Village Inequality in Western China

Increased regional inequality has been a major concern in many emerging economies like China, India, Vietnam and Thailand. However, even a large inequality is observed within the lagging regions. The objective of this paper is to look into what are the sources of within region inequality using the community surveys and a census type of households in Western China. This snapshot view of inequality within and between rural villages in western China is based on a census-type household survey in three administrative villages and a sampling survey of 286 natural villages in the poor province of Guizhou in 2004. In contrast to coastal regions, nonfarm income is distributed unevenly in this inland western region. This acco unts for the largest share of overall income inequality. But agriculture is still the rural peoples major source of livelihood in this particular location. On the expenditure side, health care is one of the most important sources of inequality. Because rural income is strongly related to human capital, the uneven access to health care will translate into a larger income gap in the long run. The analysis based on the natural village survey indicates that income varies widely across villages. Access to infrastructure and markets, education, and political participation explain most of this variation. These findings have important implications on the future development strategy in promoting lagging regions development and poverty reduction. While the overall economic development will be the main instrument to bring the majority poor out of poverty, a targeted approach has become increasingly crucial in helping the poor villages and households. It is critical to understand why these villages and households can not particulate in the growth process and how development programs and various transfer programs help them to overcome the constraints they face.Rural Development, Poverty, Inequality, Public investment, H54, O47, O53, R11, Community/Rural/Urban Development,

Village inequality in Western China: implications for development strategy in lagging regions

"Increased regional inequality has been a major concern in many emerging economies like China, India, Vietnam and Thailand. However, even a large inequality is observed within the lagging regions. The objective of this paper is to look into what are the sources of within region inequality using the community surveys and a census type of households in Western China. This snapshot view of inequality within and between rural villages in western China is based on a census-type household survey in three administrative villages and a sampling survey of 286 natural villages in the poor province of Guizhou in 2004. In contrast to coastal regions, nonfarm income is distributed unevenly in this inland western region. This accounts for the largest share of overall income inequality. But agriculture is still the rural people's major source of livelihood in this particular location. On the expenditure side, health care is one of the most important sources of inequality. Because rural income is strongly related to human capital, the uneven access to health care will translate into a larger income gap in the long run. The analysis based on the natural village survey indicates that income varies widely across villages. Access to infrastructure and markets, education, and political participation explain most of this variation. These findings have important implications on the future development strategy in promoting lagging regions development and poverty reduction. While the overall economic development will be the main instrument to bring the majority poor out of poverty, a targeted approach has become increasingly crucial in helping the poor villages and households. It is critical to understand why these villages and households can not participate in the growth process and how development programs and various transfer programs help them to overcome the constraints they face." Authors' AbstractRural development, Poverty reduction, Inequality, Public investment, China, Asia, Household surveys, Agriculture, Income Rural areas,

Resource abundance and regional development in China:

"Over the past several decades, China has made tremendous progress in market integration and infrastructure development. Demand for natural resources has increased from the booming coastal economies, causing the terms of trade to favor the resource sector, which is predominantly based in the interior regions of the country. However, the gap in economic development level between the coastal and inland regions has widened significantly. In this paper, using a panel data set at the provincial level, we show that Chinese provinces with abundant resources perform worse than their resource-poor counterparts in terms of per capita consumption growth. This trend that resource-poor areas are better off than resource-rich areas is particularly prominent in rural areas. Because of the institutional arrangements regarding property rights of natural resources, most gains from the resource boom have been captured either by the government or state owned enterprises. Thus, the windfall of natural resources has more to do with government consumption than household consumption. Moreover, in resource-rich areas, greater revenues accrued from natural resources bid up the price of non-tradable goods and hurt the competitiveness of the local economy." from Authors' AbstractRegional inequality, Resource curse, Dutch disease, Property rights, Rural-urban linkages,

Application of FGD-BCEL loss function in segmenting temporal lobes on localized CT images for radiotherapy

