Gini Coefficient Research Articles

Analysing The Implementation of Agrarian Reform Policy in Supporting National Resilience

Agrarian reform is a strategic policy that aims to redistribute land to the community, tiny farmers, and tenants to reduce land ownership inequality and improve people's welfare. Land inequality in Indonesia is very high, with the land tenure Gini index reaching 0.68, higher than the income Gini index, which stands at 0.388. This inequality not only creates socio-economic problems such as poverty and agrarian conflict but also impacts national resilience. This research uses SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to evaluate the implementation of agrarian reform policy and determine the right strategy to accelerate its implementation in supporting national resilience. This analysis identifies several strengths in the agrarian reform policy, such as government commitment and adequate infrastructure support. However, areas for improvement, such as lack of optimization of access to agrarian reform programs and slow resolution of land disputes, were also found. Opportunities include community empowerment and increased economic resources, while threats come from resistance from parties with specific interests and challenges in land redistribution. The results of this analysis are expected to provide strategic recommendations to improve the implementation of agrarian reform policies, such as strengthening cross-sectoral cooperation, increasing socialization and training, and improving access to information for the community. Thus, an effective agrarian reform program is expected to enhance community welfare and contribute to national resilience.

Sociodemographic inequalities in residential nighttime light pollution in urban Bulgaria: An environmental justice analysis

IntroductionOutdoor nighttime light (NTL) is a potential anthropogenic stressor in urban settings. While ecological studies have identified outdoor NTL exposure disparities, uncertainties remain about disparities in individual exposure levels, particularly in Europe. AimTo assess whether some populations are disproportionately affected by outdoor NTL at their residences in urban Bulgaria. MethodsWe analyzed 2023 data from a representative cross-sectional survey of 4,270 adults from the five largest Bulgarian cities. Respondents’ annual exposures to outdoor artificial nighttime luminance were measured using satellite imagery and assigned at their places of residence. We calculated the Gini coefficient as a descriptive NTL inequality measure. Associations between respondents’ NTL exposure levels and sociodemographic characteristics were assessed by estimating quantile mixed regression models. Stratified regressions were fitted by gender and for each city. ResultsWe found moderate distributive NTL inequalities, as indicated by a 0.214 Gini coefficient. Regression analyses found associations between greater NTL exposure and higher educational attainment. Respondents with incomes perceived as moderate experienced less NTL exposure at the 0.5 and 0.8 quantiles, while unemployed respondents experienced lower exposure at the 0.2 and 0.5 quantiles. We observed null associations for the elderly and non-Bulgarian ethnicities. Regardless of the quantile, greater population density was associated with higher NTL levels. Stratification by sex did not yield substantial differences in the associations. We observed notable city-specific heterogeneities in the associations, with differences in the magnitudes and directions of the associations and the NTL quantiles. ConclusionsNTL exposures appeared to embody an environmental injustice dimension in Bulgaria. Our findings suggest that some sociodemographic populations experience higher exposure levels to NTL; however, those are not necessarily the underprivileged or marginalized. Identifying populations with high exposure levels is critical to influencing lighting policies to ease related health implications.

‘Green or short: choose one’ - A comparison of walking accessibility and greenery in 43 European cities

Promoting environmentally and socially sustainable urban mobility is crucial for cities, with urban greening emerging as a key strategy. Contact with nature during travel not only enhances well-being but also promotes sustainable behaviour. However, the availability of travel greenery varies, and only recently have new datasets and computational approaches made it possible to compare the conditions in the distribution of travel greenery within and between cities quantitatively. In this study of 43 large European cities, we undertook a comparative analysis of travel greenery availability by using high-resolution spatial data and daily school trips as a marker of a daily travel need. By recognising walking accessibility as the most sustainable and equally available mode of transportation, we first estimated the proportion of the population residing within walking distance to upper secondary schools. Second, we associated the detailed school routes with monthly green cover data and compared the spatial variation in travel greenery availability between European cities, taking seasonal variation into account. Lastly, we analysed spatial inequalities of travel greenery availability within the study cities using the Gini index, the Kolm-Pollak equally-distributed equivalent (EDE) index and Moran's I. Our findings reveal a consistent negative association between accessibility and green cover implying a trade-off between access and greenery. We found large variations between European cities in the walking accessibility of schools, ranging from 44% to 98% of the population being within 1600 m of their school. Moreover, our results show substantial within-city disparities in travel greenery availability in large European cities. We demonstrated methodologically the importance of considering seasonal variations when measuring greenery availability. Our study offers empirical evidence of urban greenery availability from a mobility-focused perspective. It provides a novel understanding with which to support researchers and planners in affording the benefits of nature to more people as they travel.

