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Background: Adult-led organized settings for children (eg, classrooms) provide opportunities for physical activity (PA). The structure of setting time may influence inequalities (ie, unequalness) in the distribution of PA. This study examined differences in PA inequality by setting and time-segment purpose in time-segmented organized group settings for children. Methods: PA and setting meetings were assessed using accelerometer and video observation data from school, before-/after-school, and youth club groups (n = 30) for third- through sixth-grade children (n = 699) in 2 rural US communities. Meetings (n = 130) were time-segmented into smaller units (sessions; n = 835). Each session was assigned a purpose code (eg, PA). Accelerometer data were paired with the meetings and sessions, and the Gini coefficient quantified inequality in activity counts and moderate to vigorous PA minutes for each segment. Beta generalized estimating equations examined differences in PA inequality by setting and session purpose. Results: Activity count inequality was lowest (P <.05) during youth club meetings (Gini = 0.17, 95% CI, 0.14–0.20), and inequality in moderate to vigorous PA minutes was greatest (P <.01) during school (Gini = 0.34, 95% CI, 0.30–0.38). Organized PA sessions (Gini = 0.20, 95% CI, 0.17–0.23) had lower activity count inequality (P <.0001) than academic (Gini = 0.30, 95% CI, 0.27–0.34), enrichment (Gini = 0.31, 95% CI, 0.27–0.36), and nonactive recreation (Gini = 0.30, 95% CI, 0.25–0.34) sessions. Inequality in moderate to vigorous PA minutes was lower (P <.05) in organized PA (Gini = 0.26, 95% CI, 0.20–0.32) and free play (Gini = 0.28, 95% CI, 0.19–0.39) than other sessions. Conclusions: PA inequality differed by setting time structure, with lower inequality during organized PA sessions. The Gini coefficient can illuminate PA inequalities in organized settings and may inform population PA improvement efforts in rural communities. [ABSTRACT FROM AUTHOR]

Environmental change is increasing worldwide and many animal species face anthropogenic threats, especially diet specialists. Yet the degree to which specialist species are currently impacted by environmental change remains poorly understood. We examine how anthropogenic pressures impact dietary specialist species. We calculated indices of diet specialization for mammal species, based on the Gini inequality coefficient, and combined these indices with human pressure data. We then used spatially explicit Mantel tests to examine global patterns in mammal diet specialization. We used a generalized linear mixed model to investigate correlations between the percentage of diet specialist species in mammal communities in an area and its total species richness, human pressure and protection status (mediated through an interaction with the continent). Findings revealed that areas with many diet specialists in mammal communities are also impacted by high human pressure. Additionally, we found that the global protected area system adequately covers habitat for many mammal diet specialists, but has lower effectiveness in South America, Oceania, North America and Europe compared with Africa and Asia. Finally, we identified potential reservoirs for specialist species—places containing many highly diet specialist species and that are subject to less human pressure—which may be important for conservation efforts. [ABSTRACT FROM AUTHOR]

To address the contradiction among various sectors and the series of water challenges, the incorporation of information entropy and the Gini coefficient is proposed to depict the spatiotemporal evolution and untangle the influencing factors of the water use structure in Zhanghe Irrigation District, located in central Hubei province. Mutual information entropy was also used to characterize the interactions between water use processes. The results show that the overall water use structure becomes more reasonable over time, while the spatial fairness of regional water use declines. From 2012 to 2016, the Gini coefficient thresholds for industrial, agricultural and domestic water are [0.17,0.27], [0.10,0.12], and [0.13,0.15], respectively. The spatial equality of each sector, in descending order, is agricultural, domestic, and industrial water. Precipitation plays a crucial role in agricultural, domestic, and ecological water use, while socio-economic factors are more closely related to industrial, domestic and ecological water use. Ecological water use is correlated with the other three water use processes. These findings could provide valuable references for inter-departmental water resources dispatching and industrial layout adjustments in irrigated districts for local decision-makers. [ABSTRACT FROM AUTHOR]

[Objective] The aim of this study is to reveal the characteristics of multi-year runoff variation in different geomorphic areas in the Hekouzhen-longmen region, and to investigate responses of intra-annual runoff to soil and water conservation measures in these watersheds. [Methods] Three watersheds in different landform regions (Tuwei River, Sanchuan River, and Yan River) were selected, representing the sandy region, rocky mountain region, and loess cover region, respectively. The Gini coefficient and Lorentz asymmetry coefficient were constructed to quantify the evenness of intra-annual runoff using runoff observations during 1960 to 2019. [Results] (1) Runoff of Tuwei River, Sanchuan River, and Yan River decreased significantly during 1960 to 2019, with the decrease rate of-0.05 million m³/a,-0.03 million m³/a, and-0.02 million m³/a, respectively. (2) The Intra-annual runoff in different landform regions were different. The Gini coefficients of Tuwei River, Sanchuan River and Yan River were 0.2, 0.35 and 0.6, respectively. The intra-annual runoff in the aeolian sandy area showed the highest eveness, followed by the rocky mountain area, while the loess covered area displayed the most uneven distribution. (3) The Gini coefficient of runoff in the three landform regions showed the decreasing trend, and the concentration rate of intra-annual runoff also decreased during 1960 to 2019. (4) NDVI, terraced fields and silting dam construction had significant negative correlation with Gini coefficient of runoff in the three landform regions. [Conclusion] Soil and water conservation projects in the Hekouzhen-Longmen region played a positive role in regulating the intra-annual runoff. [ABSTRACT FROM AUTHOR]

