Gini Coefficient Research Articles

Does Google dream of electric memes? From human to computational culture

Introduction. We provide a cultural heritage informatic study of ‘internet memes’: clusters of documents carrying a collective cultural meaning. Method. Google’s computer vision data from three memes are used to discuss the cultural heritage Google provides for the indexed web using Gini coefficients and word clouds. Results. Our networks suggest that the more reducible sense-data is to a smaller number of labels, the less the internet needs to ‘remember’ to see a ‘meme’. However, when labels are less strongly connected, human inspection is required to interpret if Google captures qualities of memes. Conclusions. We show that Google can interpret aspects of memetic cultural heritage. However, it fails at understanding some cultural information about memes relative to predefined expectation. Computational tools like Google Cloud Vision can augment the heterogeneity of cultural heritage work. However closer inspection from experts is needed to interpret when computational methods represent cultural memory.

Evaluation of the Coordinated Development of the “Population–Economy” in Counties Within the Beijing–Tianjin–Hebei Urban Agglomeration

The coordinated development of urban agglomerations is a crucial means of establishing a territorial development and protection pattern with complementary advantages and high-quality development. In this study, an evaluation was performed on the coordinated development of the “population–economy” in the counties within the Beijing–Tianjin–Hebei urban agglomeration (BTHUA), focusing on the macro trend of coordinated development in this region. The evaluation methods included spatial autocorrelation analysis, the Gini coefficient, a comprehensive evaluation model, and a coupling coordination model. The results revealed that, in 2010 and 2022, the counties within the BTHUA exhibited strong positive spatial autocorrelation between evaluation indicators such as the population and economy, with notable and enhancing spatial clustering effects. The regional balance among all indicators was improved. The population distribution indicator and economic development indicator exhibited upward trends. The level of coupling coordination between the population and economy improved markedly. At the end of this paper, applicable strategies are recommended to drive economic growth and quality improvement in these counties, e.g., the orderly decentralization of the population and functions away from central urban areas to reduce the spatial carrying pressure and putting “policy guidance–fast-track resources–industrial upgrading” into practice. The purpose is to boost population–economy layout optimization and efficient resource allocation within the BTHUA.

A Fault Prediction Method for Lithium-Ion Batteries by Fusing Internal and External Features with Stacked Integration Models

Abstract Battery status is influenced by various internal and external factors, and battery management systems (BMSs) still face many challenges in fault prediction. To address issues such as neglecting external features, insufficient feature selection dimensions, and limited BMS hardware computation in real-time environments, this study proposes a lithium-ion battery fault prediction method that integrates internal and external features with a stacking ensemble model. By combining internal sensor data with external features, a sliding time window-Lempel-Ziv-Welch method is proposed. Feature importance is calculated using the Gini coefficient, and multiple discriminant correlation analysis is used for feature fusion across different domains. Finally, hyperparameters are optimized using Newton-Raphson-based optimizer algorithm, and the stacking model is trained, with recall, precision, accuracy, and area under the curve (AUC) as evaluation metrics. Experimental results show that compared to individual models, the proposed method improves precision, recall, and accuracy by 11.2%, 9.88%, and 9.1%, respectively, with an AUC of 0.897. This research aims to enhance battery fault prediction accuracy and reliability, providing new technical support for the safe and reliable operation of new energy vehicles.

CHANGES IN THE DISTRIBUTION AND CONCENTRATION OF DAIRY CATTLE IN POLAND IN 2010-2020

Polish agriculture is undergoing dynamic changes resulting from both economic processes and the European Union’s agricultural policy, particular attention is drawn to the transformation of the dairy sector. The aim of the study was to determine and assess changes in the distribution and concentration of dairy cattle in Poland between 2010 and 2020, as well as to identify key trends in regional specialization of milk production. The analysis focused on data regarding the number of farms keeping dairy cows and the regional cattle population. The study employed indicator-based analysis methods, including concentration ratios (CR4), the Gini index, and the Location Quotient (LQ). Additionally, structural and comparative analyses were conducted to identify the most significant trends. The results indicate an ongoing process of dairy cattle farming concentration, reflected in a declining number of farms engaged in milk production and an increasing share of larger herds. The highest production concentration is observed in the Podlaskie, Mazowieckie, and Wielkopolskie provinces, which together account for over 55% of the national dairy cow population. The data also confirm the process of regional specialization, as evidenced by rising LQ values in provinces with a high share of milk production. The findings suggest that Polish agriculture is moving toward greater concentration of milk production in larger farms, which enhances efficiency but simultaneously leads to the marginalization of smaller units.