IMPACT OF MICROFINANCE ON INCOME THROUGH SHGs IN MADURAI DISTRICT

This study examines the responsibility of microfinance institutions towards changes in the livelihood practices of the borrowers. The study is based on both primary and secondary data. The primary data were collected from the women Self Help Group members in Madurai District of Tamil Nadu by using interview schedules. Considering a total of 120 borrowers of Madurai, the impact of microfinance on their lives has been observed empirically by applying different statistical tools. In this study, impact of micro finance on income. For this the impact analysis of pre and post SHG members’ situation has been taken. This study contributes to the extant literature on microfinance by comparing pre-loan and post-loan phases and identified. Gini co-efficient of concentration ratio was used to measure the extent of inequalities in the distribution of income in the households of SHG members before and after joining SHGs. The upward shift in the Lorence curve towards the diagonal line for after joining SHGs, clearly shows that there is an improvement in the income inequality among the SHG members after joining SHGs. By considering the appropriate framework and approach, this study is explicable towards policymakers for designing further policies in this context and helps identify resources that need to flourish the current state in the future.

Spatiotemporal Accessibility of Rail Transport Systems in the Guangdong–Hong Kong–Macao Greater Bay Area and Its Implications on Economic Equity

Reducing inequality and fostering economic growth is the tenth global goal of the United Nations for sustainable development. Rail transport significantly influences spatial structures, industrial distributions, and is vital for regional economic integration. Despite its importance, the impact of rail transport on economic equity has not been thoroughly explored in current literature. This study aims to fill this gap by evaluating the spatiotemporal characteristics of rail transport accessibility and its implications for economic equity in the Guangdong–Hong Kong–Macao Greater Bay Area. We considered high-speed, intercity, and conventional rail transport and employ three distinct indicators—door-to-door travel time, weighted average travel time, and potential accessibility—to provide a nuanced assessment of accessibility in the region. Each indicator provides a unique perspective on how accessibility affects economic equity, collectively broadening the scope of the analysis. From 1998 to 2020, the evolution of rail transport and its consequent impact on regional economic equity is scrutinized. Advanced econometric methods, namely ordinary least squares, and spatial Durbin models, are combined with the Gini coefficient and Lorenz curve for comprehensive quantitative analysis. This approach highlights the dynamic influence of rail transport development on economic equity, contributing to the sustainable urban development discourse. The results reveal that although rail transport advancements bolster connectivity and economic growth, they also exacerbate regional economic inequality. This study provides valuable insights for urban planning and policymaking by elucidating the complex relationship between rail transport accessibility and economic equity. Our findings underscore the importance of implementing balanced and inclusive transport policies that foster growth and efficiency while mitigating socioeconomic disparities.

Delayed retirement, pension insurance and income inequality

PurposeTo investigate the potential of raising the retirement age and reforming pension insurance in mitigating intra- and inter-generational income inequality, thereby offering empirical support for governmental policy formulation.Design/methodology/approachA dynamic general equilibrium model with intertemporal iteration is developed to comprehensively assess the impact of policies raising the retirement age on income inequality, taking into account delayed retirement, survival probability, and pension insurance. The theoretical hypotheses are validated through simulation using MATLAB.FindingsThrough theoretical analysis, it is determined that, given certain assumptions are satisfied, raising the retirement age can effectively mitigate intra-generational income inequality, inter-generational income inequality under both the pay-as-you-go and fund accumulation systems. Simulation results indicate that, under current parameter settings, raising the retirement age can reduce the Gini coefficient. Furthermore, this study reveals that regardless of the pay-as-you-go or fund accumulation system, pension insurance serves as a mechanism for income redistribution and alleviating income inequality.Originality/valueIt offers a theoretical foundation for the government's policy on delayed retirement and endowment insurance.

Study on the Evolution of Spatiotemporal Dynamics and Regional Differences in the Development of Digital Agriculture in China

In the current study, an index system for digital agriculture growth was constructed. The index encompasses six key dimensions, namely production, operation, service, management, sustainability, and digital information infrastructure. Data from 30 Chinese provinces between 2011 and 2020 were collected and analyzed using the entropy method, Moran index, Dagum’s Gini coefficient, and the kernel density estimate. An in-depth analysis of the development level and spatial patterns, dynamic evolution and intra- and inter-regional differences in China (i.e., eastern, western, and central regions) was conducted. From the result, an overall growing trend of digital agriculture in China was observed, with a relatively more advanced status in the eastern region. A positive spatial dependence, showing a “high-high” and “low-low” (HH, LL) trend, was obtained. However, the regional spatial dependence has generally weakened since 2019. The intra-regional differences were large in western and eastern areas, while the greatest inter-regional differences were unveiled between western and eastern regions. The country’s overall differences mainly stemmed from inter-regional differences. The overall kernel density curves moved to the right over time, showing a trend of a gradual rise in digital agricultural growth, accompanied by a polarization pattern in the western region.

