Different brain mechanisms mediate two strategies in arithmetic: Evidence from event-related brain potentials. Neuropsychologia, 41(7), 855-862.

BackgroundBy 2013, several regions in China had introduced health insurance integration policies. However, few studies addressed the impact of medical insurance integration in China. This study investigates the catastrophic health expenditure and equity in the incidence of catastrophic health expenditure by addressing its potential determinants in both integrated and non-integrated areas in China in 2013.MethodsThe primary data are drawn from the fifth China National Health Services Survey in 2013. The final sample comprises 19,788 households (38.4%) from integrated areas and 31,797 households (61.6%) from non-integrated areas. A probit model is employed to decompose inequality in the incidence of catastrophic health expenditure in line with the methodology used for decomposing the concentration index.ResultsThe incidence of catastrophic health expenditure in integrated areas is higher than in non-integrated areas (13.87% vs. 13.68%, respectively). The concentration index in integrated areas and non-integrated areas is − 0.071 and − 0.073, respectively. Average household out-of-pocket health expenditure and average capacity to pay in integrated areas are higher than those in non-integrated areas. However, households in integrated areas have lower share of out-of-pocket expenditures in the capacity to pay than households in non-integrated areas. The majority of the observed inequalities in catastrophic health expenditure can be explained by differences in the health insurance and householders’ educational attainment both in integrated areas and non-integrated areas.ConclusionsThe medical insurance integration system in China is still at the exploratory stage; hence, its effects are of limited significance, even though the positive impact of this system on low-income residents is confirmed. Moreover, catastrophic health expenditure is associated with pro-poor inequality. Medical insurance, urban-rural disparities, the elderly population, and use of health services significantly affect the equity of catastrophic health expenditure incidence and are key issues in the implementation of future insurance integration policies.

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In China, Tahe Triassic oil field block 9 reservoir was discovered in 2002 by drilling wells S95 and S100. The distribution of the reservoir sand body is not clear. Therefore, it is necessary to study and to predict oil production from this oil field. In this study, we propose an improved Random Vector Functional Link (RVFL) network to predict oil production from Tahe oil field in China. The Spherical Search Optimizer (SSO) is applied to optimize the RVFL and to enhance its performance, where SSO works as a local search method that improved the parameters of the RVFL. We used a historical dataset of this oil field from 2002 to 2014 collected by a local partner. Our proposed model, called SSO-RVFL, has been evaluated with extensive comparisons to several optimization methods. The outcomes showed that, SSO-RVFL achieved accurate predictions and the SSO outperformed several optimization methods.