Multiple-Attribute Lorenz Functions and Gini Indices: a measure transportation approach

Based on measure transportation ideas and the related concepts of quantile functions and regions, we propose multiple-output generalizations of the traditional univariate concepts of Lorenz and concentration functions, and the related Gini and Kakwani coefficients. These new concepts have a natural interpretation, either in terms of contributions of quantile regions to the expectation of some variable of interest, or in terms of the physical notions of work and energy, which sheds new light on the nature of economic and social inequalities. When based on center-outward quantile regions, the proposed concepts pave the way to a statistically sound definition, based on multiple variables, of the notion, so far limited to bivariate characterizations, of middle-class—a notion of practical importance in various socio-economic and political contexts.

Socioeconomic Inequalities in Healthcare and Rehabilitation Expenditure: An Analysis of Costs for People with Disabilities in Iran

Background: Technological advancements, demographic shifts, and lifestyle changes have led to increased healthcare expenditures, making access to healthcare services more challenging. People with disabilities, who frequently require specialized healthcare and rehabilitation services, encounter substantial financial and structural barriers to access. Economic and social inequalities significantly influence access to rehabilitation services, often preventing individuals with disabilities, particularly in developing countries, from utilizing these services due to financial constraints and inadequate insurance coverage. Objectives: This study aims to examine socioeconomic inequalities in healthcare and rehabilitation expenses for persons with disabilities in Iran, highlighting the financial burden and disparities in access to essential services. Methods: This descriptive-analytical quantitative study utilized secondary data from a national survey conducted in 2020. The analysis employed the Gini coefficient and Concentration Index to assess socioeconomic inequalities. The dataset included responses from 483 adults with physical disabilities who were members of the Iranian Disabled Community and had participated in the original survey through a structured electronic questionnaire. The data were analyzed using Stata software. Results: The average total cost was 24,600,000 Iranian Tomans (PPP 270.09$ US), indicating significant economic pressure on individuals with disabilities. The Gini coefficient, nearing 0.90, reflects severe inequality in the distribution of total healthcare and rehabilitation expenditure among people with disabilities. This inequality implies that some individuals face high expenses for these services, while others pay much less. The Concentration Index based on income was positive, indicating that inequality favors higher-income groups, while based on educational status, inequality favors individuals with lower education levels. Conclusions: The findings reveal a significant level of inequality in healthcare and rehabilitation expenditure for individuals with disabilities. These expenses are typically high and can be particularly burdensome for this population, many of whom face challenges related to inadequate education and insufficient income. These findings emphasize the necessity of targeted policy interventions to alleviate financial barriers and ensure equitable access to rehabilitation services across socioeconomic groups. Such policies could enhance health outcomes and improve the quality of life for individuals with disabilities.

Is Globalization Coming to an End Due to the Rise in Income Inequality?

The reversal of the trend towards the decline in income inequality in the last four decades in most countries has created favorable grounds for the rise of nationalist and anti-globalization sentiments. Economic failures of countries, groups of people and individuals are among important factors that cause nationalism. The rise of nationalism in many countries in recent decades, as measured by the decline in the “pride in your own country” indicator from the World Values Survey, is statistically significantly related to the change in income inequality (Gini coefficient) within the country. When globalization is properly managed, it is good for growth and income distribution and does not lead to nationalism. But if it is accompanied by the decline in real incomes for large masses of people, nationalist political forces have additional arguments for instigating anti-globalization and isolationist sentiments. The rise in income inequality within major countries since the 1980s poses a threat not only to social stability, but also to globalization.

Study on spatial pattern and coupling of county traffic superiority degree and new-type urbanization level in Guizhou Province, China

The overall level of transportation infrastructure and the level of new urbanization are two coupled systems that complement each other. The balanced development of a region benefits from the efficient synergy of these two systems. Using methods such as the Gini coefficient and Lorenz curve, spatial autocorrelation and hotspot analysis, and models for evaluating traffic superiority and new urbanization levels, we analyzed the balance and spatial distribution characteristics of these two developments and their coupling coordination levels in 88 counties of Guizhou Province (GZP) in 2020. The results indicate that the transportation advantage level in Guizhou’s counties shows a spatial distribution that decreases outward from regions with concentrated high-speed rail and highways. In contrast, the level of new urbanization is constrained by economic development disparities, exhibiting a distinct “dual-core” spatial differentiation with Guiyang’s urban area as the main core and Zunyi and Renhuai as secondary cores. The average and maximum transportation advantage scores are higher than those of new urbanization, and the scores in higher-level development zones are superior to those in lower-level zones. Additionally, transportation advantage shows better balance compared to new urbanization. Both transportation advantage and new urbanization levels exhibit positive spatial autocorrelation, with similar hotspot areas but significantly different coldspot areas. The coordination between transportation advantage and new urbanization is relatively low, with 80.68% of counties not fully leveraging their transportation advantages. Accurately identifying the coordination phase and system state of these factors can provide valuable references for the future development of different counties.

