This paper proposes a parity recognition of blade number and manoeuvre intention classification algorithm of rotor target based on the convolutional neural network(CNN) using micro Doppler features. Firstly, the time-...This paper proposes a parity recognition of blade number and manoeuvre intention classification algorithm of rotor target based on the convolutional neural network(CNN) using micro Doppler features. Firstly, the time-frequency spectrograms are acquired from the radar echo by the short-time Fourier transform.Secondly, based on the obtained spectrograms, a seven-layer CNN architecture is built to recognize the blade-number parity and classify the manoeuvre intention of the rotor target. The constructed architecture contains a leaky rectified linear unit and a dropout layer to accelerate the convergence of the architecture and avoid over-fitting. Finally, the spectrograms of the datasets are divided into three different ratios, i.e., 20%, 33% and 50%,and the cross validation is used to verify the effectiveness of the constructed CNN architecture. Simulation results show that, on the one hand, as the ratio of training data increases, the recognition accuracy of parity and manoeuvre intention is improved at the same signal-to-noise ratio(SNR);on the other hand, the proposed algorithm also has a strong robustness: the accuracy can still reach 90.72% with an SNR of – 6 dB.展开更多
Background:With the popularization of lung cancer screening,more early-stage lung cancers are being detected.This study aims to compare three types of N classifications,including location-based N classification(pathol...Background:With the popularization of lung cancer screening,more early-stage lung cancers are being detected.This study aims to compare three types of N classifications,including location-based N classification(pathologic nodal classification[pN]),the number of lymph node stations(nS)-based N classification(nS classification),and the combined approach proposed by the International Association for the Study of Lung Cancer(IASLC)which incorporates both pN and nS classification to determine if the nS classification is more appropriate for early-stage lung cancer.Methods:We retrospectively reviewed the clinical data of lung cancer patients treated at the Cancer Hospital,Chinese Academy of Medical Sciences between 2005 and 2018.Inclusion criteria was clinical stage IA lung adenocarcinoma patients who underwent resection during this period.Sub-analyses were performed for the three types of N classifications.The optimal cutoffvalues for nS classification were determined with X-tile software.Kaplan‒Meier and multivariate Cox analyses were performed to assess the prognostic significance of the different N classifications.The prediction performance among the three types of N classifications was compared using the concordance index(C-index)and decision curve analysis(DCA).Results:Of the 669 patients evaluated,534 had pathological stage N0 disease(79.8%),82 had N1 disease(12.3%)and 53 had N2 disease(7.9%).Multivariate Cox analysis indicated that all three types of N classifications were independent prognostic factors for prognosis(all P<0.001).However,the prognosis overlaps between pN(N1 and N2,P=0.052)and IASLC-proposed N classification(N1b and N2a1[P=0.407],N2a1 and N2a2[P=0.364],and N2a2 and N2b[P=0.779]),except for nS classification subgroups(nS0 and nS1[P<0.001]and nS1 and nS>1[P=0.006]).There was no significant difference in the C-index values between the three N classifications(P=0.370).The DCA results demonstrated that the nS classification provided greater clinical utility.Conclusion:The nS classification might be a better choice for nodal classification in clinical stage IA lung adeno-carcinoma.展开更多
