Objective To establish a warehouse on acupuncture-moxibution （acup-mox） methods to explore valuable laws about research and clinical application of acup-mox in a great number of literature by use of data mining tech...Objective To establish a warehouse on acupuncture-moxibution （acup-mox） methods to explore valuable laws about research and clinical application of acup-mox in a great number of literature by use of data mining technique and to promote acup-mox research and effective treatment of diseases. Methods According to the acup-mox literature information of different types, different subjects of the aeup-mox literature are determined and the relevant database is established. In the continuously enriched subject database, the data warehouse catering to multi-subjects and multi-dimensions is set up so as to provide a platform for wider application of aeup-mox literature information. Results Based on characteristics of the acup-mox literature, many subject databases, such as needling with filiform needle, moxibustion, etc., are established and clinical treatment laws of acup-mox are revealed by use of data mining method in the database established. Conclusion Establishment of the acup-mox literature warehouse provides a standard data expression model, rich attributes and relation between different literature information for study of aeup-mox literature by more effective techniques, and a rich and standard data basis for acup-mox researches.展开更多
To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on ...To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on the upper atmosphere has been developed by a Japanese inter-university project called the Inter-university Upper atmosphere Global Observation Network （1UGONET）. The objective of this paper is to describe the infrastructure and tools developed by IUGONET. We focus on the data analysis software. It is written in Interactive Data Language （IDL） and is a plug-in for the THEMIS Data Analysis Software suite （TDAS）, which is a set of IDL libraries used to visualize and analyze satellite- and ground-based data. We present plots of upper atmospheric data provided by IUGONET as examples of applications, and verify the usefulness of the software in the study of polar science. We discuss IUGONET＇s new and unique developments, i.e., an executable file of TDAS that can run on the IDL Virtual Machine, IDL routines to retrieve metadata from the IUGONET database, and an archive of 3-D simulation data that uses the Common Data Format so that it can easily be used with TDAS.展开更多
We developed a GPU based single-pulse search pipeline(GSP)with a candidate-archiving database.Largely based upon the infrastructure of the open source PulsaR Exploration and Search Toolkit(PRESTO),GSP implements GPU a...We developed a GPU based single-pulse search pipeline(GSP)with a candidate-archiving database.Largely based upon the infrastructure of the open source PulsaR Exploration and Search Toolkit(PRESTO),GSP implements GPU acceleration of the de-dispersion and integrates a candidate-archiving database.We applied GSP to the data streams from the Commensal Radio Astronomy FAST Survey(CRAFTS),which resulted in quasi-real-time processing.The integrated candidate database facilitates synergistic usage of multiple machine-learning tools and thus improves efficient identification of radio pulsars such as rotating radio transients(RRATs)and fast radio bursts(FRBs).We first tested GSP on pilot CRAFTS observations with the FAST Ultra-Wide Band(UWB)receiver.GSP detected all pulsars known from the the Parkes multibeam pulsar survey in the corresponding sky area covered by the FAST-UWB.GSP also discovered 13 new pulsars.We measured the computational efficiency of GSP to be~120 times faster than the original PRESTO and~60 times faster than an MPI-parallelized version of PRESTO.展开更多
Objective To identify and validate the key genes of ferroptosis in phospholipase A2 receptor(PLA2R)associated membranous nephropathy through bioinformatics analysis and in vitro experiments,and to explore the potentia...Objective To identify and validate the key genes of ferroptosis in phospholipase A2 receptor(PLA2R)associated membranous nephropathy through bioinformatics analysis and in vitro experiments,and to explore the potential roleof ferroptosis in PLA2RRassociated membranous nephropathy(PMN).Methods The GSE115857 dataset obtained by retrieving the Gene Expression Omnibus(GEO)database and the ferroptosisrelated genes obtained by retrieving the FerDb database were intersected.The intersected genes were subjected to Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.The key ferroptosis genes associated with PMN were identified by intersectinggenes sseelected1usingSsupport vector machines-recursive feature elimination and least absolute shrinkage and selection operator regression.The results were validate by real-time PCR,cell counting kit-8,Western blotting and immunofluorescence