There is a high level of policy interest on the effect of trade liberalisation on inequality, especially in developing countries, because of their large vulnerable populations. India also initiated the process of liberalisation as a response to the severe balance of payments crisis of 1991. However, both rural and urban inequality has been increasing since the period 1993–1994, with urban inequality increasing at a higher rate. This study empirically examines the impact of trade openness on wage inequality using panel data for Indian states (separately for rural and urban areas). The results of this study indicate that trade openness does not lead to decrease in the wage inequality in the states and their rural areas. However, urban wage inequality is found to be increasing due to trade openness. These results are analysed and explained by various factors present in the Indian economy such as, skill biased technological changes; trade in intermediate goods; barriers to domestic labour mobility; and pattern and composition of India's exports. An interesting aspect emerging is that higher education levels lead to increase in wage inequality as returns to education and inequality are increasing and the increase is also attributed to liberalisation. JEL Codes: F16, O18, C23 [ABSTRACT FROM AUTHOR]

Although China's education development has made great progress, there are obvious regional differences in China's educational development. A systematic investigation of the regional inequality in China's educational development and its driving factors is of great significance for optimizing the allocation of educational resources and giving full play to the critical role of education in regional development. In addition, the research on the evolution and internal mechanism of educational development inequality in China can also provide experience and reference for the Global South. Therefore, we construct a comprehensive evaluation index system to measure the level of regional educational development, reveal the regional inequalities in China's educational development, and employ spatial econometric model to dissect the factors influencing the regional inequalities. The results show that China's educational development level continues to increasing from 2003 to 2020, but a significant decrease in its growth rate. In this process, regional differences in education inequality in China have gradually narrowed, which can be confirmed by changes in the Gini coefficient and Theil index. In terms of direct spillover effects, the per capita fiscal expenditure on education and urbanization rate have positive effects. In terms of indirect spillover effects, per capita GDP and per capita fiscal expenditure on education have negative effects, while population density and urbanization rate have positive effects. After replacing the weight matrix and removing the extreme values, the model also passes the robustness test. However, this mechanism is heterogeneous in different regions, therefore, we put forward the corresponding policies and measures according to the regional driving effects of influencing factors. [ABSTRACT FROM AUTHOR]

Based on the panel data of 9 provinces (autonomous regions) of the Yellow River Basin from 2011 to 2022, the evaluation index system of farmers' income quality is constructed, and the entropy method, Dagum Gini coefficient, fixed effect model and other methods are used to measure the quality of farmers' income in the Yellow River Basin, explore the regional differences and further study the influencing factors. The study shows that, first, the quality of farmers' income in the nine provinces (autonomous regions) of the Yellow River Basin from 2011 to 2022 shows an overall fluctuating upward trend, with large inter-regional differences in the quality of farmers' income, obvious characteristics of the stage, and a widening gap between regions. Second, the overall difference in the quality of farmers' income in the Yellow River Basin is gradually narrowing, and the inter-regional differences are the main cause of the relative differences in the quality of farmers' income in the Yellow River Basin. Third, the level of economic development, social security, urbanisation and financial support for agriculture are conducive to improving the quality of farmers' income, while factors such as industrial structure and demographic structure are not conducive to improving the quality of farmers' income. Accordingly, policy suggestions are made, such as paying attention to the quality of farmers' income and promoting the growth of farmers' income; eliminating the shortcomings of farmers' income quality and improving the quality level of farmers' income; optimising the industrial structure and improving the rural social security system. [ABSTRACT FROM AUTHOR]

This paper attempts to describe and explain the long-term evolution of wage inequality in imperial China, covering over two millennia from the Han dynasty to the Qing dynasty (202 BCE-1912 CE). Based on historical government records of official salaries, commodity prices, and agricultural productivity, we convert various forms of salaries to equivalent rice volumes and comparable salary benchmarks. Wage inequality is measured by salary ratios and (partial) Gini coefficients between official and peasant classes as well as within the official class. The inter-class wage inequality features an "inverted U-u" pattern—first rose before the Tang dynasty and then declined afterwards (the "inverted U" trends) with "inverted u" dynastic cycles. The intra-class wage inequality has a secular decline trend. We propose a unified framework incorporating technological, institutional, political, and social (TIPS) mechanisms to explain both long-term and short-term patterns. It is concluded that the technological mechanism dominated the rise of wage inequality, while the political mechanism (emperor-bureaucracy power tensions) drove the decline. [ABSTRACT FROM AUTHOR]

Background and objective: Equitable distribution of health resources is important to achieving equity, guaranteeing access to healthcare services, and improving societies’ health status. This study aimed to examine equity in the distribution of health resources and its association with the mortality caused by COVID-19 in South Khorasan province, east Iran. Method: This was a secondary analysis of data from a cross-sectional study conducted in South Khorasan province in 2022. Data were drawn from an existing online database (Farabar) provided by the Public Health Department of the Ministry of Health in Iran. Data related to the number of hospital beds, medical specialists and practitioners, nurses, paramedical workers, health watch, community health workers (Behvarz), healthcare financial resources, and COVID-19 mortality rate were extracted from the Farabar system for each city separately. The equity in the distribution of resources was analyzed by calculating the Gini Coefficient index and using EXCEL software. The Gini Coefficient was used to measure the distribution of health resources and services (i.e. financial resources, human resources, hospital beds, ICU beds) against population size and geographic size. Data were analyzed using SPSS software, version 25. Results: The Gini Coefficient ranged between 0.006 and 0.320. The Gini Coefficient of health care system financial (0.006) resources distribution was more equitable, while that of hospital beds (0.229) and intensive care beds (0.320) was more inequitable. The Gini Coefficient of the distribution of human resources was estimated at less than 0.3, which is relatively equitable. The COVID-19 mortality rate per 100,000 population was estimated at 113.6, lower than the national average. After controlling the confounding variable (rural population (as % of the total population)), there was no significant correlation between COVID-19 mortality and the distribution of human resources, hospital beds, and healthcare financial resources. Conclusion: According to the results, the distribution of resources relative to the province’s population was relatively equitable, and there was no significant correlation between the COVID-19 mortality rate and the distribution of human resources, hospital beds, and healthcare financial resources. This can be due to the equitable distribution of health resources. Having a better and deeper understanding of the regions and populations disproportionately impacted by COVID-19 can help with intervention and resource allocation. [ABSTRACT FROM AUTHOR]