The Influence of Open Unemployment Rates, Inflation and Minimum Wages on Income Inequality in The North Sumatra Region

Income inequality is the existence of differences in income in a society, giving rise to real income inequality in society. As a result, the rich get richer and the poor get poorer. In fact, when it comes to income inequality, the more flexible wages are, the greater the impact on employment. However, inflexible wages, which are said to be an inability to respond to changing market conditions, lead to ever-increasing poverty and inequality. This research aims to determine the correlation between the influence of open poverty levels, inflation and minimum wages on income inequality in North Sumatra. The Central Statistics Agency (BPS) noted that the level of expenditure disparity between residents in North Sumatra has widened since September 2023. The Gini ratio, which measures this inequality, is recorded as high. BPS Based on North Sumatra data, this large deviation was caused by the increase in fuel prices at the beginning of September last year. The research method used is Multiple Linear Regression which is processed using eviews 10 software. The approach used in this research uses a quantitative approach with associative analysis, with a population from the North Sumatra BPS report for 2014-2023. The results show that the open unemployment rate and minimum wage have an effect on income inequality. Therefore, the solution offered is a policy of establishing equal distribution of employment income by opening job vacancies and training as well as equal distribution of salary income which is applied evenly in various regions so as to reduce income inequality in North Sumatra

Optimizing the spatial accessibility of outdoor sports facilities: a greedy heuristic algorithm based on remote sensing images

ABSTRACT Recent studies on the accessibility of sports facilities have rarely considered the specific attributes of the facilities, limiting their ability to define service potential, and have often neglected the critical aspect of equitable access. This study proposed a novel approach based on remote sensing images to optimize the spatial accessibility of outdoor sports facilities. Using Shanghai, China, as the study area, the study identified four types of sports facilities using a deep learning object detection method, which allowed their service capacities (areas) to be measured more precisely. A greedy heuristic algorithm was then developed based on a "trade-off" strategy that seeks to optimize facility access by reconciling the objectives of enhancing access and ensuring equality and by weighing the benefits of utilizing existing resources (school facilities) against the necessity of developing new ones. The object detection method achieved precision and recall rates of 88% and 96%, respectively, and the optimization efforts resulted in a 73% increase in accessibility while also significantly reducing the Gini coefficient from 0.58 to 0.34. The proposed algorithm outperformed the random selection and all-school-opening strategies. The results indicated that the methodology can effectively create refined datasets for outdoor sports facilities and enhance their accessibility.

Inequality Bands: Seventy-five years of measuring income inequality in Latin America

Abstract Drawing on a comprehensive compilation of quantile shares and inequality measures for 34 countries, including over 5600 estimated Gini coefficients, we review the measurement of income inequality in Latin America and the Caribbean over the last seven decades. We find that there is quite a bit of uncertainty regarding inequality levels for the same country/year combinations. Differences in inequality levels estimated from household surveys alone are present but they derive from differences in the construction of the welfare indicator, the unit of analysis, or the treatment of the data. With harmonized household surveys, the discrepancies are quite small. The range, however, expands significantly when –to correct for undercoverage and underreporting especially at the top of the distribution– inequality estimates come from some combination of surveys and administrative tax data. The range increases even further when survey-based income aggregates are scaled to achieve consistency not only with tax registries but with National Accounts. Since no single method to correct for underreporting at the top is fully convincing at present, we are left with (often wide) ranges, or bands, of inequality as our best summaries of inequality levels. Reassuringly, however, the dynamic patterns are generally robust across the bands. Although the evidence roughly until the 1970s is too fragmentary and difficult to compare, clearer patterns emerge for the last fifty years. The main feature is a broad inverted U curve, with inequality rising in most countries prior to and often during the 1990s, and falling during the early 21st century, at least until around 2015, when trends appear to diverge across countries. This pattern is broadly robust but features considerable variation in timing and magnitude depending on the country.