in human renal podocyte line AB 8/13 from both the control group and model group.Results A total of 25 genes related to ferroptosis of PMN were obtained,and GO and KEGG analysis showed that these genes were mainly involved in cell ferroptosis metabolism.The key ferroptosis genes of PMN obtained by machine learning method were activating transcription factor 3(ATF3)and coiled coil domain containing 6(CCDC6).The results of in vitro experiments showed that the human renal podocyte line AB 8/13 in the model group was significantly deformed and retracted compared with the control group.The surface area density of foot processes was significantly reduced,and the podocyte cytoskeleton was allosteric.The morphology of F-actin was disordered and the expression of synaptopodin was decreased.The cell proliferation activity was significantly decreased(P<0.05).The expression of PLA2R protein was increased(P<0.05),and the expression of GPX4 protein was decreased(P<0.01).The protein and mRNA levels of ATF3 and CCDC6 were significantly up-regulated(all P<0.05).Conclusion Ferroptosis may be one of the key mechanisms in the occurrence and development of PMN.In vitro experiments show that ATF3 and CCDC6 are the key genes in the ferroptosis of PMN podocytes,whichprovidesnew insightsand ideas for the pathogenesis of PMN.展开更多
We introduce the structure of a radio astronomy phased array feeds(PAF)beamforming demonstrator.In a laboratory environment,we have demonstrated beamforming on a received 1.25 GHz sinusoidal signal and used digital we...We introduce the structure of a radio astronomy phased array feeds(PAF)beamforming demonstrator.In a laboratory environment,we have demonstrated beamforming on a received 1.25 GHz sinusoidal signal and used digital weighting techniques to plot the 2D pattern of the PAF.The radio frequency part of the demonstrator includes a 4×4 linearly polarized microstrip antenna array,all of which is connected in series with a low-noise amplifier.The signals from the central 4×2 array elements are injected into a radio frequency system-on-chip digital board,which can receive eight inputs with a bandwidth of 512 MHz.Combining the principle of undersampling,the beamforming is completed at a frequency of 1.25 GHz for the offline data,and a 2D image of the beam is plotted using beam scanning technology.展开更多
We introduced a decision tree method called Random Forests for multiwavelength data classification. The data were adopted from different databases, including the Sloan Digital Sky Survey （SDSS） Data Release five, US...We introduced a decision tree method called Random Forests for multiwavelength data classification. The data were adopted from different databases, including the Sloan Digital Sky Survey （SDSS） Data Release five, USNO, FIRST and ROSAT. We then studied the discrimination of quasars from stars and the classification of quasars, stars and galaxies with the sample from optical and radio bands and with that from optical and X-ray bands. Moreover, feature selection and feature weighting based on Random Forests were investigated. The performances based on different input patterns were compared. The experimental results show that the random forest method is an effective method for astronomical object classification and can be applied to other classification problems faced in astronomy. In addition, Random Forests will show its superiorities due to its own merits, e.g. classification, feature selection, feature weighting as well as outlier detection.展开更多
Astronomical knowledge entities,such as celestial object identifiers,are crucial for literature retrieval and knowledge graph construction,and other research and applications in the field of astronomy.Traditional meth...Astronomical knowledge entities,such as celestial object identifiers,are crucial for literature retrieval and knowledge graph construction,and other research and applications in the field of astronomy.Traditional methods of extracting knowledge entities from texts face numerous challenging obstacles that are difficult to overcome.Consequently,there is a pressing need for improved methods to efficiently extract them.This study explores the potential of pre-trained Large Language Models(LLMs)to perform astronomical knowledge entity extraction(KEE)task from astrophysical journal articles using prompts.We propose a prompting strategy called PromptKEE,which includes five prompt elements,and design eight combination prompts based on them.We select four representative LLMs(Llama-2-70B,GPT-3.5,GPT-4,and Claude 2)and attempt to extract the most typical astronomical knowledge entities,celestial object identifiers and telescope names,from astronomical journal articles using these eight combination prompts.To accommodate their token limitations,we construct two data sets:the full texts and paragraph collections of 30 articles.Leveraging the eight prompts,we test on full texts with GPT-4and Claude 2,on paragraph collections with all LLMs.The experimental results demonstrate that pre-trained LLMs show significant potential in performing KEE tasks,but their performance varies on the two data sets.Furthermore,we analyze some important factors that influence the performance of LLMs in entity extraction and provide insights for future KEE tasks in astrophysical articles using LLMs.Finally,compared to other methods of KEE,LLMs exhibit strong competitiveness in multiple aspects.展开更多