This study empirically investigates the moderating effects of institutions interacted with economic growth as determinants of cross-country income inequality. For a sample of 43 advanced and developing countries in the OECD and Varieties of Capitalism (VoC) literature over the period of 1995–2019, we test the hypothesis that the income inequality-increasing effects of GDP growth are reduced by robust institutions through interactive terms between economic growth and labour market institutions, gender-based institutions, and governance-based institutions. We use correlated random effects, feasible generalised least squares, and systems-generalised method of moments for panel data analysis using the Gini coefficient for post-tax and post-transfer household disposable income inequality as the dependent variable. Across all models, we find consistently significant statistical evidence for contingency effects between greater GDP growth rates and robust institutions. More specifically, the positive or inequality-increasing effects of greater GDP growth are shown to be reduced by stronger employment protection legislation and greater gender parity in education. Policy implications on inclusive growth thereby call for labour market reforms in terms of employment protection and improved access to education for women. [ABSTRACT FROM AUTHOR]

Integrating machine learning techniques within metaheuristics has shown promise for effectively solving combinatorial problems like the Traveling Salesman Problem (TSP). However, key challenges remain in initializing metaheuristics to balance exploration and exploitation across vast search spaces. This paper introduces a novel clustering-driven technique for constructing high-quality initial solutions to Euclidean TSP instances. Our method uses hierarchical hybrid clustering with K-means, affinity propagation, and density peaks clustering to recursively partition cities into a compressed quadtree structure. A rigorous assessment using the Davies–Bouldin index and Gini coefficient optimizes intra- and inter-cluster quality and balance at each level. The multi-tiered decomposition strategically abstracts complex optimization landscapes into localized clusters that are solved efficiently in parallel within each using heuristics such as nearest neighbor and ant colony optimization. A genetic networking heuristic then interconnects independent intra-cluster solutions to construct unified inter-cluster routes. The clustering-guided initialization provides a diverse population of initialized tours that balance global exploration against localized exploitation. To validate our method, we conduct experiments using the generated solutions to seed a simulated annealing metaheuristic. This experimental evaluation will demonstrate this technique's ability to initialize metaheuristics for TSP instances closer to optimality compared to traditional methods. [ABSTRACT FROM AUTHOR]

Brain development during childhood involves significant structural, functional, and connectivity changes, reflecting the interplay between modularity, information interaction, and functional segregation. This study aims to understand the dynamic properties of brain connectivity and their impact on cognitive development, focusing on temporal co-occurrence diversity patterns. We recruited 481 children aged 6 to 12 years from the Healthy Brain Network database. Functional MRI data were used to construct dynamic functional connectivity matrices with a sliding window approach. Modular structures were identified using multilayer network community detection, and the Dagum Gini coefficient decomposition technique, which uniquely allows for multi-faceted exploration of modular temporal co-occurrence diversities, quantified these diversities. Mediation analysis assessed the impact on small-world properties. Temporal co-occurrence diversity in brain networks increased with age, especially in the default mode, frontoparietal, and salience networks. These changes were driven by disparities within and between communities. The small-world coefficient increased with age, indicating improved information processing efficiency. To validate the impact of changes in spatiotemporal interaction disparities during childhood on information transmission within brain networks, we used mediation analysis to verify its effect on alterations in small-world properties. This study highlights the critical developmental changes in brain modularity and spatiotemporal interaction patterns during childhood, emphasizing their role in cognitive maturation. These insights into neural mechanisms can inform the diagnosis and intervention of developmental disorders. • Used multilayer networks to construct dynamic functional connectivity matrices from fMRI. • Dagum Gini coefficient explored brain network disparities, showing age-related increases. • Spatiotemporal interaction disparities increased within and between communities with age. • Mediation analysis showed spatiotemporal interaction mediates age and small-world properties. [ABSTRACT FROM AUTHOR]

The rapid increase in urban population density driven by urban development has intensified inequity in urban green space distribution. Identifying the causes of changes in green equity and developing strategies to improve urban greening are crucial for optimizing resource allocation and alleviating social inequalities. However, the long-term spatio-temporal evolution of green visibility and equity remains underexplored. This study utilized the "Time Machine" feature to capture street view images from 2014, 2017, and 2021, analyzing changes in green visibility and its equity across residential communities in Wuhan. Deep learning techniques and statistical methods, including the Gini coefficient and location quotient (LQ), were employed to assess the distribution and spatial equity of street-level greenery. The results showed that overall green visibility in Wuhan increased by 4.18% between 2014 and 2021. However, this improvement did not translate into better spatial equity, as the Gini coefficient consistently ranged between 0.4 and 0.5. Among the seven municipal districts, only the Jiang'an District demonstrated relatively equitable green visibility in 2017 and 2021. Despite a gradual reduction in disparities in green visibility, a spatial mismatch persisted between UGS growth and population distribution, leading to uneven patterns in UGS equity. This study explores the factors driving inequities in green visibility and proposes strategies to enhance urban greening. Key recommendations include integrating the green visibility equity evaluation framework into urban planning to guide fair green space allocation, prioritizing greenery in low-income neighborhoods, and reducing hardscapes to support the planting and maintenance of tall canopy trees. These measures aim to enhance accessible and visible green resources and promote equitable access across communities. [ABSTRACT FROM AUTHOR]

