Sensors are ubiquitous in the Internet of Things for measuring and collecting data. Analyzing these data derived from sensors is an essential task and can reveal useful latent information besides the data. Since the I...Sensors are ubiquitous in the Internet of Things for measuring and collecting data. Analyzing these data derived from sensors is an essential task and can reveal useful latent information besides the data. Since the Internet of Things contains many sorts of sensors, the measurement data collected by these sensors are multi-type data, sometimes contai- ning temporal series information. If we separately deal with different sorts of data, we will miss useful information. This paper proposes a method to dis- cover the correlation in multi-faceted data, which contains many types of data with temporal informa- tion, and our method can simultaneously deal with multi-faceted data. We transform high-dimensional multi-faeeted data into lower-dimensional data which is set as multivariate Gaussian Graphical Models, then mine the correlation in multi-faceted data by discover the structure of the multivariate Gausslan Graphical Models. With a real data set, we verifies our method, and the experiment demonstrates that the method we propose can correctly fred out the correlation among multi-faceted meas- urement data.展开更多
The rapid development of Internet of Things imposes new requirements on the data mining system, due to the weak capability of traditional distributed networking data mining. To meet the needs of the Internet of Things...The rapid development of Internet of Things imposes new requirements on the data mining system, due to the weak capability of traditional distributed networking data mining. To meet the needs of the Internet of Things, this paper proposes a novel distributed data-mining model to realize the seamless access between cloud computing and distributed data mining. The model is based on the cloud computing architecture, which belongs to the type of incredible nodes.展开更多
Objective This study focused on the application regularity of medicinal and dietary sub-stances(MDS)of traditional Chinese medicine(TCM)diet therapy during rehabilitation,in order to help patients with Corona Virus Di...Objective This study focused on the application regularity of medicinal and dietary sub-stances(MDS)of traditional Chinese medicine(TCM)diet therapy during rehabilitation,in order to help patients with Corona Virus Disease 2019(COVID-19)reduce sequelae and improve their life quality.Methods The official websites of the national and provincial health committees,the website of the National Administration of Traditional Chinese Medicine,the China BioMedical Literature Database(CBM),China National Knowledge Infrastructure(CNKI),China Science and Technology Journal Database(VIP),and Wanfang Database were used to search the keywords,such as“coronavirus”“novel coronavirus pneumonia”“COVID-19”“protocol”“guideline”“consensus”and“rehabilitation period”.The search time was from the establishment of databases to July 31,2022.The prevention and control protocols of various provinces and cities were manually supplemented and screened out.The information on the frequency,property,flavor,meridian tropism,and efficacy of MDS was collected for association rule analysis through the Apriori algorithm.Hierarchical cluster analysis was performed using the Euclidean distance and longest distance.Results A total of 18 protocols were screened out,including 56 lists of TCM diet therapy,and 47 kinds of MDS with a frequency of 132 times during the rehabilitation of COVID-19.Among them,six lists of diet therapy were collected from national websites,26 from local government websites,and 24 from social and academic institution websites.The intended population can be divided into seven categories including normal recovery,lung-spleen Qi deficiency,deficiency of both Qi and Yin,spleen-stomach weakness,deficiency of Yang Qi,kidney Qi deficiency,and blood deficiency.Shanyao(Dioscoreae Rhizoma)and Lianzi(Nelumbinis Semen),followed by Dazao(Jujubae Fructus)were used most commonly in MDS,with mainly flat property,sweet flavor,and spleen and lung meridians in meridian tropism.Besides,deficiency-tonifying drugs were commonly used in MDS.Through association rule analysis,12 groups of association MDS pairs were obtained.The pair of Yiyiren(Coicis Semen)and Chenpi(Citri Reticulatae Pericarpium)had the highest Lift value,and Yiyiren(Coicis Semen)was used most frequently in the MDS category for eliminating pathogenic factors.The results of complex network analysis showed that the core MDS were Yiyiren(Coicis Semen),Shanyao(Dioscoreae Rhizoma),Huangqi(Astragali Radix),Fuling(Poria),and Dazao(Jujubae Fructus).Three core categories were classified by cluster analysis,including the category of strengthening spleen,nourishing kidney,and grasping Qi,the category of removing phlegm,abating panting,and regulating Qi,and the category of strengthening the middle-energizer and reinforcing Qi.Conclusion Based on the TCM theory,most patients during the rehabilitation of COVID-19 are in a state of lingering pathogens due to deficient vital Qi.TCM diet therapy is based on the principle of“giving both reinforcing and reducing treatment”,and the MDS combinations focus on both reinforcing the health Qi and eliminating pathogenic factors.The diet therapy mainly uses the MDS with flat property and sweet flavor,which belongs to deficiency-tonifying drugs,adding suitable MDS of pathogen-eliminating drugs according to different situations.The ultimate goal is to promote lung inflammation absorption,improve pulmonary fibrosis,increase immunity,reduce the occurrence of sequelae,and improve life quality.展开更多
