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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]

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]

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]

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]

As a resource-friendly consensus protocol, Proof-of-Authority (PoA) has been widely deployed in IoT applications with blockchain technology. It relies on a fixed set of trusted nodes called validators for block generation. In contrast to traditional consensus mechanisms, PoA offers better performance but also leads to a centralized blockchain. In a centralized blockchain, PoA gives a few authorities the power to tamper with all nodes. To improve the decentralization of the protocol, this paper proposes a proof of authority based on a dynamic set of validators (DyPoA). The protocol decouples the right to generate and commit blocks to the blockchain from the authority node in the original PoA. It enables unauthenticated nodes to perform the process of packing transactions into blocks, while authenticated nodes validate and commit blocks to the blockchain. Additionally, DyPoA introduces a contribution score mechanism to measure the work accomplished by each node when a block is appended to the blockchain. Based on the contribution score, DyPoA selects and replaces validators through cryptographic sortition. We evaluate DyPoA through decentralization metrics and performance tests. The experimental results show that the Shannon entropy, Gini coefficient, and Nakamoto coefficient of DyPoA are 1.5 times, 0.7 times, and 1.7 times that of the original PoA, respectively, and achieve a 2.2x throughput improvement and 3x latency reduction compared to the original PoA. [ABSTRACT FROM AUTHOR]

In the process of implementing innovation-driven strategy, it is of great strategic significance to build a digital innovation ecosystem (DIES) with different characteristics and coordinated development. To scientifically measure the development level of China's DIES, the paper conducts an in-depth study on the distribution dynamics, regional differences, and convergence of the development of DIES in China and the four regions. This paper takes the relevant data of 31 provinces and cities in China from 2010 to 2019 as samples, uses the standard deviation ellipse method and Markov chain to characterize their distribution dynamics, uses the Dagum Gini coefficient to analyze their differences, and finally uses the coefficient of variation and spatial panel model to analyze σ convergence and β convergence. This research shows that the development level of China's DIES is generally on the rise, but there is a significant difference between regions, showing a decreasing spatial feature from the core provinces to the peripheral areas that are too far away from the epicenters to compete with the primary economic domain. The differences in the development of the DIES generally show a downward trend, and the differences are mainly regional. However, the DIES development in China and its four regions show both viable and promising convergence characteristics although the convergence speed and trends are different. The innovative contributions of this paper are as follows: quantitatively measure the development level of China's DIES, scientifically reveal the regional characteristics of the development level of DIES, and identify the sources of regional differences, dynamic evolution trends, and convergence characteristics. It not only makes up for the deficiency of quantitative research on DIES, but also helps to grasp the development status of China's DIES accurately, and provides theoretical support and scientific reference for its policy formulation and development direction. [ABSTRACT FROM AUTHOR]

The increasing housing prices in Türkiye have generated substantial public concern due to their potential to disrupt social and economic stability, exacerbate social inequality, and contribute to criminal issues. This study investigates the multifaceted impacts of housing prices on crime rates within the Turkish context. Utilizing annual data encompassing 26 regions in Türkiye from 2016 to 2019, we adopt a sophisticated mediating effect model to analyze the intricate relationships between pertinent variables. Our findings show that housing prices directly and indirectly influence crime rates. Notably, the mediating role of the Gini coefficient is unveiled, shedding light on its function in moderating the relationship between housing price escalation and crime rates in landTürkiye. This study underscores the pivotal role of economic distortion as a mediating factor in understanding the nexus between rising housing costs and the incidence of criminal activities in the Turkish context. [ABSTRACT FROM AUTHOR]

To address the conservative excavator working device configuration obtained by traditional design methods, a lightweight structure design method was proposed in this study based on automatically generated surrogate model. A finite element model of the working device was first constructed, and its accuracy was verified against experimental results. By incorporating the Gini coefficient to compute the information entropy pertaining to the relationship between variables and responses, the entropy-weighted TOPSIS method has been significantly enhanced. Subsequently, the comprehensive contributions of the boom design parameters to the mass, deformation, and stress responses were calculated, and the parameters exerting significant effects were selected as the design variables through the application of the improved TOPSIS. Next, the working device optimisation model was subsequently established using the minimum mass as the target and the stress and deformation as constraints. And then, a surrogate model of the working device was constructed using 500 sample points. Finally, a genetic algorithm was employed to derive a lightweight design of the excavator boom based on the surrogate model. The results indicate that the proposed method reduced the weight of the considered hydraulic excavator boom by 9.30%; further, a finite element simulation verified that the stress and deformation met the design requirements of the boom. [ABSTRACT FROM AUTHOR]

With the continuous increase of older adults, population ageing has become a public policy issue worldwide. Gaining insight into the current state of population ageing and its impact on income inequality is essential for designing effective and equitable policies that support economic development and social stability. This study, focusing on rural China, explores the relationship between population ageing and Gini coefficient of income, using nationally representative rural household data collected by the Ministry of Agriculture and Rural Affairs of China from 2003 to 2020. Results based on the decoupling index and decomposition method reveal that the issue of income inequality in the surveyed rural areas has not intensified with the progression of ageing, which overturns the predominant view in existing research that population ageing exacerbates income inequality. The findings indicate that the inhibitory effect of increasing transfer income on income inequality has become more pronounced as ageing deepens, and the income structural effect of rural residents in China has played a role in reducing the Gini coefficient. Based on these results, some suggestions are proposed such as raising parental allowance, improving rural production and living environment, constrcuting the long-term care system, and implementing multifaceted measures to enhance the income level of rural older adults. [ABSTRACT FROM AUTHOR]

The growth of timber assortment is related to site conditions and forest management measures. To our knowledge, however, the effects and relative importance of these factors on the growth of different timber assortments of Chinese fir have not yet been explored. Based on data from long-term fixed observation plots in the northwest of the Chinese fir distribution zone, we examined the effects of planting density and the site index on the timber assortment structure of Chinese fir. Furthermore, we quantified the relative importance of stand factors (age, planting density, stand density index, number of living trees, Gini coefficient, and site index) in determining the growth of various timber assortments. The results showed that the wood yield of all timber assortment types increased as the site quality improved. The outturn and outturn rate of large- and medium-diameter timber were negatively correlated with the planting density. Before the age of 22, planting density had a negative impact on total timber yield and small-diameter timber outturn. After 22 years, planting density had a positive impact on total timber yield and small-diameter timber outturn. SDI (stand density index), age, and SD (stand density) were the most important factors influencing total timber yield and small-diameter timber. The relative importance of age to large-diameter timber was the greatest, followed by SI (site index) and SD. The effects of age, SD, SI, and PD (planting density) on the medium-diameter timber were greater than those of SDI and Gini coefficient. The results indicate small- and medium-diameter timber as the primary target timber assortment types to be cultivated in the study area, while large-diameter timber cannot be effectively produced under the current site conditions. Our findings provide valuable insights for the management of Chinese fir plantations and the directed cultivation of target timber assortments in the northwest of the Chinese fir distribution zone. [ABSTRACT FROM AUTHOR]

