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To scientifically evaluate the implementation of the River Chief System (RCS), accelerate the overall improvement of the water ecological environment, and promote the sustainable development of river and lake functions, this study selects 26 evaluation indicators from six aspects, including the effectiveness of organization and management, the effectiveness of water resources protection, the effectiveness of water environment management, the effectiveness of water pollution prevention and control, the effectiveness of water ecological restoration, and the effectiveness of the management of the waterside shoreline, and establishes an evaluation system for the effectiveness of the implementation of the RCS. Among the 26 indicators, data for the qualitative indicators mainly come from a series of statistical yearbooks and RCS reports, while data for the quantitative indicators are obtained through scoring by more than 20 experts and calculating the average. The CRITIC objective weighting method is improved from three aspects of comparison intensity, correlation coefficient, and degree of variation, and the subjective weighting of indicators is carried out using the AHP 1–5 scale method. The optimal linear combination of subjective and objective weighting results is obtained using the combination weighting method with game theory, which is auxiliary to the set pair analysis. Considering the "certainty" and "uncertainty" in the evaluation process, the four-element connection number model of set pair analysis is established to evaluate the implementation effect of the RCS in Henan Province from 2018 to 2021. The results show that the implementation effect of the RCS in Henan Province improves year by year and reaches excellent in 2019. The results of this study can be used as a reference for evaluating the work of the RCS in other regions and can also provide a reference for the study of evaluation problems in other fields. [ABSTRACT FROM AUTHOR]

The sustainability of financing is an important measure in the development of supply chains. However, the difficulty and high cost of financing have always been critical factors hindering the sustainable development of small and medium-sized enterprises (SMEs). Blockchain technology (BT) is an effective tool to relieve the current problem. Based on it, this study aims to establish Blockchain-driven incentives and restraint mechanisms for SME financing using a dynamic game model in which financial institutions (FIs) and new agricultural business entities (NABEs) are regarded as game subjects. By analyzing the impact of key parameters on the equilibrium state of the game for all stakeholders, several findings are drawn as follows. (1) The usage of BT affects FI loan strategies by influencing their cost in supply chain financing. (2) The usage of BT affects NABE's strategy choice by influencing their loan interest rate. (3) The usage of BT affects NABE's strategy choice by influencing their default losses. (4) The usage of BT affects NABE's and FI's strategy choices by influencing their additional benefits. This study provides decision-making support for optimal strategy decisions under different conditions and serves as a theoretical reference for the government in formulating financing incentive and restraint mechanisms. [ABSTRACT FROM AUTHOR]

Implementing the low-carbon transformation strategy has become an inevitable choice for manufacturing enterprises. However, suppliers often overlook the impact of consumers' preferences for low-carbon products (LCPs) on their own low-carbon strategies. Based on this idea, this study uses game theory models to analyze how consumer preferences affect suppliers' decision-making and coordination strategies in low-carbon supply chains (LCSCs). Results show that (1) manufacturers and retailers are more likely to produce and promote LCPs as consumers become more sensitive to carbon emission reduction (CER); (2) manufacturers are less likely to produce LCPs but retailers are more likely to promote them as consumers become more sensitive to promotional rates; and (3) manufacturers are less likely to produce LCPs but retailers are more likely to promote them as consumers become more sensitive to retail prices. This study concludes that consumer preferences play a crucial role in determining suppliers' decisions and coordination strategies in LCSCs. [ABSTRACT FROM AUTHOR]

In the public–private partnership (PPP) supply chain, trust serves as the foundation for collaboration between investment companies and suppliers. However, due to many uncertain factors, the evolution of trust remains a "black box" phenomenon. In order to analyze the impact of the evolution of trust in the PPP supply chain on investment companies and suppliers' strategic choices, and promote the healthy and sustainable development of PPP supply chain projects, this paper establishes a trust evolutionary game model, which analyzes the evolutionary paths under different scenarios and explores the impact of parameters on the cooperative strategies of participants. The findings indicate that trust asymmetry or an increase in trust can facilitate investment companies and suppliers to opt for positive cooperation strategies. Furthermore, both parties' strategies are less influenced by their initial willingness and more by trust degree. The moral risk coefficient and information asymmetry coefficient have a negative effect on the cooperative strategies, with the moral risk coefficient of investment companies exhibiting a more significant impact on the entire cooperation process. Moreover, both parties can only choose positive strategies when the information asymmetry coefficient is low. This study holds significant implications for promoting cooperation, enhancing contract performance, safeguarding the interests of all parties, and increasing cooperation satisfaction. [ABSTRACT FROM AUTHOR]

A MCOHP (micro-channel oscillating heat pipe) can provide lightweight and efficient temperature control capabilities for aerospace spacecraft with a high power and small size. The research about the heat flow effects on the thermal performance of MCOHPs is both necessary and essential for aerospace heat dissipation. In this paper, the heat flow effects on the thermal performance of MCOHPs are summarized and studied. The flow thermal performance enhancement changes of MCOHPs are given, which are caused by the heat flow work fluids of nano-fluids, gases, single liquids, mixed liquids, surfactants, and self-humidifying fluids. The use of graphene nano-fluids as the heat flow work medium can reduce the thermal resistance by 83.6%, which can enhance the maximum thermal conductivity by 105%. The influences of gravity and flow characteristics are also discussed. The heat flow pattern changes with the work stage, which affects the flow mode and the heat and mass transfer efficiency of OHP. The effective thermal conductivity varies from 4.8 kW/(m·K) to 70 kW/(m·K) when different gases are selected as the working fluid in OHP. The study of heat flow effects on the thermal performance of MCOHPs is conducive to exploring in-depth aerospace applications. [ABSTRACT FROM AUTHOR]

