BACKGROUND:The dynamic monitoring of immune status is crucial to the precise and individualized treatment of sepsis.In this study,we aim to introduce a model to describe and monitor the immune status of sepsis and to ...BACKGROUND:The dynamic monitoring of immune status is crucial to the precise and individualized treatment of sepsis.In this study,we aim to introduce a model to describe and monitor the immune status of sepsis and to explore its prognostic value.METHODS:A prospective observational study was carried out in Zhongshan Hospital,Fudan University,enrolling septic patients admitted between July 2016 and December 2018.Blood samples were collected at days 1 and 3.Serum cytokine levels(e.g.,tumor necrosis factor-α[TNF-α],interleukin-10[IL-10])and CD14+monocyte human leukocyte antigen-D-related(HLA-DR)expression were measured to serve as immune markers.Classifi cation of each immune status,namely systemic inflammatory response syndrome(SIRS),compensatory anti-inflammatory response syndrome(CARS),and mixed antagonistic response syndrome(MARS),was defined based on levels of immune markers.Changes of immune status were classifi ed into four groups which were stabilization(SB),deterioration(DT),remission(RM),and non-remission(NR).RESULTS:A total of 174 septic patients were enrolled including 50 non-survivors.Multivariate analysis discovered that IL-10 and HLA-DR expression levels at day 3 were independent prognostic factors.Patients with MARS had the highest mortality rate.Immune status of 46.1%patients changed from day 1 to day 3.Among four groups of immune status changes,DT had the highest mortality rate,followed by NR,RM,and SB with mortality rates of 64.7%,42.9%,and 11.2%,respectively.CONCLUSIONS:Severe immune disorder defi ned as MARS or deterioration of immune status defi ned as DT lead to the worst outcomes.The preliminary model of the classifi cation and dynamic monitoring of immune status based on immune markers has prognostic values and is worthy of further investigation.展开更多
A novel method is proposed for the supervised classification of multifrequency polarimetric synthetic aperture radar （PolSAR） images. The coherency matrices in P-, L-, and C-bands are mapped onto a 9×9 matrix ...A novel method is proposed for the supervised classification of multifrequency polarimetric synthetic aperture radar （PolSAR） images. The coherency matrices in P-, L-, and C-bands are mapped onto a 9×9 matrix Ω based on the eigenvalue decomposition of the coherency matrix of each band. A boxcar filter is then performed on the matrix Ω. The filtered data are put into a complex Wishart classifier. Finally, the effectiveness of the proposed method is demonstrated with JPL/AIRSAR multifrequency PolSAR data acquired over the Flevoland area.展开更多
网络流量识别是网络管理和安全服务的基础.随着互联网的不断扩展及其复杂性的增加,传统基于规则的识别方法或流行为特征的方法正在面临着巨大挑战.受自然语言处理(Nature Language Processing, NLP)启发,本文提出了一种多特征融合的加...网络流量识别是网络管理和安全服务的基础.随着互联网的不断扩展及其复杂性的增加,传统基于规则的识别方法或流行为特征的方法正在面临着巨大挑战.受自然语言处理(Nature Language Processing, NLP)启发,本文提出了一种多特征融合的加密流量快速分类方法 .该方法通过融合数据包和字节序列特征来完成网络流的特征表示,采用双元字节编码将所选特征扩展为双字节序列,增加了字节的上下文语义特征;通过与数据包特征处理相适应的池化方法来最大限度保留数据包的特征信息,从而使所提模型具有更强的抗噪能力和更精确的分类能力.本文方法分别在ISCX-2016和一个包含66个热门应用程序的私有数据集(ETD66)上进行验证,并与其他模型展开比较.结果表明:本文所提方法在ISCX-2016及ETD66上的测试精度和性能都明显优于其他流量分类模型,分别取得了98.2%和98.6%的识别准确率,从而证明了所提方法的特征提取能力和强泛化能力.展开更多
Paralytic shellfi sh poisoning(PSP)microalgae,as one of the harmful algal blooms,causes great damage to the of fshore fi shery,marine culture,and marine ecological environment.At present,there is no technique for real...Paralytic shellfi sh poisoning(PSP)microalgae,as one of the harmful algal blooms,causes great damage to the of fshore fi shery,marine culture,and marine ecological environment.At present,there is no technique for real-time accurate identifi cation of toxic microalgae,by combining three-dimensional fluorescence with machine learning(ML)and deep learning(DL),we developed methods to classify the PSP and non-PSP microalgae.The average classifi cation accuracies of these two methods for microalgae are above 90%,and the accuracies for discriminating 12 microalgae species in PSP and non-PSP microalgae are above 94%.When the emission wavelength is 650-690 nm,the fl uorescence characteristics bands(excitation wavelength)occur dif ferently at 410-480 nm and 500-560 nm for PSP and non-PSP microalgae,respectively.The identification accuracies of ML models(support vector machine(SVM),and k-nearest neighbor rule(k-NN)),and DL model(convolutional neural network(CNN))to PSP microalgae are 96.25%,96.36%,and 95.88%respectively,indicating that ML and DL are suitable for the classifi cation of toxic microalgae.展开更多
