For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiograp...For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiographs vary with the size of fast neutron sources,the size of fiber cross-section and the imaging geometry. The results suggest that the following qualifications are helpful for a good point spread function: The cross-section of scintillating fibers not greater than 200 μm×200 μm,the size of neutron source as small as a few millimeters,the distance between the source and the scintillating fiber array greater than 1 m,and inspected samples placed as close as possible to the array. The results give suggestions not only to experiment considerations but also to the estimation of spatial resolution for a specific system.展开更多
The impacts of AMSU-A and IASI（Infrared Atmospheric Sounding Interferometer） radiances assimilation on the prediction of typhoons Vicente and Saola（2012） are studied by using the ensemble transform Kalman filter/t...The impacts of AMSU-A and IASI（Infrared Atmospheric Sounding Interferometer） radiances assimilation on the prediction of typhoons Vicente and Saola（2012） are studied by using the ensemble transform Kalman filter/three-dimensional variational（ETKF/3DVAR） Hybrid system for the Weather Research and Forecasting（WRF） model. The experiment without assimilating radiance data in 3DVAR is compared with two experiments using the 3DVAR and ETKF/3DVAR hybrid systems to assimilate AMSU-A radiance,respectively. The results show that AMSU-A radiance data have slight positive impacts on track forecasts of the 3DVAR system. When the ETKF/3DVAR hybrid system is employed, typhoon track forecast skills are greatly improved. For 36-h forecasts, the hybrid system has a lower root-mean-square error for wind and temperature at most levels, and specific humidity at low levels, compared to 3DVAR. It is also found that, on average, the use of the IASI radiance data along with AMSU-A radiance data in the hybrid system further increases the track, wind, and specific humidity forecast accuracy compared to the experiment without IASI radiance assimilation.展开更多
Background:Infectious diseases such as SARS and H1N1 can significantly impact people’s lives and cause severe social and economic damages.Recent outbreaks have stressed the urgency of effective research on the dynami...Background:Infectious diseases such as SARS and H1N1 can significantly impact people’s lives and cause severe social and economic damages.Recent outbreaks have stressed the urgency of effective research on the dynamics of infectious disease spread.However,it is difficult to predict when and where outbreaks may emerge and how infectious diseases spread because many factors affect their transmission,and some of them may be unknown.Methods:One feasible means to promptly detect an outbreak and track the progress of disease spread is to implement surveillance systems in regional or national health and medical centres.The accumulated surveillance data,including temporal,spatial,clinical,and demographic information can provide valuable information that can be exploited to better understand and model the dynamics of infectious disease spread.The aim of this work is to develop and empirically evaluate a stochastic model that allows the investigation of transmission patterns of infectious diseases in heterogeneous populations.Results:We test the proposed model on simulation data and apply it to the surveillance data from the 2009 H1N1 pandemic in Hong Kong.In the simulation experiment,our model achieves high accuracy in parameter estimation(less than 10.0%mean absolute percentage error).In terms of the forward prediction of case incidence,the mean absolute percentage errors are 17.3%for the simulation experiment and 20.0%for the experiment on the real surveillance data.Conclusion:We propose a stochastic model to study the dynamics of infectious disease spread in heterogeneous populations from temporal-spatial surveillance data.The proposed model is evaluated using both simulated data and the real data from the 2009 H1N1 epidemic in Hong Kong and achieves acceptable prediction accuracy.We believe that our model can provide valuable insights for public health authorities to predict the effect of disease spread and analyse its underlying factors and to guide new control efforts.展开更多
基金Supported by the Foundation of Double-Hundred Talents of China Academy of Engineering Physics (Grant No. 2004R0301)
文摘For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiographs vary with the size of fast neutron sources,the size of fiber cross-section and the imaging geometry. The results suggest that the following qualifications are helpful for a good point spread function: The cross-section of scintillating fibers not greater than 200 μm×200 μm,the size of neutron source as small as a few millimeters,the distance between the source and the scintillating fiber array greater than 1 m,and inspected samples placed as close as possible to the array. The results give suggestions not only to experiment considerations but also to the estimation of spatial resolution for a specific system.
基金Supported by the National(Key)Basic Research and Development(973)Program of China(2013CB430102)National Natural Science Foundation of China(41375025)Innovation Scientific Research Program for College Graduates of Jiangsu Province(CXZZ12-0490)
文摘The impacts of AMSU-A and IASI（Infrared Atmospheric Sounding Interferometer） radiances assimilation on the prediction of typhoons Vicente and Saola（2012） are studied by using the ensemble transform Kalman filter/three-dimensional variational（ETKF/3DVAR） Hybrid system for the Weather Research and Forecasting（WRF） model. The experiment without assimilating radiance data in 3DVAR is compared with two experiments using the 3DVAR and ETKF/3DVAR hybrid systems to assimilate AMSU-A radiance,respectively. The results show that AMSU-A radiance data have slight positive impacts on track forecasts of the 3DVAR system. When the ETKF/3DVAR hybrid system is employed, typhoon track forecast skills are greatly improved. For 36-h forecasts, the hybrid system has a lower root-mean-square error for wind and temperature at most levels, and specific humidity at low levels, compared to 3DVAR. It is also found that, on average, the use of the IASI radiance data along with AMSU-A radiance data in the hybrid system further increases the track, wind, and specific humidity forecast accuracy compared to the experiment without IASI radiance assimilation.
基金supported by Hong Kong Baptist University Strategic Development FundHong Kong General Research Grant HKBU12202114。
文摘Background:Infectious diseases such as SARS and H1N1 can significantly impact people’s lives and cause severe social and economic damages.Recent outbreaks have stressed the urgency of effective research on the dynamics of infectious disease spread.However,it is difficult to predict when and where outbreaks may emerge and how infectious diseases spread because many factors affect their transmission,and some of them may be unknown.Methods:One feasible means to promptly detect an outbreak and track the progress of disease spread is to implement surveillance systems in regional or national health and medical centres.The accumulated surveillance data,including temporal,spatial,clinical,and demographic information can provide valuable information that can be exploited to better understand and model the dynamics of infectious disease spread.The aim of this work is to develop and empirically evaluate a stochastic model that allows the investigation of transmission patterns of infectious diseases in heterogeneous populations.Results:We test the proposed model on simulation data and apply it to the surveillance data from the 2009 H1N1 pandemic in Hong Kong.In the simulation experiment,our model achieves high accuracy in parameter estimation(less than 10.0%mean absolute percentage error).In terms of the forward prediction of case incidence,the mean absolute percentage errors are 17.3%for the simulation experiment and 20.0%for the experiment on the real surveillance data.Conclusion:We propose a stochastic model to study the dynamics of infectious disease spread in heterogeneous populations from temporal-spatial surveillance data.The proposed model is evaluated using both simulated data and the real data from the 2009 H1N1 epidemic in Hong Kong and achieves acceptable prediction accuracy.We believe that our model can provide valuable insights for public health authorities to predict the effect of disease spread and analyse its underlying factors and to guide new control efforts.