Transformation and Inequity of Urban Green Space in Guangzhou: Drivers and Policy Implications Under Rapid Urbanization

Urban green space (UGS) is crucial for urban sustainability, yet equity in access to urban green space remains a global challenge amidst rapid urbanization. Guangzhou, a megacity in China’s Pearl River Delta, exemplifies this challenge, with its population increasing from 5.9 million in 1990 to 18.7 million in 2020, leading to intensified land use conflicts. This study analyzes the changes in urban green space across three strategic zones—Old Guangzhou, New Guangzhou, and Future Guangzhou—compared to other areas, and equity over time using land use transfer matrices, landscape indices, hotspot analysis, and the Gini coefficient. It also explores the driving factors behind these changes. The results show a 16% decline in total UGS area from 1990 to 2020, with fragmentation peaking between 2000 and 2010, as indicated by a 24% increase in patch density and an 18% decrease in connectivity; growing spatial inequity, with the overall Gini coefficient rising over time—Old Guangzhou exhibited severe inequality (0.806) due to the scarcity of community-level urban green space, while Future Guangzhou demonstrated a relatively balanced distribution (0.523); and a shift in policy focus from basic greening to ecological prioritization after 2010, which slowed UGS loss but failed to address the disparities between core and peripheral areas. These findings are significant not only for Guangzhou but also reflect broader global issues faced by urban areas undergoing rapid urbanization. This study provides a comprehensive framework for balancing urban growth with equity, offering valuable insights for rapidly urbanizing regions worldwide.

Random forest grid fault prediction based on genetic algorithm optimization

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to economic losses. This paper proposes a Random Forest grid fault prediction model based on Genetic Algorithm optimization (GA-RF) to classify the grid fault types, which improves the distribution network fault prediction accuracy by constructing an optimized random forest model. Specifically, the model’s performance is initially enhanced by calculating the Gini index for each feature. The weather attributes with higher Gini indices are subsequently selected as pivotal features to alleviate the detrimental impact of unnecessary attributes on the model. In addition, a genetic algorithm is used to optimize the parameters of the random forest model for early warning of grid fault occurrence. The experimental results demonstrate that the proposed GA-RF in this paper achieves significantly higher accuracy compared to Random Forest (RF), Support Vector Machine (SVM), and Linear Regression (LR). Specifically, it outperforms them by 14.77%, 23.22%, and 13.77% respectively. This method effectively supports the safe and stable operation of the power system.

Equity of National Essential Public Health Services (NEPHS) in Mainland China, 2019: a cross-sectional study based on the NEPHS database

BackgroundChina’s National Essential Public Health Service (NEPHS) Program was launched in 2009 to deliver population-based public health and individual health management services to all residents at 800,000 primary health-care centers nationwide. This study assessed NEPHS utilization data and evaluated usage inequities using comprehensive nationwide data.MethodsA cross-sectional study was conducted, selecting 16 indicators (out of 18) from 12 service packages to evaluate inequity. These included 4 indicators for services provided to all residents and 12 for pregnant women, new mothers, children aged 0–6 years, and patients with hypertension, diabetes, severe mental disorders, or tuberculosis. Data on service utilization and target populations for these indicators across the 31 provinces and 453 cities in mainland China were obtained from the NEPHS database and management platform for the period January 1 to December 31, 2019. Service utilization rates and bias-corrected bootstrap confidence intervals (CIs) were calculated to determine utilization. Inequities were assessed using the Gini coefficient and Sitthiyot-Holasut composite inequality index at the national and provincial levels, and the Theil index was employed to decompose overall inequity into within-region and between-region subgroups.ResultsThe NEPHS collected health records for 88.25% of China’s permanent residents (95% CI: 79.23%–98.82%). The nationwide vaccination coverage rate was 97.44% (95% CI: 91.33%–99.91%). Newborn visit and child health management rates for children aged 0–6 years were 92.08% (95% CI: 74.85%–98.34%) and 90.87% (95% CI: 82.49%–98.47%), respectively. At the national level, NEPHS service utilization in 2019 was generally equitable, with Gini coefficients below 0.4 for the 15 indicators. Potential large equity gaps were observed in the provision of health education services in Shanghai [Gini coefficient = 0.358 (95% CI: 0.219, 0.444)], Inner Mongolia [Gini coefficient = 0.370 (95% CI: 0.073, 0.440)] and Xinjiang [Gini coefficient = 0.457 (95% CI: 0.217, 0.502)]. Additionally, the utilization of family planning education and sanitation inspection services also indicated potential large and severe equity gap in 13 provinces. The Theil indices revealed that inequities primarily existed within rather than between regions. Province-level results indicated perfect equity in health record management and vaccination coverage, while several provinces showed potential equity gaps in health education and family planning services. Potential equity gaps were also observed in health management services for patients with hypertension and diabetes, particularly in Beijing, Hunan and Xinjiang.ConclusionsThis study provides evidence for health planning in China’s primary health sector and guidance for analyzing equity in national health programs similar to the NEPHS Program.

