Changes in the Distribution of Wealth in China 1995-2002

This paper investigates some major changes in the wealth distribution in China using the data from two national household surveys conducted in 1995 and 2002. The surveys collected rich information on household wealth and its components, enabling a detailed analysis of changes in wealth distribution among Chinese households. Our analysis indicates that the wealth distribution in China as a whole became much more unequal in 2002 than it was in 1995. The housing reform, in which public apartments were sold to urban households at extremely low prices, has accelerated the accumulation of wealth among urban households on the one hand, and widened the wealth gap between urban and rural areas on the other.China, wealth, income, distribution, inequality, households

Divergent Means and Convergent Inequality of Incomes among the Provinces and Cities of Urban China

China, spatial inequality, incomes, wages, convergence, divergence

中國居民收入差距的擴大及其原因 = The cause of the enlargement of income disparities in China

引言 中国的经济体制改革已经进行了将近二十年。在这一过程中, 居民收入分配的格局发生了很大变化。 本章试图对收入分配格局的变化,特别上收入差距扩大的状况作一考察。由于收入分配涉及的面很广,本章拟集中考察收入分配变化的一些重要方面。 为了更好地考察改革以来收入分配的变化情况,还拟对改革以前中国居民收入分配的特点作一简要的回顾与分析, 以便对这种变化的起点和背景有一个基本的了解和判断。 中国的经济改革是同经济发展或增长紧密地联系在一起的,换言之, 中国从计划经济向市场经济转换的过程是同从二元经济向现代经济转换的过程交织在一起的。中国居民收入分配格局的变化是在这样两个转变的过程中实现的。因此, 本章还试图从经济发展、经济改革以及与此有关的政策因素中去分析收入差距变化的原因。 在本章的最后, 我们拟对今后如何改进收入分配提出一些具有政策含义的建议。 本章所引用的资料, 有一部分来自于中国社会科学院经济研究所收入分配课题组(以下简称经济所课题组) 对1988年和1995年城乡居民收入分配状况所作的抽样调查, 有一部分来自于国家统计局以及其他渠道。凡未注明出处者, 均来自于上述两次抽样调查

Fault2SeisGAN: A method for the expansion of fault datasets based on generative adversarial networks

The development of supervised deep learning technology in seismology and related fields has been restricted due to the lack of training sets. A large amount of unlabeled data is recorded in seismic exploration, and their application to network training is difficult, e.g., fault identification. To solve this problem, herein, we propose an end-to-end training data set generative adversarial network Fault2SeisGAN. This network can expand limited labeled datasets to improve the performance of other neural networks. In the proposed method, the Seis-Loss is used to constrain horizon and amplitude information, Fault-Loss is used to constrain fault location information, and the Wasserstein distance is added to stabilize the network training to generate seismic amplitude data with fault location labels. A new fault identification network model was trained with a combination of expansion and original data, and the model was tested using actual seismic data. The results show that the use of the expanded dataset generated in this study improves the performance of the deep neural network with respect to seismic data prediction. Our method solves the shortage of training data set problem caused by the application of deep learning technology in seismology to a certain extent, improves the performance of neural networks, and promotes the development of deep learning technology in seismology

Allelic Variation Contributes to Bacterial Host Specificity

Understanding the molecular parameters that regulate cross-species transmission and host adaptation of potential pathogens is crucial to control emerging infectious disease. Although microbial pathotype diversity is conventionally associated with gene gain or loss, the role of pathoadaptive nonsynonymous single-nucleotide polymorphisms (nsSNPs) has not been systematically evaluated. Here, our genome-wide analysis of core genes within Salmonella enterica serovar Typhimurium genomes reveals a high degree of allelic variation in surface-exposed molecules, including adhesins that promote host colonization. Subsequent multinomial logistic regression, MultiPhen and Random Forest analyses of known/suspected adhesins from 580 independent Typhimurium isolates identifies distinct host-specific nsSNP signatures. Moreover, population and functional analyses of host-associated nsSNPs for FimH, the type 1 fimbrial adhesin, highlights the role of key allelic residues in host-specific adherence in vitro. Together, our data provide the first concrete evidence that functional differences between allelic variants of bacterial proteins likely contribute to pathoadaption to diverse hosts

Embracing the Market: Entry into Self-Employment in Transitional China, 1978-1996

This paper introduces labor market transition as an intervening process by which the macro institutional transition to a market economy alters social stratification outcome. Rather than directly addressing income distribution, it examines the pattern of workers’ entry into self-employment in reform-era China (1978-1996), focusing on rural-urban differences and the temporal trend. Analyses of data from a national representative survey in China show that education, party membership and cadre status all deter urban workers’ entry into self-employment, while education promotes rural workers’ entry into self-employment. As marketization proceeds, the rate of entry into self-employment increases in both rural and urban China, but urban workers are increasingly more likely to take advantages of the new market opportunities. In urban China, college graduates and cadres are still less likely to be involved in self-employment, but they are becoming more likely to do so in the later phase of reform. The diversity of transition scenarios is attributed to rural-urban differences in labor market structures.http://deepblue.lib.umich.edu/bitstream/2027.42/39897/3/wp512.pd

Conflict Risk Assessment between Non-Cooperative Drones and Manned Aircraft in Airport Terminal Areas

Recent years have seen an increase in events of drone incursion into airport terminal areas, leading to safety concerns and disruptions to airline operations. It is of great importance to identify the potential conflict, especially for those non-cooperative drones, as their intentions are always unknown. For the safe operation of air traffic, this paper proposes a conflict risk assessment method between non-cooperative drones and manned aircraft in the terminal area. First, the trajectory data of manned aircraft and drones are obtained. Real-time cylindrical protection zones are established around manned aircraft according to the separation interval for safe operation between the drone and the manned aircraft at different altitudes. Secondly, trajectory predictions for the manned aircraft and the drone are conducted, respectively. A quartile regression bidirectional gate recurrent unit neural network is proposed in this research for the trajectory prediction of the drones. The model integrates the bidirectional gated recurrent unit structure and the quartile regression structure. The performance indicators confirm the superiority of the proposed model. Based on the trajectory prediction results, it is then determined whether there is a conflict risk between the drone and manned aircraft by comparing the position distribution of the drone as well as the real-time cylindrical protection zone of the manned aircraft. The conflict probability between the drone and the manned aircraft is then calculated. The prediction accuracy of conflict probability is estimated by Monte Carlo simulation methods. The collision probability prediction accuracy of manned aircraft and drones at different flight stages and altitudes ranges from 73% to 97%, which shows the reliability of the proposed method. Finally, the collision probability between the drone and the manned aircraft at the closest encountering point and the estimated time to reach the closest encountering point are calculated. This paper predicts the conflict risk between the drone and manned aircraft, thus providing theoretical support for the safe operation of air transport in low-altitude environments