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The purpose of this article is to map the state-of-art of entropy, a knowledge domain which has drawn a great interest of researchers from a variety of academic fields in modern times. The journal Entropy, which focuses completely on entropy and is therefore regarded as the most prominent journal, has been purposefully chosen for this study in order to examine the intellectual structure of the field. Data from the Web of Science database for the years 2008 through 2021 were gathered. Scientometric indicators, literature growth, co-authorship, co-citation, keyword co-occurrences, co-word, citation, and bibliographic coupling, are studied using VOS Viewer. Highly cited papers, most prolific authors, countries and institutions are also identified. The results of the study admit that the linear growth trend of entropy articles has increased over the course of the investigation. Highest number of the publications were contributed from China, and the institution that contributed the most articles was the Chinese Academy of Sciences. A cluster analysis of the keywords shows that the research hotspots are primarily focused on "entropy," with the highest frequency and link strength. The high density of the co-words of "entropy," "information," "model" and "Shannon entropy" has also proved them to be the most mature and centralized area of entropy field. [ABSTRACT FROM AUTHOR]

Accurate risk assessment of international scientific and technological (S&T) cooperation is significant to international cooperation. In this paper, 5 risk dimensions with respect to the political, economic, social, cultural as well as technological of the regional comprehensive economic partnership countries (RCEP) are selected to establish a proper S&T cooperation index system for risk assessment. To calculate the weight of each index, a cross-entropy combination weighting method is proposed based on the combination weighting method of game theory. Furthermore, the standard cloud model is constructed by using the golden ratio, and the risk of S&T cooperation among the RCEP countries is analyzed by the cloud model. The results show that the combination weighting method proposed in this paper is effective, and its calculation is simpler than that of the game theory combination weighting method. Besides, compared with political, social, cultural, and technological indicators, economic indicators have a greater impact on S&T cooperation risk. Furthermore, it is also obtained from the results that the risk of S&T cooperation with China and the Philippines is at a lower to low level and medium to higher level, respectively, and the risk of S&T cooperation with other countries is all at a lower to medium level. [ABSTRACT FROM AUTHOR]

Evaluating the importance of nodes in coal transportation networks and identifying influential nodes is a crucial study in the field of network science, vital for ensuring the stable operation of such complex networks. However, most existing studies focus on the performance analysis of single-medium networks, lacking research on combined transportation, which is not applicable to China's coal transportation model. To address this issue, this paper first establishes a static topological structure of China's coal-iron-water combined transportation network based on complex network theory, constructing a node importance evaluation index system through four centrality indicators. Subsequently, an enhanced TOPSIS method (GRE-TOPSIS) is proposed based on the Grey Relational Entropy Weight (GRE) to identify key nodes in the complex network from local and positional information dimensions. Compared to previous studies, this research emphasizes composite networks, breaking through the limitations of single-medium network research, and combines gray relational analysis with entropy weighting, enhancing the objectivity of the TOPSIS method. In the simulation section of this paper, we establish the model of China's coal-iron-water combined transportation network and use the algorithm to comprehensively rank and identify key nodes in 84 nodes, verifying its performance. Network efficiency and three other parameters are used as measures of network performance. Through simulated deliberate and random attacks on the network, the changing trends in network performance are analyzed. The results show that in random attacks, the performance drops to around 50% after damaging nearly 40 ordinary nodes. In contrast, targeting close to 16 key nodes in deliberate attacks achieves a similar effect. Once key nodes are well protected, the network exhibits a certain resistance to damage. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to provide scientific guidance for the integration of industrialization and information (TIOII). In recent years, TIOII has promoted the development of intelligent manufacturing in China. However, many enterprises blindly invest in TIOII, which affects their normal production and operation. Design/methodology/approach: This study establishes an efficiency evaluation model for TIOII. In this paper, entropy analytic hierarchy process (AHP) constraint cone and cross-efficiency are added based on traditional data envelopment analysis (DEA) model, and entropy AHP–cross-efficiency DEA model is proposed. Then, statistical analysis is carried out on the integration efficiency of enterprises in Guangzhou using cross-sectional data, and the traditional DEA model and entropy AHP–cross-efficiency DEA model are used to analyze the integration efficiency of enterprises. Findings: The data show that the efficiency of enterprise integration is at a medium level in Guangzhou. The efficiency of enterprise integration has no significant relationship with enterprise size and production type but has a low negative correlation with the development level of enterprise integration. In addition, the improved DEA model can better reflect the real integration efficiency of enterprises and obtain complete ranking results. Originality/value: By adding the entropy AHP constraint cone and cross-efficiency, the traditional DEA model is improved. The improved DEA model can better reflect the real efficiency of TIOII and obtain complete ranking results. [ABSTRACT FROM AUTHOR]

More and more Chinese enterprises have participated in the Belt and Road initiative (BRI) since its launch in 2013. However, have they all actually benefited? Which companies otherwise have benefited most from the plan? To answer these questions, this paper analyzes the impact of the BRI on Chinese enterprises. Among several findings, it reveals that the performance of companies remained low even though the initiative policy initially stimulated performance, the performance of enterprises depends on the geographical location of enterprises and that the returns of China's outward foreign direct investment in various industries became more volatile with only the mining industry enjoying better returns. Thus, the paper shows that the BRI offers Chinese enterprises opportunities but also brings challenges for companies to optimize the allocation of their resources and improve the performance of their investments. [ABSTRACT FROM AUTHOR]

(1) In recent years, with China's increasing investment in the transportation industry, the construction of highways and bridges has flourished, bringing great convenience to people's lives. At the same time, there are many uncertain factors in the process of bridge construction, being prone to construction risks. In order to meet the requirements of sustainable development, it is necessary to accurately evaluate the safety risk level of bridge construction. Therefore, it is necessary to establish a new scientific safety risk evaluation system for highway bridge construction. (2) Methods. Based on the relevant standards and specifications, this paper establishes a highway bridge construction safety risk evaluation index system, and then uses the cloud entropy weight method to objectively weight each risk index, using cloud model theory to conduct a risk assessment, and through the cloud model images directly determine the overall risk level of bridge construction, and the level of risk indicators. (3) Results. Applying this method to the construction safety risk assessment of a particular bridge, the overall construction risk level of the bridge is obtained as "level 4", and the risk levels of the four first-level indicators are also all "level 4". (4) Conclusions. The cloud entropy weight method proposed in this paper and the traditional AHP-Extenics method are applied to a bridge construction safety risk evaluation, and the evaluation results obtained are consistent. However, this paper uses the cloud model to improve the entropy weight method in order to calculate the weights, which fully reflects the objectivity of the assignment. The cloud model is used for evaluation, and the risk level of indicators can be determined visually with images. [ABSTRACT FROM AUTHOR]