Assessment of Green Innovation Efficiency in Chinese Industrial Enterprises Based on an Improved Relational Two-Stage DEA Approach: Regional Disparities and Convergence Analysis

Industrial enterprises are characterized by significant energy consumption and high emissions. Therefore, the implementation of green innovation by these enterprises is beneficial for promoting sustainable economic development and safeguarding the ecological environment. In this study, a relational two-stage DEA model containing shared inputs and undesired outputs is constructed to evaluate and decompose the green innovation efficiency (GIE) of Chinese industrial enterprises across 30 provinces from 2012 to 2021. Since the objective function of this model is nonlinear, a heuristic search method is employed for its resolution. On the basis of efficiency evaluation, the Gini coefficient, kernel density estimation, and convergence analysis are further employed to investigate the regional disparities and convergence properties in the two-stage efficiency of green innovation. Our findings are as follows: (1) The average GIE of Chinese industrial enterprises demonstrates a fluctuating upward trajectory, with significant regional disparities observed between provinces. (2) Regional disparities in R&D efficiency (RDE) and achievement conversion efficiency (ACE) have diminished in all regions. Super-variable density and interregional differences serve as the primary sources of regional disparities in RDE and ACE, respectively. (3) The presence of absolute and conditional convergence in RDE and ACE is observed across all regions. To improve the GIE of Chinese industrial enterprises, it is imperative to emphasize the heterogeneous impact of economic levels, industrial structure, and the degree of openness across various regions and stages of green innovation.

Inequality in Physical Activity in Organized Group Settings for Children: A Cross-Sectional Study.

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

2022 insights on hospital bed distribution in Saudi Arabia: evaluating needs to achieve global standards

BackgroundEquitable geographical distribution of health resources, such as hospital beds, is fundamental in ensuring public accessibility to healthcare services. This study examines the distribution of hospital beds across Saudi Arabia's 20 health regions.MethodsA secondary data analysis was conducted using the 2022 Saudi Ministry of Health Statistical Yearbook. The study focused on calculating the hospital beds-per-1,000-people ratio across Saudi Arabia's 20 health regions. The analysis involved comparing regional bed distributions using the Gini index and Lorenz curve to assess the distribution of hospital beds.ResultsThe national average beds-per-1,000-people ratio was 2.43, serving a population of approximately 32.2 million. The calculated mean Gini index for bed distribution was 0.15, which indicates a relatively equitable distribution. Further analysis revealed some regional disparities, with health regions like Makkah and Jeddah displaying critically low bed-to-population ratios. In contrast, others like Al-Jouf and the Northern region reported higher ratios. The study also identified the need for an additional 17,062 beds to meet international standards of 2.9 beds per 1,000 people.ConclusionsThe findings revealed a national average beds-per-1,000-people ratio of 2.43, with some regional disparities. The study highlights the critical need for targeted healthcare planning and policy interventions to address the uneven distribution of hospital beds across Saudi Arabia.Trial registrationNot applicable.

Group bargaining: A model of international treaty ratification

We consider non-cooperative bargaining over a fixed surplus between two groups that may differ in size and the supermajority threshold they employ for within-group ratification. We find that total allocation to a group does not depend on group size and increases with the supermajority threshold. We use the Gini coefficient to study within-group inequality as an outcome of interest and find that inequality increases with group size and decreases with the supermajority threshold. Finally, we study delegation by concentrating the ability to influence proposals within a subset of group members. Delegation to a subgroup decreases the group's total allocation because non-delegates accept lower allocations. Inequality is higher if delegation is employed, and it is decreasing in the size of the delegate committee.

Globalisation and the efficiency-equity trade-off

We revisit the effects of globalisation over the past 50 years in a large sample of advanced and emerging countries. We use accessions to Globalisation Clubs (WTO, OECD, EU), financial liberalisation and an instrument for trade openness to study the trade-off between efficiency (proxied by real GDP per capita and TFP) and equity (proxied by the labour share of income and the Gini index of inequality). We find that (i) most of our episodes lead to an increase in trade openness (ii) the effects on GDP per capita are mostly positive with some interesting exceptions and (iii) there is little evidence that globalisation shocks lead to more inequality.

Spatial non-equilibrium and distribution dynamic evolution of the development level of national physical fitness in China's provinces.