The usage of a subset of observed stars in a CCD image to find their corresponding matched stars in a stellar catalog is an important issue in astronomical research. Subgraph isomorphic-based algorithms are the most w...The usage of a subset of observed stars in a CCD image to find their corresponding matched stars in a stellar catalog is an important issue in astronomical research. Subgraph isomorphic-based algorithms are the most widely used methods in star catalog matching. When more subgraph features are provided, the CCD images are recognized better. However, when the navigation feature database is large, the method requires more time to match the observing model. To solve this problem, this study investigates further and improves subgraph isomorphic matching algorithms. We present an algorithm based on a locality-sensitive hashing technique, which allocates quadrilateral models in the navigation feature database into different hash buckets and reduces the search range to the bucket in which the observed quadrilateral model is located. Experimental results indicate the effectivity of our method.展开更多
Considering features of stellar spectral radiation and sky surveys, we established a computational model for stellar effective temperatures, detected angular parameters and gray rates. Using known stellar flux data in...Considering features of stellar spectral radiation and sky surveys, we established a computational model for stellar effective temperatures, detected angular parameters and gray rates. Using known stellar flux data in some bands, we estimated stellar effective temperatures and detected angular parameters using stochastic particle swarm optimization （SPSO）. We first verified the reliability of SPSO, and then determined reasonable parameters that produced highly accurate estimates under certain gray deviation levels. Finally, we calculated 177 860 stellar effective temperatures and detected angular parameters using data from the Midcourse Space Experiment （MSX） catalog. These derived stellar effective temperatures were accurate when we compared them to known values from literatures. This research makes full use of catalog data and presents an original technique for studying stellar characteristics. It proposes a novel method for calculating stellar effective temperatures and detecting angular parameters, and provides theoretical and practical data for finding information about radiation in any band.展开更多
There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing env...There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers' ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.展开更多
We present a catalog of 3339 hot emission-line stars(ELSs)identified from 451695 O,B and A type spectra,provided by LAMOST Data Release 5(DR5).We developed an automated Python routine that identified 5437 spectra havi...We present a catalog of 3339 hot emission-line stars(ELSs)identified from 451695 O,B and A type spectra,provided by LAMOST Data Release 5(DR5).We developed an automated Python routine that identified 5437 spectra having a peak between 6561 and 6568.False detections and bad spectra were removed,leaving 4138 good emission-line spectra of 3339 unique ELSs.We re-estimated the spectral types of 3307 spectra as the LAMOST Stellar Parameter Pipeline(LASP)did not provide accurate spectral types for these emission-line spectra.As Herbig Ae/Be stars exhibit higher excess in near-infrared and mid-infrared wavelengths than classical Ae/Be stars,we relied on 2 MASS and WISE photometry to distinguish them.Finally,we report 1089 classical Be,233 classical Ae and 56 Herbig Ae/Be stars identified from LAMOST DR5.In addition,928 B[em]/A[em]stars and 240 CAe/CBe potential candidates are identified.From our sample of 3339 hot ELSs,2716 ELSs identified in this work do not have any record in the SIMBAD database and they can be considered as new detections.Identification of such a large homogeneous set of emission-line spectra will help the community study the emission phenomenon in detail without worrying about the inherent biases when compiling from various sources.展开更多