This study was performed to observe the effects of water on photosynthesis and water-related physiology in dominant shrubs in shell sand habitats.Four-year-old Periploca sepium seedlings were used as model species.A g...This study was performed to observe the effects of water on photosynthesis and water-related physiology in dominant shrubs in shell sand habitats.Four-year-old Periploca sepium seedlings were used as model species.A gradient of 12 water levels was established by artificially supplying the shell sand with water up to saturation and then allowing natural evapotranspiration to occur.The photo synthetic,chlorophyll fluorescence and stem sap flow parameters of P.sepium were measured under a range of water conditions.The different soil water conditions were classified according to the responses of these parameters.(1)With the increase in the relative water content(RWC)of the shell sand,the parameters of leaf photosynthesis,chlorophyll fluorescence and water-related physiology in P.sepium showed significant critical responses.The net photo synthetic rate(Pn),transpiration rate(Tr),instantaneous water use efficiency(WUE),potential water use efficiency(WUEi),maximum photochemical efficiency(Fv/Fm),actual photochemical efficiency(ΦPSII)and daily accumulation of stem sap flow all increased first and then decreased with increasing RWC,but the corresponding water conditions associated with their maximum values were not the same.An RWC of 69.40%was determined to be the optimal water condition for photosynthesis and water-related physiological activity in P.sepium.At an RWC of 36.61%,the mechanism of photosynthetic inhibition in P.sepium changed from stomatal limitation to nonstomatal limitation;this was also the minimum water requirement for maintaining normal photo synthetic processes.An RWC of 50.27%resulted in the highest WUE in P.sepium,indicating that moderate drought stress increased WUE.(2)Based on the quantitative relationship between the photo synthetic parameters of P.sepium and the shell sand water gradient,the soil water availability was classified into 6 water grades.The RWC range for maintaining strong photosynthesis and high WUE in P.sepium was 63.22-69.98%.(3)Gas exchange in P.sepium was inhibited under drought and waterlogging stresses.Under these conditions,the photosynthetic electron transport chain was blocked,and the dissipation of light energy as heat increased,which ultimately led to a decline in photo synthetic productivity;moreover,transpiration and dissipation were aggravated,and water transmission and utilization processes in P.sepium were hindered.A significant negative feedback regulation mechanism in the photosynthetic and water-related physiological processes of P.sepium was observed;this mechanism allowed P.sepium growing in shell sand to be highly adaptable to water stress.展开更多
基金the National Natural Science Foundation of China(81471840,81171837)the Shanghai Traditional Medicine Development Project(ZY3-CCCX3-3018,ZHYY-ZXYJH-201615)the Key Project of Shanghai Municipal Health Bureau(2016ZB0202).
文摘BACKGROUND:The dynamic monitoring of immune status is crucial to the precise and individualized treatment of sepsis.In this study,we aim to introduce a model to describe and monitor the immune status of sepsis and to explore its prognostic value.METHODS:A prospective observational study was carried out in Zhongshan Hospital,Fudan University,enrolling septic patients admitted between July 2016 and December 2018.Blood samples were collected at days 1 and 3.Serum cytokine levels(e.g.,tumor necrosis factor-α[TNF-α],interleukin-10[IL-10])and CD14+monocyte human leukocyte antigen-D-related(HLA-DR)expression were measured to serve as immune markers.Classifi cation of each immune status,namely systemic inflammatory response syndrome(SIRS),compensatory anti-inflammatory response syndrome(CARS),and mixed antagonistic response syndrome(MARS),was defined based on levels of immune markers.Changes of immune status were classifi ed into four groups which were stabilization(SB),deterioration(DT),remission(RM),and non-remission(NR).RESULTS:A total of 174 septic patients were enrolled including 50 non-survivors.Multivariate analysis discovered that IL-10 and HLA-DR expression levels at day 3 were independent prognostic factors.Patients with MARS had the highest mortality rate.Immune status of 46.1%patients changed from day 1 to day 3.Among four groups of immune status changes,DT had the highest mortality rate,followed by NR,RM,and SB with mortality rates of 64.7%,42.9%,and 11.2%,respectively.CONCLUSIONS:Severe immune disorder defi ned as MARS or deterioration of immune status defi ned as DT lead to the worst outcomes.The preliminary model of the classifi cation and dynamic monitoring of immune status based on immune markers has prognostic values and is worthy of further investigation.
基金supported in part by the National Natural Science Fundation of China(4117131761132008+1 种基金61490693)Aeronautical Science Foundation of China(20132058003)
文摘A novel method is proposed for the supervised classification of multifrequency polarimetric synthetic aperture radar （PolSAR） images. The coherency matrices in P-, L-, and C-bands are mapped onto a 9×9 matrix Ω based on the eigenvalue decomposition of the coherency matrix of each band. A boxcar filter is then performed on the matrix Ω. The filtered data are put into a complex Wishart classifier. Finally, the effectiveness of the proposed method is demonstrated with JPL/AIRSAR multifrequency PolSAR data acquired over the Flevoland area.