This paper seeks to measure the influence of personal circumstances and inequality of opportunity on income and employment status in Kazakhstan. It identifies individual effort and circumstances as determinants. The analysis suggests that the higher education variable explains about one-third and one-fifth of the variations in income and employment status, respectively. The paper tests (and rejects) the hypothesis that the final outcomes of income and employment status are not affected by cultural identity with the Russian ethnicity used as a proxy. The analysis is based on the Household Budget Survey conducted by the Agency of Statistics of the Republic of Kazakhstan for 2003 and 2005. It applies ordinary least squares and logit models and calculates Gini coefficients for all the regions of Kazakhstan using predicted incomes based on the individual factors affecting the final outcomes. The study shows that the Russian ethnicity variable is associated with higher income and better employment prospects in Kazakhstan, which suggests that there is scope for policy measures to improve opportunities for other language groups. [ABSTRACT FROM AUTHOR]

Optimization challenges necessitate the development of strategies to address computational complexity, aiming to increase efficiency, reduce expenses, or improve the allocation and management of resources. Decomposition, notably clustering, offers streamlined solutions. K-means, Affinity Propagation, and Density Peaks are foundational for clustering unlabeled data. Hierarchical clustering enhances robustness through multi-level decomposition. The evaluation considers quantitative metrics and domain-specific assessments. Alternative representations like cluster-based abstractions offer new perspectives for complex problems. This paper introduces a novel hierarchical framework for solving the Euclidean Traveling Salesman Problem (TSP) using compressed quadtrees topology via recursive hybrid clustering. The cities are hierarchically clustered into a compressed quadtree, optimizing intra-cluster cohesion and inter-cluster separation, assessed by certain adequate indexes such as the Davies-Bouldin index and Gini coefficient. The 2D hierarchical representation enhances parallelizability for concurrent optimization. The compressed quadtree is embedded into crossed cubes to improve scalability, fault tolerance, and economic resource utilization. A one-by-one dilation 2 embedding minimizes distance distortions. The integration of recursive hybrid clustering, compressed quadtrees, and crossed cubes offers an innovative framework for hierarchical decomposition and parallelization in Euclidean TSP optimization. [ABSTRACT FROM AUTHOR]

Agroforestry practices (AFPs) play a critical role in enhancing income and reducing poverty. This study assessed the effect of AFPs on income and poverty status of farmers in Lay Armachiho (LA), Bahir Dar Zuria (BDR), and Banja districts of Northwestern Ethiopia. 387 households, and 63 key informants were interviewed. Data were analyzed using descriptive statistics, FGT index, Gini coefficient, and multiple linear regression. About 49.35% of the respondents are categorized poor with a poverty gap of 18.93 and a poverty severity level of 9.7. Banja was the greatest with persons below poverty level (59.2%), followed by BDR (49.72%). Agroforestry practices contribute 28.43% to household income. Income from AFPs lowered the poverty ratio, poverty gap index, and poverty severity level of households by 13%, 9%, and 7%, respectively. Income from AFPs lowered the area between the line of equality and the Lorenz curve, as well as the Gini coefficient, by 7.97%. AFPs also lowered the income disparity of households in all districts. Age, AFPs land size, road accessibility, irrigation, AFPs experience, and AFPs types affect households AFPs income positively. Family size and membership to credit institutions had a negative effect. Thus, in order to lower poverty and raise household income, labor productivity, the credit service system, the road and irrigation infrastructure, and AFPs all need to be improved and scaled up. [ABSTRACT FROM AUTHOR]

Spatial inequality erodes social cohesion and political stability, impacting global sustainable development and human well-being. This study examines spatial inequality in China across economic, social, environmental, infrastructural, and innovation dimensions, exploring how these inequalities evolve with economic development. Drawing on the Sustainable Development Goals and Chinese planning goals, we selected 13 indicators pertinent to human well-being. We employed the population-weighted coefficient of variation, Gini coefficient, and Moran's I to assess spatial inequalities and analyzed their relationship with economic growth. The findings reveal that China currently exhibits the highest spatial inequality in innovation and the lowest in the social dimension. Since 1990, most indicators have trended towards decreasing spatial inequality, except for unemployment rates and carbon emissions, which have increased. The economic and innovation gap between the eastern coastal regions and the central and western regions has widened, whereas disparities in housing, healthcare, roads, and digitalization have narrowed. China's experience demonstrates that Williamson's inverted U-shaped hypothesis extends beyond the economic domain to encompass education, healthcare, infrastructure, and digitalization, providing policy insights for addressing regional inequalities in China in the post-pandemic era. [ABSTRACT FROM AUTHOR]

For coordinated regional growth and the development of high-quality manufacturing, China must narrow its regional energy efficiency gap and catch up inter-regionally. This paper focuses on whether China's inter-provincial manufacturing energy efficiency has technological diffusion and a catch-up effect and explores its possible influencing factors, which are important for narrowing the differences in China's manufacturing energy efficiency and promoting the improvement of the overall level of efficiency. Between 2011 and 2020, 30 Chinese manufacturing industries will be evaluated using a non-radial distance function model under environmental conditions. By employing the Dagum Gini coefficient method, regional disparities were analyzed, with hyper-variable density and efficiency discrepancies between regions making a noteworthy contribution. This paper evaluated a catch-up effect by constructing a frontier productivity model that considered the influence of China's manufacturing energy efficiency. Results show a general rise in energy efficiency, particularly in coastal regions, higher than inland ones. The Gini coefficient of energy efficiency in manufacturing experienced a slight increase; however, when comparing it to the regional efficiency frontier, the catch-up effect and technology diffusion effect of China's provincial manufacturing energy efficiency become more pronounced when taking into account the national efficiency frontier; the sub-regional manufacturing energy efficiency catch-up effect has different performances; the catch-up and technology diffusion effect is more evident after controlling for Economic development, innovation levels, the environmental regulation, and the proportion of high-energy-consumption output value and other influencing factors. [ABSTRACT FROM AUTHOR]