Natural products,as major resources for drug discovery historically,are gaining more attentions recently due to the advancement in genomic sequencing and other technologies,which makes them attractive and amenable to ...Natural products,as major resources for drug discovery historically,are gaining more attentions recently due to the advancement in genomic sequencing and other technologies,which makes them attractive and amenable to drug candidate screening.Collecting and mining the bioactivity information of natural products are extremely important for accelerating drug development process by reducing cost.Lately,a number of publicly accessible databases have been established to facilitate the access to the chemical biology data for small molecules including natural products.Thus,it is imperative for scientists in related fields to exploit these resources in order to expedite their researches on natural products as drug leads/candidates for disease treatment.PubChem,as a public database,contains large amounts of natural products associated with bioactivity data.In this review,we introduce the information system provided at PubChem,and systematically describe the applications for a set of PubChem web services for rapid data retrieval,analysis,and downloading of natural products.We hope this work can serve as a starting point for the researchers to perform data mining on natural products using PubChem.展开更多
Although weakly interacting massive particle （WIMP） scenario is very well motivated, it is not guaran- teed to be the truth. It is important to keep mind open and consider other well-motivated scenarios. In this pap...Although weakly interacting massive particle （WIMP） scenario is very well motivated, it is not guaran- teed to be the truth. It is important to keep mind open and consider other well-motivated scenarios. In this paper, we briefly review several possible non-WIMP dark matter （DM） candidates. First, we discuss details on asymmetric DM models, in which the baryon asymmetry in standard model sector is related to the asymmetry in DM sector. We discuss how DM relic abundance is determined in such models. Also we cover the possible interesting ex- perimental signatures induced by its asymmetric nature. Then we consider ultralight DM candidates, i.e., axion and dark photon. In such scenarios, DM should be treated as a coherently oscillating background, instead of each individual particle. Searching strategies for such DM candidates is very different than those in conventional DM models. We discuss several interesting experiments looking for these ultralight particles. We also cover interesting subtleties encountered in those experiments.展开更多
基金the Project"The Basic Research on Internet of Things Architecture"supported by National Key Basic Research Program of China(No.2011CB302704)supported by National Natural Science Foundation of China(No.60802034)+2 种基金Specialized Research Fund for the Doctoral Program of Higher Education(No.20070013026)Beijing Nova Program(No.2008B50)"New generation broadband wireless mobile communication network"Key Projects for Science and Technology Development(No.2011ZX03002-002-01)
文摘Sensors are ubiquitous in the Internet of Things for measuring and collecting data. Analyzing these data derived from sensors is an essential task and can reveal useful latent information besides the data. Since the Internet of Things contains many sorts of sensors, the measurement data collected by these sensors are multi-type data, sometimes contai- ning temporal series information. If we separately deal with different sorts of data, we will miss useful information. This paper proposes a method to dis- cover the correlation in multi-faceted data, which contains many types of data with temporal informa- tion, and our method can simultaneously deal with multi-faceted data. We transform high-dimensional multi-faeeted data into lower-dimensional data which is set as multivariate Gaussian Graphical Models, then mine the correlation in multi-faceted data by discover the structure of the multivariate Gausslan Graphical Models. With a real data set, we verifies our method, and the experiment demonstrates that the method we propose can correctly fred out the correlation among multi-faceted meas- urement data.
文摘The rapid development of Internet of Things imposes new requirements on the data mining system, due to the weak capability of traditional distributed networking data mining. To meet the needs of the Internet of Things, this paper proposes a novel distributed data-mining model to realize the seamless access between cloud computing and distributed data mining. The model is based on the cloud computing architecture, which belongs to the type of incredible nodes.
基金Jiangxi Traditional Chinese Medicine Young and Middle-aged Backbone Talent Preject Second Batch(1242001415).
