Leeches and earthworms are the main ingredients of Shuxuetong injection compositions,whichare natural biomedicines.Near infrared(NIR)diffuse reflection spectroscopy has been used forquality assurance of Chinese medici...Leeches and earthworms are the main ingredients of Shuxuetong injection compositions,whichare natural biomedicines.Near infrared(NIR)diffuse reflection spectroscopy has been used forquality assurance of Chinese medicines.In the present work,NIR spectroscopy was proposed as arapid and nondestructive technique to assess the moisture content(MC),soluble solid content(SSC)and hypoxanthine content(HXC)of leeches and earthworms.This study goal was toimprove NIR models for accurate quality control of leech and earthworm using outlier multiplediagnoses(OMD).OMD was composed of four outlier detection methods:spectrum outlier di-agnostic(MD),leverage diagnostic(LD),principal component scores diagnostic(PCSD)andfactor loading diagnostic(FLD),Conventional outlier diagnoses(MD,LD)and OMD werecompared,and the best NIR models were those based on OMD.The correlation coefficients(R)for leech were 0.9779,0.9616 and 0.9406 for MC,SSC and HXC,respectively.The values ofrelative standard error of prediction(RSEP)for leech were 2.3%,5.1%and 9.0%for MC,SSC and HXC,respectively.The values of R for earthworm were 0.9478,0.9991 and 0.9605 for MC,SSC and HXC,respectively.The values of RSEP for earthworm were 8.8%,2.4%and 12%for MC,SSC and HXC,respectively.The performance of the NIR models was certainly improved by OMD.展开更多
Vehicular emissions in China in 2006 and 2010 were calculated at a high spatial resolution based on the data released by the National Bureau of Statistics, by taking the emission standards into consideration. China's...Vehicular emissions in China in 2006 and 2010 were calculated at a high spatial resolution based on the data released by the National Bureau of Statistics, by taking the emission standards into consideration. China's vehicular emissions of carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH3), fine particulate matters (PM2.5), inhalable particulate matters (PMlo), black carbon (BC), and organic carbon (OC) were 30,113.9, 4593.7, 6838.0, 20.9, 400.2, 430.5,285.6, and 105.1 Gg, respectively, in 2006 and 34,175.2, 5167.5, 7029.4, 74.0, 386.4, 417.1, 270.9, and 106.2 Gg, respectively, in 2010. CO, VOCs, and NH3 emissions were mainly from motorcycles and light-duty gasoline vehicles, whereas NOx, PMzs, PMlo, and BC emissions were mainly from rural vehicles and heavy- duty diesel trucks. OC emissions were mainly from motorcycles and heavy-duty diesel trucks. Vehicles of pre-China I (vehicular emission standard of China before phase I) and China I (vehicular emission standard of China in phase I) were the primary contributors to all of the pollutant emissions except NH3, which was mainly from China III and China IV gasoline vehicles. The total emissions of all the pollutants except NH3 changed little from 2006 to 2010. This finding can be attributed to the implementation of strict emission standards and to improvements in oil quality.展开更多
文摘Leeches and earthworms are the main ingredients of Shuxuetong injection compositions,whichare natural biomedicines.Near infrared(NIR)diffuse reflection spectroscopy has been used forquality assurance of Chinese medicines.In the present work,NIR spectroscopy was proposed as arapid and nondestructive technique to assess the moisture content(MC),soluble solid content(SSC)and hypoxanthine content(HXC)of leeches and earthworms.This study goal was toimprove NIR models for accurate quality control of leech and earthworm using outlier multiplediagnoses(OMD).OMD was composed of four outlier detection methods:spectrum outlier di-agnostic(MD),leverage diagnostic(LD),principal component scores diagnostic(PCSD)andfactor loading diagnostic(FLD),Conventional outlier diagnoses(MD,LD)and OMD werecompared,and the best NIR models were those based on OMD.The correlation coefficients(R)for leech were 0.9779,0.9616 and 0.9406 for MC,SSC and HXC,respectively.The values ofrelative standard error of prediction(RSEP)for leech were 2.3%,5.1%and 9.0%for MC,SSC and HXC,respectively.The values of R for earthworm were 0.9478,0.9991 and 0.9605 for MC,SSC and HXC,respectively.The values of RSEP for earthworm were 8.8%,2.4%and 12%for MC,SSC and HXC,respectively.The performance of the NIR models was certainly improved by OMD.
基金supported by the Chinese Academy of Sciences Strategic Priority Research Program Grant (No.: XDB05020000)the National Natural Science Foundation of China (No. 41230642)the National key technology research and development program of the ministry of Science and technology of China (No. 2014BAC22B06)
文摘Vehicular emissions in China in 2006 and 2010 were calculated at a high spatial resolution based on the data released by the National Bureau of Statistics, by taking the emission standards into consideration. China's vehicular emissions of carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH3), fine particulate matters (PM2.5), inhalable particulate matters (PMlo), black carbon (BC), and organic carbon (OC) were 30,113.9, 4593.7, 6838.0, 20.9, 400.2, 430.5,285.6, and 105.1 Gg, respectively, in 2006 and 34,175.2, 5167.5, 7029.4, 74.0, 386.4, 417.1, 270.9, and 106.2 Gg, respectively, in 2010. CO, VOCs, and NH3 emissions were mainly from motorcycles and light-duty gasoline vehicles, whereas NOx, PMzs, PMlo, and BC emissions were mainly from rural vehicles and heavy- duty diesel trucks. OC emissions were mainly from motorcycles and heavy-duty diesel trucks. Vehicles of pre-China I (vehicular emission standard of China before phase I) and China I (vehicular emission standard of China in phase I) were the primary contributors to all of the pollutant emissions except NH3, which was mainly from China III and China IV gasoline vehicles. The total emissions of all the pollutants except NH3 changed little from 2006 to 2010. This finding can be attributed to the implementation of strict emission standards and to improvements in oil quality.