We compare the performance of Bayesian Belief Networks （BBN）, Multilayer Perception （MLP） networks and Alternating Decision Trees （ADtree） on separating quasars from stars with the database from the 2MASS and FI...We compare the performance of Bayesian Belief Networks （BBN）, Multilayer Perception （MLP） networks and Alternating Decision Trees （ADtree） on separating quasars from stars with the database from the 2MASS and FIRST survey catalogs. Having a training sample of sources of known object types, the classifiers are trained to separate quasars from stars. By the statistical properties of the sample, the features important for classifica- tion are selected. We compare the classification results with and without feature selection. Experiments show that the results with feature selection are better than those without feature selection. From the high accuracy found, it is concluded that these automated methods are robust and effective for classifying point sources. They may all be applied to large survey projects （e.g. selecting input catalogs） and for other astronomical issues, such as the parameter measurement of stars and the redshift estimation of galaxies and quasars.展开更多
基金Supported by National Natural Science Foundation of China: No.81072883
文摘Objective To establish a warehouse on acupuncture-moxibution （acup-mox） methods to explore valuable laws about research and clinical application of acup-mox in a great number of literature by use of data mining technique and to promote acup-mox research and effective treatment of diseases. Methods According to the acup-mox literature information of different types, different subjects of the aeup-mox literature are determined and the relevant database is established. In the continuously enriched subject database, the data warehouse catering to multi-subjects and multi-dimensions is set up so as to provide a platform for wider application of aeup-mox literature information. Results Based on characteristics of the acup-mox literature, many subject databases, such as needling with filiform needle, moxibustion, etc., are established and clinical treatment laws of acup-mox are revealed by use of data mining method in the database established. Conclusion Establishment of the acup-mox literature warehouse provides a standard data expression model, rich attributes and relation between different literature information for study of aeup-mox literature by more effective techniques, and a rich and standard data basis for acup-mox researches.
基金supported by the Special Edu-cational Research Budget(Research Promotion)[FY2009]the Special Budget(Project)[FY2010 and later years]from the Ministry of Education,Culture,Sports,Science and Technology(MEXT),Japansupported by the GRENE Arctic Climate Change Research Project,Japan
文摘To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on the upper atmosphere has been developed by a Japanese inter-university project called the Inter-university Upper atmosphere Global Observation Network （1UGONET）. The objective of this paper is to describe the infrastructure and tools developed by IUGONET. We focus on the data analysis software. It is written in Interactive Data Language （IDL） and is a plug-in for the THEMIS Data Analysis Software suite （TDAS）, which is a set of IDL libraries used to visualize and analyze satellite- and ground-based data. We present plots of upper atmospheric data provided by IUGONET as examples of applications, and verify the usefulness of the software in the study of polar science. We discuss IUGONET＇s new and unique developments, i.e., an executable file of TDAS that can run on the IDL Virtual Machine, IDL routines to retrieve metadata from the IUGONET database, and an archive of 3-D simulation data that uses the Common Data Format so that it can easily be used with TDAS.
基金supported by the National Natural Science Foundation of China(NSFCGrant Nos.11988101,11725313,11690024,12041303,U1731238,U2031117,U1831131 and U1831207)+2 种基金supported by the Science and Technology Foundation of Guizhou Province(No.LKS[2010]38)support by the Youth Innovation Promotion Association CAS(id.2021055)cultivation project for FAST scientific payoff and research achievement of CAMS-CAS。
文摘We developed a GPU based single-pulse search pipeline(GSP)with a candidate-archiving database.Largely based upon the infrastructure of the open source PulsaR Exploration and Search Toolkit(PRESTO),GSP implements GPU acceleration of the de-dispersion and integrates a candidate-archiving database.We applied GSP to the data streams from the Commensal Radio Astronomy FAST Survey(CRAFTS),which resulted in quasi-real-time processing.The integrated candidate database facilitates synergistic usage of multiple machine-learning tools and thus improves efficient identification of radio pulsars such as rotating radio transients(RRATs)and fast radio bursts(FRBs).We first tested GSP on pilot CRAFTS observations with the FAST Ultra-Wide Band(UWB)receiver.GSP detected all pulsars known from the the Parkes multibeam pulsar survey in the corresponding sky area covered by the FAST-UWB.GSP also discovered 13 new pulsars.We measured the computational efficiency of GSP to be~120 times faster than the original PRESTO and~60 times faster than an MPI-parallelized version of PRESTO.