文摘Objective This study focused on the application regularity of medicinal and dietary sub-stances(MDS)of traditional Chinese medicine(TCM)diet therapy during rehabilitation,in order to help patients with Corona Virus Disease 2019(COVID-19)reduce sequelae and improve their life quality.Methods The official websites of the national and provincial health committees,the website of the National Administration of Traditional Chinese Medicine,the China BioMedical Literature Database(CBM),China National Knowledge Infrastructure(CNKI),China Science and Technology Journal Database(VIP),and Wanfang Database were used to search the keywords,such as“coronavirus”“novel coronavirus pneumonia”“COVID-19”“protocol”“guideline”“consensus”and“rehabilitation period”.The search time was from the establishment of databases to July 31,2022.The prevention and control protocols of various provinces and cities were manually supplemented and screened out.The information on the frequency,property,flavor,meridian tropism,and efficacy of MDS was collected for association rule analysis through the Apriori algorithm.Hierarchical cluster analysis was performed using the Euclidean distance and longest distance.Results A total of 18 protocols were screened out,including 56 lists of TCM diet therapy,and 47 kinds of MDS with a frequency of 132 times during the rehabilitation of COVID-19.Among them,six lists of diet therapy were collected from national websites,26 from local government websites,and 24 from social and academic institution websites.The intended population can be divided into seven categories including normal recovery,lung-spleen Qi deficiency,deficiency of both Qi and Yin,spleen-stomach weakness,deficiency of Yang Qi,kidney Qi deficiency,and blood deficiency.Shanyao(Dioscoreae Rhizoma)and Lianzi(Nelumbinis Semen),followed by Dazao(Jujubae Fructus)were used most commonly in MDS,with mainly flat property,sweet flavor,and spleen and lung meridians in meridian tropism.Besides,deficiency-tonifying drugs were commonly used in MDS.Through association rule analysis,12 groups of association MDS pairs were obtained.The pair of Yiyiren(Coicis Semen)and Chenpi(Citri Reticulatae Pericarpium)had the highest Lift value,and Yiyiren(Coicis Semen)was used most frequently in the MDS category for eliminating pathogenic factors.The results of complex network analysis showed that the core MDS were Yiyiren(Coicis Semen),Shanyao(Dioscoreae Rhizoma),Huangqi(Astragali Radix),Fuling(Poria),and Dazao(Jujubae Fructus).Three core categories were classified by cluster analysis,including the category of strengthening spleen,nourishing kidney,and grasping Qi,the category of removing phlegm,abating panting,and regulating Qi,and the category of strengthening the middle-energizer and reinforcing Qi.Conclusion Based on the TCM theory,most patients during the rehabilitation of COVID-19 are in a state of lingering pathogens due to deficient vital Qi.TCM diet therapy is based on the principle of“giving both reinforcing and reducing treatment”,and the MDS combinations focus on both reinforcing the health Qi and eliminating pathogenic factors.The diet therapy mainly uses the MDS with flat property and sweet flavor,which belongs to deficiency-tonifying drugs,adding suitable MDS of pathogen-eliminating drugs according to different situations.The ultimate goal is to promote lung inflammation absorption,improve pulmonary fibrosis,increase immunity,reduce the occurrence of sequelae,and improve life quality.
基金supported by the Intramural Research Program of the National Institutes of Health,National Library of Medicine
文摘Natural products,as major resources for drug discovery historically,are gaining more attentions recently due to the advancement in genomic sequencing and other technologies,which makes them attractive and amenable to drug candidate screening.Collecting and mining the bioactivity information of natural products are extremely important for accelerating drug development process by reducing cost.Lately,a number of publicly accessible databases have been established to facilitate the access to the chemical biology data for small molecules including natural products.Thus,it is imperative for scientists in related fields to exploit these resources in order to expedite their researches on natural products as drug leads/candidates for disease treatment.PubChem,as a public database,contains large amounts of natural products associated with bioactivity data.In this review,we introduce the information system provided at PubChem,and systematically describe the applications for a set of PubChem web services for rapid data retrieval,analysis,and downloading of natural products.We hope this work can serve as a starting point for the researchers to perform data mining on natural products using PubChem.
文摘Although weakly interacting massive particle （WIMP） scenario is very well motivated, it is not guaran- teed to be the truth. It is important to keep mind open and consider other well-motivated scenarios. In this paper, we briefly review several possible non-WIMP dark matter （DM） candidates. First, we discuss details on asymmetric DM models, in which the baryon asymmetry in standard model sector is related to the asymmetry in DM sector. We discuss how DM relic abundance is determined in such models. Also we cover the possible interesting ex- perimental signatures induced by its asymmetric nature. Then we consider ultralight DM candidates, i.e., axion and dark photon. In such scenarios, DM should be treated as a coherently oscillating background, instead of each individual particle. Searching strategies for such DM candidates is very different than those in conventional DM models. We discuss several interesting experiments looking for these ultralight particles. We also cover interesting subtleties encountered in those experiments.