The evolution of power system is a dynamic and complex process. Whether the evolution of power system can adapt to the macro environment and develop with all subsystems within the system depends on the matching and integration development among different evolutionary subjects. Based on the dissipation theory and Brusselator model, this paper constructs an evolutionary synergy model of the power system, and quantitatively analyzes the evolutionary synergy relationship between the evolving subjects of the power system and the overall evolutionary process of the power system. Then, from the socio- technical system transformation theory, we analyze the evolutionary elements of macro-environmental level, meso-institutional level and micro-beneficial level in the process of system transformation in China and the interaction among them. Finally, by comparing the entropy changes of the evolutionary participant subjects and the overall power system at each stage, the endogenous mechanism of the power system, the external elements and their interactions on the system development are studied in order to reveal the evolutionary synergistic law of China's power system and make suggestions for the development of the new power system. [ABSTRACT FROM AUTHOR]

Railway transportation system is one of the most important components of the integrated transportation system. A functional and efficient railway transportation system can be conducive to sustainable development of society and economy, thus highlighting the importance of studies on railway transportation efficiency. Therefore, this research proposes the cross‐efficiency evaluation method based on the relative entropy evaluation method (CERE) to evaluate railway transportation efficiency in China. Firstly, the research constructs an evaluation indicators system for railway transportation efficiency from the perspective of input‐output. Secondly, the paper obtains cross‐efficiency matrix by using the cross‐efficiency evaluation method (CE). Then, the study takes the obtained the cross‐efficiency matrix as the decision matrix of multiple criteria decision‐making (MCDM) problem, and applies the relative entropy evaluation method to evaluate the efficiency of railway transportation. Finally, the empirical analysis of the efficiency evaluation results for 18 railway transportation companies shows that, in 2019, Taiyuan Railway Transportation Company has the highest efficiency score, owing probably to a greater coal railway transportation demand and an advanced railway heavy haul transportation technology; railway transportation companies in the Eastern China typically have the highest efficiency scores, owing probably to a greater regional railway transportation demand. [ABSTRACT FROM AUTHOR]

Selecting the right partner is a key factor for the successful construction of the strategic alliance of prefabricated construction enterprises in China. Based on the summarization of domestic and foreign studies, combined with the characteristics of the strategic alliance of prefabricated construction enterprises, the paper has constructed an evaluation indicator system of the partner selection of the strategic alliance of prefabricated construction enterprises in China. The paper also has conducted an empirical study on the evaluation model of partner selection of the strategic alliance of prefabricated construction enterprises in China by using the method Entropy Weight-TOPSIS. The research results show that the five most influential second-level indicators are commercial housing sales capability, property management capability, commitment of capital, commitment of talents, and product innovation capability. The model constructed in the paper can comprehensively evaluate and select the strategic alliance partners of prefabricated construction enterprises in China. [ABSTRACT FROM AUTHOR]

This paper chooses the most representative second-tier coastal cities in the critical period of China's economic transformation as the research object. This paper innovatively constructs the evaluation system of manufacturing transformation and upgrading environmental measurement from the specific content contained in ''Made in China 2025'' which leads the transformation and upgrading of China's manufacturing industry. Using the combination of factor analysis and cluster analysis, combined with the entropy weight method of objective weighting, the measurement and difference of coastal environment in manufacturing transformation and upgrading are studied. The results show that the development environment of the transformation and upgrading of the manufacturing industries in different cities is quite different. The most prominent feature of the empirical analysis is that Hangzhou is a typical city, showing that the supporting factors of innovation capability play an important role in the transformation and upgrading of manufacturing. [ABSTRACT FROM AUTHOR]

The development of Xiongan New Area in Hebei Province, China, as a significant national choice, has considerable strategic significance for the integrated growth of Beijing, Tianjin, and Hebei. This paper proposes a cloud model for the suitability evaluation of the construction of Xiongan New Area based on entropy weight analysis, taking into account the geological conditions, groundwater environment, environmental geological problems, and other factors of the suitability of image city development. According to the research, the suitability evaluation findings for the project building employing the cloud model are in strong accord with those of the traditional model and have some application potential. The evaluation's findings indicate that the project construction in Xiongan New Area is acceptable, with suitable and relatively suitable sites making up 81.4% of the total area and excellent circumstances for project development, construction, and usage. This study offers helpful direction for Xiongan New Area's urban land-space design and serves as a useful point of comparison for studies looking at the viability of other deep Quaternary Plain region engineering buildings. [ABSTRACT FROM AUTHOR]

Suitability assessment is an essential initial step in the scientific utilization of underground space. It plays a significant role in providing valuable insights for optimizing planning and utilization strategies. Utilizing urban underground space has the potential to enhance the capacity of urban infrastructure and public service facilities, as well as mitigate issues such as traffic congestion and land scarcity. To effectively plan and utilize urban underground space, it is crucial to conduct a suitability assessment. This assessment helps identify the factors that influence the utilization of underground space and their impacts, offering guidance on avoiding unfavorable conditions and ensuring the safety of planned underground facilities. To achieve objective and reasonable evaluation results, this paper proposed an assessment method that combines entropy and CRITIC (CRiteria Importance Through Intercriteria Correlation) weighting. Taking Xiong'an New Area as a study area, a suitability assessment indicator system for underground space was established. The system included criteria indicators and sub-criteria indicators. By analyzing the weights, the study identified the difference of suitability and critical affecting factors for shallow, sub-shallow, sub-deep, and deep underground space. The results showed that deep layers had better suitability than shallow layers in the study area. The regions with inferior and worse suitability were mostly located around Baiyangdian Lake, with proportions of acreage at 54.69% for shallow layer, 42.06% for sub-shallow layer, 41.69% for sub-deep layer, and 42.03% for deep layer. Additionally, the dominant affecting factors of suitability varied in different layers of underground space. These findings provide valuable evidence for the scientific planning and disaster prevention of underground space in Xiong'an New Area, and also serve as references for studying suitability in other areas. [ABSTRACT FROM AUTHOR]

In this paper, the factors influencing the passenger flow of rail transit stations in Shanghai of China are studied by using the entropy weight-grey correlation model. The model assumptions and the corresponding variables are proposed, including traffic accessibility, built environment, regional characteristics of the district to which the rail transit station belongs, conditions of the station and spatial location, which affect the passenger flow of rail transit stations. Based on the assumptions and the variables, the entropy weight-grey correlation model for analyzing the passenger flow of urban rail transit stations is presented. By collecting the data of passenger flow of rail transit stations and corresponding influencing factors in Shanghai, the results of the entropy weight-grey correlation model are obtained. It is shown that the influencing factors, such as the distances from the rail transit station to the adjacent third-class hospital and the adjacent large commercial plazas, district committees, parking areas and the transaction price of important plots, and the gross output value of the tertiary industry, have significant impacts on the passenger flow of a subway station. Finally, some suggestions are proposed for the local governments to formulate improved policies for rail transit development. The conclusions can provide a reference for the development of rail transit in other large cities and countries. [ABSTRACT FROM AUTHOR]

