We propose a method to determine the optimal power of the microwave resonance transition that simultaneously improves the signal-to-noise ratio and reduces line width based on saturation broadening theory and experime...We propose a method to determine the optimal power of the microwave resonance transition that simultaneously improves the signal-to-noise ratio and reduces line width based on saturation broadening theory and experiment. Saturation broadening spectra of the ground state hyperfine transition of trapped 199Hg＋ ions are measured and analyzed. The value of the optimal microwave power is obtained by using the proposed method and is verified. Rabi oscillations decay spectra of trapped 199Hg＋ ions are observed and the optimal microwave irradiation time for the maximum transition signal intensity is determined. This work will help to improve the short-term frequency stability of the mercury ion microwave frequency standard.展开更多
The China Infectious Disease Automated-alert and Response System（CIDARS） was successfully implemented and became operational nationwide in 2008. The CIDARS plays an important role in and has been integrated into the...The China Infectious Disease Automated-alert and Response System（CIDARS） was successfully implemented and became operational nationwide in 2008. The CIDARS plays an important role in and has been integrated into the routine outbreak monitoring efforts of the Center for Disease Control（CDC） at all levels in China. In the CIDARS, thresholds are determined using the ？Mean＋2SD？ in the early stage which have limitations. This study compared the performance of optimized thresholds defined using the ？Mean ＋2SD？ method to the performance of 5 novel algorithms to select optimal ？Outbreak Gold Standard（OGS）？ and corresponding thresholds for outbreak detection. Data for infectious disease were organized by calendar week and year. The ？Mean＋2 SD？, C1, C2, moving average（MA）, seasonal model（SM）, and cumulative sum（CUSUM） algorithms were applied. Outbreak signals for the predicted value（Px） were calculated using a percentile-based moving window. When the outbreak signals generated by an algorithm were in line with a Px generated outbreak signal for each week, this Px was then defined as the optimized threshold for that algorithm. In this study, six infectious diseases were selected and classified into TYPE A（chickenpox and mumps）, TYPE B（influenza and rubella） and TYPE C [hand foot and mouth disease（HFMD） and scarlet fever]. Optimized thresholds for chickenpox（P_（55））, mumps（P_（50））, influenza（P_（40）, P_（55）, and P_（75））, rubella（P_（45） and P_（75））, HFMD（P_（65） and P_（70））, and scarlet fever（P_（75） and P_（80）） were identified. The C1, C2, CUSUM, SM, and MA algorithms were appropriate for TYPE A. All 6 algorithms were appropriate for TYPE B. C1 and CUSUM algorithms were appropriate for TYPE C. It is critical to incorporate more flexible algorithms as OGS into the CIDRAS and to identify the proper OGS and corresponding recommended optimized threshold by different infectious disease types.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 11074282 and 11474320
文摘We propose a method to determine the optimal power of the microwave resonance transition that simultaneously improves the signal-to-noise ratio and reduces line width based on saturation broadening theory and experiment. Saturation broadening spectra of the ground state hyperfine transition of trapped 199Hg＋ ions are measured and analyzed. The value of the optimal microwave power is obtained by using the proposed method and is verified. Rabi oscillations decay spectra of trapped 199Hg＋ ions are observed and the optimal microwave irradiation time for the maximum transition signal intensity is determined. This work will help to improve the short-term frequency stability of the mercury ion microwave frequency standard.
基金supported by the Key Laboratory of Public Health Safety of the Ministry of Education,Fudan University,China(No.GW2015-1)
文摘The China Infectious Disease Automated-alert and Response System（CIDARS） was successfully implemented and became operational nationwide in 2008. The CIDARS plays an important role in and has been integrated into the routine outbreak monitoring efforts of the Center for Disease Control（CDC） at all levels in China. In the CIDARS, thresholds are determined using the ？Mean＋2SD？ in the early stage which have limitations. This study compared the performance of optimized thresholds defined using the ？Mean ＋2SD？ method to the performance of 5 novel algorithms to select optimal ？Outbreak Gold Standard（OGS）？ and corresponding thresholds for outbreak detection. Data for infectious disease were organized by calendar week and year. The ？Mean＋2 SD？, C1, C2, moving average（MA）, seasonal model（SM）, and cumulative sum（CUSUM） algorithms were applied. Outbreak signals for the predicted value（Px） were calculated using a percentile-based moving window. When the outbreak signals generated by an algorithm were in line with a Px generated outbreak signal for each week, this Px was then defined as the optimized threshold for that algorithm. In this study, six infectious diseases were selected and classified into TYPE A（chickenpox and mumps）, TYPE B（influenza and rubella） and TYPE C [hand foot and mouth disease（HFMD） and scarlet fever]. Optimized thresholds for chickenpox（P_（55））, mumps（P_（50））, influenza（P_（40）, P_（55）, and P_（75））, rubella（P_（45） and P_（75））, HFMD（P_（65） and P_（70））, and scarlet fever（P_（75） and P_（80）） were identified. The C1, C2, CUSUM, SM, and MA algorithms were appropriate for TYPE A. All 6 algorithms were appropriate for TYPE B. C1 and CUSUM algorithms were appropriate for TYPE C. It is critical to incorporate more flexible algorithms as OGS into the CIDRAS and to identify the proper OGS and corresponding recommended optimized threshold by different infectious disease types.