ObjectivesThe aim of this study was to find a new loss function to automatically segment temporal lobes on localized CT images for radiotherapy with more accuracy and a solution to dealing with the classification of class-imbalanced samples in temporal lobe segmentation.MethodsLocalized CT images for radiotherapy of 70 patients with nasopharyngeal carcinoma were selected. Radiation oncologists sketched mask maps. The dataset was randomly divided into the training set (n = 49), the validation set (n = 7), and the test set (n = 14). The training set was expanded by rotation, flipping, zooming, and shearing, and the models were evaluated using Dice similarity coefficient (DSC), Jaccard similarity coefficient (JSC), positive predictive value (PPV), sensitivity (SE), and Hausdorff distance (HD). This study presented an improved loss function, focal generalized Dice-binary cross-entropy loss (FGD-BCEL), and compared it with four other loss functions, Dice loss (DL), generalized Dice loss (GDL), Tversky loss (TL), and focal Tversky loss (FTL), using the U-Net model framework.ResultsWith the U-Net model based on FGD-BCEL, the DSC, JSC, PPV, SE, and HD were 0.87 ± 0.11, 0.78 ± 0.11, 0.90 ± 0.10, 0.87 ± 0.13, and 4.11 ± 0.75, respectively. Except for the SE, all the other evaluation metric values of the temporal lobes segmented by the FGD-BCEL-based U-Net model were improved compared to the DL, GDL, TL, and FTL loss function-based U-Net models. Moreover, the FGD-BCEL-based U-Net model was morphologically more similar to the mask maps. The over- and under-segmentation was lessened, and it effectively segmented the tiny structures in the upper and lower poles of the temporal lobe with a limited number of samples.ConclusionsFor the segmentation of the temporal lobe on localized CT images for radiotherapy, the U-Net model based on the FGD-BCEL can meet the basic clinical requirements and effectively reduce the over- and under-segmentation compared with the U-Net models based on the other four loss functions. However, there still exists some over- and under-segmentation in the results, and further improvement is needed

Credit risk prediction for small and medium enterprises utilizing adjacent enterprise data and a relational graph attention network

Credit risk prediction for small and medium enterprises (SMEs) has long posed a complex research challenge. Traditional approaches have primarily focused on enterprise-specific variables, but these models often prove inadequate when applied to SMEs with incomplete data. In this innovative study, we push the theoretical boundaries by leveraging data from adjacent enterprises to address the issue of data deficiency. Our strategy involves constructing an intricate network that interconnects enterprises based on shared managerial teams and business interactions. Within this network, we propose a novel relational graph attention network (RGAT) algorithm capable of capturing the inherent complexity in its topological information. By doing so, our model enhances financial service providers' ability to predict credit risk even in the face of incomplete data from target SMEs. Empirical experiments conducted using China's SMEs highlight the predictive proficiency and potential economic benefits of our proposed model. Our approach offers a comprehensive and nuanced perspective on credit risk while demonstrating the advantages of incorporating network-wide data in credit risk prediction

Text mining-based patent analysis of BIM application in construction

As a data tool applicable to the full life-cycle of construction engineering and management, Building Information Modeling (BIM) has great potential for significantly increasing project productivity and performance. Awareness of BIM application hotspots and forecasting its trends can drive innovations in construction field. Using patents as data resources, this study develops an effective framework integrating the citation network analysis and the topic clustering technology to identify BIM application information and forecast its trends. This framework comprises three-step analysis:(1) quantitative characteristic analysis of patent outputs; (2) Social Network Analysis (SNA)-based co-occurrence network analysis; and (3) identification of BIM topics using a Latent Dirichlet Allocation (LDA). Finally, the case demonstrates the effectiveness of this framework contributing to promote technological development and innovation of BIM. The contributions of this study are threefold: (1) an innovative text mining-based framework for BIM patent analysis in construction is developed; (2) patents that have focused on identifying the application hotspots and development trend of BIM in accordance with our developed framework are reviewed; and (3) a signpost for technological development and innovation of BIM is provided

β-diversity in temperate grasslands is driven by stronger environmental filtering of plant species with large genomes

Elucidating mechanisms underlying community assembly and biodiversity patterns is central to ecology and evolution. Genome size (GS) has long been hypothesized to potentially affect species' capacity to tolerate environmental stress and might therefore help drive community assembly. However, its role in driving β-diversity (i.e., spatial variability in species composition) remains unclear. We measured GS for 161 plant species and community composition across 52 sites spanning a 3200-km transect in the temperate grasslands of China. By correlating the turnover of species composition with environmental dissimilarity, we found that resource filtering (i.e., environmental dissimilarity that includes precipitation, and soil nitrogen and phosphorus concentrations) affected β-diversity patterns of large-GS species more than small-GS species. By contrast, geographical distance explained more variation of β-diversity for small-GS than for large-GS species. In a 10-year experiment manipulating levels of water, nitrogen, and phosphorus, adding resources increased plant biomass in species with large GS, suggesting that large-GS species are more sensitive to the changes in resource availability. These findings highlight the role of GS in driving community assembly and predicting species responses to global change