While China's digital trade is developing rapidly, it is facing the problem of uncoordinated and uneven regional development. In order to explore countermeasures to bridge the differences in regional digital trade, this paper first measures the development level of digital trade in 11 provinces of the Yangtze River Economic Belt through entropy-weighting TOPSIS. Secondly, the fuzzy set Qualitative Comparative Analysis method was used to analyze the influencing factors and improvement paths of digital trade development in various provinces of the Yangtze River Economic Belt. The research results show that: first, the current development level of digital trade is gradually weakening from east to west, especially the development of digital trade in the Yangtze River Delta region is the best, showing a large regional imbalance and uncoordinated development. What's more, the market size and urbanization have the most significant impact on the development of digital trade. Finally, we examine the reliability of the results by sensitivity analysis, and find that our ranking results are robust. In the future, China should continue to actively promote the coordinated development strategy of regional economy and participate in international digital trade exchanges and cooperation, so as to promote the coordinated and high-quality development of digital trade. [ABSTRACT FROM AUTHOR]

The spatial interaction model is an effective way to explore the geographical disparities inherent in the Belt and Road Initiative (BRI) by simulating spatial flows. The traditional gravity model implies the hypothesis of equilibrium points without any reference to when or how to achieve it. In this paper, a dynamic gravity model was established based on the Maximum Entropy (MaxEnt) theory to estimate and monitor the interconnection intensity and dynamic characters of bilateral relations. In order to detect the determinants of interconnection intensity, a Geodetector method was applied to identify and evaluate the determinants of spatial networks in five dimensions. The empirical study clearly demonstrates a heterogeneous and non-circular spatial structure. The main driving forces of spatial-temporal evolution are foreign direct investment, tourism and railway infrastructure construction, while determinants in different sub-regions show obvious spatial differentiation. Southeast Asian countries are typically multi-island area where aviation infrastructure plays a more important role. North and Central Asian countries regard oil as a pillar industry where power and port facilities have a greater impact on the interconnection. While Western Asian countries are mostly influenced by the railway infrastructure, Eastern European countries already have relatively robust infrastructure where tariff policies provide a greater impetus. [ABSTRACT FROM AUTHOR]

Background: As the world's largest coal producer, China was accounted for about 46% of global coal production. Among present coal mining risks, methane gas (called gas in this paper) explosion or ignition in an underground mine remains ever-present. Although many techniques have been used, gas accidents associated with the complex elements of underground gassy mines need more robust monitoring or warning systems to identify risks. This paper aimed to determine which single method between the PCA and Entropy methods better establishes a responsive weighted indexing measurement to improve coal mining safety. Methods: Qualitative and quantitative mixed research methodologies were adopted for this research, including analysis of two case studies, correlation analysis, and comparative analysis. The literature reviewed the most-used multi-criteria decision making (MCDM) methods, including subjective methods and objective methods. The advantages and disadvantages of each MCDM method were briefly discussed. One more round literature review was conducted to search publications between 2017 and 2019 in CNKI. Followed two case studies, correlation analysis and comparative analysis were then conducted. Research ethics was approved by the Shanxi Coking Coal Group Research Committee. Results: The literature searched a total of 25,831publications and found that the PCA method was the predominant method adopted, and the Entropy method was the second most widely adopted method. Two weighting methods were compared using two case studies. For the comparative analysis of Case Study 1, the PCA method appeared to be more responsive than the Entropy. For Case Study 2, the Entropy method is more responsive than the PCA. As a result, both methods were adopted for different cases in the case study mine and finally deployed for user acceptance testing on 5 November 2020. Conclusions: The findings and suggestions were provided as further scopes for further research. This research indicated that no single method could be adopted as the better option for establishing indexing measurement in all cases. The practical implication suggests that comparative analysis should always be conducted on each case and determine the appropriate weighting method to the relevant case. This research recommended that the PCA method was a dimension reduction technique that could be handy for identifying the critical variables or factors and effectively used in hazard, risk, and emergency assessment. The PCA method might also be well-applied for developing predicting and forecasting systems as it was sensitive to outliers. The Entropy method might be suitable for all the cases requiring the MCDM. There is also a need to conduct further research to probe the causal reasons why the PCA and Entropy methods were applied to each case and not the other way round. This research found that the Entropy method provides higher accuracy than the PCA method. This research also found that the Entropy method demonstrated to assess the weights of the higher dimension dataset was higher sensitivity than the lower dimensions. Finally, the comprehensive analysis indicates a need to explore a more responsive method for establishing a weighted indexing measurement for warning applications in hazard, risk, and emergency assessments. [ABSTRACT FROM AUTHOR]

Recently, rapid urbanization has contributed to an increasingly dominant trend of people congregating around river basins. As a result, significant changes in land use structure occur, leading to alterations in ecosystem structure and gradual degradation of ecological service functions. Using the DLB (Dianchi Lake Basin) in southwestern China as the research area, this essay analyzed its land use structure in 2020 and constructed an urban eco-resilience evaluation system based on the three dimensions of "resistibility, adaptability, and recuperability" derived from the eco-resilience theory. Meanwhile, the physical coupling model was used to calculate the coupling coordination degree of land use and eco-resilience in the area. Research shows: (1) the DLB is a complete and relatively independent ecosystem, with diverse land use types in the watershed, and the land use structure of the watershed is related to altitude and economic development; (2) the overall eco-resilience of the area has significant spatial differences in distribution. The eco-resilience of the lakeside built-up area is the lowest eco-resilience, and the regions with higher resilience are primarily those surrounding the lake or hills. (3) According to the coupling coordination degree model, the calculated coupling degree of land use and eco-resilience is 0.49, and the coordination degree is 0.38, indicating early stages of the coupling coordination progress. This paper developed a comprehensive evaluation model of land use and river basin eco-resilience, and studied the coupling relationship between the two. This holds theoretical and practical significance for ecological protection and sustainable development of DLB. [ABSTRACT FROM AUTHOR]

With the steady development of China's economy, under the new economic normal, the creative cultural industry has been continuously optimized and developed in terms of structure, scale and quality, and the connotation of the creative cultural industry has been continuously enriched, forming a three-dimensional and diversified pattern. With the help of high-tech, culture, multimedia and other means, the current creative cultural industry is continuously absorbing and integrating it on a large scale, promoting the optimization, upgrading and innovative development of the industry. The consumer competitiveness evaluation in creative and cultural industries is a classical MAGDM problems. In this paper, WDBA method is designed for solving the probabilistic linguistic MAGDM(PL-MAGDM) with the completely unknown weights. In the end, an empirical application for consumer competitiveness evaluation in creative and cultural industries is used to demonstrate the use of the developed method. The proposed method can also contribute to the selection of suitable alternative successfully in other selection problems. [ABSTRACT FROM AUTHOR]