High-quality development is the primary task of comprehensively building a socialist, modern country, as well as the primary task of building urban agglomerations in China. Based on the five development concepts, this paper used the entropy method to measure the High Quality Development Index (HQDI) of the five major urban agglomerations. The results showed that the HQDI of the five major urban agglomerations shows a fluctuating upward trend. First, using the Dagum Gini coefficient to explore the sources of HQDI development differences in urban agglomerations, we found that the main source of HQDI differences in urban agglomerations was interregional differences, while intra-regional differences were not important. Second, kernel density estimation was used to test the dynamic evolution trend of HQDI within urban agglomerations. There was a polarisation phenomenon in the HQDI of urban agglomerations, such as the Pearl River Delta urban agglomeration and the Chengdu-Chongqing urban agglomeration. But overall, the degree of imbalance had decreased. Third, using geographic detectors to examine the driving factors of HQDI in urban agglomerations, we found that the main driving forces for improving HQDI in urban agglomerations were economic growth, artificial intelligence technology and fiscal decentralisation. All the interaction factors had greater explanatory power for the spatial differentiation of HQDI, which can be divided into two types: two-factor improvement and non-linear improvement. This study is conducive to improving and enriching the theoretical system for evaluating the high quality development of urban agglomerations, and provides policy references for promoting the high quality development of urban agglomerations. [ABSTRACT FROM AUTHOR]

This study defines the concept of major and minor countries and establishes a multidimensional and dynamic assessment system to evaluate the influence of countries participating in global climate governance. We systematically calculate 45 indicators for 53 countries across 9 global climate negotiation interest groups over the seven years. Our findings indicate a significant difference in influence between major and minor countries. This gap is particularly significant regarding losses incurred from climate disasters, with a more than fourfold difference between the top 25% and the bottom 25% in the influence rankings. The influence-climate disaster Index Gini coefficient further indicates that climate governance is characterized by extreme inequality. We argue that this phenomenon arises because those with more decisive influence in global climate governance do not bear losses from climate disasters commensurate with their influence. Therefore, their willingness to participate in climate governance is lower than those who suffer greater consequences. [ABSTRACT FROM AUTHOR]

Spatiotemporal change in precipitation induced by climate change can be a concern for riverine disasters. The relationship between precipitation and flow discharge in the 8 rivers from northeast to southwest of Japan (either mainstream or tributary) in which neither manmade dam nor reservoir is present was investigated based on observed data at the stream gauging stations managed by the Ministry of Land, Infrastructure, Transport and Tourism of the Japanese government. Observed data of air temperature, precipitation, etc. by the Japan Meteorological Agency vicinity of the gauging station in the 8 rivers basins were also used in the analyses. The precipitation concentration index (PCI) which is the Gini coefficient of precipitation during a year, and the Gini coefficient of flow discharge were computed for about half a century. The results reveal that annual maximum flow discharge can be related closely to the extreme rainfall events such as annual maximum daily or hourly precipitation. Obtained trends of the PCI were all positive and statistically significant at the 1% level, indicating that an in – equality in rainfall distribution during a year has been accelerated as the air temperature has risen in the basins. Whereas obtained trends of the Gini coefficient of the flow discharge were either positive or negative, and very weakly correlated with the trends in the PCI. Temporal precipitation distributions in a year have changed in the 8 rivers basin, i.e. light rain days (0 – 1 mm/day) have increased whereas rain days with 1 – 10 mm/day have decreased, while no such trend is seen in flow discharge in the 8 rivers. The interaction between surface and subsurface flows, and soil moisture may play important roles in moderating the effects of spatiotemporal change in precipitation. The flow discharge, however, can increase immediately in response to the precipitation when rainfall intensity is sufficiently strong. [ABSTRACT FROM AUTHOR]

In order to explore the use of side-polished fibre (SPF) for microprobe-type "lab-on-fibre", this study presents an analysis of the surface roughness in side-polished fiber (SPF) using the gray level co-occurrence matrix (GLCM) texture feature analysis method. Experimental results show that the flat areas of the SPF polished surface exhibit texture characteristics with high mean values in contrast and entropy, and low mean values in the angular second moment (ASM), homogeneity, and correlation. Employing the random forest (RF) feature importance ranking method based on the Gini coefficient and out-of-bag (OOB) error estimation, this study assesses the sensitivity of various GLCM texture parameters in classifying different roughness levels of the SPF polished surfaces. A feature subset comprising variance, ASM, entropy, and contrast is identified as optimal. Utilizing this subset, the paper conducts an RF classification validation experiment on the roughness of the SPF polished surfaces, with results showing an RF classification accuracy of 95.65%.This research provides evidence for exploring the impact of rough polished surfaces in SPF optic sensors on the light coupling mechanism with environmental materials and its influence on sensor sensitivity. It lays the foundation for exploring the precise identification of high-sensitivity areas on SPF polished surfaces. [ABSTRACT FROM AUTHOR]

Demographic ageing has influenced the well-being of the population. Issues that need to be addressed in terms of generating vulnerability in older adults (aged 60+) include social exclusion. Using the longitudinal Survey of Health, Ageing and Retirement in Europe (SHARE), this study proposes a measure of social exclusion among older adults represented by five underlying dimensions: exclusion from material resources, from social relationships, from basic services, from participation in civic activities and from neighbourhoods. This measure is then associated with individual and collective factors using a multilevel linear regression model, which captures differences between countries and individuals over three years. The main results indicate that being female, having a high level of education, and living in an urban area are significant factors in the risk of social exclusion. Additionally, trust in government has a negative association while the Gini coefficient variable and belonging to Southern and Eastern European countries have positive associations. These regions are characterised by a more family-based, dependent culture, but exclusion in old age is also reflected in different political, historical, and socio-cultural contexts over time, which makes older people less likely to be socially excluded today. [ABSTRACT FROM AUTHOR]

