982 research outputs found

    A new species of Ludovicius from China (Diptera: Dolichopodidae)

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    We review the species of the Ludovicius emeishanus-group from China, and describe one species as new to scicence, viz. Ludovicius songshanensis sp. n. We present a key to species of the group from China, and discuss the distribution of the Ludovicius emeishanus group in China

    Probability density forecasts for steam coal prices in China:The role of high-frequency factors

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    Abstract Coal plays a key role in China's economy as a dominant primary energy resource. In this paper, we provide probability density forecasts for weekly steam coal prices in China based on daily factors such as renewable energy source, Daqing oil, Japanese natural gas, Australia steam coal prices, coal mining industry index, A-share power sector index, A-share index, coal industry index, and temperature. The empirical results show that the influence of temperature lasts longer than other factors, while the Australia steam coal prices, renewable energy source and A-share index are the three best predictors for steam coal prices. It is also shown that the high-frequency factors are useful to forecast steam coal prices and that considering the nonlinearity of coal prices can improve the forecast accuracy by about 22%. We further provide the probability density forecasts for steam coal prices based on the influence of all the selected factors, the results suggest that our proposed method can provide accurate and satisfying probability density forecasts. Given these results, the policy-makers can make effective strategies which can not only adjust the energy structure but also ensure economic growth

    The Hercostomus ulrichi group from Palaearctic China (Diptera: Dolichopodidae)

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    Anew species group, the Hercostomus ulrichi group, is established. The species of this group are reviewed. The following two species are described as new to science: Hercostomus anae sp. n. and H. geniculatus sp. n

    Evidence for cross-protection but not type-replacement over the 11 years after human papillomavirus vaccine introduction

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    Examination of cross-protection and type replacement after human papillomavirus (HPV) vaccine introduction is essential to guide vaccination recommendations and policies. The aims of this study were to examine trends in non-vaccine-type HPV: 1) genetically related to vaccine types (to assess for cross-protection) and 2) genetically unrelated to vaccine types (to assess for type replacement), among young women 13-26 years of age during the 11 years after HPV vaccine introduction. Participants were recruited from a hospital-based teen health center and a community health department for four cross-sectional surveillance studies between 2006 and 2017. Participants completed a survey that assessed sociodemographic characteristics and behaviors, and cervicovaginal swabs were collected and tested for 36 HPV genotypes. We determined changes in proportions of non-vaccine-type HPV prevalence and conducted logistic regression to determine the odds of infection across the surveillance studies, propensity-score adjusted to control for selection bias. Analyses were stratified by vaccination status. Among vaccinated women who received only the 4-valent vaccine (n = 1,540), the adjusted prevalence of HPV types genetically related to HPV16 decreased significantly by 45.8% (adjusted odds ratio [AOR] = 0.48, 95% confidence interval [CI] = 0.31-0.74) from 2006-2017, demonstrating evidence of cross-protection. The adjusted prevalence of HPV types genetically related to HPV18 did not change significantly (14.2% decrease, AOR = 0.83, 95% CI = 0.56-1.21). The adjusted prevalence of HPV types genetically unrelated to vaccine types did not change significantly (4.2% increase, AOR = 1.09, CI = 0.80-1.48), demonstrating no evidence of type replacement. Further studies are needed to monitor for cross-protection and possible type replacement after introduction of the 9-valent HPV vaccine

    Forecasting carbon prices in the Shenzhen market, China:The role of mixed-frequency factors

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    In this study, the hybrid of combination-mixed data sampling regression model and back propagation neural network (combination-MIDAS-BP) is proposed to perform real-time forecasting of weekly carbon prices in China's Shenzhen carbon market. In addition to daily energy, economy and weather conditions, environmental factor is introduced into predictive indicators. The empirical results show that the carbon price is more sensitive to coal, temperature and AQI (air quality index) than to other factors. It is also shown that the forecast accuracy of the proposed model is approximately 30% and 40% higher than that of combination-MIDAS models and benchmark models, respectively. Given these forecast results, China's government and enterprises can effectively manage nonlinear, nonstationary, and irregular carbon prices, providing a better investing and managing tool from behavioural economics. (C) 2019 Elsevier Ltd. All rights reserved
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