In China, as an important source of renewable energy, the standard biogas production module (SBPM) plays a key role and accounts for the majority of biogas production. Given its greater environmental pollution, it is particularly important to assess its quantitative sustainability status for optimizing system design and policy-making. This paper conducted the sustainability assessments of the open-loop standard biogas production module (OL-SBPM) and closed-loop standard biogas production module (CL-SBPM). Compared with the OL-SBPM system, the CL-SBPM system integrates a power generation subsystem. To evaluate two types of systems quantitatively, energy, emergy and entropy methods have been utilized in this study. The results illustrated that only partial indicators are more sustainable in the CL-SBP system rather than all indicators by comparing with the OL-SBPM system, which is contrary to the prevailing view. Taking the information entropy as an example, the equivalent information entropy flow values of the OL-SBPM and CL-SBPM systems are 2.04 × 1025 bits and 1.47 × 1025 bits, respectively, which also demonstrate that the OL-SBPM system has more useful information resulting in higher degree of sustainability. Therefore, these two systems need to be selected according to the existing conditions, rather than the subjective ideation. [ABSTRACT FROM AUTHOR]

The human body needs nutrients to maintain its regular physiological activity. It requires 40 essential nutrients, including macronutrients (carbohydrates, protein, and fat) and micronutrients (vitamins and minerals). Although macronutrient intake has been improved in China due to people's increased social awareness, the population's micronutrient intake remains insufficient. Objective: The current food evaluation system is primarily used to assess macronutrients, while an effective assessment method for micronutrients is still lacking. Fruits and vegetables are low-energy food sources that mainly provide vitamins and minerals and supply the human body with various micronutrients. Methods: In this paper, the entropy and fuzzy recognition methods were used to construct the Vitamin Index (Vitamin Index = Vitamin A Index + Vitamin Comprehensive Index + Vitamin Matching Index) and Mineral Index (Mineral Index = Calcium Index + Mineral Comprehensive Index + Mineral Matching Index) and to evaluate the micronutrient quality of 24 vegetables and 20 fruits. Results: The assessment results showed that Chinese dates displayed the highest Vitamin and Mineral Index among fruits (Vitamin Index = 2.62 and Mineral Index = 2.63), while collard greens had the highest Vitamin Index of the vegetables, at 2.73, and red amaranth had the highest Mineral Index, at 2.74. Conclusions: The study introduces a new method for assessing the nutritional quality of micronutrients, which provides a new idea for assessing the nutrient quality of agricultural products. [ABSTRACT FROM AUTHOR]

With the continuous construction of transportation infrastructure, intersection nodes have been increasing rapidly, bringing growing numbers of tunnel- and exit-adjacent sections (TEAS) in mountain expressways in China. With the complex variation in the surrounding environment, drivers always face congestion and confusion on tunnel and the exit connecting sections (TECS) without adequate length, meanwhile excessively long TECS create detours. To better provide a sustainable design strategy for TEAS, based on a certain section of expressway in Shaanxi, China, this paper establishes a theoretical calculation model through analysis. The characteristics of traffic flow and drivers' light adaptation at tunnel exit are obtained through data collection and driving tests, and the length requirements of the tunnel and exit connecting sections (TECS) are discussed. A VISSIM microscopic simulation model is also built under various design schemes and entropy-based multi-attribute decision making (EBMADM) is used to objectively calculate the weights of the four selected evaluation indexes. Then, the design schemes of the TECS with different lengths have been comprehensively evaluated. The results show the match between the evaluation results of EBMADM with theoretical calculations under existing traffic conditions, which proves the rationality of EBMADM in such problems. For more cases, the results of the EBMADM evaluation show a positive correlation between the length of TECS for the best performing design scheme with traffic volume and diverging ratio. [ABSTRACT FROM AUTHOR]

As a new economic form that has emerged from the technological and digital revolution, the digital economy has great benefits to the green development of the economy, protection of the ecological environment, and improvement in social well-being. This study examines whether the digital economy affects the inclusive green growth (IGG). Measurement index system for the digital economy and IGG from 2013 to 2020 in China was constructed and the entropy evaluation method and super-efficiency epsilon-based measure (Super-EBM) model was used to evaluate them. We examined the direct effect, mediation effect, and spatial spillover effect of the digital economy on IGG using the basic regression model, mediating effect model, and the spatial Durbin model. Our results revealed that the development of the digital economy has clear regional differences. The role of digital economy on IGG has positive direct effects and positive spatial spillover effects. The digital economy affects IGG through industrial structure upgrading, so industrial structure upgrading has a significant intermediary effect. By comparing the coefficients, we found that the spatial spillover effects are stronger than the direct effects. Absorbing the spillover of the digital economy in surrounding areas is particularly important for promoting IGG. Heterogeneity analysis revealed that the digital economy is better for IGG and releases more digital dividends in eastern China. Finally, the research conclusions of this paper provide reference for the Chinese government to formulate relevant policies to deepen the integration of digital information technology and IGG, and promote the coordinated development of regional digital economy and IGG. [ABSTRACT FROM AUTHOR]

In compensation events in some parts of China, funds for water and ecological compensation are usually allocated using the factor allocation method, which often fails to satisfy all stakeholders and affects the overall efficiency of ecological compensation Managers need to rethink the effectiveness of the fund allocation method in order to reduce stakeholder complaints and maintain the stability of the ecological protection system. In addition, the dynamic adjustment of the weights in the funding allocation process is an important means of satisfying stakeholders in real time. This paper is based on the entropy weight method (EWM), which has an objective weighting process, introduces fuzzy cognitive map (FCM) theory, integrates objective entropy weights with the state values in FCM, and uses the advantages of the objective assignment of EWM to compensate for the subjective nature of the initial assignment of FCM. At the same time the correlation weights of FCM provide a feedback mechanism for EWM allocation, which makes EWM dynamically adjustable and enhances the practicality of EWM allocation, resulting in an EWM-FCM integration method. The feedback function of the method was used to calculate the case of water ecological compensation funds allocated for the Yellow River (Henan section) in China, and a variety of options for the allocation ratio of water ecological compensation funds were calculated. Stakeholders could choose the appropriate option according to the agreement, which improved the efficiency and satisfaction of the allocation. [ABSTRACT FROM AUTHOR]

This paper defines five criteria and identifies 21 indicators for the modernization level of a province or a city in modern China. It collects raw index data from 31 provinces in China, between 2007 and 2017, and introduces formula for its dimensionless processing. An improved entropy method (IEM) is proposed for the evaluation of the modernization in urban areas, based on the five criteria and 21 indicators. A practical study was implemented in Anhui province employing the said IEM. The results demonstrate that the IEM is being effective in evaluating the modernization level in urban areas. [ABSTRACT FROM AUTHOR]

Due to the significant intermittent, stochastic and non-stationary nature of wind power generation, it is difficult to achieve the desired prediction accuracy. Therefore, a wind power prediction method based on improved variational modal decomposition with permutation entropy is proposed. First, based on the meteorological data of wind farms, the Spearman correlation coefficient method is used to filter the meteorological data that are strongly correlated with the wind power to establish the wind power prediction model data set; then the original wind power is decomposed using the improved variational modal decomposition technique to eliminate the noise in the data, and the decomposed wind power is reconstructed into a new subsequence by using the permutation entropy; with the meteorological data and the new subsequence as input variables, a stacking deeply integrated prediction model is developed; and finally the prediction results are obtained by optimizing the hyperparameters of the model algorithm through a genetic algorithm. The validity of the model is verified using a real data set from a wind farm in north-west China. The results show that the mean absolute error, root mean square error and mean absolute percentage error are improved by at least 33.1%, 56.1% and 54.2% compared with the autoregressive integrated moving average model, the support vector machine, long short-term memory, extreme gradient enhancement and convolutional neural networks and long short-term memory models, indicating that the method has higher prediction accuracy. [ABSTRACT FROM AUTHOR]