文摘网络流量识别是网络管理和安全服务的基础.随着互联网的不断扩展及其复杂性的增加,传统基于规则的识别方法或流行为特征的方法正在面临着巨大挑战.受自然语言处理(Nature Language Processing, NLP)启发,本文提出了一种多特征融合的加密流量快速分类方法 .该方法通过融合数据包和字节序列特征来完成网络流的特征表示,采用双元字节编码将所选特征扩展为双字节序列,增加了字节的上下文语义特征;通过与数据包特征处理相适应的池化方法来最大限度保留数据包的特征信息,从而使所提模型具有更强的抗噪能力和更精确的分类能力.本文方法分别在ISCX-2016和一个包含66个热门应用程序的私有数据集(ETD66)上进行验证,并与其他模型展开比较.结果表明:本文所提方法在ISCX-2016及ETD66上的测试精度和性能都明显优于其他流量分类模型,分别取得了98.2%和98.6%的识别准确率,从而证明了所提方法的特征提取能力和强泛化能力.
基金Supported by the National Natural Science Foundation of China(No.41972244)partially supported by the Science and Technology Basic Resources Survey of the Ministry of Science and Technology(No.2018FY100201)+3 种基金the National Key Research and Development Program(No.2019YFC1407900)to Siyu GOUShuai ZHANGWenyu GANand Tianjiu JIANG。
文摘Paralytic shellfi sh poisoning(PSP)microalgae,as one of the harmful algal blooms,causes great damage to the of fshore fi shery,marine culture,and marine ecological environment.At present,there is no technique for real-time accurate identifi cation of toxic microalgae,by combining three-dimensional fluorescence with machine learning(ML)and deep learning(DL),we developed methods to classify the PSP and non-PSP microalgae.The average classifi cation accuracies of these two methods for microalgae are above 90%,and the accuracies for discriminating 12 microalgae species in PSP and non-PSP microalgae are above 94%.When the emission wavelength is 650-690 nm,the fl uorescence characteristics bands(excitation wavelength)occur dif ferently at 410-480 nm and 500-560 nm for PSP and non-PSP microalgae,respectively.The identification accuracies of ML models(support vector machine(SVM),and k-nearest neighbor rule(k-NN)),and DL model(convolutional neural network(CNN))to PSP microalgae are 96.25%,96.36%,and 95.88%respectively,indicating that ML and DL are suitable for the classifi cation of toxic microalgae.
基金supported by the Forestry Science and Technology Innovation Project of Shandong Province(No.2019LY006)the National Natural Science Foundation of China(No.31770761)+1 种基金Open Research Fund Program of Shandong Key Laboratory of Eco-Environmental Science for Yellow River Delta(Binzhou University)(No.2020KFJJ03)the Taishan Scholars Program of Shandong ProvincemChina(No.TSQN201909152)。
文摘This study was performed to observe the effects of water on photosynthesis and water-related physiology in dominant shrubs in shell sand habitats.Four-year-old Periploca sepium seedlings were used as model species.A gradient of 12 water levels was established by artificially supplying the shell sand with water up to saturation and then allowing natural evapotranspiration to occur.The photo synthetic,chlorophyll fluorescence and stem sap flow parameters of P.sepium were measured under a range of water conditions.The different soil water conditions were classified according to the responses of these parameters.(1)With the increase in the relative water content(RWC)of the shell sand,the parameters of leaf photosynthesis,chlorophyll fluorescence and water-related physiology in P.sepium showed significant critical responses.The net photo synthetic rate(Pn),transpiration rate(Tr),instantaneous water use efficiency(WUE),potential water use efficiency(WUEi),maximum photochemical efficiency(Fv/Fm),actual photochemical efficiency(ΦPSII)and daily accumulation of stem sap flow all increased first and then decreased with increasing RWC,but the corresponding water conditions associated with their maximum values were not the same.An RWC of 69.40%was determined to be the optimal water condition for photosynthesis and water-related physiological activity in P.sepium.At an RWC of 36.61%,the mechanism of photosynthetic inhibition in P.sepium changed from stomatal limitation to nonstomatal limitation;this was also the minimum water requirement for maintaining normal photo synthetic processes.An RWC of 50.27%resulted in the highest WUE in P.sepium,indicating that moderate drought stress increased WUE.(2)Based on the quantitative relationship between the photo synthetic parameters of P.sepium and the shell sand water gradient,the soil water availability was classified into 6 water grades.The RWC range for maintaining strong photosynthesis and high WUE in P.sepium was 63.22-69.98%.(3)Gas exchange in P.sepium was inhibited under drought and waterlogging stresses.Under these conditions,the photosynthetic electron transport chain was blocked,and the dissipation of light energy as heat increased,which ultimately led to a decline in photo synthetic productivity;moreover,transpiration and dissipation were aggravated,and water transmission and utilization processes in P.sepium were hindered.A significant negative feedback regulation mechanism in the photosynthetic and water-related physiological processes of P.sepium was observed;this mechanism allowed P.sepium growing in shell sand to be highly adaptable to water stress.