Using the fuzzy cluster analysis and the temperature-salinity(T-S) similarity number analysis of cruise conductivity-temperature-depth(CTD) data in the upper layer(0–300 m) of the northern South China Sea(NSCS), we c...Using the fuzzy cluster analysis and the temperature-salinity(T-S) similarity number analysis of cruise conductivity-temperature-depth(CTD) data in the upper layer(0–300 m) of the northern South China Sea(NSCS), we classify the upper layer water of the NSCS into six water masses: diluted water(D), surface water(SS),the SCS subsurface water mass(U_S), the Pacific Ocean subsurface water mass(U_P), surface-subsurface mixed water(SU) and subsurface-intermediate mixed water(UI). A new stacked stereogram is used to illustrate the water mass distribution, and to examine the source and the distribution of U_P, combining with the sea surface height data and geostrophic current field. The results show that water mass U_P exists in all four seasons with the maximum range in spring and the minimum range in summer. In spring and winter, the U_P intrudes into the Luzon Strait and the southwest of Taiwan Island via the northern Luzon Strait in the form of nonlinear Rossby eddies, and forms a high temperature and high salinity zone east of the Dongsha Islands. In summer, the U_P is sporadically distributed in the study area. In autumn, the U_P is located in the upper 200 m layer east of Hainan Island.展开更多
Natural products(NPs) are compounds that are derived from natural sources such as plants, animals, and microisms. Therapeutics has benefited from numerous drug classes derived from natural product sources. The Biophar...Natural products(NPs) are compounds that are derived from natural sources such as plants, animals, and microisms. Therapeutics has benefited from numerous drug classes derived from natural product sources. The Biopharmaceutics Drug position Classification System(BDDCS) was proposed to serve as a basis for predicting the importance of transporters and enzymes in determining drug bioavailability and disposition. It categorizes drugs into one of four biopharmaceutical classes according to their water solubility and extent of metabolism. The present paper reviews 109 drugs from natural product sources: 29% belong to class 1(high solubility, extensive metabolism), 22% to class 2(low solubility, extensive metabolism), 40% to class 3(high solubility, poor metabolism), and 9% to class 4(low solubility, poor metabolism). Herein we evaluated the characteristics of NPs in terms of BDDCS class for all 109 drugs as wells as for subsets of NPs drugs derived from plant sources as antibiotics. In the 109 NPs drugs, we piled 32 drugs from plants, 50%(16) of total in class 1, 22%(7) in class 2 and 28%(9) in class 3, none found in class 4; Meantime, the antibiotics were found 5(16%) in class 2, 22(71%) in class 3, and 4(13%) in class 4; no drug was found in class 1. Based on this classification, we anticipate BDDCS to serve as a useful adjunct in evaluating the potential characteristics of new natural products.展开更多
With the rapid development of intelligent traffic information monitoring technology,accurate identification of vehicles,pedestrians and other objects on the road has become particularly important.Therefore,in order to...With the rapid development of intelligent traffic information monitoring technology,accurate identification of vehicles,pedestrians and other objects on the road has become particularly important.Therefore,in order to improve the recognition and classification accuracy of image objects in complex traffic scenes,this paper proposes a segmentation method of semantic redefine segmentation using image boundary region.First,we use the Seg Net semantic segmentation model to obtain the rough classification features of the vehicle road object,then use the simple linear iterative clustering(SLIC)algorithm to obtain the over segmented area of the image,which can determine the classification of each pixel in each super pixel area,and then optimize the target segmentation of the boundary and small areas in the vehicle road image.Finally,the edge recovery ability of condition random field(CRF)is used to refine the image boundary.The experimental results show that compared with FCN-8s and Seg Net,the pixel accuracy of the proposed algorithm in this paper improves by 2.33%and 0.57%,respectively.And compared with Unet,the algorithm in this paper performs better when dealing with multi-target segmentation.展开更多
