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The purpose of this paper is to establish a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities in Henan Province.

The clustering process is divided into two stages. In the first stage, grey cloud clustering coefficient vectors are obtained by grey cloud clustering. In the second stage, with the help of the weight kernel clustering function, the general representation of the weight vector group of kernel clustering is given. And a new coefficient vector of kernel clustering that integrates the support factors of the adjacent components was obtained in this stage. The entropy resolution coefficient of grey cloud clustering coefficient vector is set as the demarcation line of the two stages, and a two-stage grey cloud clustering model, which combines grey and randomness, is proposed.

This paper demonstrates that 18 cities in Henan Province are divided into five categories, which are in accordance with five drought hazard levels. And the rationality and validity of this model is illustrated by comparing with other methods.

This paper provides a practical and effective new method for drought risk assessment and, then, provides theoretical support for the government and production departments to master drought information and formulate disaster prevention and mitigation measures.

The model in this paper not only solves the problem that the result and the rule of individual subjective judgment are always inconsistent owing to not fully considering the randomness of the possibility function, but also solves the problem that it’s difficult to ascertain the attribution of decision objects, when several components of grey clustering coefficient vector tend to be balanced. It provides a new idea for the development of the grey clustering model. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

This paper aims to present a novel approach to facial recognition that enhances privacy by using radio frequency identification (RFID) technology combined with transformer models, eliminating the need for visual data and thus reducing privacy risks associated with traditional image-based systems.

The proposed RFID-transformer recognition system (RTRS) uses RFID technology to capture signal features such as phase and received signal strength indicator, which are then processed by a transformer model. The model is specifically designed to handle structured RFID data, capturing subtle patterns and dependencies to achieve accurate biometric recognition. The system’s performance was validated through comprehensive experiments involving different environmental conditions and user scenarios.

The experimental results demonstrate that the RTRS system achieves a recognition accuracy of 98.91%, maintaining robust performance across various challenging conditions, including low-light environments and changes in face orientation. In addition, the system provides a high level of privacy preservation by avoiding the collection and storage of visual data.

To the best of the authors’ knowledge, this work introduces the first RFID-based facial recognition system that fully leverages transformer models, offering a privacy-preserving alternative to traditional image-based methods. The system’s ability to perform accurately in diverse scenarios while ensuring user privacy makes it a significant advancement in biometric technology.

The possibility function-based grey clustering model has evolved into a complete approach for dealing with uncertainty evaluation problems. Existing models still have problems with the choice dilemma of the maximum criteria and instances when the possibility function may not accurately capture the data's randomness. This study aims to propose a multi-stage skewed grey cloud clustering model that blends grey and randomness to overcome these problems.

First, the skewed grey cloud possibility (SGCP) function is defined, and its digital characteristics demonstrate that a normal cloud is a particular instance of a skewed cloud. Second, the border of the decision paradox of the maximum criterion is established. Third, using the skewed grey cloud kernel weight (SGCKW) transformation as a tool, the multi-stage skewed grey cloud clustering coefficient (SGCCC) vector is calculated and research items are clustered according to this multi-stage SGCCC vector with overall features. Finally, the multi-stage skewed grey cloud clustering model's solution steps are then provided.

The results of applying the model to the assessment of college students' capacity for innovation and entrepreneurship revealed that, in comparison to the traditional grey clustering model and the two-stage grey cloud clustering evaluation model, the proposed model's clustering results have higher identification and stability, which partially resolves the decision paradox of the maximum criterion.

Compared with current models, the proposed model in this study can dynamically depict the clustering process through multi-stage clustering, ensuring the stability and integrity of the clustering results and advancing grey system theory.

This study examines the effect of cross-border network ties of returnee entrepreneurs on the foreign market diversity of their ventures. The study further investigates how two cross-cultural competencies (global mindset and cultural intelligence) moderate this effect.

A sample of 135 returnee entrepreneurial ventures from China was used to test the hypotheses.

This study finds that returnee entrepreneurs tend to enter into a wide range of culturally different country groups when returnee entrepreneurs have strong cross-border network ties. Moreover, global mindset and cultural intelligence function as complements in strengthening the effect of the cross-border network ties on foreign market diversity.

The authors contribute to both returnee entrepreneurship and foreign market entry literature in two ways. First, by examining the effect of cross-border network ties on foreign market entry, the authors add new and important insights into the role of social networks in the pre-internationalization phase. This is useful in understanding the internationalization process of new ventures founded by returnees, which have not been fully understood in returnee entrepreneurship literature. Second, by examining the moderating roles of global mindset and cultural intelligence, the authors enhance the understanding of the extent to which cross-border networks can be valuable in foreign market entry.

Implementing effective marketing strategies can reduce consumers' perceived risks and promote the development of the remanufacturing market. The paper aims to explore the impact of two marketing strategies on the remanufacturing decisions of an original equipment manufacturer (OEM) and investigates the design of the optimal warranty service (WS) and consumer education (CE) strategies. Moreover, the authors also examine the optimal marketing strategy choices using the three criteria of OEM: profitability, consumer surplus and environmental impact (EI).

The authors develop a stylized model by game theory, which characterizes how an OEM that produces and sells both new and remanufactured products (RPs) should design the optimal remanufacturing marketing activity, and how to choose between different remanufacturing marketing strategies. Moreover, consumer's utility theory is used to describe consumers' perception of different remanufacturing marketing strategies to derive product demand.