Background: In the context of public health emergencies, the presence of medical and health talents (MHT) is critically important for support in any country or region. This study aims to analyze the spatial and temporal distributions and evolution of MHT in China and propose strategies and recommendations for promoting a balanced distribution. Methods: This research used data from 31 provinces in China to construct a multidimensional index system for measuring the agglomeration level of MHT. The indices include talent agglomeration density (TAD), talent agglomeration scale (TAS), talent agglomeration intensity (TAI), and talent agglomeration equilibrium (TAE). Using provincial data from the years 1982, 1990, 2000, 2010, and 2020, a spatiotemporal analysis of the MHT agglomeration levels was conducted. Furthermore, the regional dynamic distribution of MHT was analyzed using kernel density estimation diagrams. The spatial autocorrelation of MHT was assessed through global and local Moran's I, and the spatial gap and decomposition of MHT were analyzed using the Dagum Gini coefficient. Results: From the temporal level, the TAD and TAI of MHT showed an increasing trend over the studied period, whereas TAS decreased and TAE first increased and then decreased from 1982 to 2020. At the spatial level, the TAD, TAS, TAI, and TAE of MHT exhibited varied patterns among the eastern, central, and western regions of China, showing significant geographical disparities, generally demarcated by the Hu Huanyong Line. The regional dynamic distribution level of MHT in the country and the three regions were expanding. Spatial autocorrelation analysis using global and local Moran's I for TAD, TAS, TAI, and TAE demonstrated significant regional differences. The Dagum Gini coefficient of TAD, TAS, TAI, and TAE revealed divergent trends in regional disparities, with overall declines in disparities for TAD and TAI, a slight increase for TAS, and fluctuating patterns for TAE. Conclusions: From a temporal perspective, the overall number of MHT in China has been increasing annually at the national and provincial levels. From the spatial perspective, TAD, TAS, TAI, and TAE exhibit significant differences among the three regions. Kernel analysis reveals that the distribution differences are gradually expanding in national level and varying in regional level. Moreover, the global and local Moran's I indices reveal varying spatial autocorrelation for TAD, TAS, TAI, and TAE. The Dagum Gini coefficients of TAD, TAS, TAI, and TAE show different patterns of decomposition. [ABSTRACT FROM AUTHOR]

This study aims to develop an efficient model to predict the arrears behavior of electricity users by integrating multi-scale feature learning with a backpropagation (BP) neural network. The goal is to provide accurate early warning systems and enhanced risk management tools for power companies. The BP neural network algorithm adjusts weights to minimize prediction errors, while multi-scale feature learning captures the diversity and regularity of user behavior by extracting data from various time dimensions, such as daily, weekly, and monthly intervals. First, electricity usage and weather data from the UMass Smart Dataset are preprocessed, including steps such as data cleaning, standardization, and normalization. Next, features are extracted across three time scales—daily, weekly, and monthly. These features are then input into the BP neural network model using the multi-scale feature learning method. A hierarchical neural network structure is designed to address the characteristics of different scales in distinct layers. Key model parameters are optimized, and a sensitivity analysis is conducted. The experimental results demonstrate that the BP neural network model incorporating multi-scale features outperforms traditional BP neural network models and other control models in several evaluation metrics. Specifically, the Gini coefficient is 0.55, the Kolmogorov-Smirnov statistic is 0.60, the Matthews correlation coefficient is 0.45, and specificity is 0.82. These results indicate that the proposed method offers significant improvements in capturing user behavior patterns and enhancing prediction accuracy. The study concludes that the effective fusion of multi-scale features not only enhances the model's prediction performance but also strengthens its generalization ability. This method provides an advanced risk management tool for power companies, helping to increase the operational efficiency of smart grids and encouraging further research toward greater intelligence in the field. [ABSTRACT FROM AUTHOR]

The coupled development of new-type urbanization (NTU) and rural revitalization (RR) represents a critical proposition put forth by China for forging a novel paradigm of urban-rural relationship. Initially, this study employs the entropy method to quantify NTU and RR. Subsequently, it carries out a comprehensive analysis concerning their coupled relationship with the relative development degree model (RDDM), coupled coordination degree model (CCDM), Dagum Gini coefficient, kernel density estimation, and Tobit model. The findings drawn from the study indicate from 2011 to 2022, NTU and RR in the Yangtze River Economic Belt (YREB) have exhibited a consistent upward trajectory, but lagging NTU disorders are widely distributed and numerous. The coupled coordination degree (CCD) of NTU and RR constantly improves, transitioning from moderate imbalance to primary coordination, exhibiting a spatial distribution of a "high in the east and low in the west". The relative disparity between the coupled development of NTU and RR demonstrates a slowly narrowing trend, whereas the absolute disparity indicates an expanding trend. Among the influencing factors, the development of the agricultural industry exerts the most significant positive impact on the coupled development, whereas the level of financial support for agriculture exerts a dampening effect, which is heterogeneous in nature. [ABSTRACT FROM AUTHOR]