(Un)just Distribution of Visible Green Spaces? A Socio-Economic Window View Analysis on Residential Buildings: The City of Cologne as Case Study

As urbanization processes, climate disasters such as heat waves, or pandemics such as COVID-19, increase, prioritizing visible green space is crucial to provide equitable access to green spaces for vulnerable groups with limited mobility. In the long term, this will enable sustainable and resilient urban development. In this study, we examined green window views in residential buildings to identify patterns of distributive equity for seniors and children, considering their socioeconomic status for the first time. We combined the methodology around the BGWVI and the methodological framework by Huang et al. (Urban Forestry & Urban Greening 95: 128,313:1–128,313:12, 2024) to measure the visibility potential of green spaces for approximately 160,000 residential buildings in order to geostatistically analyze the equity of the spatial distribution of visible urban green spaces. Using the Gini coefficient, the share index, and the location entropy, an evaluation of the access to visible green spaces according to socio-economic status and age group was carried out at the district level for the City of Cologne, Germany. The results show that children and the elderly have slightly higher percentages of visible green space than the social mean percentage. In addition, the influence of the mean net household income on visual green spaces is low. These findings underscore the importance of visibility as an access alternative in urban green space planning for an equitable and resilient urban environment.

Evaluating the comprehensive water resources utilization level in China: Dynamic distribution analysis and spatial convergence insights.

This research provides an overview of the comprehensive water resources utilization level (CWRULE) in China, highlighting its significance in national water management. The study aims to evaluate performance and trends in CWRULE across various regions. Employing methods such as the Dagum Gini coefficient, spatial kernel density estimation, and spatial convergence models, the analysis explores regional disparities, distribution dynamics, and convergence trends. Key findings indicate that while national water resources management has improved annually, significant disparities persist between the coastal eastern and central regions versus the western and northeastern regions, where CWRULE indicators remain relatively low. Notably, the convergence speed in the central, western, and northeastern regions increases significantly after controlling for variables, showcasing the beneficial impacts of policy support, economic development, and technological advancements. In contrast, the eastern region exhibits weak convergence, underscoring the necessity for targeted strategies to enhance water resources management and efficiency.

An Improved Quantitative Analysis Method for the Unequal Supply and Demand of Ecosystem Services and Hierarchical Governance Suggestions

Quantifying the unequal supply and demand of ecosystem services (ESs) is a prerequisite for hierarchical ecological governance decisions. However, previous studies have largely overlooked the scale effect of spatially adjacent units and the role of spatial compactness in shaping inequality. To address these research gaps, this study conducted a survey in six counties within the Danjiangkou Basin in China. By adopting a moving window-based local Gini coefficient method, we quantified the inequality in the supply and demand of ESs in this region, and introduced a refined coefficient of variation to measure spatial compactness, analyzing the impact of urbanization on this inequality. The results indicate that the inequality in the supply and demand of ESs in this region is gradually intensifying. However, from a local perspective, the inequality exhibits significant spatial heterogeneity, decreasing gradually from urban centers to suburbs and rural areas, while maintaining strong spatial continuity. Furthermore, we found that urbanization is the primary factor exacerbating this inequality, while compact urban development can mitigate it. The findings of this study can provide practical guidance for cross-county ecological coordination, ecological restoration, and sustainable urban development.

Disparities in Out-of-Pocket Expenditures Among Hospitalized Patients With COVID-19 in Iran: A Decomposition Analysis of Inequality.

