclusive of structural break data. Further analysis using the bootstrap Autoregressive Distributed Lag (ARDL) bound testing method corroborates the relationship between these key variables. The study reveals unidirectional co-integration over time among green technology innovations, renewable and non-renewable energy, per capita income, population, and CO2 emissions as per the Granger causality test. Interestingly, our findings suggest that while green technology innovation, per capita income, and renewable energy contribute to the reduction of CO2 emissions, non-renewable energy consumption and population growth exacerbate them. These insights offer valuable guidance for policymakers in formulating comprehensive strategies to enhance environmental quality through the promotion of renewable energy and green technology innovations, with a specific emphasis on the Chinese context. [ABSTRACT FROM AUTHOR]

This research proposes an enhanced teaching–learning based optimization (ETLBO) algorithm to realize an efficient path planning for a mobile robot. Four strategies are introduced to accelerate the teaching–learning based optimization (TLBO) algorithm and optimize the final path. Firstly, a divide-and-conquer design, coupled with the Dijkstra method, is developed to realize the problem transformation so as to pave the way for algorithm deployment. Secondly, the interpolation method is utilized to smooth the traveling route as well as to reduce the problem dimensionality. Thirdly, an opposition-based learning strategy is embedded into the algorithm initialization to create initial solutions with high qualities. Finally, a novel, individual update method is established by hybridizing the TLBO algorithm with differential evolution (DE). Simulations on benchmark functions and MRPP problems are conducted, and the proposed ELTBO is compared with some state-of-the-art algorithms. The results show that, in most cases, the ELTBO algorithm performs better than other algorithms in both optimality and efficiency. [ABSTRACT FROM AUTHOR]

This study constructs a regulatory system for information sharing on industrial internet platforms from a technical and socio-legal perspective. A differentiated game is used to construct decentralized, centralized, and cost-sharing contract decision-making scenarios to obtain the optimal level of efforts for information-sharing regulation. Through a comparative analysis, the optimal solutions under the three scenarios were derived. These solutions were then analyzed through numerical simulations using Matlab2016a. Our research demonstrates the following: (1) Centralized decision-making is most beneficial to the development of information-sharing regulatory systems. (2) Beyond a critical value for the local government cost subsidy coefficients, changes in these coefficients have a more pronounced effect on improving the economic efficiency of the regulatory system, and vice versa. That is, when the cost subsidy coefficient is higher than 1/2, increasing the cost subsidy coefficient has a more pronounced effect on improving the economic efficiency of the information-sharing regulatory system. (3) In all scenarios, an increase in the regulatory effort can effectively enhance the reputation of the information-sharing regulatory system. This study further extends the research on information-sharing regulations and provides a practical guide to industrial internet platforms. [ABSTRACT FROM AUTHOR]