The authors provided a simple method for calculating Wiener numbers of molecular graphs with symmetry in 1997.This paper intends to further improve on it and simplifies the calculation of the Wiener numbers of the mol...The authors provided a simple method for calculating Wiener numbers of molecular graphs with symmetry in 1997.This paper intends to further improve on it and simplifies the calculation of the Wiener numbers of the molecular graphs.展开更多
We introduce the triple crossing number, a variation of the crossing number, of a graph, which is the minimal number of crossing points in all drawings of the graph with only triple crossings. It is defined to be zero...We introduce the triple crossing number, a variation of the crossing number, of a graph, which is the minimal number of crossing points in all drawings of the graph with only triple crossings. It is defined to be zero for planar graphs, and to be infinite for non-planar graphs which do not admit a drawing with only triple crossings. In this paper, we determine the triple crossing numbers for all complete multipartite graphs which include all complete graphs.展开更多
ABSTRACT． Led。 be the n^(th) Lucas number， n＞0． Let p be an odd prime． In this paperwe prove a general theorem． According to the theorem we give an algorithm by using whichthe equationl-(n)＝px^(2) can be ...ABSTRACT． Led。 be the n^(th) Lucas number， n＞0． Let p be an odd prime． In this paperwe prove a general theorem． According to the theorem we give an algorithm by using whichthe equationl-(n)＝px^(2) can be solved for arbitrary given p．Por example，we find its all solutionsfor 1000＜p＜40000． By the end of the paper an Interestingconjecture Is presented．展开更多
粮食的霉变严重影响其品质与食品安全,而常规检测手段存在速度慢以及需要大量专业实验室设备和操作人员等缺陷,近红外光谱分析技术具有分析速度快、非破坏性、测试重现性好、易于实现在线分析和操作简单等诸多优点,是一种很有潜力的快...粮食的霉变严重影响其品质与食品安全,而常规检测手段存在速度慢以及需要大量专业实验室设备和操作人员等缺陷,近红外光谱分析技术具有分析速度快、非破坏性、测试重现性好、易于实现在线分析和操作简单等诸多优点,是一种很有潜力的快速检测方法。该研究基于近红外光谱分析技术建立了霉情检测模型,对不同霉变程度稻谷进行近红外光谱的快速识别预测研究,旨在开发一种可以快速鉴别霉变稻谷定性、定量模型。研究对4种(2018年牡丹江27号、2019年牡丹江27号、龙粳长粒香和牡响1号)不同霉变程度共960组霉变稻谷样品进行定性判别模型研究,其中一阶导数+9点平滑+因子化法建立的定性判别模型准确度较高,样品之间的距离S均值大于1,分辨效果好,通过留一交互验证验证模型的平均准确率为93.00%;基于近红外光谱对4种不同霉变程度共300组霉变稻谷样品进行霉菌菌落总数的定量模型研究,通过矢量归一化法+偏最小二乘法(partial least squares,PLS)定量分析建立定量判别模型,其交叉验证的均方根误差(root mean square error of cross-validation,RMSECV)、决定系数(corrlation coefficient of determination,R^(2))、性能与偏差之比(ratio of performance to deviation,RPD)和预测均方根误差(root mean squared error of predicition,RMSEP)分别为0.470、0.904 5、3.24和0.45,模型精确度较好的。经过分析方法优选后而建立的霉变判别模型显示,霉变是影响近红外光谱变化的主导因素,而稻谷的品种与年际对其影响较小。研究结果可为基于近红外光谱分析技术对不同运输过程中的稻谷实现快速预测其霉变程度或其霉菌数量以及用于集装箱内粮食霉变情况监控在线实时监测装备的研究提供参考。展开更多
基金supported by the National Natural Science Foundation of China (61901514)the Young Talent Program of Air Force Early Warning Academy (TJRC425311G11)。
文摘This paper proposes a parity recognition of blade number and manoeuvre intention classification algorithm of rotor target based on the convolutional neural network(CNN) using micro Doppler features. Firstly, the time-frequency spectrograms are acquired from the radar echo by the short-time Fourier transform.Secondly, based on the obtained spectrograms, a seven-layer CNN architecture is built to recognize the blade-number parity and classify the manoeuvre intention of the rotor target. The constructed architecture contains a leaky rectified linear unit and a dropout layer to accelerate the convergence of the architecture and avoid over-fitting. Finally, the spectrograms of the datasets are divided into three different ratios, i.e., 20%, 33% and 50%,and the cross validation is used to verify the effectiveness of the constructed CNN architecture. Simulation results show that, on the one hand, as the ratio of training data increases, the recognition accuracy of parity and manoeuvre intention is improved at the same signal-to-noise ratio(SNR);on the other hand, the proposed algorithm also has a strong robustness: the accuracy can still reach 90.72% with an SNR of – 6 dB.
基金supported by CAMS Innovation Fund for Med-ical Sciences(grant number:2021-I2M-C&T-B-061)Beijing Hope Run Special Fund of Cancer Foundation of China(grant number:LC2022A22)+1 种基金Beijing Municipal Natural Science Foundation(grant num-ber:7184238)National Natural Science Foundation of China(grant number:81701692).