Early Southern Mesopotamia shows a complex history of expansion of (irrigated) farming in relation to urban developments and changing landscapes. As a first step to study expanding irrigated farming system, an irrigation-related agent-based model was developed to explore farm(land)s and irrigation systems in relation to decision-making processes, both of farms and their farmlands (an agriculture unit) and collective decision-making processes for irrigation system management—especially sharing water between farms. The decision-making processes include options to move farms, expand the system, or start a new system, as these would be options available for Mesopotamian farmers as well. In this text, we report how model parameters contribute to the generation of various patterns of yields and expansion of farms and system. Additionally, the Gini coefficient (based on yields) is applied to estimate levels of inequality among farmers. Our results show how (1) human decision-making determines the level of influence of and benefits for farms, as well as the overall irrigation system; (2) Gini values effectively capture the degree of inequality in yields among farms based on water availability; and (3) our model is a suitable base for further study, by incorporating additional agents into the irrigation system and expanding the spatial–temporal scales of the irrigated landscapes, to reach a more comprehensive understanding of the evolutionary dynamics of irrigation systems in Southern Mesopotamia. [ABSTRACT FROM AUTHOR]

Despite the increase of the share of highly-educated women, gender wage gap remains an ongoing issue in developing countries. The increase in women's education would provide them with more job opportunities resulting in higher employment rate amongst women and, thus, lower gender pay gap. In Palestine, the share of women with high education is 62% while their labor force participation rate is only 18%. This paper examines the effects of gender higher education on wage inequality in the Palestinian context. The study applied the Mincer equation to study the determinants of wage, while the decomposed Gini coefficient is used to measure the contribution of education and other factors to overall wage inequality. The study used data from the labor force survey (LFS) which is conducted by the Palestinian Central Bureau of Statistics (PCBS) covering the period from 2010 to 2020. Results show that those with higher education have relatively higher wages as compared to those with only high education or with school education. Results also show that gender wage inequality has increased during the study period (2010–2020), but the contribution of both gender and education differences to the overall wage inequality has decreased. In general, the gender pay gap remains a crucial issue in the Palestinian context with a persisting decreasing pay gap over time across all education levels. Policymakers shall orient efforts towards investing in women's education, thus increasing their empowerment in the labor market, which in turn would improve the level of development and economic growth in the country. [ABSTRACT FROM AUTHOR]

Exploring the regional differences and convergence of urban land green use efficiency (ULGUE) is of great significance for urban green development and the goal of carbon neutrality. Based on the panel data of 282 prefecture-level cities in China from 2006 to 2019, this paper uses the SBM-Undesirable model to calculate ULGUE in China, then uses Dagum Gini coefficient decomposition, coefficient of variation and panel data model to reveal the regional differences and convergence of ULGUE. The results show that ULGUE in China increased from 0.441 to 0.555 in 2006–2019. The number of cities in the medium–low efficiency range is dominant, accounting for more than 54%. There are differences in ULGUE among the three major regions, which shows the distribution pattern of west > east > central. ULGUE in China has significant spatial agglomeration characteristics, and its overall, intra-regional and inter-regional differences show a downward trend. Over-variable density is the main source of the overall difference, with an average contribution rate of 49.71%. ULGUE across the country and in the three regions of east, central and west in China exist significant σ convergence, absolute β and conditions β convergence. The research results are helpful to objectively evaluate ULGUE in China, and provide decision-making reference for promoting the green, low-carbon and sustainable use of urban land and achieving the goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

Damming can promote flood control, water supply, power generation, and shipping but often changes the downstream hydrological regimes, producing adverse externality effects. Maximizing downstream social and ecological benefits will inevitably reduce upstream power generation. This study presents two novel bi-level hybrid game models, called the non-cooperative hybrid game model (NCHG) and the cooperative hybrid game model (CHG), to facilitate integrated water resource management in reservoir systems. The performance index of propensity to disrupt is applied to evaluate the stability of CHG, and an improved reliability index and Gini coefficient are adopted to evaluate the reliability and equity of both two models. The Three Gorges Reservoir and its adjacent cities were chosen as a case to inspect the two models' performance. A range of scheduling schemes was derived by proposed bi-level hybrid game models in wet, normal, and dry years. Results reveal that (i) the RI values of the watershed system obtained by the CHG are less than those in NCHG in three typical years (for example, 0.1201 VS 0.1930 in the wet year), showing higher systemic reliability. The Gini coefficients of the watershed system obtained by the CHG are all less than those obtained by the NCHG in all typical years (for example, 0.1016 VS 0.1020 in the wet year), which shows better performance of CHG on fairness for the allocation results; (ii) in the case of a multi-function reservoir system, the CHG generates favorable allocation schemes with higher systemic characteristic values by 32.43, 34.39, and 33.54 in wet, normal, and dry years, respectively, than those in NCHG (32.03, 33.16, and 31.42 in wet, normal, and dry years, respectively); (iii) compared with NCHG, the economic benefits obtained by CHG decreased by 0.98%, 1.04%, and 5.42% in wet, normal, and dry years, respectively; the social negative benefits decreased by 3.49%, 9.84%, and 28.69%; and the ecological negative benefits decreased by 1.77%, 5.65%, and 5.59%, respectively. It indicates that a minor sacrifice of the reservoir benefit could significantly improve the welfare at the system level by the CHG. The developed CHG can provide optimal water scheduling schemes in balancing inter-regional water conflicts and can be widely used to produce an equilibrium management strategy for a multi-function reservoir system. [ABSTRACT FROM AUTHOR]

Green manufacturing has become a necessary way to promote new industrialization and realize the high-quality development of China's manufacturing industry. Based on the panel data of 30 provinces in China from 2012 to 2022, this paper constructs a comprehensive evaluation index system for the green manufacturing development level and introduces the TOPSIS- Gray correlation method to comprehensively measure the green manufacturing development level of China as a whole and the four major regions in the eastern, central, western, and northeastern parts of the country. The regional differences, distribution dynamics and evolutionary trends of China's green manufacturing development level are also explored with the help of the Gini coefficient, kernel density estimation and Markov chain methods. Research Findings: (1) The green manufacturing development level in China is on an upward trend, with an overall spatial distribution pattern of "East is superior and West is inferior". (2) There are regional differences in the green manufacturing development level in China, and the differences are widening, with interregional differences being the main reason for this overall difference. (3) The country as a whole, the central region and the western region are polarized to varying degrees, with the rest of the country showing an improvement in polarization. (4) Without considering spatial factors, the development of green manufacturing in each province experiences "club convergence" in the short term, and it is difficult to realize rapid development. Considering spatial factors, China's green manufacturing development level is generally characterized by "elevated in proximity to high levels and suppressed in proximity to low levels", and in the long run, it shows a distribution trend toward the concentration of high values. The findings of this study can provide new ideas for promoting synergistic efficient development of green manufacturing in China. [ABSTRACT FROM AUTHOR]