The standard interpretation of inequality uses a number, such as the Gini coefficient, to compare income inequality across countries. These numbers apply universal upper limits to the maximum feasible inequality (Gini = 100) in vastly diverse economies even though floors for socially acceptable living standards vary quite a bit in different societies. I develop a new measure of income inequality — the Nationally Representative Inequality Extraction Ratio (NR IER) — and apply it to 112 countries. The NR IER uses country-by-country social and economic parameters to measure the distance between the actual income distribution and the country-specific feasible limit (a counterfactual distribution). I ground the counterfactual distribution in a functional income concept, corresponding to Marx's concept of exploitation. NR IERs are inversely related to per-capita income and exceed the feasible limits in the world's poorest countries. However, I find little variation in extractive inequality between closed autocracies (e.g., China) — where corruption is expectedly extractive — and liberal democracies (e.g., USA). Controlling for different political regimes, the NR IER explains over 60 per cent of a person's income anywhere in the world. [ABSTRACT FROM AUTHOR]

China is struggling to facilitate the application of renewable portfolio standards to realize sustainable economic growth. As such, improving the current distribution mechanism is crucial. In this paper, the context‐dependent data envelopment analysis and multi‐objective linear programming are combined to allocate the renewables quota for each province. This integrated approach can maximize total electricity generation while minimizing the total CO2 emission with considering the disparity of production technology level. Then, the extended Gini coefficient is employed to assess the fairness of new quota mechanism. We find that (1) the eastern region is the most efficient during the power generation process. During 2016–2019, the efficiency in the western region presents an upward trend. (2) The allocation results indicate that Inner Mongolia and Qinghai have the greatest pressure to absorb renewable energy electricity, while Guangdong and Guizhou can instead reduce the most. Shandong and Inner Mongolia face the greatest burden in conserving non‐renewable electricity. (3) Compared to 2020, the newly allocated scheme can mitigate inequality, with the Gini coefficient changing from 0.264 in 2020 to 0.248 after the allocation. Meanwhile, the reallocation reduces the Gini coefficient related to renewable electricity, non‐renewable electricity, and CO2 emissions by 0.003, 0.028, and 0.073, respectively at the 2020 level. [ABSTRACT FROM AUTHOR]

We measure the regional gaps in green total factor productivity (GTFP) growth by using the Dagum's Gini coefficient based on panel data for 306 cities from 1996 to 2017, then adopt a geographical detector to test the contribution of resource misallocation to the unbalanced growth in GTFP. The results show that Chinese agricultural GTFP continues to grow, but the overall growth gap has expanded year by year, mainly due to the inter-provincial gap. Compared with land, labor and machinery, fertilizer misallocation is the main factor driving the unbalanced growth in GTFP. Moreover, the interaction contribution of fertilizer misallocation with any one resource misallocation is higher than that in a single factor. Finally, resource misallocation also leads to unbalanced growth in technological progress and technical efficiency, but more so for the latter. Our research helps to provide a new solution to the "dilemma" of food security and ecological security from the perspective of optimizing resource allocation. [ABSTRACT FROM AUTHOR]

Ecological Welfare Performance (EWP) is a core issue in sustainable development and ecological civilization. Although Guangdong Province is one of China's most developed economies and most highly urbanized areas, there is a gap in the evaluation of the ecological welfare performance of the province. Previous studies have mainly calculated the performance of ecological welfare from a static viewpoint or only from the perspective of network efficiency, and few researchers have considered dynamic characteristics and network structures. This research focuses on 21 prefecturelevel cities in Guangdong Province and measures their ecological welfare performance by applying the dynamic network slacks-based measure (DNSBM) model. Using the Dagum Gini coefficient, this study identifies the sources and contributions of differences in ecological welfare performance among regions in Guangdong Province. The results reveal a low overall level of ecological welfare, with levels of ecological welfare showing an uneven distribution among the 21 cities. EWP and economic growth are spatially mismatched. The overall variations in the ecological welfare performance in the province are mainly due to ultra-high-density contributions. Therefore, we recommend that Guangdong Province strengthen overall regional coordinated development and promote high-quality "shared" development in the northern, eastern, and western areas. [ABSTRACT FROM AUTHOR]

Objectives: Describe the prevalence, frequency, and longitudinal development of regulatory offences within Dutch inland shipping on both the ship and business level. Examine whether latent groups with differing trajectories can be distinguished and compare differences between these trajectory groups. Methods: Longitudinal inland shipping inspection data from several inspection agencies are analysed. Lorenz curves and Gini coefficients are used to describe offence distributions. Group-based trajectory modelling is applied to analyse the longitudinal development of regulatory violations of ships and corporations. Between-group comparisons are made using (multivariate) analysis of variance. Results: A skewed distribution of offending on both the ship and business level is found. On both levels of analysis, four trajectory groups display differing developments in the distribution of offending. Although differences in characteristics between trajectory groups were present, effect sizes were small. Conclusions: Disproportionality in corporate offending at both levels of analysis is in constant motion. Regulators need to regularly (re)identify their target groups. [ABSTRACT FROM AUTHOR]

In order to solve the problem of mining and analyzing athlete training monitoring information, the author proposes a deep learning based integration of athlete training monitoring information. The author proposes a deep learning based method for integrating athlete training monitoring information, deploying agents on various data source nodes, collecting athlete training information from each data source, and implementing denoising and dimensionality reduction on the monitoring information; Building an information integration model based on convolutional neural networks in deep learning; Extracting monitoring information features through convolutional layers, and fusing information with similar features into the same category through output layer classifiers, completing the integration of athlete training volume monitoring information. The experimental results show that as the number of iterations increases, the classification accuracy of the integrated model based on convolutional neural networks is continuously improving, while the error is continuously decreasing and getting closer to zero. When the maximum iteration number is 100, the model accuracy is 99.74%. The average Gini coefficient of the author's research method is higher, indicating a higher integration accuracy of the method. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to prognosing European economic crises through the development of an economic–financial risk sensitivity model. The model integrates key macroeconomic indicators such as government deficit (NETGDP), GINI coefficient, social protection expenditure (ExSocP), unemployment rate (UNE), research and development spending (RDGDP), and tax structures (TXSwoSC), assessing their role in predicting economic vulnerability across European countries. By applying the Kruskal–Wallis non-parametric test on data from 324 observations across multiple countries, significant differences were identified in the distribution of these variables. The results show that government policies related to social protection, R&D, and taxation play an important role in a country's resilience to economic shocks. On the other hand, indicators such as income inequality and unemployment exhibit less variation, reflecting global economic conditions. The model provides a comprehensive risk assessment framework, allowing for the early detection of potential economic crises and guiding policy adjustments to mitigate risks. This methodology offers valuable insights into the sensitivity of European economies to financial disruptions, emphasizing the importance of fiscal policies and social expenditure in maintaining economic stability. [ABSTRACT FROM AUTHOR]