文摘Background:With the popularization of lung cancer screening,more early-stage lung cancers are being detected.This study aims to compare three types of N classifications,including location-based N classification(pathologic nodal classification[pN]),the number of lymph node stations(nS)-based N classification(nS classification),and the combined approach proposed by the International Association for the Study of Lung Cancer(IASLC)which incorporates both pN and nS classification to determine if the nS classification is more appropriate for early-stage lung cancer.Methods:We retrospectively reviewed the clinical data of lung cancer patients treated at the Cancer Hospital,Chinese Academy of Medical Sciences between 2005 and 2018.Inclusion criteria was clinical stage IA lung adenocarcinoma patients who underwent resection during this period.Sub-analyses were performed for the three types of N classifications.The optimal cutoffvalues for nS classification were determined with X-tile software.Kaplan‒Meier and multivariate Cox analyses were performed to assess the prognostic significance of the different N classifications.The prediction performance among the three types of N classifications was compared using the concordance index(C-index)and decision curve analysis(DCA).Results:Of the 669 patients evaluated,534 had pathological stage N0 disease(79.8%),82 had N1 disease(12.3%)and 53 had N2 disease(7.9%).Multivariate Cox analysis indicated that all three types of N classifications were independent prognostic factors for prognosis(all P<0.001).However,the prognosis overlaps between pN(N1 and N2,P=0.052)and IASLC-proposed N classification(N1b and N2a1[P=0.407],N2a1 and N2a2[P=0.364],and N2a2 and N2b[P=0.779]),except for nS classification subgroups(nS0 and nS1[P<0.001]and nS1 and nS>1[P=0.006]).There was no significant difference in the C-index values between the three N classifications(P=0.370).The DCA results demonstrated that the nS classification provided greater clinical utility.Conclusion:The nS classification might be a better choice for nodal classification in clinical stage IA lung adeno-carcinoma.
基金The National Natural Science Foundation of China under contract No.41776027the National Basic Research Program of China under contract Nos 2015CB954004 and 2009CB421208the Open Fund of the Key Laboratory of Ocean Circulation and Waves,Chinese Academy of Sciences under contract No.KLOCW1808
文摘Using the fuzzy cluster analysis and the temperature-salinity(T-S) similarity number analysis of cruise conductivity-temperature-depth(CTD) data in the upper layer(0–300 m) of the northern South China Sea(NSCS), we classify the upper layer water of the NSCS into six water masses: diluted water(D), surface water(SS),the SCS subsurface water mass(U_S), the Pacific Ocean subsurface water mass(U_P), surface-subsurface mixed water(SU) and subsurface-intermediate mixed water(UI). A new stacked stereogram is used to illustrate the water mass distribution, and to examine the source and the distribution of U_P, combining with the sea surface height data and geostrophic current field. The results show that water mass U_P exists in all four seasons with the maximum range in spring and the minimum range in summer. In spring and winter, the U_P intrudes into the Luzon Strait and the southwest of Taiwan Island via the northern Luzon Strait in the form of nonlinear Rossby eddies, and forms a high temperature and high salinity zone east of the Dongsha Islands. In summer, the U_P is sporadically distributed in the study area. In autumn, the U_P is located in the upper 200 m layer east of Hainan Island.
基金supported by China Scholarship Council(No.201208320187CSC)
文摘Natural products(NPs) are compounds that are derived from natural sources such as plants, animals, and microisms. Therapeutics has benefited from numerous drug classes derived from natural product sources. The Biopharmaceutics Drug position Classification System(BDDCS) was proposed to serve as a basis for predicting the importance of transporters and enzymes in determining drug bioavailability and disposition. It categorizes drugs into one of four biopharmaceutical classes according to their water solubility and extent of metabolism. The present paper reviews 109 drugs from natural product sources: 29% belong to class 1(high solubility, extensive metabolism), 22% to class 2(low solubility, extensive metabolism), 40% to class 3(high solubility, poor metabolism), and 9% to class 4(low solubility, poor metabolism). Herein we evaluated the characteristics of NPs in terms of BDDCS class for all 109 drugs as wells as for subsets of NPs drugs derived from plant sources as antibiotics. In the 109 NPs drugs, we piled 32 drugs from plants, 50%(16) of total in class 1, 22%(7) in class 2 and 28%(9) in class 3, none found in class 4; Meantime, the antibiotics were found 5(16%) in class 2, 22(71%) in class 3, and 4(13%) in class 4; no drug was found in class 1. Based on this classification, we anticipate BDDCS to serve as a useful adjunct in evaluating the potential characteristics of new natural products.
