As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decompos...As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system.展开更多
The volatile chemical components of Radix Paeoniae Rubra (RPR) were analyzed by gas chromatography-mass spectrometry with the method of heuristic evolving latent projections and overall volume integration. The results...The volatile chemical components of Radix Paeoniae Rubra (RPR) were analyzed by gas chromatography-mass spectrometry with the method of heuristic evolving latent projections and overall volume integration. The results show that 38 volatile chemical components of RPR are determined, accounting for 95.21% of total contents of volatile chemical components of RPR. The main volatile chemical components of RPR are (Z, Z)-9,12-octadecadienoic acid, n-hexadecanoic acid, 2-hydroxy- benzaldehyde, 1-(2-hydroxy-4-methoxyphenyl)-ethanone, 6,6-dimethyl-bicyclo[3.1.1] heptane-2-methanol, 4,7-dimethyl-benzofuran, 4-(1-methylethenyl)-1-cyclohexene-1-carboxaldehyde, and cyclohexadecane.展开更多
Chromatography-mass spectrometry(GC-MS)was used to analyze the volatile components of cut tobacco samples with the help of heuristic evolving latent projections(HELP).After extracting with simultaneous distillation an...Chromatography-mass spectrometry(GC-MS)was used to analyze the volatile components of cut tobacco samples with the help of heuristic evolving latent projections(HELP).After extracting with simultaneous distillation and extraction method,the volatile components in cut tobacco were detected by GC-MS.Then the obtained original two-dimensional data were resolved into pure mass spectra and chromatograms.The qualitative analysis was performed by similarity searches in the national institute of standards and technology(NIST)mass database with the obtained pure mass spectrum of each component and the quantitative results were obtained by calculating the volume of total two-way response.The accuracy of qualitative and quantitative results were greatly improved by using the two-dimensional comprehensive information of chromatograms and mass spectra.107 of 141 separated constituents in the total ion chromatogram of the volatile components were identified and quantified,accounting for about 88.01% of the total content.The result proves that the developed method is powerful for the analysis of complex cut tobacco samples.展开更多
Thermal energy storage(TES)is a key technology for renewable energy utilization and the improvement of the energy efficiency of heat processes.Sectors include industrial process heat and conventional and renewable pow...Thermal energy storage(TES)is a key technology for renewable energy utilization and the improvement of the energy efficiency of heat processes.Sectors include industrial process heat and conventional and renewable power generation.TES systems correct the mismatch between supply and demand of thermal energy.In the medium to high temperature range(100~1000℃),only limited storage technology is commercially available and a strong effort is needed to develop a range of storage technologies which are efficient and economical for the very specific requirements of the different application sectors.At the DLR's Institute of Technical Thermodynamics,the complete spectrum of high temperature storage technologies,from various types of sensible over latent heat to thermochemical heat storages are being developed.Different concepts are proposed depending on the heat transfer fluid(synthetic oil,water/steam,molten salt,air)and the required temperature range.The aim is the development of cost effective,efficient and reliable thermal storage systems.Research focuses on characterization of storage materials,enhancement of internal heat transfer,design of innovative storage concepts and modelling of storage components and systems.Demonstration of the storage technology takes place from laboratory scale to field testing(5 kW^1 MW).The paper gives an overview on DLR's current developments.展开更多
A class of latent ancestral graph for modelling the dependence structure of structural vector autoregressive （VAR） model affected by latent variables is proposed. The graphs are mixed graphs with possibly two kind o...A class of latent ancestral graph for modelling the dependence structure of structural vector autoregressive （VAR） model affected by latent variables is proposed. The graphs are mixed graphs with possibly two kind of edges, namely directed and bidirected edges. The vertex set denotes random variables at dif- ferent times. In Gaussian case, the latent ancestral graph leads to a simple parameterization model. A modified iterative conditional fitting algorithm is presented to obtain maximum likelihood esti- mation of the parameters. Furthermore, a log-likelihood criterion is used to select the most appropriate models. Simulations are performed using illustrative examples and results are provided to demonstrate the validity of the methods.展开更多