Physical health is fundamental to a country's socio-economic advancement. An in-depth exploration of the spatial distribution and dynamic evolution of national physical fitness across China is crucial for enhancing the country's overall physical health. This study aims to provide valuable insights into the geographical and temporal patterns of physical fitness, informing strategies for national physical fitness improvement. Employing data from China's national physical fitness monitoring of 31 provinces, cities, and districts for the years 2005, 2010, and 2015, this study utilizes the Gini coefficient, its decomposition, and nonparametric density estimation methods. These techniques are applied to analyze the spatial disparities and temporal trends in national physical fitness levels among different demographics, including the overall population, males, females, and urban and rural residents. The study reveals that the regional disparity in China's national physical fitness initially narrowed and then expanded across the general population, females, and in both urban and rural areas, while consistently increasing among males. In terms of geographical distribution, the East, Middle, and West regions show significant heterogeneity, with the East-West gap being the most pronounced (Gini coefficients of 0.0249, 0.0230, 0.0263). The contribution rate of regional gaps was highest (54.40% -64.69%), followed by regional disparities (24.78% -27.15%), and the contribution of hypervariable density difference was the smallest (10.53% -19.75%). Despite a slight improvement in overall national physical fitness, the absolute regional disparities have further widened. Provinces with lower levels of national physical fitness demonstrate a 'club convergence' trend, indicating regional clustering of similar fitness levels. Additionally, a 'catch-up effect' is evident in rural areas, particularly in provinces with historically lower levels of national physical fitness. These findings suggest the need for region-specific public health strategies to address the growing disparities in national physical fitness across China.

Spatiotemporal Distribution and Regional Imbalance of China’s Digital Economy

The digital economy is an important driving force for promoting national economic growth and achieving high-quality economic transformation, and is a key force in achieving the sustainable development goals (SDGs). This paper measures the digital economy development level of 30 provinces in China from 2013 to 2021 utilizing the entropy of weighting approach, and in order to further reveal its intrinsic laws and differences, it uses three-dimensional kernel density analysis, the Dagum Gini coefficient, spatial autocorrelation analysis, and cold hot spot analysis to explore the spatial and temporal evolution characteristics of the digital economy and its regional imbalance. The empirical results show that ① China’s digital economy has been steadily increasing, spatially showing the characteristics of gradual decrease from east to west and from coast to inland, with obvious spatial agglomeration characteristics and an increasing trend. ② There are obvious regional imbalances in the digital economy, with the southeast coastal region leading significantly. ③ The overall regional differences are large but reduced, mainly from intra-regional differences, the and inter-regional contribution is low. The research in this paper provides data support for revealing the spatial and temporal evolution characteristics of digital economic development and provides new path support for the balanced development of China’s regional digital economy.

Surface roughness analysis of side-polished fiber based on the importance of texture features

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.

Analysis of team success based on technical match-play performance in the Australian Football League Women’s (AFLW) competition

ABSTRACT An understanding of the effect contextual data may have on key match-play technical performance indicators in the Australian Football League Women’s (AFLW) competition is warranted due to its rapid evolution. To address this, predictive models were fit to determine which technical match-play data, including new contextual information, more accurately predict AFLW match outcomes (win/loss, margin), and what are the most important contexts and technical predictors of team performance? Thirteen random forest models were fit, each with greater data contextual interaction including relative to opposition and harder-to-attain match-play variables, field location, and individual player contributions. Models were assessed by prediction performance on match outcome in a holdout sample and variable importance through Mean Decrease in Gini Index. Effective kicks and entries into attacking locations were important in models. Territory gained, contexts of relative performance to the opposition, and locational information around actions improved prediction. This methodology represents the most in-depth analysis of women’s Australian football technical match-play performance to date. Commentary presented surrounded issues of using aggregated datasets, prediction with match-play success as a dependent variable, and that detailed, process-oriented approaches are needed in future to avoid large assumptions.

DCAI-CLUD: a data-centric framework for the construction of land-use datasets

A high-quality land-use dataset is crucial for constructing a high-performance land-use classification model. Due to the complexity and spatial heterogeneity of land-use, the dataset construction process is inefficient and costly. This challenge affects the quality of datasets, consequently impacting the model’s performance. The emerging field of Data-Centric Artificial Intelligence (DCAI) is expected to deliver techniques for dataset optimization, offering a promising solution to the problem. Therefore, this study proposes a data-centric framework named DCAI-CLUD for the construction of land-use datasets. Based on this framework, the accuracy and rate of data labeling are improved by 5.93 and 28.97%. The Gini index of the dataset and the proportion of samples with non-mixed land-use categories are enhanced by 3.27 and 8.52%. The overall accuracy (OA) and Kappa of the land-use classification model improved significantly by 27.87 and 58.08%. This study is the first to introduce DCAI into the field of geographic information and remote sensing and verify its effectiveness. The proposed framework can effectively improve the construction efficiency and quality of the dataset and synchronously optimize the model performance. Based on the proposed framework, we constructed a multi-source land-use dataset of major cities in China named CN-MSLU-100K.