The coupling coordination of digitalization and green development has become an inevitable requirement for building a new development pattern and achieving high-quality development of China's economy. Based on the panel data of 284 Chinese cities from 2011 to 2021, this study uses the coupling coordination degree model, Dagum Gini coefficient, spatial convergence, Markov transfer probability matrix, and panel Tobit model to quantitatively analyze the spatial–temporal evolution characteristics and influencing factors of the coupling coordination degree of digitization and green development. The study results show that the coupling coordination degree (CCD) of digitalization and green development has an overall increasing trend during the study period, and the eastern region is higher than other regions which showing spatial non-equilibrium characteristics. The spatial difference of the CCD continues to downward, and inter-regional differences are the main source of the CCD. In the long run, there is a "catch-up effect" between cities with low CCD and those with high CCD, and the CCD of digitalization and green development will tend to a steady state. The transfer type of the CCD has the characteristics of "club convergence", the probability of maintaining the original state is high, and the overall CCD shows a good development trend in the future. Factors such as environmental regulation, green innovation, industrial structure upgrading and financial efficiency can significantly contribute to the CCD of digitalization and green development. The above findings provide empirical evidence of the CCD of digitalization and green development to achieve high-quality economic development. [ABSTRACT FROM AUTHOR]

Exploring the coupling coordination degree (CCD) between digital village construction (DVC) and agricultural carbon emissions (ACE) is crucial for promoting village revitalization and sustainable agricultural development. Analyzing data from 30 provinces in China in 2011–2020, this paper employs the CCD model, the Dagum Gini coefficient, and the geographic detector for in-depth analysis. The results show that the overall level of CCD gradually increases over time, but the national CCD still remains in a state of "low coordination," and there are apparent spatial differences in the CCD among provinces. In addition, the overall difference in CCD shows a decreasing trend, and the contribution of inter-regional differences has gradually become the most critical source of CCD's regional difference. Finally, the spatial differences of CCD are the result of two-factor interaction, among which the innovation level is the most core driving factor. The above findings provide important implications for China and other developing countries to fully leverage the interaction between village digitalization and agricultural decarbonization to promote sustainable agricultural development. [ABSTRACT FROM AUTHOR]

High-quality economic development (HQED) in China is an important embodiment for adapting new normal of economy and implementing new concept of sustainable development. Accurately portraying the evolution trajectory of China's HQED and tracing sources of its spatial–temporal disparities are of great significance for promoting balanced and healthy economic development. Since the evolution of HQED is dynamic and motivated by the need for continuously monitoring the time-varying process of HQED, we develop a functional high-quality economic development index (HQEDI(t)) in the context of functional data analysis. We use the functional ANOVA to examine the significance of disparities between regions, in terms of static absolute level and dynamic development potentials, based on the continuous measurement of provincial HQED. The extended functional Dagum Gini coefficient is also used to decompose the overall and structural inequality of China's HQED. The results show the following. (1) The overall level of China's HQED has been steadily increasing, and innovation efficiency is the leading factor for improvement of China's HQED. (2) Uneven development between regions exists only at the absolute level and grow velocity of HQED, but it is not significant in acceleration. (3) The overall regional disparities of China's HQED show a downward trend, and inter-regional disparities dominate the inequality of HQED. We make a contribution to the idea of a dynamic framework for evaluating HQED and provide guidance for policy-making authorities to formulate target development policies. [ABSTRACT FROM AUTHOR]

This paper aims to analyze trends in income and consumption inequality for paid and self-employed households and examine to what extent changes in aggregate consumption and income inequality can be explained by changes in their permanent and transitory components over time using data from the Italian Survey of Household Wealth (SHIW) covering the period 1989-2016. The results obtained from the Generalized Method of Moments (GMM) analysis reveal differences in consumption and income inequality, as well as their permanent and transitory components, between self-employed and payroll households. In particular, self-employed households experience higher levels of both income and consumption inequality, the increase in total income and consumption inequality is mainly driven by an increase in its transitory component. Furthermore, findings from other descriptive measures of inequality, such as the Gini coefficient, the variance of the log, 90th/10th, and 50th/10th percentile ratios, support the notion that income inequality is higher than consumption inequality across all groups, with self-employed households exhibiting a more pronounced difference. [ABSTRACT FROM AUTHOR]

Machine learning (ML) algorithms have been proven to be effective methods in steel design and production processes. In this study, the feature analysis and prediction of slag entrapment in continuous casting process were carried out based on XGBoost model. Results show that the area under the curve (AUC) and accuracy of BO-XGBoost are 0.811 and 0.756, respectively, which are higher than PSO-XGBoost and GA-XGBoost. Feature analysis shows that mold flux, oscillation frequency, serial number, inner arc, casting speed (CS) and slab width are the key features which affect the entrapped slag defect, based on Gini coefficient and SHAP values. In addition, partial dependence plots of SHAP value suggest that it is conducive to product the qualified slabs with less entrapped slag defect, when the oscillation frequency is 60–140 cpm, inner arc is 7.5–9.5 m, CS is 0.35–1.2 m/min, serial number is less than 5, slab width is less than 1300 mm and 2# mold flux. [ABSTRACT FROM AUTHOR]

We construct a dynamic theoretical analysis framework on how the development of digital economy affects income inequality, and then, we put forward competitive hypotheses about the technology-biased of digital economy. We select the provincial data of China from 2011 to 2019 as the research objects, and we use the CHFS and CFPS databases to measure the Gini coefficient as the indicator of income inequality. We adopt panel data fixed effect model, threshold model to verify which one of the competitive hypotheses is correct. The empirical study shows that the digital economy has a threshold effect on income inequality. The digital economy does not have a significant effect on income inequality at the early stage of development, increases income inequality after a certain level of development, and decreases income inequality when the digital economy is developed. This conclusion holds robustly after endogenous and robustness tests. From the macro perspective, the digital economy contributes to the increase in labor share, but only in regions with large numbers of high-skilled workers can reduce income equality. From the micro-perspective, the development of the digital economy and the increase in wage income jointly reduce income inequality. However, digital economy would reduce wage income when the digital economy is undeveloped, and increased wage income when the digital economy is developed. Therefore, the technological progress of digital economy would transform from bias to unbias. With the development of digital economy, the number of workers who can enjoy digital welfare will be more and more. [ABSTRACT FROM AUTHOR]