Traditional villages embody China's long-standing farming culture and are the carriers for the inheritance and development of traditional culture in rural China. However, because of the continuous erosion of rural space due to China's rapid urbanization, traditional villages are gradually declining and even disappearing. Protecting traditional villages has become a significant scientific problem in the implementation of the "Rural Vitalization Strategy" in the new era. The study of the spatial distribution pattern of traditional villages and its influencing factors is an important basis for formulating macro-protection policies for traditional villages in China. However, the existing literature is one-sided and subjectivity in revealing the influencing factors, making it difficult to form accurate and comprehensive protection policies. Employing the Gini coefficient, kernel density estimation, and the Geographically Weighted Regression (GWR) model, this study analyzes the impact of human settlements factors on the spatial distribution patterns of traditional villages in Liaoning province. Results can be summated as follows. (1) The spatial distribution of traditional villages in Liaoning exhibits a clustered pattern. (2) In terms of the geographical regional scale, the distribution is highly uneven and mainly concentrated in the western region of Liaoning. At the municipal scale, the distribution is relatively uneven and primarily located in the cities of Chaoyang, Jinzhou, Huludao, Panjin, Anshan, and Dalian. (3) The majority of traditional villages are distributed along the southwest–northeast axis of the standard deviation ellipse, which corresponds with the main mountain ranges of Liaoning. (4) The distribution density features a western continuous clustering, central and eastern scattered clustering, and edge clustering pattern. (5) The spatial distribution patterns of traditional villages in Liaoning are influenced by various human settlements factors, with spatial variation in the nature and intensity of the effects of these factors. (6) The natural factors of human settlements are the dominant factors in the spatial distribution patterns of traditional villages, while the humanistic factors of human settlements have a dual impact on these patterns. This paper presents novel ideas for the study of the spatial distribution pattern of traditional villages, scientific support for the development of the disciplines of rural geography and the geography of human settlements, and new scientific decision-making and theoretical support for the protection and utilization of traditional villages. [ABSTRACT FROM AUTHOR]

The coordination development of the Water-Energy-Food complex system (WEF CS) is vital to realizing the Sustainable Development Goals of the United Nations. However, the existing research ignores the influence of external environment, and it is not clear which dimension is the key driving mechanism for coordinated development of WEF CS. Herein, it built a theoretical framework of "system unit-nexus-natural environment" WEF CS based on the logical framework of "unit-nexus-external environment", and adopted Dagum Gini coefficient, coupling coordination degree, and grey correlation models to explore the sustainable development ability of water resource, energy resource and food resource of the Yellow River Basin (YRB). It showed that (1) the overall development level of WEF CS showed significant stage differences, indicating upstream > downstream > midstream; (2) the overall Gini coefficient decreased from 0.123 in 2004 to 0.084 in 2020, and the spatial mismatch of development level mainly came from the difference between reaches; (3) the influencing factors of the key zones that hindered the development of WEF CS chiefly came from the nexus dimension. This study provides insights into optimizing spatial adaptation pattern and improving coordination development in basins. [ABSTRACT FROM AUTHOR]

The array of wildfire activities instigated by human endeavors has emerged as a significant source of atmospheric pollution, posing considerable risks to both public health and property safety. This study harnesses Sentinel-2 satellite data, employing a variety of methods including spectral index methods, thresholding, and the Random Forest (RF) model for active fire spot detection. The research encompasses a wide range of land cover types across various Chinese regions. Utilizing the Gini coefficient, the study assesses the importance of spectral and texture features in the RF, culminating in the selection of an optimal feature combination for the construction of a bespoke RF model tailored for active fire detection. The research utilized texture features based on the Grey Level Co-occurrence Matrix (GLCM), demonstrating their significant contribution to enhancing the accuracy of fire detection using the RF model. Our analysis reveals that GLCM-based texture features, which form 40% of the model's final feature set, are crucial for improving detection accuracy. The optimized RF model demonstrates a marked superiority in identifying active fires, achieving an overall accuracy of 86.1%. The study results demonstrate that the bespoke RF model is suitable for detecting active fire across various land cover environments in China. [ABSTRACT FROM AUTHOR]