Applying blockchain to supply chain financing is an effective way to solve the problems of financing difficulties, high financing costs, and slow financing for small and medium-sized enterprises (SMZEs). Using evolutionary game theory, this study constructs a tripartite game model and analyzes the influence of blockchain technology on the evolutionary stability strategies for financial institutions (FIs), core enterprises (CEs), and SMZEs, in which the default losses of CEs and SMZEs are assumed to be dynamic. The results of this study are as follows: (1) When CEs and SMZESs' default losses are lower than some critical value, they tend to break their promises. (2) When accounts receivable are greater than some critical value, CEs cannot repay on time because they can make a relatively large profits from delayed repayment, whereas SMZEs can be constrained to be trustworthy. Finally, the results using numerical simulation show that both relatively large default losses and enough large, trustworthy income sources can make CEs and SMZEs tend to keep their promises; in turn, CEs would be non-paying and the SMZEs tend to be trustworthy for relatively large accounts receivable. The results provide theoretical support for realizing healthy and sustainable development for supply chain finance. [ABSTRACT FROM AUTHOR]

An appropriate project delivery system plays an essential role in sustainable construction project management. Due to the complexity of practical problems and the ambiguity of human thinking, selecting an appropriate project delivery system (PDS) is an enormous challenge for owners. This paper aims to develop a PDS selection method to deal with the related-indicators case by combining the advantages of Pythagorean fuzzy sets (PFSs) and Pythagorean fuzzy weighted Muirhead mean (PFWMM) operators. The contributions of this paper are as follows: (1) This study innovatively introduced the PFWMM operator to deal with PDS selection problems for the case of the relevance among all indicators affecting PDSs selection in a complex environment. (2) A new method of solving indicators' weights was proposed to adapt to the related-indicators PDS selection problem, through investigating the differences between the ideal PDS and the alternative PDS under all indicators. (3) A decision-making framework for PDS selection was constructed by comprehensive use of the advantages of PFSs and the PFWMM operator in dealing with related-indicators PDS decision-making problems. An example of selecting a PDS is exhibited to illustrate the effectiveness and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

The Markov random field model (MRF) has attracted a lot of attention in the field of remote sensing semantic segmentation. But, most MRF-based methods fail to capture the various interactions between different land classes by using the isotropic potential function. In order to solve such a problem, this paper proposed a new generalized probability inference with an anisotropic penalty for the object-based MRF model (OMRF-AP) that can distinguish the differences in the interactions between any two land classes. Specifically, an anisotropic penalty matrix was first developed to describe the relationships between different classes. Then, an expected value of the penalty information (EVPI) was developed in this inference criterion to integrate the anisotropic class-interaction information and the posteriori distribution information of the OMRF model. Finally, by iteratively updating the EVPI terms of different classes, segmentation results could be achieved when the iteration converged. Experiments of texture images and different remote sensing images demonstrated that our method could show a better performance than other state-of-the-art MRF-based methods, and a post-processing scheme of the OMRF-AP model was also discussed in the experiments. [ABSTRACT FROM AUTHOR]

Project procurement method (PPM) selection influences the efficiency of project implementation. Owners are presented with different options for project delivery. However, selecting the appropriate PPM poses great challenges to owners, given the existence of ambiguous information. The interval neutrosophic set (INS) shows power to handle imprecise and ambiguous information. This paper aims to develop a PPM selection model under an interval neutrosophic environment for owners. The main contributions of this paper are as follows: (1) The similarity measure is innovatively introduced with interval neutrosophic information to handle the PPM selection problem. (2) The similarity measure based on minimum and maximum operators is applied to construct a decision-making model for PPM selection, through considering the truth, falsity, and indeterminacy memberships simultaneously. (3) This study establishes a PPM selection method with INS by applying similarity measures, that takes account into the determinacy, indeterminacy, and hesitation from the decision experts when giving an evaluation value. A case study on selecting PPM is made to show the applicability of the proposed approach. Finally, the results of the proposed method are compared with those of existing methods, which exhibit the superiority of the proposed PPM selection method. [ABSTRACT FROM AUTHOR]

Interval Pythagorean fuzzy set (IPFS), which can handle imprecise and ambiguous information, has attracted considerable attention in both theory and practice. However, one of the main difficulties under IPFSs is the comparison between interval numbers. To overcome this shortcoming, connection number theory is first introduced, and interval numbers are transformed into connection numbers in the operating process. Considering that similarity measures play an important role in assessing the degree between ideal and proposal alternatives in the decision making process, this paper aims to develop new similarity measures with IPFSs and apply them to multi-criteria decision making (MCDM) problems. The main contributions of this paper are as follows: (1) introduction of a comparison method through transforming interval numbers into connection numbers; (2) development of three new similarity measures with IPFSs based on the minimum and maximum operators, and investigation of their properties; (3) calculation of the similarity measures considering weights of membership and non-membership degrees; (4) establishment of an interval Pythagorean fuzzy decision making method applying the presented similarity measures. A case study on selecting a project delivery system is made to show the applicability of the proposed approach. [ABSTRACT FROM AUTHOR]