This paper presents an empirical analysis of hierarchical tendencies and functional patterns in the development of Mainland China’s space-economy by operationalizing the concept of “megaregions.” Drawing on the burgeoning literature on megaregions, we first argue that under conditions of economic globalization the megaregion concept does indeed present an effective tool to study the spatial agglomeration of the key components of China’s economic development. Second, we analyze the development status and the key functional characteristics of 16 prospective Chinese megaregions by constructing an index system consisting of 5 functions and 36 indicators. Third, we calculate an entropy index to rank megaregions according to their overall development status and reveal functional differences by applying cluster analysis. We find that the Yangtze River Delta, Beijing–Tianjin–Hebei Metropolitan Area, and the Pearl River Delta stand out, identify different varieties of megaregions according to their dominant functional characteristics, and explore the main policy dimensions of the persistent west–east divides observed. The paper is concluded with a discussion of potential avenues for future research. [ABSTRACT FROM PUBLISHER]

The Kubuqi Desert is the seventh-largest desert in China. Under the leadership of the central, autonomous region and local governments, the ecological situation has undergone historic changes. In this paper, we select Hangjin Banner and Dalate Banner, which have the most widely distributed deserts and use 347 households as the research perspective to construct the evaluation index system of the government's ecological environment governance effect. The entropy method is used to evaluate the governance effect, and the ordinary least squares and quantile regression are used to compare the evaluation differences of different publics. The research found the following. (1) The public believes that the government's ecological governance measures have achieved good results in the third-level index analysis. The ecological environment in the desert area has been significantly improved; that is, the survival rate of trees has increased, the area of vegetation coverage and vegetation types have increased, and the frequency of sandstorms has decreased. However, the intensity of sandstorms and the flow of water sources did not change significantly. The various types of public income have increased significantly compared to before the governance. The public takes the ecological priority as the concept and actively participates in the government's governance implementation, which means that the ecological awareness and behavior are higher. (2) Among the second-level index, the weights and scores in descending order are public economic characteristics: 45.53% and 0.4840, public ecological behavior: 25.62% and 0.1682, public ecological effect perception: 18.35% and 0.1240, and public ecological awareness: 10.51% and 0.0291. The comprehensive evaluation result is 0.8054, which is in the first grade, and the effect is excellent. (3) The public comprehensive evaluation results of the two regions are similar. Hangjin Banner is 0.8209 and Dalate Banner is 0.8557, both in the first grade. The effect is excellent. (4) In the OLS regression results, gender has a significant positive impact on evaluating the government's ecological environment governance effect. Age, ethnicity, and occupation have a significant negative impact. As the quintile increases, the influence of gender, age, and ethnicity first increases and then decreases. The maximum regression coefficient of gender at the 50% quantile is 0.714, which has a significant positive effect. Age has a significant negative impact at each quantile. The regression coefficient of ethnicity at the 50% quantile is the highest -0.357, which has a significant negative impact. Occupation only has a significant negative impact at the low quintile. [ABSTRACT FROM AUTHOR]

Summary: Predicting mobile users' future traffic usage plays an important role for mobile operators to optimize their services. Although a variety of prediction methods have been proposed and applied to this issue, none of them could answer whether the users' traffic behaviors can be predicted. By employing the entropy theory, this paper analyzes the predictability of users' behaviors on traffic types and accounts. Moreover, the mobile network traffic data collected from a major city in China is utilized to test the entropy theory and reveal the accuracy levels. Furthermore, by comparing the prediction results between the years 2012 and 2014, a conclusion is drawn that a large portion of users' behaviors can be predicted, but their traffic usage habits become more difficult to predict in 2014 than in 2012. The results also imply that different entropies achieve more similar predictability in 2014 than in 2012, which indicates the consistency of users' behaviors. Overall, this study reveals the predictability and consistency of users' behavior, which is of great significance for mobile operators. [ABSTRACT FROM AUTHOR]

This paper defines five criteria and identifies 21 indicators for the modernization level of a province or a city in modern China. It collects raw index data from 31 provinces in China, between 2007 and 2017, and introduces formula for its dimensionless processing. An improved entropy method (IEM) is proposed for the evaluation of the modernization in urban areas, based on the five criteria and 21 indicators. A practical study was implemented in Anhui province employing the said IEM. The results demonstrate that the IEM is being effective in evaluating the modernization level in urban areas.

Urban expansion is a hot topic in land use/land cover change (LUCC) researches. In this paper, maximum entropy model and cellular automata (CA) model are coupled into a new CA model (Maxent-CA) for urban expansion. This model can help to obtain transition rules from single-period dataset. Moreover, it can be constructed and calibrated easily with several steps. Firstly, Maxent-CA model was built by using remote sensing data of China in 2000 (basic data) and spatial variables (such as population density and Euclidean distance to cities). Secondly, the proposed model was calibrated by analyzing training samples, neighborhood structure and spatial scale. Finally, this model was verified by comparing logistic regression CA model and their simulation results. Experiments showed that suitable sampling ratio (sampling ratio equals the proportion of urban land in the whole region) and von Neumann neighborhood structure will help to yield better results. Spatial structure of simulation results becomes simple as spatial resolution decreases. Besides, simulation accuracy is significantly affected by spatial resolution. Compared to simulation results of logistic regression CA model, Maxent-CA model can avoid clusters phenomenon and obtain better results matching actual situation. It is found that the proposed model performs well in simulating urban expansion of China. It will be helpful for simulating even larger study area in the background of global environment changes. [ABSTRACT FROM AUTHOR]

Digital transformation, as a significant shift in optimizing enterprise resource allocation and enhancing information connectivity, offers the opportunity to stimulate the endogenous dynamics of corporate green governance. Employing a sample of 3,002 listed companies in China, a fixed-effects model, and the entropy power method to formulate a green governance index system, this study examines how digital transformation affects corporate green governance concerning carbon peaking and carbon neutrality objectives. According to these findings, the implementation of the digital transformation improves corporate green governance, each unit increase in digital transformation correlates with a 1.91% enhancement in green governance. Moreover, an examination of the mechanisms shows that green governance can be promoted by addressing information asymmetry and enhancing operational efficiency. Additionally, the association between corporate green governance and digital transformation is moderated favorably by strategic aggressiveness. Furthermore, our results indicate that digital transformation contributes significantly to the advancement of green governance within enterprises located in areas with high digital financing and strong technology integration capacities. Digitalization has a stronger effect on promoting green governance for enterprises in pilot regions than in non-pilot regions in terms of carbon emission trading. This study not only assists enterprises in elucidating the developmental trajectory of digital transformation amid carbon peaking and carbon neutrality goals but also provides a reference for decision-making on how digital technology can empower corporate green governance and promote sustainable economic growth. [ABSTRACT FROM AUTHOR]