基金Supported in part by the Shaanxi Natural Science Basic Research Program(2022JM-298)the National Natural Science Foundation of China(52172324)+1 种基金Shaanxi Provincial Key Research and Development Program(2021SF-483)the Science and Technology Project of Shaan Provincal Transportation Department(21-202K,20-38T)。
文摘With the rapid development of intelligent traffic information monitoring technology,accurate identification of vehicles,pedestrians and other objects on the road has become particularly important.Therefore,in order to improve the recognition and classification accuracy of image objects in complex traffic scenes,this paper proposes a segmentation method of semantic redefine segmentation using image boundary region.First,we use the Seg Net semantic segmentation model to obtain the rough classification features of the vehicle road object,then use the simple linear iterative clustering(SLIC)algorithm to obtain the over segmented area of the image,which can determine the classification of each pixel in each super pixel area,and then optimize the target segmentation of the boundary and small areas in the vehicle road image.Finally,the edge recovery ability of condition random field(CRF)is used to refine the image boundary.The experimental results show that compared with FCN-8s and Seg Net,the pixel accuracy of the proposed algorithm in this paper improves by 2.33%and 0.57%,respectively.And compared with Unet,the algorithm in this paper performs better when dealing with multi-target segmentation.
文摘The authors provided a simple method for calculating Wiener numbers of molecular graphs with symmetry in 1997.This paper intends to further improve on it and simplifies the calculation of the Wiener numbers of the molecular graphs.
文摘We introduce the triple crossing number, a variation of the crossing number, of a graph, which is the minimal number of crossing points in all drawings of the graph with only triple crossings. It is defined to be zero for planar graphs, and to be infinite for non-planar graphs which do not admit a drawing with only triple crossings. In this paper, we determine the triple crossing numbers for all complete multipartite graphs which include all complete graphs.
文摘ABSTRACT． Led。 be the n^(th) Lucas number， n＞0． Let p be an odd prime． In this paperwe prove a general theorem． According to the theorem we give an algorithm by using whichthe equationl-(n)＝px^(2) can be solved for arbitrary given p．Por example，we find its all solutionsfor 1000＜p＜40000． By the end of the paper an Interestingconjecture Is presented．
文摘粮食的霉变严重影响其品质与食品安全,而常规检测手段存在速度慢以及需要大量专业实验室设备和操作人员等缺陷,近红外光谱分析技术具有分析速度快、非破坏性、测试重现性好、易于实现在线分析和操作简单等诸多优点,是一种很有潜力的快速检测方法。该研究基于近红外光谱分析技术建立了霉情检测模型,对不同霉变程度稻谷进行近红外光谱的快速识别预测研究,旨在开发一种可以快速鉴别霉变稻谷定性、定量模型。研究对4种(2018年牡丹江27号、2019年牡丹江27号、龙粳长粒香和牡响1号)不同霉变程度共960组霉变稻谷样品进行定性判别模型研究,其中一阶导数+9点平滑+因子化法建立的定性判别模型准确度较高,样品之间的距离S均值大于1,分辨效果好,通过留一交互验证验证模型的平均准确率为93.00%;基于近红外光谱对4种不同霉变程度共300组霉变稻谷样品进行霉菌菌落总数的定量模型研究,通过矢量归一化法+偏最小二乘法(partial least squares,PLS)定量分析建立定量判别模型,其交叉验证的均方根误差(root mean square error of cross-validation,RMSECV)、决定系数(corrlation coefficient of determination,R^(2))、性能与偏差之比(ratio of performance to deviation,RPD)和预测均方根误差(root mean squared error of predicition,RMSEP)分别为0.470、0.904 5、3.24和0.45,模型精确度较好的。经过分析方法优选后而建立的霉变判别模型显示,霉变是影响近红外光谱变化的主导因素,而稻谷的品种与年际对其影响较小。研究结果可为基于近红外光谱分析技术对不同运输过程中的稻谷实现快速预测其霉变程度或其霉菌数量以及用于集装箱内粮食霉变情况监控在线实时监测装备的研究提供参考。
