The optical potential ambiguity is a long-standing problem in the analysis of elastic scattering data.For a specific collid-ing system,ambiguous potential families can lead to different behaviors in the nearside and f...The optical potential ambiguity is a long-standing problem in the analysis of elastic scattering data.For a specific collid-ing system,ambiguous potential families can lead to different behaviors in the nearside and farside scattering components.By contrast,the envelope method can decompose the experimental data into two components with negative and positive deflection angles,respectively.Hence,a question arises as to whether the comparison between the calculated nearside(or farside)component and the derived positive-deflection-angle(or negative-deflection-angle)component can help analyze the potential ambiguity problem.In this study,we conducted a trial application of the envelope method to the potential ambiguity problem.The envelope method was improved by including uncertainties in the experimental data.The colliding systems of 16O+28Si at 215.2 MeV and 12C+12C at 1016 MeV were considered in the analyses.For each colliding system,the angular distribution experimental data were described nearly equally well by two potential sets,one of which is“surface transpar-ent”and the other is refractive.The calculated angular distributions were decomposed into nearside and farside scattering components.Using the improved envelope method,the experimental data were decomposed into the positive-deflection-angle and negative-deflection-angle components,which were then compared with the calculated nearside and farside components.The capability of the envelope method to analyze the potential ambiguities was also discussed.展开更多
The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces ...The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°,0.02°, 2 km, and 1.25 s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.展开更多
Substantially glazed facades are extensively used in contemporary high-rise buildings to achieve attractive architectural aesthetics.Inherent conflicts exist among architectural aesthetics,building energy consumption,...Substantially glazed facades are extensively used in contemporary high-rise buildings to achieve attractive architectural aesthetics.Inherent conflicts exist among architectural aesthetics,building energy consumption,and solar energy harvesting for glazed facades.In this study,we addressed these conflicts by introducing a new dynamic and vertical photovoltaic integrated building envelope(dvPVBE)that offers extraordinary flexibility with weather-responsive slat angles and blind positions,superior architectural aesthetics,and notable energy-saving potential.Three hierarchical control strategies were proposed for different scenarios of the dvPVBE:power generation priority(PGP),natural daylight priority(NDP),and energy-saving priority(ESP).Moreover,the PGP and ESP strategies were further analyzed in the simulation of a dvPVBE.An office room integrated with a dvPVBE was modeled using EnergyPlus.The influence of the dvPVBE in improving the building energy efficiency and corresponding optimal slat angles was investigated under the PGP and ESP control strategies.The results indicate that the application of dvPVBEs in Beijing can provide up to 131%of the annual energy demand of office rooms and significantly increase the annual net energy output by at least 226%compared with static photovoltaic(PV)blinds.The concept of this novel dvPVBE offers a viable approach by which the thermal load,daylight penetration,and energy generation can be effectively regulated.展开更多
BACKGROUND Occult hepatitis B infection(OBI)is characterized by the detection of hepatitis B virus(HBV)DNA in serum(usually HBV DNA<200 IU/mL)or the liver but negativity for hepatitis B surface antigen(HBsAg).The d...BACKGROUND Occult hepatitis B infection(OBI)is characterized by the detection of hepatitis B virus(HBV)DNA in serum(usually HBV DNA<200 IU/mL)or the liver but negativity for hepatitis B surface antigen(HBsAg).The diagnosis of OBI relies on the sensitivity of assays used in the detection of HBV DNA and HBsAg.HBsAg assays with inadequate sensitivity or inability to detect HBV S variants may lead to misdiagnosis of OBI in people with overt HBV infection.CASE SUMMARY We report a HBsAg-negative but hepatitis B envelope antigen-positive patient who had a significant HBV DNA level.The patient was initially diagnosed as having OBI.However,sequence analysis revealed a unique insertion of amino acid residues at positions 120-124 in the S protein,which affects the formation of a disulfide bond that is associated with the formation of a loop.It is well known that there is an overlap between the S protein and Pol protein.We found that this new insertion site occurred in polymerase/reverse transcriptase domain,indi-cating that this insertion might be involved in HBV pathogenicity.The patient was finally diagnosed with a false OBI.CONCLUSION An insertion of amino acid residues at positions 120-124 of the S protein affects the formation of immunodominant epitopes and results in negative HBsAg levels.展开更多
函数型聚类分析在统计学领域被广泛关注,其分析过程通常在降维目标实现后进行。为了有效解决函数型主成分聚类问题,文章结合局部线性嵌入算法(Locally Linear Embedding,LLE)在非线性空间下的适用性,提出了一种局部线性下的函数型主成...函数型聚类分析在统计学领域被广泛关注,其分析过程通常在降维目标实现后进行。为了有效解决函数型主成分聚类问题,文章结合局部线性嵌入算法(Locally Linear Embedding,LLE)在非线性空间下的适用性,提出了一种局部线性下的函数型主成分分析模型(LLE Function Principle Component Analysis,LFPCA)。首先,采用函数型主成分分析法作为降维目标方法,改进了FPCA的算法模型,通过将LLE算法的权重系数矩阵与函数型主成分定义相结合,构建出一个适用于非线性空间下的聚类算法;其次,在求解算法的过程中定义了函数型主成分得分,并结合EM算法构建出GMM模型来近似函数型算法的概率密度函数,使模型更高效且适用性更强;最后,通过随机模拟实验及应用分析验证了LFPCA算法模型在真实数据集上具有良好的聚类效能。展开更多
基金This work was supported by the National Natural Science Foundation of China(Nos.12005047 and U1832105).