The results reveal that increasing the warranty and education levels will not always improve the firm's profitability; the result depends heavily on the size of the functionality-oriented consumer (FOC) segment. Remanufacturing marketing strategies might harm the OEM, consumers and environment under certain conditions. Moreover, the optimal marketing strategy selections are jointly influenced by the FOC segment and the new production cost. There exist triple-win regions in which the OEM should not hesitate to perform WS and CE.

Few studies focus on the design and choice of remanufacturing marketing strategies, especially considering the role of consumer perceived behavior. This research contributes the behavioral remanufacturing marketing management and provides managerial implications for the implementation of OEM remanufacturing marketing strategy.

This paper investigates how a regulator pursuing social welfare maximization designs an optimal subsidy scheme to stimulate technology innovation in the presence of a consumer green premium. Specifically, the authors solve the following questions: (1) Does the consumers' green premium affect the design of the subsidy scheme? (2) How should the firm choose a green technology innovation strategy under the optimal subsidy scheme? (3) Does technology innovation bring higher social welfare and lower environmental impact?

The authors first develop a game model to explore the impact of subsidy schemes on social welfare without considering technology innovation. Then the authors investigate two innovation strategies, in-house innovation and external introduction, under the optimal subsidy scheme. Finally, they illustrate the optimal choices of innovation strategy for the firm, consumers and regulators.

The results reveal that the subsidy scheme will not always increase social welfare, which depends on the environmental improvement coefficient of the unit green level. The optimal subsidy level increases with the green premium, but it is not related to the size of the consumer green segment. Moreover, the success rate of in-house innovation will raise the optimal green level, but the company benefits from an increased success rate of in-house innovation only when the green segment is large enough. The green segment size and external green level jointly determine the choice of technology innovation strategy.

This research is the first to analyze this problem while considering the green demand and subsidy scheme simultaneously as drivers of a firm's technology innovation, thereby providing new managerial implications for decisions by the regulator and firms.

A section of in-service PE gas pipeline in Guocun, Beijing, was found to appear gas leaking at the electrofusion (EF) joint. This study is dedicated to reveal the material cause of EF joint failure to help with a more accurate prediction of service life of PE gas pipe and further normalize the construction of PE gas pipeline.

Defect detection was carried out on the leaking EF joint using ultrasonic phased array. The mechanical degradation and structural aging behavior was studied by tension test, FTIR technology, TG test and DSC test. The organic components in the soil surrounding the PE gas pipe failure area were qualitatively identified.

The results showed that the organic surfactants in the soil environment could accelerate the aging behavior of PE material, leading to a deterioration of mechanical properties and a serious reduction in the ability of the PE pipe and EF joint, especially at the welding defect, to resist external force.

A novel study was conducted to investigate the failure cause of the EF joint of in-service PE gas pipe, incorporating the analysis of environmental factors and structural deterioration.

The service environment of urban polyethylene (PE) pipes has a crucial influence on their long-term safety and performance. Based on the application and structural performance analysis of PE pipe failure cases, this study aims to investigate the impact of organic substances in the soil on the aging behavior of PE pipes by designing organic solutions with different concentrations, which are based on the composition of organic substances in the soil environment, and periodic immersion tests.

Soil samples in the vicinity of the failed pipes were analyzed by gas chromatography-mass spectrometry, sensitive organic substances were screened and soaking solutions of different concentrations were designed. After the soaking test, the PE pipe samples were analyzed using differential scanning calorimetry, Fourier-transform infrared spectroscopy and other testing methods.

The performance difference between the outer surface and the middle of the cross section of PE pipes highlights the influence of the soil service environment on their aging. Different organic solutions can have varying impacts on the aging behavior of PE pipes when immersed. For instance, when exposed to amine organic solutions, PE pipes may have an increased weight and decreased material yield strength, although there is no reduction in their thermal or oxygen stability. On the contrary, when subjected to ether organic solutions, the surface of PE pipe specimens may be affected, leading to a reduction in material fracture elongation and a decrease in their thermal and oxygen stability. Furthermore, immersion in either amine or ether organic solutions may result in the production of hydroxyl and other aging groups on the surface of the material.

Understanding the potential impact of organic substances in the soil environment on the aging of PE pipe ensures the long-term performance and safety of urban PE pipe. This research approach will provide valuable insights into improving the durability and reliability of urban PE pipes in soil environments.

The purpose of this study is to modify cerium dioxide with fumaric acid (CeO₂-f) to improve its compatibility and dispersibility in epoxy resin and to investigate the effect of the content on the coating performance.

To investigate whether CeO₂-f reacts with epoxy resin by ring opening, CeO₂-f and epoxy resin-treated CeO₂-f (Ce CeO₂-f/EP) were analyzed by infrared radiation (IR), X-ray diffraction (XRD) and ultraviolet-visible diffuse reflectance spectroscopy (UV-Vis). To reveal the effect of different content on coatings properties, neutral salt spray test (NSST) and electrochemical test were performed.

The results of IR, XRD, X-ray photoelectron spectroscopy and UV-Vis indicated that fumaric acid attached to the CeO₂ surface by chemical bonding and underwent a ring-opening reaction with epoxy resin, thus, improving the compatibility of CeO₂ in epoxy resin. NSST and electrochemical impedance spectroscopy results showed that the coatings containing 5% CeO₂-f exhibited the optimal corrosion resistance. The reason is that a dense conversion film was established on the substrate surface.

The epoxy coatings using CeO₂-f as fillers with synergistic inhibition ability are promising for the protection of carbon steel.