The article "Crime Incidence: High Immigration Versus Low Immigration European Union Countries" by Thompson and Jozefowicz analyzes the impact of immigration on robbery and burglary rates in European Union countries. The study found that while immigration was not significant in robbery models, a 1% increase in per capita immigration rate led to a 0.07% increase in burglaries in the full sample. In countries with high immigration rates, a 1% increase in immigration resulted in a 0.27% increase in burglaries, possibly due to social disorganization theory or employment rate differences. The findings suggest that differentiating samples based on immigration rates may offer insights for policy decisions in the EU. [Extracted from the article]

To examine the role of inequality in academic achievement, we analyse a cross-national dataset including data from three cycles from 2012 to 2018 from the PISA, an international assessment of 15-year-old students' math, reading, and science performance. The Gini coefficient and gender inequality index (GII) were used as metrics for a country's economic inequality and gender inequality, respectively. The results show that gender inequality has a negative association with academic achievement for both boys and girls. Moreover, gender inequality has a stronger association with academic achievement than does economic inequality. We also find that gender inequality in reproductive health may contribute substantially to the association between gender inequality and academic achievement. Despite substantial advances in gender equality worldwide, multisectoral and multilevel approaches from the community to the country level are needed to ensure substantial long-term reductions in economic, gender, and educational inequalities. [ABSTRACT FROM AUTHOR]

Maintaining and improving ecological resilience is of great practical significance for the Yellow River Basin to reduce potential ecological risks and deliver sustainable development. Based on the essential characteristics of evolutionary resilience, this paper developed an ecological resilience index system of "resistance-recovery-reconstruction-renewal" and calculated the ecological resilience of 75 prefecture-level cities in the Yellow River Basin from 2007 to 2021 with the improved TOPSIS method. Then the spatiotemporal evolution characteristics of ecological resilience were analyzed using the gravity center-standard deviation ellipse, Dagum Gini coefficient decomposition, and spatial autocorrelation analysis. Furthermore, the dynamic spatial Durbin model (DSDM) was used to investigate the influencing factors of ecological resilience. The main results are as follows: (1) The ecological resilience of the Yellow River Basin showed an overall fluctuating upward trend, and the average annual growth rate in the downstream region was larger than in the upstream and midstream regions. (2) Cities with similar levels of ecological resilience were distributed in a "large settlement, small scattered" pattern. The center of gravity shifted to the southeast, and the spatial distribution exhibited a "northwest-southeast" pattern and a trend towards an "east–west" pattern. The primary source of spatial differences was the intensity of transvariation. (3) The ecological resilience in the Yellow River Basin showed significant spatial clustering, with the H–H clustering area shifting from the Hubao-Eyu urban agglomeration to the Shandong Peninsula urban agglomeration, and the L–L clustering area mainly distributed around the Central Plains city cluster. (4) The ecological resilience of the Yellow River Basin exhibited significant snowball, spillover, and siphon effects in time, space, and space-time dimensions, respectively. In the short and long term, population density and openness significantly positively affected the ecological resilience of local and surrounding cities. Urbanization had a long-term effect on ecological resilience without a short-term effect. GDP per capita and industrial structure only imparted a significant positive influence on local ecological resilience. The negative spatial spillover of the intensity of financial investment in technological innovation gradually turned into a positive effect. [ABSTRACT FROM AUTHOR]

Rapid urbanization has led to increasingly prominent urban heat island phenomena and social inequality. It is urgent to quantify the threshold area of urban parks from multiple perspectives to maximize the cooling effect and improve the equity of park cooling services. Using 33 urban parks in Harbin City as research objects, four indices, i.e., park cooling intensity (PCI), park cooling distance (PCD), park cooling area (PCA), and park cooling efficiency (PCE), were used to explore the park cooling effect and the threshold value of efficiency (TVoE) of the size. The OD (origin–destination) matrix model was constructed to assess the spatial accessibility from the community to the cooling range. The Gini coefficient was used to assess the equity of cooling range accessibility. The relative contribution of each influencing factor to the cooling indicator was quantified through regression modeling. The results showed that the average PCI was 3.27 ℃, the average PCD was 277 m, the average PCA was 115.35 ha, and the average PCE was 5.74. Gray space area was the dominant factor for PCI, PCD, and PCA (relative contributions of 100%, 31%, and 19%, respectively). Park area was the dominant factor for PCE (relative contribution of 28%). The TVoE of park sizes based on PCA and PCE were calculated as 82.37 ha and 2.56 ha, respectively. 39.2% and 94.01% of communities can reach cooling ranges within 15 min in walk mode and transit mode, respectively. Approximately 18% of neighborhood residents are experiencing severe inequities in cooling range accessibility. This study can guide park design that maximizes cooling effects, as well as inform city planners on more equitable allocation of urban park resources. [ABSTRACT FROM AUTHOR]

Intergenerational health mobility serves as a crucial indicator that reflects both social class mobility and health inequality. In this study, we constructed a comprehensive index to evaluate the health of residents in terms of physical, psychological and social adaptation dimensions using data from the China Family Panel Studies from 2010 to 2018. It then measured intergenerational health mobility using the intergenerational rank correlation coefficient method. Furthermore, the dynamic evolutionary trend, spatial differences and their sources, and the convergence characteristics of intergenerational health mobility were revealed by nonparametric kernel density estimation, the Dagum Gini coefficient, and the σ(β) convergence model, respectively. The formation mechanisms were explored using the quadratic assignment procedure. The results showed a general improvement but unbalanced trend of intergenerational health mobility in China, and hypervariable density was identified as the primary factor contributing to this difference. The σ convergence characteristics and β convergence mechanism were verified in China and its three regions. Environmental quality, industrial structure, and accessibility of medical and health resources had significant and decreasing effects on the spatial differences in intergenerational health mobility across China, with varying impacts observed among the three regions. This study not only provides empirical insights into understanding the dynamics laws of intergenerational health mobility and promoting regional coordinated development in China but also offers valuable guidance for formulating healthcare policies in developing countries and for achieving the United Nations Sustainable Development Goals. [ABSTRACT FROM AUTHOR]