文摘The optical potential ambiguity is a long-standing problem in the analysis of elastic scattering data.For a specific collid-ing system,ambiguous potential families can lead to different behaviors in the nearside and farside scattering components.By contrast,the envelope method can decompose the experimental data into two components with negative and positive deflection angles,respectively.Hence,a question arises as to whether the comparison between the calculated nearside(or farside)component and the derived positive-deflection-angle(or negative-deflection-angle)component can help analyze the potential ambiguity problem.In this study,we conducted a trial application of the envelope method to the potential ambiguity problem.The envelope method was improved by including uncertainties in the experimental data.The colliding systems of 16O+28Si at 215.2 MeV and 12C+12C at 1016 MeV were considered in the analyses.For each colliding system,the angular distribution experimental data were described nearly equally well by two potential sets,one of which is“surface transpar-ent”and the other is refractive.The calculated angular distributions were decomposed into nearside and farside scattering components.Using the improved envelope method,the experimental data were decomposed into the positive-deflection-angle and negative-deflection-angle components,which were then compared with the calculated nearside and farside components.The capability of the envelope method to analyze the potential ambiguities was also discussed.
基金the financial support of the National Key R&D Program of China(2021YFC3000701)the China Seismic Experimental Site in Sichuan-Yunnan(CSES-SY)for providing data for this study.
文摘The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°,0.02°, 2 km, and 1.25 s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.
基金supported by the National Natural Science Foundation of China(52078269 and 52325801).
文摘Substantially glazed facades are extensively used in contemporary high-rise buildings to achieve attractive architectural aesthetics.Inherent conflicts exist among architectural aesthetics,building energy consumption,and solar energy harvesting for glazed facades.In this study,we addressed these conflicts by introducing a new dynamic and vertical photovoltaic integrated building envelope(dvPVBE)that offers extraordinary flexibility with weather-responsive slat angles and blind positions,superior architectural aesthetics,and notable energy-saving potential.Three hierarchical control strategies were proposed for different scenarios of the dvPVBE:power generation priority(PGP),natural daylight priority(NDP),and energy-saving priority(ESP).Moreover,the PGP and ESP strategies were further analyzed in the simulation of a dvPVBE.An office room integrated with a dvPVBE was modeled using EnergyPlus.The influence of the dvPVBE in improving the building energy efficiency and corresponding optimal slat angles was investigated under the PGP and ESP control strategies.The results indicate that the application of dvPVBEs in Beijing can provide up to 131%of the annual energy demand of office rooms and significantly increase the annual net energy output by at least 226%compared with static photovoltaic(PV)blinds.The concept of this novel dvPVBE offers a viable approach by which the thermal load,daylight penetration,and energy generation can be effectively regulated.
基金Supported by the Shanghai Municipal Commission of Health and Family Planning,No.PKJ2018-Y05.
文摘BACKGROUND Occult hepatitis B infection(OBI)is characterized by the detection of hepatitis B virus(HBV)DNA in serum(usually HBV DNA<200 IU/mL)or the liver but negativity for hepatitis B surface antigen(HBsAg).The diagnosis of OBI relies on the sensitivity of assays used in the detection of HBV DNA and HBsAg.HBsAg assays with inadequate sensitivity or inability to detect HBV S variants may lead to misdiagnosis of OBI in people with overt HBV infection.CASE SUMMARY We report a HBsAg-negative but hepatitis B envelope antigen-positive patient who had a significant HBV DNA level.The patient was initially diagnosed as having OBI.However,sequence analysis revealed a unique insertion of amino acid residues at positions 120-124 in the S protein,which affects the formation of a disulfide bond that is associated with the formation of a loop.It is well known that there is an overlap between the S protein and Pol protein.We found that this new insertion site occurred in polymerase/reverse transcriptase domain,indi-cating that this insertion might be involved in HBV pathogenicity.The patient was finally diagnosed with a false OBI.CONCLUSION An insertion of amino acid residues at positions 120-124 of the S protein affects the formation of immunodominant epitopes and results in negative HBsAg levels.
文摘函数型聚类分析在统计学领域被广泛关注,其分析过程通常在降维目标实现后进行。为了有效解决函数型主成分聚类问题,文章结合局部线性嵌入算法(Locally Linear Embedding,LLE)在非线性空间下的适用性,提出了一种局部线性下的函数型主成分分析模型(LLE Function Principle Component Analysis,LFPCA)。首先,采用函数型主成分分析法作为降维目标方法,改进了FPCA的算法模型,通过将LLE算法的权重系数矩阵与函数型主成分定义相结合,构建出一个适用于非线性空间下的聚类算法;其次,在求解算法的过程中定义了函数型主成分得分,并结合EM算法构建出GMM模型来近似函数型算法的概率密度函数,使模型更高效且适用性更强;最后,通过随机模拟实验及应用分析验证了LFPCA算法模型在真实数据集上具有良好的聚类效能。