In this paper, we define the portfolio return as fuzzy average yield and risk as hybrid-entropy and variance to deal with the portfolio selection problem with both random uncertainty and fuzzy uncertainty, and propose a mean-variance hybrid-entropy model (MVHEM). A multi-objective genetic algorithm named Non-dominated Sorting Genetic Algorithm II (NSGA-II) is introduced to solve the model. We make empirical comparisons by using the data from the Shanghai and Shenzhen stock exchanges in China. The results show that the MVHEM generally performs better than the traditional portfolio selection models. [ABSTRACT FROM AUTHOR]

Based on a Driving Forces-Pressure-State-Impact-Response (DPSIR) model, this paper takes a macroenvironmental, socioeconomic perspective to build an evaluation model to address sustainable Chinese wind power developments and to quantize the development results. From a combination of entropy weight and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, the sustainable wind power development level in China is examined, the development trends analyzed, and the trends and underlying laws identified, all of which provides new information for Chinese wind power sustainability. It was found that Chinese sustainable socioeconomic wind power development has been growing year on year. However, the wind power ecological sustainability fell and then rose slowly, indicating that these subsystems both influence the sustainable development of wind power. [ABSTRACT FROM AUTHOR]

• The CIV and the DIV are innovatively proposed for index calculation. • This paper proposed the QCI based on EWM-FAHP and calibrated by FEM. • Damage correction function was used to measure the more deteriorating effect. • Suggestions can be put forward for the maintenance and repair of ballastless track by QCI. This paper aims to guide the maintenance and repair of ballastless track quality by determining a set of comprehensive evaluation indices. We take the China Railway Track System (CRTS) III slab track as an example and mainly look at two typical types of damage, namely, cracking and interlayer debonding. Based on the entropy weight method-fuzzy analytic hierarchy process (EWM-FAHP), cracking interspace volume (CIV) and debonding interspace volume (DIV) and subsequent weights were proposed to measure the damage degree. In addition, a model containing cracking and debonding was established using the ABAQUS finite element software, and these weights were modified based on the models' calculated results. Then, the quality condition index (QCI) was determined to assess the quality state of the slab track in a comprehensive manner. This index was further used in a case study to evaluate the quality of the slab tracks in real-scenario cases and thereby bring forward appropriate O&M suggestions. [ABSTRACT FROM AUTHOR]

The rise in mixed traffic has resulted in increased traffic congestion and accidents across China. The primary objective of this study was to accurately evaluate the operational efficiency and safety of signalized intersections in a mixed-traffic environment and to perform a spatial analysis of intersection traffic conflicts, as well as to apply physics theories to solve practical problems in traffic. The mixed nature of mixed traffic is a form of chaos. Through the matching analysis of mixed-traffic characteristics and entropy, entropy can be used effectively describe the mixed state of a signalized intersection and quantify traffic chaos and disorder. The results of this study show that the entropy flow in a motor-vehicle traffic environment is 0.3807, and the evaluation grade is C. Meanwhile, the entropy flow of a mixed motor vehicle–nonmotor vehicle–pedestrian traffic environment is 0.4084 and the evaluation grade is D, indicating an increase in confusion at intersections in this type of traffic environment compared to in a motor-vehicle traffic environment. The proposed model provides a scientific and systematic method for evaluating the signalized intersection operation in mixed-traffic environments, offering a reliable theoretical foundation for improving intersection travel efficiency and safety. [ABSTRACT FROM AUTHOR]

To investigate the relationship between the marine industry and regional development, and assess its impact on the marine economy. The study creates an evaluation index system for the coupling relationship between the marine economy and regional development. It applies coupling theory and combines the hierarchical analysis method with the entropy weight method to determine the weight of each index. By constructing the coupling degree and coupling coordination degree model, this paper quantitatively analyzes the coupling relationship and applies the coefficient of variation to assess the coordinated development differences between different regions. The study utilized data from the official China Marine Statistical Yearbook. The analysis revealed an upward trend in the coupling degree of the marine economy and regional development during the study period, increasing from 0.58 to 0.72. This indicated a significant strengthening of the interaction and synergistic development between the two. In typical coastal areas, the coupling degree increased from 0.62 to 0.78, indicating the significant contribution of the marine industry to the region's comprehensive economic development. The study proposes policy recommendations to enhance the adjustment of the marine industrial structure and technological innovation, promote inter-regional cooperation and resource sharing, and strengthen marine environmental protection and sustainable resource utilization. These measures aim to promote the development of the marine economy while safeguarding marine resources. • The dynamic relationship between Marine industry and regional development is analyzed. • Construct the evaluation index system of Marine economy. • Assess the differences in coordinated development between different regions. [ABSTRACT FROM AUTHOR]

Occupational pneumoconiosis brings great difficulties to the diagnosis of professional doctors due to its complex lung characteristics. Computer-aided diagnosis has opened up new research ideas for researchers, but due to the inherent small data characteristics of medical data sets, it performs poorly in specific practice. In this paper, we propose a weighted information flow data incremental network (WIDINet) for pneumoconiosis staging based on existing research results. WIDINet first uses random attribute masking technology to obtain incremental data with higher data quality, and then uses prior knowledge and multi-granularity attention modules to solve the problem of low reliability of feature screening networks based on incremental data. At the end of the WIDINet diagnostic model, this article uses the KL weighted judgment algorithm to measure the difference between the test chest radiograph and China's current national gold standard to achieve staged diagnosis of the target task. In the experimental verification part, we used the pneumoconiosis data set collected in our laboratory to prove that the WIDINet staging diagnosis model has an accuracy of 93.4%, a precision of 87.8%, a sensitivity of 78.4%, a specificity of 95.6%, and an F1score of 84.9%. The area under the curve (AUC) reaches 96%.Code: https://github.com/ nonoXwb/SDom (github.com) [ABSTRACT FROM AUTHOR]

The shaft-type tubular pumping station has the remarkable characteristics of a large flow rate and high efficiency. It can realize the functions of irrigation, pumping, and drainage through pumping and generating conditions considering tides. Moreover, it is widely used in the plain area of eastern China and the tidal area along the marine region. Due to the different topological features of the airfoil of the impeller, the energy evolution characteristics of the shaft-type tubular pumping station during pumping and generating conditions remain unclear. The entropy generation theory was introduced to numerically simulate the flow pattern and energy characteristics in the shaft-type channel, impeller, and straight channel in operation conditions. The results show that the flow pattern is stable when the shaft-type channel and the straight-type channel are used as the inlet channel under pumping and generating conditions, and a low-pressure region occurs in the contraction section of the shaft-type channel. The velocity of sections of the inlet and outlet and the middle section of the impeller in the generating condition is larger than that in the pumping condition. In addition, the difference in the static pressure on the blade surface nearby the hub is large. With a change in the position of the wingspan, the difference gradually decreases from the small flow condition to the large flow condition. There is a high-entropy production rate zone in the channel contraction section and the shaft-type wall surface of the shaft-type flow channel. When the straight-type channel is used as the outlet flow channel, a high-entropy production region appears near the inlet water surface. In the pumping condition, a high-entropy production area is found at the inlet of the impeller, the blade groove channel, and the inlet of the guide vane. In the generating condition, a high-entropy production area is found at the out-of-impeller outlet, the blade groove channel, and the outlet of the guide vane. These research achievements have some reference value for the design of the shaft-type tubular pumping station considering tides and the study of hydraulic performance, along with the energy characteristics of the channels. [ABSTRACT FROM AUTHOR]

