Epilepsy is a central nervous system disorder in which brain activity becomes abnormal.Electroencephalogram(EEG)signals,as recordings of brain activity,have been widely used for epilepsy recognition.To study epilep-ti...Epilepsy is a central nervous system disorder in which brain activity becomes abnormal.Electroencephalogram(EEG)signals,as recordings of brain activity,have been widely used for epilepsy recognition.To study epilep-tic EEG signals and develop artificial intelligence(AI)-assist recognition,a multi-view transfer learning(MVTL-LSR)algorithm based on least squares regression is proposed in this study.Compared with most existing multi-view transfer learning algorithms,MVTL-LSR has two merits:(1)Since traditional transfer learning algorithms leverage knowledge from different sources,which poses a significant risk to data privacy.Therefore,we develop a knowledge transfer mechanism that can protect the security of source domain data while guaranteeing performance.(2)When utilizing multi-view data,we embed view weighting and manifold regularization into the transfer framework to measure the views’strengths and weaknesses and improve generalization ability.In the experimental studies,12 different simulated multi-view&transfer scenarios are constructed from epileptic EEG signals licensed and provided by the Uni-versity of Bonn,Germany.Extensive experimental results show that MVTL-LSR outperforms baselines.The source code will be available on https://github.com/didid5/MVTL-LSR.展开更多
In the present study,we aimed to assess the chemical composition changes of Semen Euphorbiae(SE)and Semen Euphorbiae Pulveratum(SEP)by UPLC-Q-TOF/MS and multivariate statistical methods.The UPLC-Q-TOF/MS method and SI...In the present study,we aimed to assess the chemical composition changes of Semen Euphorbiae(SE)and Semen Euphorbiae Pulveratum(SEP)by UPLC-Q-TOF/MS and multivariate statistical methods.The UPLC-Q-TOF/MS method and SIMCA-P software were used to analyze the changes of chemical components of SE and SEP based on PCA and PLS-DA multivariate statistical methods.A"component-target-disease"network model was constructed by Intelligent Platform for Life Sciences of traditional Chinese medicine(TCM)to predict potential related diseases.The differences of chemical composition were significant between SE and SEP.Under positive ion mode,the amounts of Euphorbia factor L2,L3,L7a,L8,L9 and lathyrol were obviously decreased after processing.Under negative ion mode,the amounts of aesculetin,bisaesculetin,ingenol and cetylic acid were increased obviously,while Euphorbia factor L1,L4 and L5 were decreased obviously after processing,and the components of euphobiasteroid,aesculetin,lathyrol and linoleic acid among the 14 differentiated compounds were closely related to the SE-related diseases through the"component-target-disease"network model.UPLC-Q-TOF/MS technology in combination with multivariate statistical methods had certain advantages in studying the complex changes of chemical composition before and after manufacturing pulveratum of SE.It provided a basis for clarifying the toxicity-attenuated mechanisms of SE manufacturing pulveratum,and laid the foundation for its further development and utilization.展开更多
基金supported in part by the National Natural Science Foundation of China(Grant No.82072019)the Shenzhen Basic Research Program(JCYJ20210324130209023)of Shenzhen Science and Technology Innovation Committee+6 种基金the Shenzhen-Hong Kong-Macao S&T Program(Category C)(SGDX20201103095002019)the Natural Science Foundation of Jiangsu Province(No.BK20201441)the Provincial and Ministry Co-constructed Project of Henan Province Medical Science and Technology Research(SBGJ202103038 and SBGJ202102056)the Henan Province Key R&D and Promotion Project(Science and Technology Research)(222102310015)the Natural Science Foundation of Henan Province(222300420575)the Henan Province Science and Technology Research(222102310322)The Jiangsu Students’Innovation and Entrepreneurship Training Program(202110304096Y).
文摘Epilepsy is a central nervous system disorder in which brain activity becomes abnormal.Electroencephalogram(EEG)signals,as recordings of brain activity,have been widely used for epilepsy recognition.To study epilep-tic EEG signals and develop artificial intelligence(AI)-assist recognition,a multi-view transfer learning(MVTL-LSR)algorithm based on least squares regression is proposed in this study.Compared with most existing multi-view transfer learning algorithms,MVTL-LSR has two merits:(1)Since traditional transfer learning algorithms leverage knowledge from different sources,which poses a significant risk to data privacy.Therefore,we develop a knowledge transfer mechanism that can protect the security of source domain data while guaranteeing performance.(2)When utilizing multi-view data,we embed view weighting and manifold regularization into the transfer framework to measure the views’strengths and weaknesses and improve generalization ability.In the experimental studies,12 different simulated multi-view&transfer scenarios are constructed from epileptic EEG signals licensed and provided by the Uni-versity of Bonn,Germany.Extensive experimental results show that MVTL-LSR outperforms baselines.The source code will be available on https://github.com/didid5/MVTL-LSR.
基金Beijing Natural Science Foundation(Grant No.7182097)National Natural Science foundation of China(Grant No.81673597)National Key Research and Development Program of China(Grant No.2018YFE0197900)。
文摘In the present study,we aimed to assess the chemical composition changes of Semen Euphorbiae(SE)and Semen Euphorbiae Pulveratum(SEP)by UPLC-Q-TOF/MS and multivariate statistical methods.The UPLC-Q-TOF/MS method and SIMCA-P software were used to analyze the changes of chemical components of SE and SEP based on PCA and PLS-DA multivariate statistical methods.A"component-target-disease"network model was constructed by Intelligent Platform for Life Sciences of traditional Chinese medicine(TCM)to predict potential related diseases.The differences of chemical composition were significant between SE and SEP.Under positive ion mode,the amounts of Euphorbia factor L2,L3,L7a,L8,L9 and lathyrol were obviously decreased after processing.Under negative ion mode,the amounts of aesculetin,bisaesculetin,ingenol and cetylic acid were increased obviously,while Euphorbia factor L1,L4 and L5 were decreased obviously after processing,and the components of euphobiasteroid,aesculetin,lathyrol and linoleic acid among the 14 differentiated compounds were closely related to the SE-related diseases through the"component-target-disease"network model.UPLC-Q-TOF/MS technology in combination with multivariate statistical methods had certain advantages in studying the complex changes of chemical composition before and after manufacturing pulveratum of SE.It provided a basis for clarifying the toxicity-attenuated mechanisms of SE manufacturing pulveratum,and laid the foundation for its further development and utilization.
