Betulin(BE)has exceedingly become a potential natural product,providing multiple pharmacological and biological activi-ties,including anti-cancer,anti-viral,and anti-inflammatory benefits.Previous research indicated t...Betulin(BE)has exceedingly become a potential natural product,providing multiple pharmacological and biological activi-ties,including anti-cancer,anti-viral,and anti-inflammatory benefits.Previous research indicated that the solvatomorphism of BE can easily occur through crystallization with different organic solvents.This property of BE can directly affect its extraction,isolation,and preparation process.In this study,a system of thermogravimetry(TG)-differential thermal analysis(DTA)coupled with mass spectrometry(MS)with electron ionization(EI)and photoionization(PI)capability,equipped with the skimmer-type interface(i.e.,skimmer-type interfaced TG-DTA-EI/PI-MS system),as a real-time and onsite analysis technique,was employed.Then,four solvatomorphs of BE,namely,with pyridine and water(A),sec-butanol(B),n,n-dimethylformamide(DMF)(C),and isopropanol(V),were analyzed for the first time.Finally,five kinds of the main volatile gaseous species,including H2O,pyridine,sec-butanol,DMF,and isopropanol,were identified clearly.Furthermore,the multi-step desolvation processes of the four solvatomorphs of BE were revealed by this system for the first time.This system showed great potential for the rapid and accurate analysis of various solvatomorphs of natural products.展开更多
Radar data, which have incomparably high temporal and spatial resolution, and lightning data, which are great indicators of severe convection, have been used to improve the initial field and increase the accuracies of...Radar data, which have incomparably high temporal and spatial resolution, and lightning data, which are great indicators of severe convection, have been used to improve the initial field and increase the accuracies of nowcasting and short-term forecasting. Physical initialization combined with the three-dimensional variational data assimilation method(PI3 DVarrh) is used in this study to assimilate two kinds of observation data simultaneously, in which radar data are dominant and lightning data are introduced as constraint conditions. In this way, the advantages of dual observations are adopted. To verify the effect of assimilating radar and lightning data using the PI3 DVarrh method, a severe convective activity that occurred on 5 June 2009 is utilized, and five assimilation experiments are designed based on the Weather Research and Forecasting(WRF) model. The assimilation of radar and lightning data results in moister conditions below cloud top, where severe convection occurs;thus, wet forecasts are generated in this study.The results show that the control experiment has poor prediction accuracy. Radar data assimilation using the PI3 DVarrh method improves the location prediction of reflectivity and precipitation, especially in the last 3-h prediction, although the reflectivity and precipitation are notably overestimated. The introduction of lightning data effectively thins the radar data, reduces the overestimates in radar data assimilation, and results in better spatial pattern and intensity predictions. The predicted graupel mixing ratio is closer to the distribution of the observed lightning,which can provide more accurate lightning warning information.展开更多
基金supported by National Key R&D Program of China(Grant No.2016YFC1000900)National Science and Technology Major Project of China(Grant Nos.2017ZX09101001003,2018ZX09711001-010)+1 种基金National Natural Science Foundation of China(NSFC)(Grant No.81703473)CAMS Innovation Fund for Medical Sciences(Grant No.2017-I2M-3-010).
文摘Betulin(BE)has exceedingly become a potential natural product,providing multiple pharmacological and biological activi-ties,including anti-cancer,anti-viral,and anti-inflammatory benefits.Previous research indicated that the solvatomorphism of BE can easily occur through crystallization with different organic solvents.This property of BE can directly affect its extraction,isolation,and preparation process.In this study,a system of thermogravimetry(TG)-differential thermal analysis(DTA)coupled with mass spectrometry(MS)with electron ionization(EI)and photoionization(PI)capability,equipped with the skimmer-type interface(i.e.,skimmer-type interfaced TG-DTA-EI/PI-MS system),as a real-time and onsite analysis technique,was employed.Then,four solvatomorphs of BE,namely,with pyridine and water(A),sec-butanol(B),n,n-dimethylformamide(DMF)(C),and isopropanol(V),were analyzed for the first time.Finally,five kinds of the main volatile gaseous species,including H2O,pyridine,sec-butanol,DMF,and isopropanol,were identified clearly.Furthermore,the multi-step desolvation processes of the four solvatomorphs of BE were revealed by this system for the first time.This system showed great potential for the rapid and accurate analysis of various solvatomorphs of natural products.
基金the National Key Research and Development Program of China (2017YFC1502102)National Natural Science Youth Fund of China (41905089)。
文摘Radar data, which have incomparably high temporal and spatial resolution, and lightning data, which are great indicators of severe convection, have been used to improve the initial field and increase the accuracies of nowcasting and short-term forecasting. Physical initialization combined with the three-dimensional variational data assimilation method(PI3 DVarrh) is used in this study to assimilate two kinds of observation data simultaneously, in which radar data are dominant and lightning data are introduced as constraint conditions. In this way, the advantages of dual observations are adopted. To verify the effect of assimilating radar and lightning data using the PI3 DVarrh method, a severe convective activity that occurred on 5 June 2009 is utilized, and five assimilation experiments are designed based on the Weather Research and Forecasting(WRF) model. The assimilation of radar and lightning data results in moister conditions below cloud top, where severe convection occurs;thus, wet forecasts are generated in this study.The results show that the control experiment has poor prediction accuracy. Radar data assimilation using the PI3 DVarrh method improves the location prediction of reflectivity and precipitation, especially in the last 3-h prediction, although the reflectivity and precipitation are notably overestimated. The introduction of lightning data effectively thins the radar data, reduces the overestimates in radar data assimilation, and results in better spatial pattern and intensity predictions. The predicted graupel mixing ratio is closer to the distribution of the observed lightning,which can provide more accurate lightning warning information.