With the continuous development of digital technology, the widespread use of virtual spokespersons to promote city images is becoming increasingly prevalent. This study responds to this trend by employing a factor analysis and entropy weight methodology to explore the different dimensions and priorities in shaping the image of virtual city spokespersons in China. The aim is to offer insights into the design strategies and directions for shaping the image of virtual city spokespersons. For the research, we first conducted a literature review and semi-structured interviews to investigate the requirements of users in mainland China and Hong Kong regarding the image shaping of virtual city spokespersons. Building upon this groundwork, a questionnaire was designed and distributed, and it successfully gathered 512 valid responses. Subsequently, a factor analysis was utilized to identify eight key dimensions in shaping the images of Chinese virtual city spokespersons: "Design elements", "Anthropomorphism", "Evolutionary", "Emotionalization", "Narrativity", "Culturalism", "Interactivity", and "Reliability". Then, the entropy weighting method was applied to analyze the weights of each indicator within these dimensions. The results revealed that "Design elements" have the highest priority in shaping the image of virtual city spokespersons, followed by "Anthropomorphism", "Emotionalization", "Evolutionary", "Culturalism", "Narrativity", "Reliability", and "Interactivity". Based on these findings, a series of design optimization strategies are proposed, including but not limited to shaping visually appealing images aligned with user perceptions, establishing emotional connections with users, and meeting the functional experience needs of users. These strategies not only contribute to the image shaping of virtual city spokespersons, but also provide vital guidance for innovative directions in promoting the publicity and marketing of Chinese cities. [ABSTRACT FROM AUTHOR]

Local site conditions play an important role in the effective application of strong motion recordings. In the China National Strong Motion Observation Network System (NSMONS), some of the stations do not provide borehole information, and correspondingly, do not assign the site classes yet. In this paper, site classification methodologies for free-field strong motion stations are reviewed and the limitations and uncertainties of the horizontal-to-vertical spectral ratio (HVSR) methods are discussed. Then, a new method for site classification based on the entropy weight theory is proposed. The proposed method avoids the head or tail joggle phenomenon by providing the objective and subjective weights. The method was applied to aftershock recordings from the 2008 Wenchuan earthquake, and 54 free-field NSMONS stations were selected for site classification and the mean HVSRs were calculated. The results show that the improved HVSR method proposed in this paper has a higher success rate and could be adopted in NSMONS. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new concept of convergence which is based on the metric entropy measure recently proposed by Granger et al. (2004, Journal of Time Series Analysis 25, 649–69) to investigate economic convergence in China. This entropy measure compares whole distributions of growth rates across individual provinces. Separately, based on this same entropy measure, we also implement cluster analysis to identify any convergence clubs. Our four main conclusions are: (1) while we certainly reject the null hypothesis that there exists a nationwide convergence, we do find that there exist convergence clubs for both the pre- and post-reform periods, (2) we find a number of very small convergence clubs. In particular, there are eleven and six convergence clubs for the pre- and post-reform periods, respectively, (3) in comparing the number and size of convergence clubs for both the pre- and post-reform periods, it could be argued that the extent of convergence is more prevalent during the post-reform period than during the pre-reform period and (4) convergence groups cannot be simply characterized by such unique features as region or the extent of policy preference level that are commonly used in the literature. [ABSTRACT FROM AUTHOR]

Regional innovation systems (RISs) characterized periodical and is suitable for analyzing the Chinese economy which has entered the new normal. However, few scholars analyze and identify the stage of RISs from the perspective of life cycle. This paper divides the life cycle of RISs into four stages: initial stage, growth stage, maturity stage, and decline stage. Based on the analysis of the characteristics in every stage of the life cycle in the RISs, this paper constructs entropy weight disturbing attribute model to identify the stage of 31 provincial innovation systems in China. The research results show that all the RISs in maturity stage belong to the eastern developed regions, and innovation achievement capacity is significant. The RISs are widely distributed which are in the growth stage. The innovation efficiency capacity, innovation growth capacity and innovation network capacity of RISs which are in growth stage are in a high level. The provinces with the innovation system in the initial stage are mainly in the backward areas of the west, and the innovation growth capacity is better than other innovation capacities. Mastering the evolutionary stage of the RISs is helpful to promote the implementation of innovation-driven development strategies. [ABSTRACT FROM AUTHOR]

In recent years, credit scoring has become an efficient tool to assist financial institutions in identifying potential default borrowers, and the combined model is widely viewed as a useful vehicle. In this study, after pre-processing based on random forest, we propose a combined logistic regression algorithm and artificial neural network model to improve the predictive performance based on actual data from a rural commercial bank under the condition that loan quality directly affects the profitability of the bank. The combined model requires a step with an entropy method to determine the entropy weights of the logistic regression model and artificial neural network model. The experimental results reveal that the proposed combined model outperforms the two base models on four evaluation metrics: accuracy (ACC), area under the curve (AUC), Kolmogorov-Smirnov statistic (KS), and Brier score (BS). Moreover, the model is superior to a state-of-the-art ensemble model, stacking. [ABSTRACT FROM AUTHOR]

According to literature review and the data of China's logistics listed companies, this paper firstly designs the high-quality development evaluation system of logistics enterprises and establishes the panel data model group. Secondly, the method of entropy weight-Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS method) is used to synthesize and regress the indexes, and obtains that the fitting degree of the model is low, which is caused by the lack of data of some indicators in the logistics enterprises. Due to the gray nature of data information, the improved gray relational model and the three-dimensional gray relational model are constructed to study, in-depth, the strategic focus and breakthrough of high-quality development of Chinese logistics enterprises. The research finds that the innovation and the operation ability of Chinese logistics enterprises are weak, which shows specifically in the following aspects: (1) The irrational structure of the employees, the proportion of employees with a bachelor degree or above is small, and the high-education personnel fail to significantly promote the corporate performance; (2) R&D expenditure has little effect on the high-quality development of enterprises. The proportion of R&D expenses is small and cannot be translated into actual benefits, and the ability of enterprise management innovation is insufficient. According to these findings, this paper gives three lean paths for the high-quality development of China's logistics enterprises. [ABSTRACT FROM AUTHOR]