The latent membrane protein(LMP1)encoded by EBV is expressed in the majority of EBV-associated human malignancies,suggesting it is one of the major oncogenic factors in EBV-mediated carcinogenesis.In the previous stud...The latent membrane protein(LMP1)encoded by EBV is expressed in the majority of EBV-associated human malignancies,suggesting it is one of the major oncogenic factors in EBV-mediated carcinogenesis.In the previous studies we experimentally demonstrated that the DNAzymes targeting LMP1 could specifically down-regulate the expression of LMP1,leading to an increased radiosensitivity both in cells and in展开更多
Multi-label classification problems arise frequently in text categorization, and many other related applications. Like conventional categorization problems, multi-label categorization tasks suffer from the curse of hi...Multi-label classification problems arise frequently in text categorization, and many other related applications. Like conventional categorization problems, multi-label categorization tasks suffer from the curse of high dimensionality. Existing multi-label dimensionality reduction methods mainly suffer from two limitations. First, latent nonlinear structures are not utilized in the input space. Second, the label information is not fully exploited. This paper proposes a new method, multi-label local discriminative embedding (MLDE), which exploits latent structures to minimize intraclass distances and maximize interclass distances on the basis of label correlations. The latent structures are extracted by constructing two sets of adjacency graphs to make use of nonlinear information. Non-symmetric label correlations, which are the case in real applications, are adopted. The problem is formulated into a global objective function and a linear mapping is achieved to solve out-of-sample problems. Empirical studies across 11 Yahoo sub-tasks, Enron and Bibtex are conducted to validate the superiority of MLDE to state-of-art multi-label dimensionality reduction methods.展开更多
Three pairs of primers were designed and synthesized from nucleotide sequences of garlic latent virus （GLV）, onion yellow dwarf virus （OYDV）, and leek yellow stripe virus （LYSV） by using PCR primer design softwa...Three pairs of primers were designed and synthesized from nucleotide sequences of garlic latent virus （GLV）, onion yellow dwarf virus （OYDV）, and leek yellow stripe virus （LYSV） by using PCR primer design software. The expected fragments about 170 bp, 287 bp, and 191 bp were amplified by RT-PCR for GLV, OYDV, and LYSV, respectively in disease-infected plants of potato onion （Allium cepa L., Aggregatum group）, but such fragments were not obtained from healthy-looking plants and virus-free seedlings of shoot-tips. The amplified products ofGLV, OYDV and LYSV were cloned into pGEM-T vectors, and transformed into Escherichia coli. JM109. The recombinant plasmids were obtained and sequenced. The nucleotide sequences were compared with corresponding viral nucleotide sequences reported in GenBank by performing a NCBI BLAST. The analysis showed that their homology attained 75% to 90%,89.5% to 96.1%,and 91.6% to 96.3% in GLV, OYDV, and LYSV, respectively. The total RNA of 6.34 ug·uL^-1 from infected plants was diluted to a series of 10^-1 to 10^5 and the detection sensitivity of RT-PCR was 10^4 （about 4 ng）. Thus, a method of identification and detection by RT-PCR of GLV, OYDV, and SLYV was established.展开更多
目的探讨orthogonal projection to latent structures(OPLS)方法的原理、特点及其在代谢组学高维数据分析中的应用。方法通过R语言编程实现OPLS方法,利用模拟试验探索OPLS的特性及适用条件,并通过实际数据进行验证。结果利用一个OPLS...目的探讨orthogonal projection to latent structures(OPLS)方法的原理、特点及其在代谢组学高维数据分析中的应用。方法通过R语言编程实现OPLS方法,利用模拟试验探索OPLS的特性及适用条件,并通过实际数据进行验证。结果利用一个OPLS预测主成分的模型拟合效果与利用偏最小二乘(PLS)多个主成分的模型拟合效果相同,同时具有较好的判别能力,其得分图的可视化效果优于PLS。结论 OPLS能够有效去除自变量矩阵X中与因变量Y无关的信息,使模型变得简单、易于解释,同时具有较好的可视化效果,可有效地用于代谢组学数据分析中。展开更多
基于统计机器翻译模型的问句检索模型,其相关性排序机制主要依赖于词项间的翻译概率,然而已有的模型没有很好地控制翻译模型的噪声,使得当前的问句检索模型存在不完善之处.文中提出一种基于主题翻译模型的问句检索模型,从理论上说明,该...基于统计机器翻译模型的问句检索模型,其相关性排序机制主要依赖于词项间的翻译概率,然而已有的模型没有很好地控制翻译模型的噪声,使得当前的问句检索模型存在不完善之处.文中提出一种基于主题翻译模型的问句检索模型,从理论上说明,该模型利用主题信息对翻译进行合理的约束,达到控制翻译模型噪声的效果,从而提高问句检索的结果.实验结果表明,文中提出的模型在MAP(Mean Average Precision)、MRR(Mean Reciprocal Rank)以及p@1(precision at position one)等指标上显著优于当前最先进的问句检索模型.展开更多
基金supported by the National Natural Science Foundation of China(62273354,61673387,61833016).