Disparities in Out-of-Pocket Expenditures Among Hospitalized Patients With COVID-19 in Iran: A Decomposition Analysis of Inequality.

The impact of community pharmacies on equity in access to professional rapid antigen testing for SARS-CoV-2 in Portugal.

The impact of community pharmacies on equity in access to professional rapid antigen testing for SARS-CoV-2 in Portugal.

Spatio-temporal evolution and drivers of coupling coordination between digital infrastructure and inclusive green growth: Evidence from the Yangtze River economic belt.

Spatio-temporal evolution and drivers of coupling coordination between digital infrastructure and inclusive green growth: Evidence from the Yangtze River economic belt.

Tree-based Ensemble Algorithms and Feature Selection Method for Intelligent Distributed Denial of Service Attack Detection

DDoS is one of hackers’ mainstay weapons which can cause a decrease in network performance and damage servers. To overcome DDoS attacks, the challenge is to detect and block attacks simultaneously. Traditional classification methods are not effective at distinguishing between attack traffic and normal traffic. In this study, we introduce an ensemble-based machine learning algorithm, paired with an improved Gini index for feature selection, to detect DDoS attacks. Our approach used UNSW_NB15 dataset from Kaggle. Three tree-based ensemble algorithms are used in this research, namely Random Forest, XGBoost, and AdaBoost. By combining each ensemble algorithms with enhanced gini index, all those three algorithms outperformed the baseline models that used single decision tree classifier. XGBoost with gini index achieved the best result with 97.30% for accuracy, recall, and precision, and 96.90% for F1-score. This approach is able to improve the algorithm’s performance while loweing the number of features.

Temporal Changes in Racial Disparities of HIV Linkage to Care from 2013 to 2020: A Statewide Cohort Analysis.

Racial disparities have historically existed regarding HIV care outcomes, including linkage to care. This study aims to explore the contribution of contextual features (e.g., socioeconomic and structural environmental factors) to the temporal change of county-level racial disparities in linkage to care. This is a statewide population-based retrospective cohort study. The patient-level variables in the South Carolina HIV registry system were used to calculate the aggregated county-level linkage to care percentage. Then, we used four indices to measure racial disparities in the county-level percentage of timely linkage to care, i.e., the Black-White ratio, index of disparity (ID), weighted ID, and Gini coefficient. Linear mixed-effect models were used to estimate the relationship between a variety of contextual features and disparity indexes. The analysis included data from 2013 to 2020, with 2013 as the start year due to the availability of key contextual features and 2020 as the end year based on the most recent HIV registry data available at the time of this study. Across 46 counties in South Carolina, racial disparity in linkage to care persisted between 2013 and 2020, as indicated by all four indices. When using ID, weighted ID, and Gini as outcomes, counties with lower degrees of racial residential segregation and stronger family structure were at higher risk of racial disparities in linkage to care. For weighted ID only, counties with fewer primary care providers (β = - 4.22; 95% CI, - 7.23 ~ 1.23) had larger racial disparities in linkage to care. Furthermore, for Gini only, counties with higher income inequalities (β = 0.01; 95% CI, 0.00 ~ 0.02) had larger racial disparities in linkage to care. Efforts to address racial disparities should continue, and innovative approaches, specifically those that focus on social and structural factors, should be developed and implemented for populations that have poor HIV outcomes in the USA.

Research on blasting damage to tunnel surrounding rock based on acoustic full waveform signal analysis

In order to study the application of Acoustic Full Waveform Signal analysis in blasting damage to tunnel surrounding rock, a formula for blasting damage increment considering cumulative effects was proposed by analyzing the Acoustic Full Waveform Signal before and after blasting, based on the concepts of elastic waves and damage degree. This formula allows the cumulative damage law of surrounding rock blasting to be calculated and analyzed. Furthermore, by introducing the Lorentz curve, Gini coefficient, and fractal theory, and combining them with the surrounding rock blasting damage law, their practicality in studying blasting damage was verified. By combining the change in the dominant frequency and amplitude of the Acoustic Full Waveform Signal before and after rock blasting, the variation law in the frequency domain was obtained and confirmed using the wavelet packet energy spectrum. The results showed that blasting damage intensified with the increase in the number of blasts, but the damage increment gradually decreased. The corresponding signal time-frequency characteristics were marked by the reduction of acoustic wave speed and amplitude, the shift of the main frequency and energy to lower frequencies, and the gradual decrease in the main frequency amplitude.