259 research outputs found

    Migration and Urban Poverty and Inequality in China

    No full text
    Using data from recent surveys of migrants and local residents in 10 cities in 2005, this paper examines how migration influences measurements of urban poverty and inequality in China, and also compares how other indicators of well-being differ for migrants and local residents. Contrary to previous studies that report that the income poverty rate of migrant households is 1.5 times that of local resident households, we find relatively small differences in the poverty rates of migrants and local residents. Although the hourly wages of migrants are much lower than those of local residents, migrant workers work longer hours and have lower dependency ratios and higher labor force participation rates. Including migrants increases somewhat measures of urban income inequality. Significant differences between migrants and local residents are found for non-income welfare indicators such as housing conditions and access to social insurance programs.migration, urban, poverty, inequality, social protection, China

    Corrigendum to ‘Thiophene donor for NIR-II fluorescence imaging guided photothermal/photodynamic/chemo combination therapy’ [Acta Biomaterialia 127 (2021) 287-297]

    No full text
    The authors regret to report that the affiliation for author Dewen Liu was published incorrectly. The correct affiliation is as follows: Artemisinin Research Center, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China. The authors apologise for any inconvenience caused.link_to_subscribed_fulltex

    Can China's rural elderly count on support from adult children ? implications of rural-to-urban migration

    No full text
    This paper shows that support from the family continues to be an important source of support for the rural elderly, particularly the rural elderly over 70 years of age. Decline in likelihood of co-residence with, or in close proximity to, adult children raises the possibility that China's rural elderly will receive less support in the forms of both income and in-kind instrumental care. Although descriptive evidence on net financial transfers suggests that the elderly with migrant children will receive similar levels of financial transfers as those without migrant children, the predicted variance associated with these transfers implies a higher risk that elderly with migrant children may fall into poverty. Reducing the risk of low incomes among the elderly is one important motive for new rural pension initiatives supported by China's government, which are scheduled to be expanded to cover all rural counties by the end of the 12th Five Year Plan in 2016.Rural Poverty Reduction,Population Policies,Services&Transfers to Poor,Regional Economic Development,Labor Policies

    External force detection for physical human-robot interaction using dynamic model identification

    No full text
    Nowadays as more and more tasks require humans to collaborate with robots in modern industry, and the focus of many robotic researchers worldwide has turned towards human-robot collaboration. In human-robot interaction, ensuring the safety issues has the absolute priority for all other research work. In this context, sensorless collision detection and fast response researches in robotics contribute significantly to solve the safety issues. However, existing approaches for collision detection involve in the usage of external sensors, not fit for closed industrial robots or the offline observer based on robot’s the generalized momentum, poor in the real time response. In this study, a different method of external forces detection for sensor-less industrial robots using dynamics model identification is proposed. The main idea of our method is to identify the external torques by the comparison of the actual motor torques with the predicted joint torques based on dynamics model. Without using any extra sensors, a strict dynamics model including the parameterized friction torques has been formulated only by utilizing the measurements of the joint angles and joint torques. In addition, the essential response strategies in the post-contact stage are the main directions for our following research. Finally, the model accuracy and performance of the proposed method were evaluated in a 6-DOF manipulator. The experimental results demonstrated the reliability of our detection method basically.</p

    Enhancing the Generalization for Text Classification through Fusion of Backward Features

    No full text
    Generalization has always been a keyword in deep learning. Pretrained models and domain adaptation technology have received widespread attention in solving the problem of generalization. They are all focused on finding features in data to improve the generalization ability and to prevent overfitting. Although they have achieved good results in various tasks, those models are unstable when classifying a sentence whose label is positive but still contains negative phrases. In this article, we analyzed the attention heat map of the benchmarks and found that previous models pay more attention to the phrase rather than to the semantic information of the whole sentence. Moreover, we proposed a method to scatter the attention away from opposite sentiment words to avoid a one-sided judgment. We designed a two-stream network and stacked the gradient reversal layer and feature projection layer within the auxiliary network. The gradient reversal layer can reverse the gradient of features in the training stage so that the parameters are optimized following the reversed gradient in the backpropagation stage. We utilized an auxiliary network to extract the backward features and then fed them into the main network to merge them with normal features extracted by the main network. We applied this method to the three baselines of TextCNN, BERT, and RoBERTa using sentiment analysis and sarcasm detection datasets. The results show that our method can improve the sentiment analysis datasets by 0.5% and the sarcasm detection datasets by 2.1%
    corecore