Rural revitalization (R), new-type urbanization (U) and the ecological environment (E) are a unity of complementary advantages and mutual promotion and coexistence, the coupling and coordination of the three is the key to realizing the Chinese modernization and the harmonious coexistence of human beings and nature. Based on China's provincial panel data from 2011 to 2022, this paper constructed a comprehensive evaluation index for the R-U-E system, using the entropy method, coupled coordination model, Dagum's Gini coefficient, kernel density estimation, spatial correlation analysis, and spatial Durbin model to explore the level of comprehensive development, spatial-temporal evolutionary characteristics of coupled coordination, regional differences and spatial effects of the three systems. The following results were observed: (1) The comprehensive index of rural revitalizationand new-type urbanization exhibits a growing trend and significant regional differences, with East China outperforming other regions, but the average value of below 0.5 needs to be further improved. The ecological environment index exhibits a smoother growth trend, higher in South China than in other regions. (2) The level of R-U-E coupling coordination has increased year on year, from barely coordinated to primary coordination. (3) The spatial imbalance in coupling coordination has improved both nationally and in the seven regions, with the largest intra-regional differences in South China and the smallest intra-regional differences in Central China. The differences between the Northeast and Central China regions exhibit a widening trend, while the differences between all other regions exhibit a decreasing trend. Interregional variations are the main factor affecting overall variance, but their impact on the overall variance is gradually diminishing. (4) The level of coupling coordination has obvious spatial correlation, and the "high-high" and "low-low" cluster aggregation characteristics was evident. (5) Government behavior and the levels of economic growth, human capital, and digitization significantly contribute to the coupled and coordinated development of the region and, at the same time, have a significant spatial spillover effect on neighboring provinces; the degree of openness to the outside world contributed to the coordinated development of the region, while it had an inhibitory effect on the neighboring provinces; and the drive to innovate has only a certain contributing effect on the neighboring regions. Targeted policy measures in response to this paper's empirical findings may provide policymakers with a reference point for achieving regional sustainable development goals. [ABSTRACT FROM AUTHOR]

Background: Internet searches offer an indicator of public attention and possible demand for certain things. Studying the spatiotemporal characteristics of the public's concern for vaccination can determine the spatiotemporal distribution of demand for vaccines in China, and capture the changes in the health awareness of the Chinese population, thus informing future vaccination strategies. Methods: Based on the collection of Baidu search indices for vaccination-related keywords in 363 cities in China, This paper seeks to explore the spatiotemporal changes and regional differences in public attention toward vaccination in China by using the seasonal index, seasonal concentration index, Herfindahl index, Moran index, and Dagum Gini coefficient. Results: The following findings are presented. First, there are significant seasonal fluctuations and unbalanced monthly distributions of vaccination-related public attention in China. Second, the public attention in Chinese cities shows the spatial characteristics of "leading in the east, followed by the central, western and northeastern regions". The spatial correlation of attention has been strengthened, and the high-high clusters are mainly distributed in the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Greater Bay Area (GBA) urban agglomerations. Third, regional differences in overall public attention narrowed in China, with intra-regional differences narrowing in seven regions (Northwest China, Central China, and so on), and intra-regional differences increasing in East China. The dominant role in the Gini coefficient changes from transvariation intensity to inter-regional differences. Conclusion: Major public health emergencies stimulate the public's attention to health topics. Although the short-term increase in vaccination-related public attention was not observed to translate into a long-term increase in public vaccine literacy, the seasonal and regional differences in vaccination-related public attention in China have significantly narrowed before and after COVID-19, suggesting that the imbalance between public health literacy levels has improved. [ABSTRACT FROM AUTHOR]

Scientific estimation of China's transport carbon reduction potential (CERP) and exploration of its temporal and spatial characteristics and influencing factors are important bases for formulating emission reduction policies. Based on the dual perspective of equity and efficiency, we assess the CERP of the transportation industry in 30 provinces in China from 2010 to 2019 and analyze its spatio-temporal evolution characteristics using the Kernel density estimation method. Then, the Dagum Gini coefficient is used to measure the regional differences and sources of the CERP, and its influencing factors are analyzed with the help of the random effects panel Tobit regression model. The results show that: (1) from 2000 to 2019, the CERP of the transportation industry in China and the three regions show an oscillating upward trend, with a spatial pattern of "high in the west and low in the east". (2) The overall difference in the CERP of the transportation industry shows a fluctuating downward trend, and the difference in hypervariable density has the highest contribution rate. The inter-regional differences between the West and other regions are the largest, and the intra-regional difference pattern shows the pattern of western > central > east. (3) The technological improvement, industrial structure, and scale of transportation industry development have a significant positive impact on the CERP of the transportation industry. The influence of urbanization influence and environmental regulation have a significant negative influence. [ABSTRACT FROM AUTHOR]

The structure of personal networks reflects how we organise and maintain social relationships. The distribution of tie strengths in personal networks is heterogeneous, with a few close, emotionally intense relationships and a larger number of weaker ties. Recent results indicate this feature is universal across communication channels. Within this general pattern, there is a substantial and persistent inter-individual variation that is also similarly distributed among channels. The reason for the observed universality is yet unclear—one possibility is that people's traits determine their personal network features on any channel. To address this hypothesis, we need to compare an individual's personal networks across channels, which is a non-trivial task: while we are interested in measuring the differences in tie strength heterogeneity, personal network size is also expected to vary a lot across channels. Therefore, for any measure that compares personal networks, one needs to understand the sensitivity with respect to network size. Here, we study different measures of personal network similarity and show that a recently introduced alter-preferentiality parameter and the Gini coefficient are equally suitable measures for tie strength heterogeneity, as they are fairly insensitive to differences in network size. With these measures, we show that the earlier observed individual-level persistence of personal network structure cannot be attributed to network size stability alone, but that the tie strength heterogeneity is persistent too. We also demonstrate the effectiveness of the two measures on multichannel data, where tie strength heterogeneity in personal networks is seen to moderately correlate for the same users across two communication channels (calls and text messages). [ABSTRACT FROM AUTHOR]