Retrievability measures the influence a retrieval system has on the access to information in a given collection of items. This measure can help in making an evaluation of the search system based on which insights can be drawn. In this paper, we investigate the retrievability in an integrated search system consisting of items from various categories, particularly focussing on datasets, publications and variables in a real-life digital library. The traditional metrics, that is, the Lorenz curve and Gini coefficient, are employed to visualise the diversity in retrievability scores of the three retrievable document types (specifically datasets, publications, and variables). Our results show a significant popularity bias with certain items being retrieved more often than others. Particularly, it has been shown that certain datasets are more likely to be retrieved than other datasets in the same category. In contrast, the retrievability scores of items from the variable or publication category are more evenly distributed. We have observed that the distribution of document retrievability is more diverse for datasets as compared to publications and variables. [ABSTRACT FROM AUTHOR]

Research has shown that building public trust in institutions contributes to vaccine confidence. However, this association has not been validated in the cross-cultural context, which requires retesting using a larger, and more representative cross-cultural sample and considering potential moderating factors, such as sociocultural context. Using a large sample from Gallup (involving 102,156 participants from 134 countries), we explored the link of institutional trust and vaccine confidence in a global context, and the role of cultural religiosity and individualism in this relationship. Individual-level institutional trust and vaccine confidence were measured using respective Gallup data. Country-level cultural religiosity scores were used to capture the sociocultural context, while Hofstede's individualism scores reflected the societal inclination towards individual or collective orientation. The results of the multilevel analyses found that institutional trust positively correlates with vaccine confidence on the global scale. Furthermore, the benefits of institutional trust on vaccine confidence is weaker in more religious or individualistic countries. We also identified several individual and cross-country characteristics that influence vaccine confidence, such as age, income, Gini coefficient, and uncertainty avoidance. These findings reveal the influence of individual factors on vaccine confidence and emphasize the importance of understanding the interaction of personal factors with sociocultural context. [ABSTRACT FROM AUTHOR]

Analyzing the inequality characteristics and influencing factors of CO2 emissions per capita (CEPC) is conducive to balancing regional development and CO2 emissions reduction. This study applied the Gini coefficient and Theil index to investigate the CEPC inequalities during 2005–2017 at the county level in Jiangsu Province, China. Considering the spatial spillover and interaction effects, the factors influencing CEPC were analyzed by a hierarchical spatial autoregressive model. The results showed that the inequalities in CEPC first increased and then decreased at the inter-regional, and inter-county levels. The spatial pattern of CEPC was stable, and there was a significantly positive spatial autocorrelation of CEPC at the county level. The High-High type counties were mainly located in Sunan (southern Jiangsu). The spatial interaction effects of the CEPC between the prefecture and county levels indicated that governments at the prefecture level should integrate their county governments to reduce the CEPC. Moreover, carbon intensity, GDP per capita, land urbanization, and industrial structure play an important role in reducing CEPC. Our findings provide a scientific basis for formulating reasonable and effective carbon emission reduction policies. [ABSTRACT FROM AUTHOR]

The present study identifies economic, political, and institutional variables that influence the distribution of personal incomes in the Eurozone countries facing severe fiscal imbalances, namely Greece, Italy, Portugal, and Spain. Crucially, this paper is the first to investigate the effect of the corrective arm of the Stability and Growth Pact, the so-called Excessive Deficit Procedure (EDP), on the income distribution of the aforementioned economies, where EDP was imposed over a long time period. The empirical results of this study show that (i) EDP impact depends on the specific mix of policy measures undertaken and that (ii) a high public debt does not reflect the existence of common factors shaping income distribution in the four Southern European economies. The share of labor income in total income, constitutes a significant determinant of income inequality. However, we find that the relationship between labor share and income inequality is also country-specific, depending on the intrinsic characteristics of each individual economic system. [ABSTRACT FROM AUTHOR]

The authors have employed several techniques to account for model uncertainty in the inequality-growth model. However, the BMA technique is the most prominent approach that solves model uncertainty in the inequality-growth literature. This study applied a recent BMA analysis using panel data to examine the role of fiscal policy on income inequality in 37 OECD countries from 2000 to 2015. Fiscal policy (in terms of tax revenue increase) serves as a redistributive tool or instrument to transfer income from higher income earners to lower earners and is considered a mechanism for income equality. To the best of the author's knowledge, only a few empirical growth studies have considered fiscal policy impact in their income inequality model setup. Our work contributes to very little research on the fiscal policy–income nexus using a novel BMA and MCMC regression as a robust methodology. Our empirical evidence on the role of fiscal policy on income inequality has found three variables, namely, economic growth, fiscal policy, and urban population, to impact income inequality significantly. We also found that the countries are conditionally neither converging nor diverging because of the probability of their coefficient being high at 100%. As expected, the coefficient of fiscal policy has a significant negative relationship with income inequality, indicating that fiscal policy reduces income inequality significantly by an average of 22% (with 100% certainty) for both BMA and Bayes models in OECD countries. [ABSTRACT FROM AUTHOR]

This paper aims to understand whether a shift towards a more balanced cash transfer and service-based welfare system is valuable in terms of reducing income inequality and what factors mostly contribute to the income inequality evolution. To examine this, I first impute the monetary values of in-kind benefits and then reassess Gini coefficients across countries and welfare regimes. I also compare the role of cash transfers by functions and, more importantly, by how they are allocated. By means of factor source decomposition, the elasticities confirm wages as being the income source that creates most inequalities, while taxes play the most equalising role together with cash transfers. However, universal services such as healthcare and compulsory education outperform most of the cash transfers included in the analysis, with a stronger effect in the Mediterranean countries. Although in-kind services play a marginal role in explaining the changes in the Gini coefficient between 2008 and 2017, results suggest that a coordinated view of cash transfers and public services, as well as increasing the share of non-contributory means tested transfers, can reduce income inequality in all welfare regimes. [ABSTRACT FROM AUTHOR]