文摘As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system.
基金Project(20235020) supported by the National Natural Science Foundation of China
文摘The volatile chemical components of Radix Paeoniae Rubra (RPR) were analyzed by gas chromatography-mass spectrometry with the method of heuristic evolving latent projections and overall volume integration. The results show that 38 volatile chemical components of RPR are determined, accounting for 95.21% of total contents of volatile chemical components of RPR. The main volatile chemical components of RPR are (Z, Z)-9,12-octadecadienoic acid, n-hexadecanoic acid, 2-hydroxy- benzaldehyde, 1-(2-hydroxy-4-methoxyphenyl)-ethanone, 6,6-dimethyl-bicyclo[3.1.1] heptane-2-methanol, 4,7-dimethyl-benzofuran, 4-(1-methylethenyl)-1-cyclohexene-1-carboxaldehyde, and cyclohexadecane.
基金Project supported by the Postdoctoral Foundation of Changde Cigarette FactoryProject(20060400887) supported by China Postdoctoral Science Foundation
文摘Chromatography-mass spectrometry(GC-MS)was used to analyze the volatile components of cut tobacco samples with the help of heuristic evolving latent projections(HELP).After extracting with simultaneous distillation and extraction method,the volatile components in cut tobacco were detected by GC-MS.Then the obtained original two-dimensional data were resolved into pure mass spectra and chromatograms.The qualitative analysis was performed by similarity searches in the national institute of standards and technology(NIST)mass database with the obtained pure mass spectrum of each component and the quantitative results were obtained by calculating the volume of total two-way response.The accuracy of qualitative and quantitative results were greatly improved by using the two-dimensional comprehensive information of chromatograms and mass spectra.107 of 141 separated constituents in the total ion chromatogram of the volatile components were identified and quantified,accounting for about 88.01% of the total content.The result proves that the developed method is powerful for the analysis of complex cut tobacco samples.
基金funded through the basic DLR funding of the Helmholtz AssociationSpecific support for several projects was given by the German Federal Ministry of Economics and Technology and the German Federal Ministry for the Environment,Nature Conservation and Nuclear SafetyThe CellFlux project is funded by E.ON AG as part of the International Research Initiative.Responsibility for the content of this publication lieswith the authors
文摘Thermal energy storage(TES)is a key technology for renewable energy utilization and the improvement of the energy efficiency of heat processes.Sectors include industrial process heat and conventional and renewable power generation.TES systems correct the mismatch between supply and demand of thermal energy.In the medium to high temperature range(100~1000℃),only limited storage technology is commercially available and a strong effort is needed to develop a range of storage technologies which are efficient and economical for the very specific requirements of the different application sectors.At the DLR's Institute of Technical Thermodynamics,the complete spectrum of high temperature storage technologies,from various types of sensible over latent heat to thermochemical heat storages are being developed.Different concepts are proposed depending on the heat transfer fluid(synthetic oil,water/steam,molten salt,air)and the required temperature range.The aim is the development of cost effective,efficient and reliable thermal storage systems.Research focuses on characterization of storage materials,enhancement of internal heat transfer,design of innovative storage concepts and modelling of storage components and systems.Demonstration of the storage technology takes place from laboratory scale to field testing(5 kW^1 MW).The paper gives an overview on DLR's current developments.