The process of urbanization, which leads to increased population density, changes in land use patterns, and heightened demand for industrial and domestic water use, exacerbates the contradiction between the supply and demand of water resources. This study examines the discrepancies between the supply and demand of water resources amidst urbanization, utilizing data from 110 cities within the Yangtze River Economic Belt (YREB) spanning from 2012 to 2021. The research employs the projection pursuit clustering model and the Dagum Gini coefficient method to evaluate the developmental status of water resources. While the Yangtze River Delta (YRD) region maintains a leading position with a water resources development score of 9.827 in 2023, there is a 2.2% increase in intra-regional disparity. The water resources development score for the City Cluster in the Middle Reaches of the Yangtze River (CCRYR) has experienced a decline, from 8.263 in 2012 to 8.016 in 2021; however, a reduction in intra-regional disparities has been observed since the implementation of the 2016 Outline of the Yangtze River Economic Belt Development Plan (YREBP), which suggests the policy's efficacy. The Chengdu-Chongqing Economic Zone (CCEZ), despite its initially lower level of development, has demonstrated significant growth, with scores rising from 7.036 in 2012 to 7.347 in 2021. Collectively, the water resources development in the YREB exhibits an upward trend, yet the development remains uneven. The CCRYR shows a catching-up effect because of the YREBP, and the differences in other regions are widening. The research results provide decision-making support for water resources planning and management, and are of great significance in promoting the sustainable use of water resources. [ABSTRACT FROM AUTHOR]

In order to objectively analyze the situation of spatial matching and carrying capacity of water resources in Henan Province, this paper evaluated the situation of spatial matching and carrying capacity of water resources in Henan Province from 2012 to 2021 by constructing Lorentz curve, improving mutation series model and mature-element extension model based on the data of total water resources and population, and used obstacle degree model to diagnose the main factors affecting the carrying capacity. At the same time, based on the water resources situation and the planned annual supply and demand of Henan Province, the multi-objective optimal allocation model of water resources was constructed. The results show that the spatial distribution of water-irrigated area and water-population is in equilibrium, while the spatial equilibrium of water-secondary industry production value and water-green coverage area is poor. From 2012 to 2021, the overall water resources carrying capacity of Henan Province is gradually increased, and the evaluation comprehensive value is increased steadily. The carrying capacity of water resources in Henan Province is mainly affected by natural population growth rate, industrial water consumption, population density, surface water resources, water production modulus and annual average precipitation. Water resources allocation can be divided into five water allocation schemes, and different schemes have different water use benefits, which can provide reference for regional water allocation [ABSTRACT FROM AUTHOR]

In the context of promoting educational equity and improving welfare, exploring ways to further enhance residents' subjective well-being from the perspective of educational equity holds significant practical importance. This study uses the educational Gini coefficient to measure the educational inequality index across different provinces and cities, and matches it with data from the China Family Panel Studies (CFPS) to investigate the relationship between educational inequality and residents' subjective well-being. The research findings reveal a significant negative correlation between educational inequality and residents' well-being, with observed heterogeneity. Specifically, educational inequality has a greater negative impact on groups with lower levels of well-being, rural areas, and the central and western regions of China. Mechanism analysis confirms the income distribution effect and economic growth effect of educational inequality. Therefore, increasing attention to the issue of educational equity and understanding the well-being effects of educational inequality are of great significance for the Chinese government in improving residents' welfare in the new era. [ABSTRACT FROM AUTHOR]

Expanding upon the Driver-Pressure-State-Impact-Response (DPSIR) model system, this work employs the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach, Kernel density estimation, Spatial autocorrelation, Dagum Gini coefficient, and geographic detectors to evaluate the ecological security level of China’s tourism industry from 2010 to 2020. Examining the tourism ecological security’s spatio-temporal evolution, geographical disparities, and driving variables is the goal of this study. One thing that stands out from the data is that (1) there is a clear increase trend in the time series of tourism ecological security (TES). (2) There is spatial variability and lack of landscape equilibrium when the general geographical distribution pattern in space gradually decreases from east to west. (3) According to the Dagum Gini coefficient, there is a decreasing geographical non-equilibrium of tourism ecological security, with the main cause of this non-equilibrium being the inter-regional disparity between the east and west. (4) The factors affecting the tourism ecological security are complex and diverse. These factors are closely related to the economy, environment and population of the city. The findings provide a reference for the sustainable development of regional tourism ecology. [ABSTRACT FROM AUTHOR]

As industrial technologies advance, climate change and environmental pollution increasingly pose threats to human health. This study examines the coupling coordination characteristics between ecological environmental civilization (EEC) and resident public health (RPH) to promote both higher public health standards and enhanced societal sustainability. Utilizing panel data from 31 provinces in China spanning from 2010 to 2022, this paper constructs evaluation indices for EEC and RPH. Initially, the entropy method is employed to determine the development levels of each domain. Subsequently, a modified coupling coordination degree (CCD) model is applied to assess the CCD between EEC and RPH. This research further investigates the spatiotemporal evolution trends of the CCD using methods such as the Dagum Gini coefficient, kernel density estimation (KDE), and Markov chains. Finally, the panel Tobit model is utilized to analyze factors influencing the CCD. Findings reveal that during the study period, both EEC and RPH in China exhibited a stable upward trend, although the overall development level remained relatively low. The CCD showed consistent growth both nationally and across three major regions. Overall inequality in coupling coordination, as measured by Dagum Gini coefficient, has decreased, with the coefficient reducing from 0.0316 in 2010 to 0.0199 in 2022. KDE results indicate a rightward shift in the density curve of the CCD, suggesting a significant reduction in absolute disparities. Panel Tobit regression analysis shows that economic development, urbanization, and education levels significantly and positively influence the CCD on a national scale, with urbanization having the most substantial impact, followed by economic development and education levels. [ABSTRACT FROM AUTHOR]