The popularization of financial literacy has become a global trend, with governments across the world expressing commitment to continuously enhancing the financial literacy of their citizens to improve the country's overall financial well-being. However, there is a lack of research evaluating the actual effects of financial literacy on Chinese households. This study first investigated the micro impact of financial literacy on the household stock profit level using data from the 2019 China Household Finance Survey. As most existing studies use factor analysis to measure financial literacy from a single dimension of financial knowledge, our study additionally used the entropy method to construct a composite evaluation system of financial literacy from four dimensions: financial skills, knowledge, attitudes, and behaviors. The ordinary least squares model was utilized as the primary regression model to estimate the correlation, and the average financial literacy of other households in the same community was selected as an instrumental variable. Further instrumental variable regression analysis was conducted using the two-stage least squares method. Three robustness tests were performed to ensure the reliability of the research findings. The results demonstrate that financial literacy significantly enhances household stock profit levels. The mediation effect analysis indicates that financial literacy affects stock profit levels through financial information attention. Moreover, financial literacy has a more substantial promoting effect on stock profit levels for households with members working for state-owned enterprises and those living in first-tier cities. This study confirms the value of financial literacy; identifies important channels for residents to increase their property income; and provides important guidance for the government, educational organizations, and financial institutions. This also injects more vigor into market participation to improve the persistently sluggish Chinese stock market. [ABSTRACT FROM AUTHOR]

Oxalis debilis Kunth, an invasive plant native to South America, has already spread extensively throughout various regions in China including West China, East China, Central China, and South China. It poses a certain degree of damage to the local ecosystem and demonstrates significant invasive potential. Utilizing distribution information along with environmental variables such as bioclimate, soil factors, elevation, and UV-B radiation, the MaxEnt model combined with ArcGIS was employed to forecast the potential distribution of O. debilis in China. The ROC curve was employed to assess the accuracy of the model, while the jackknife test was utilized to identify dominant environmental variables and determine their optimal values. The simulated AUC value was 0.946 ± 0.004, and the predicted results exhibited a remarkable concordance with the actual outcomes, thereby indicating that the Maxent model demonstrated a high level of confidence in its predictive capabilities. The potential distribution of O. debilis in China spanned 18,914,237 km2, accounting for 19.70% of the total land area. This distribution was primarily observed in East, Central, and South China, with Guangdong, Guangxi, and Guizhou being identified as highly suitable habitats for O. debilis. Furthermore, it was observed that the distribution of O. debilis is primarily influenced by environmental variables such as the precipitation of the driest month, the monthly diurnal range, the mean temperature of the wettest quarter, and the isothermality. The findings can serve as a valuable point of reference for the prevention and monitoring of O. debilis spread, thereby contributing to the protection of China's agricultural, forestry, and ecological environments. It is imperative to acknowledge the hazards associated with O. debilis, closely monitor its invasion, and prevent uncontrolled dissemination. [ABSTRACT FROM AUTHOR]

The traditional Tibetan area of China is an ethnically and culturally significant region with a historical geographical connection. This study investigates the spatial-temporal distribution patterns and entropy changes of historical and cultural heritage by examining the association between cultural heritage and socio-historical factors. It utilizes analytical methods such as information entropy and incorporates temporal, spatial, and typological information from the data obtained in the Third National Cultural Relics Census. The findings are as follows: (1) The three major regions in the Tibetan area of China alternately serve as development cores for the traditional Tibetan area, exhibiting a fluctuating "dispersion-aggregation" trend of historical and cultural heritage, which also displays notable regional variations. (2) The quantity and entropy change of historical and cultural heritage exhibit correlations between different periods, but there are also some intergenerational differences. (3) The spatial-temporal distribution pattern of historical and cultural heritage demonstrates an inter-era correlation, indicating that socio-historical development is a nonlinear process characterized by both "transition" and "accumulation". These findings are of significant importance for further understanding the social evolutionary process of human settlements in high-altitude areas and for the comprehensive protection of cultural heritage in ethnic regions. [ABSTRACT FROM AUTHOR]

Assessment of ecoenvironmental vulnerability plays an important role in the guidance of regional planning, the construction and protection of ecological environment, which requires comprehensive consideration on regional resources, environment, ecology, society and other factors. Based on the driving mechanism and evolution characteristics of ecoenvironmental vulnerability in cold and arid regions of China, a novel evaluation index system on ecoenvironmental vulnerability is proposed in this paper. For the disadvantages of conventional entropy weight method, an improved entropy weight assessment model on ecoenvironmental vulnerability is developed and applied to evaluate the ecoenvironmental vulnerability in western Jilin Province of China. The assessing results indicate that the model is suitable for ecoenvironmental vulnerability assessment, and it shows more reasonable evaluation criterion, more distinct insights and satisfactory results combined with the practical conditions. The model can provide a new method for regional ecoenvironmental vulnerability evaluation.

The Songnen Plain in Northeast China is the only remaining black soil agricultural area in the world and is an important food base for China. The groundwater resources in this area are abundant, but human activities have caused them polluted. This paper established a groundwater vulnerability assessment to characterize the influence of human activities which used an entropy weight method. The index was tested using the nitrate pollution distribution in the groundwater to verify the effectiveness of this method. The results showed that areas with high specific vulnerability were distributed in the northern and eastern parts of the Songnen Plain and were consistent with areas that showed serious nitrate pollution of the groundwater. The correlation coefficient between these areas was 0.2536, which greatly improved the vulnerability assessment without superimposing human activities in the model. The results clearly showed that human activities increased groundwater vulnerability on the Songnen Plain. The evaluation method provided a reference for similar evaluations and a basis for the protection and management of groundwater resources in this region. [ABSTRACT FROM AUTHOR]

• An integrated model for sustainable supplier selection. • Considers all three sustainability perspectives simultaneously. • Obtains criteria weights by both subjective and objective methods. • Two types of weights are combined by Deviation Maximization method reasonably. • An improved fuzzy MULTIMOORA method to rank sustainable suppliers. With the increasing awareness of environmental protection and social responsibility, sustainable supplier selection (SSS) has been receiving more and more attention. However, traditional methods for selecting sustainable suppliers suffer from three main drawbacks: (i) Few existing studies have considered criteria weightings that have been determined both subjectively and objectively, reasonably and simultaneously. Moreover, among these limited studies, existing methods for combining weightings that have been calculated both subjectively and objectively provide only a poor degree of differentiation. (ii) Although MULTIMOORA method has high potential to solve the complex SSS problem, few researchers have given it much attention. (iii) The current Reference Point Approach within MULTIMOORA is not comprehensive as it only considers the distance between the alternative and the positive ideal point. Together, these drawbacks result in both inefficiency and ineffectiveness in SSS. This paper proposes a novel fuzzy MULTIMOORA-based method for SSS. The proposed method, firstly, obtains weights by both group Best Worst Method (subjective method) and fuzzy Shannon Entropy Method (objective method), respectively. Then the two types of weights are combined by Deviation Maximization method, reasonably and effectively. Finally, the paper introduces an improved fuzzy MULTIMOORA method to rank alternative suppliers, which considers both the minimum distance from the positive ideal point and the maximum distance from the negative ideal point. The practicability and effectiveness of the proposed method is verified in an illustrative application in Company L, a well-known international forklift truck manufacturer in China. [ABSTRACT FROM AUTHOR]