基金supported in part by the National Natural Science Foundation of China(60375003)the Aeronautics and Astronautics Basal Science Foundation of China(03I53059)
文摘A class of latent ancestral graph for modelling the dependence structure of structural vector autoregressive （VAR） model affected by latent variables is proposed. The graphs are mixed graphs with possibly two kind of edges, namely directed and bidirected edges. The vertex set denotes random variables at dif- ferent times. In Gaussian case, the latent ancestral graph leads to a simple parameterization model. A modified iterative conditional fitting algorithm is presented to obtain maximum likelihood esti- mation of the parameters. Furthermore, a log-likelihood criterion is used to select the most appropriate models. Simulations are performed using illustrative examples and results are provided to demonstrate the validity of the methods.
文摘The latent membrane protein(LMP1)encoded by EBV is expressed in the majority of EBV-associated human malignancies,suggesting it is one of the major oncogenic factors in EBV-mediated carcinogenesis.In the previous studies we experimentally demonstrated that the DNAzymes targeting LMP1 could specifically down-regulate the expression of LMP1,leading to an increased radiosensitivity both in cells and in
基金supported by the National Natural Science Foundation of China(61472305)the Science Research Program,Xi’an,China(2017073CG/RC036CXDKD003)the Aeronautical Science Foundation of China(20151981009)
文摘Multi-label classification problems arise frequently in text categorization, and many other related applications. Like conventional categorization problems, multi-label categorization tasks suffer from the curse of high dimensionality. Existing multi-label dimensionality reduction methods mainly suffer from two limitations. First, latent nonlinear structures are not utilized in the input space. Second, the label information is not fully exploited. This paper proposes a new method, multi-label local discriminative embedding (MLDE), which exploits latent structures to minimize intraclass distances and maximize interclass distances on the basis of label correlations. The latent structures are extracted by constructing two sets of adjacency graphs to make use of nonlinear information. Non-symmetric label correlations, which are the case in real applications, are adopted. The problem is formulated into a global objective function and a linear mapping is achieved to solve out-of-sample problems. Empirical studies across 11 Yahoo sub-tasks, Enron and Bibtex are conducted to validate the superiority of MLDE to state-of-art multi-label dimensionality reduction methods.
基金Supported by Department Education of Heilongjiang Province of China (10531146)
文摘Three pairs of primers were designed and synthesized from nucleotide sequences of garlic latent virus （GLV）, onion yellow dwarf virus （OYDV）, and leek yellow stripe virus （LYSV） by using PCR primer design software. The expected fragments about 170 bp, 287 bp, and 191 bp were amplified by RT-PCR for GLV, OYDV, and LYSV, respectively in disease-infected plants of potato onion （Allium cepa L., Aggregatum group）, but such fragments were not obtained from healthy-looking plants and virus-free seedlings of shoot-tips. The amplified products ofGLV, OYDV and LYSV were cloned into pGEM-T vectors, and transformed into Escherichia coli. JM109. The recombinant plasmids were obtained and sequenced. The nucleotide sequences were compared with corresponding viral nucleotide sequences reported in GenBank by performing a NCBI BLAST. The analysis showed that their homology attained 75% to 90%,89.5% to 96.1%,and 91.6% to 96.3% in GLV, OYDV, and LYSV, respectively. The total RNA of 6.34 ug·uL^-1 from infected plants was diluted to a series of 10^-1 to 10^5 and the detection sensitivity of RT-PCR was 10^4 （about 4 ng）. Thus, a method of identification and detection by RT-PCR of GLV, OYDV, and SLYV was established.
文摘基于统计机器翻译模型的问句检索模型,其相关性排序机制主要依赖于词项间的翻译概率,然而已有的模型没有很好地控制翻译模型的噪声,使得当前的问句检索模型存在不完善之处.文中提出一种基于主题翻译模型的问句检索模型,从理论上说明,该模型利用主题信息对翻译进行合理的约束,达到控制翻译模型噪声的效果,从而提高问句检索的结果.实验结果表明,文中提出的模型在MAP(Mean Average Precision)、MRR(Mean Reciprocal Rank)以及p@1(precision at position one)等指标上显著优于当前最先进的问句检索模型.