Around the world, undernutrition causes more than half of all deaths in children under 5 years of age. It also increases children's vulnerability to common diseases, impairs recovery, and stunts their physical and mental development. This paper investigates the state of child health and the assessment of health inequalities in children under 5 years, utilising Multiple Indicators Cluster Surveys across 36 districts in Punjab, Pakistan. We suggest a new household-based health index to identify health disparities and to help policymakers implement more successful domestic policies to offset inequalities. Additionally, this study estimates the health disparities for robustness checks applying the Palma ratio and Gini coefficient. The study's findings revealed that every second child in Punjab is malnourished and that 51% of children in Punjab had not received all of their recommended vaccinations. The results also show that health disparities in low-income districts are worse than in high-income districts. The findings further demonstrate that important contributors to health disparities include parental illiteracy, poverty, and political backwardness. This study recommends a multifaceted policy intervention to address child immunization, undernutrition, and infectious disease legislation, as well as income inequality, to reduce health disparities. [ABSTRACT FROM AUTHOR]

This study establishes an indicator system encompassing economic, social, and environmental dimensions to assess the level of green development in animal husbandry from 2010 to 2020. It further examines the coupling coordination degree within each dimension. The Dagum Gini coefficient is employed to scrutinize the regional disparities in coupling coordination degree of the economic benefit, social benefit, and environmental benefit of the green development in Chinese animal husbandry. Additionally, Moran's I is utilized to identify the degree of spatial autocorrelation and aggregation types. The results demonstrate the following: (1) From 2010 to 2020, the level of green development in the animal husbandry in China has steadily improved. Among the three dimensions, economic benefits exhibit the highest performance, followed by environmental benefits and social benefits. There are obvious regional disparities in the green development of animal husbandry, which are "strong in north and weak in south" and "strong in west and weak in east." The Gini coefficient for green development in the animal husbandry in China experienced a fluctuating upward trend. (2) From 2010 to 2020, the overall coupling coordination degree of the economic benefit, social benefit, and environmental benefit of green development in the animal husbandry in China remains at a rudimentary level and demonstrates a steady upward trend. Spatially, it manifests an agglomeration pattern primarily centered around Beijing, with the northeastern region being the main focus. (3) The Gini coefficient for the coupling coordination degree experienced a slight fluctuating upward trend. In terms of inter-regional disparities, significant differences are observed between the northeastern region and the central region, as well as between the northeastern region and the eastern region. In terms of contribution to disparities, inter-regional contributions were the most substantial, followed by super-variable density, with intra-regional contributions being the smallest. (4) The coupling coordination degree displayed spatial autocorrelation, with "high-high" aggregation areas predominantly concentrated in the northeastern region. [ABSTRACT FROM AUTHOR]

Consistent evidence points to the detrimental effects of income inequality on population health. Income inequality may be associated with online gambling, which is of concern since gambling is a risk factor for adverse mental health conditions, such as depression and suicide ideation. Thus, the overall objective of this study is to study the role of income inequality on the odds of participating in online gambling. Data from 74,501 students attending 136 schools participating in the 2018/2019 Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary behaviour (COMPASS) survey were used. The Gini coefficient was calculated based on school census divisions (CD) using the Canada 2016 Census linked with student data. We used multilevel modeling to explore the association between income inequality and self-reported participation in online gambling in the last 30 days, while controlling for individual- and area-level characteristics. We examined whether mental health (depressive and anxiety symptoms, psychosocial wellbeing), school connectedness, and access to mental health programs mediate this relationship. Adjusted analysis indicated that a standardized deviation (SD) unit increase in Gini coefficient (OR = 1.17, 95% CI 1.05, 1.30) was associated with increased odds of participating in online gambling. When stratified by gender, the association was significant only among males (OR = 1.12, 95% CI 1.03, 1.22). The relationship between higher income inequality and greater odds for online gambling may be mediated by depressive and anxiety symptoms, psychosocial well-being, and school connectedness. Evidence points to further health consequences, such as online gambling participation, stemming from exposure to income inequality. [ABSTRACT FROM AUTHOR]

Purpose: Myelomeningocele is the most severe birth defect compatible with long-term survival. It accounts for 5.7% of neurological surgeries in Nigeria. However, the exact cause of this neural tube defect remains unidentified. This study aims to determine if seasonal variation is a potential environmental contributor. Method: This study prospectively recruited 242 children diagnosed with myelomeningocele at the University of Nigeria Teaching Hospital (UNTH), Enugu, Nigeria, between January 2010 and December 2022. Our primary outcome was the seasonal occurrence of myelomeningocele, while covariates included gender, birth order, maternal folic acid supplementation (FAS), and parental age. The estimated month of conception was derived from the mother's last menstrual period (LMP), and the occurrence of myelomeningocele across the various seasons in which these babies were conceived was assessed using the Lorenz curve and the Gini coefficient. Results: 242 patients were studied with a male-to-female ratio of 1.26. The majority of cases were lumbosacral (93.4%), and none of the mothers commenced FAS before conception. The highest proportion of cases (39.7%) occurred during the hottest period of the dry season (January–March), while the lowest proportion (15.7%) occurred during the early wet season (April–June). The Gini index of 0.29, and the Gini coefficient derived from 100,000 Monte Carlo simulations of 0.24, indicate a significant variation in the distribution of myelomeningocele cases across different seasons of conception. Conclusion: The seasonal occurrence of myelomeningocele with a peak in January–March suggests a potential association with environmental factors including oxidative stress induced by solar radiation. [ABSTRACT FROM AUTHOR]

We compared alpha diversity indices of the intestinal microbiota in adolescents with obesity and normal body weight, taking into account their ethnicity. Intestinal biocenosis was studied by metasequencing of amplicon libraries of V3-V4 fragments of the 16S rRNA gene. The alpha diversity of the microbiota was assessed using classical and alternative indices. Statistically significant differences in intestinal microbiota were observed between Russians with obesity and Buryats with normal body weight, as well as between Russians with obesity and Buryats with obesity when assessing the Shannon—Weaver, Chao1 indices, Faith phylogenetic diversity index, ACE, Fisher, Gini coefficient, Margalef, and Menkhinik indices. It was shown that alpha diversity indices can be used to assess significance of differences and variability of the intestinal microbiota in multifactorial diseases such as obesity in adolescents; however, the scope of application of the criteria should be considered. [ABSTRACT FROM AUTHOR]