文摘Objective To identify and validate the key genes of ferroptosis in phospholipase A2 receptor(PLA2R)associated membranous nephropathy through bioinformatics analysis and in vitro experiments,and to explore the potential roleof ferroptosis in PLA2RRassociated membranous nephropathy(PMN).Methods The GSE115857 dataset obtained by retrieving the Gene Expression Omnibus(GEO)database and the ferroptosisrelated genes obtained by retrieving the FerDb database were intersected.The intersected genes were subjected to Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.The key ferroptosis genes associated with PMN were identified by intersectinggenes sseelected1usingSsupport vector machines-recursive feature elimination and least absolute shrinkage and selection operator regression.The results were validate by real-time PCR,cell counting kit-8,Western blotting and immunofluorescence in human renal podocyte line AB 8/13 from both the control group and model group.Results A total of 25 genes related to ferroptosis of PMN were obtained,and GO and KEGG analysis showed that these genes were mainly involved in cell ferroptosis metabolism.The key ferroptosis genes of PMN obtained by machine learning method were activating transcription factor 3(ATF3)and coiled coil domain containing 6(CCDC6).The results of in vitro experiments showed that the human renal podocyte line AB 8/13 in the model group was significantly deformed and retracted compared with the control group.The surface area density of foot processes was significantly reduced,and the podocyte cytoskeleton was allosteric.The morphology of F-actin was disordered and the expression of synaptopodin was decreased.The cell proliferation activity was significantly decreased(P<0.05).The expression of PLA2R protein was increased(P<0.05),and the expression of GPX4 protein was decreased(P<0.01).The protein and mRNA levels of ATF3 and CCDC6 were significantly up-regulated(all P<0.05).Conclusion Ferroptosis may be one of the key mechanisms in the occurrence and development of PMN.In vitro experiments show that ATF3 and CCDC6 are the key genes in the ferroptosis of PMN podocytes,whichprovidesnew insightsand ideas for the pathogenesis of PMN.
基金funded by the National Key R&D Program of China under No.2022YFC2205300the National Natural Science Foundation of China(NSFC,grant Nos.12073067 and 11973078)the Chinese Academy of Sciences(CAS)“Light of West China”Program under No.2022-XBQNXZ012 and No.2020-XBQNXZ-018。
文摘We introduce the structure of a radio astronomy phased array feeds(PAF)beamforming demonstrator.In a laboratory environment,we have demonstrated beamforming on a received 1.25 GHz sinusoidal signal and used digital weighting techniques to plot the 2D pattern of the PAF.The radio frequency part of the demonstrator includes a 4×4 linearly polarized microstrip antenna array,all of which is connected in series with a low-noise amplifier.The signals from the central 4×2 array elements are injected into a radio frequency system-on-chip digital board,which can receive eight inputs with a bandwidth of 512 MHz.Combining the principle of undersampling,the beamforming is completed at a frequency of 1.25 GHz for the offline data,and a 2D image of the beam is plotted using beam scanning technology.
基金Supported by the National Natural Science Foundation of ChinaThis paper is funded by the National Natural Science Foundation of China under grant under GrantNos. 10473013, 90412016 and 10778724 by the 863 project under Grant No. 2006AA01A120
文摘We introduced a decision tree method called Random Forests for multiwavelength data classification. The data were adopted from different databases, including the Sloan Digital Sky Survey （SDSS） Data Release five, USNO, FIRST and ROSAT. We then studied the discrimination of quasars from stars and the classification of quasars, stars and galaxies with the sample from optical and radio bands and with that from optical and X-ray bands. Moreover, feature selection and feature weighting based on Random Forests were investigated. The performances based on different input patterns were compared. The experimental results show that the random forest method is an effective method for astronomical object classification and can be applied to other classification problems faced in astronomy. In addition, Random Forests will show its superiorities due to its own merits, e.g. classification, feature selection, feature weighting as well as outlier detection.
基金supported by the National Natural Science Foundation of China(NSFC,Grant Nos.12273077,72101068,12373110,and 12103070)National Key Research and Development Program of China under grants(2022YFF0712400,2022YFF0711500)+2 种基金the 14th Five-year Informatization Plan of Chinese Academy of Sciences(CAS-WX2021SF-0204)supported by Astronomical Big Data Joint Research Centerco-founded by National Astronomical Observatories,Chinese Academy of Sciences and Alibaba Cloud。
文摘Astronomical knowledge entities,such as celestial object identifiers,are crucial for literature retrieval and knowledge graph construction,and other research and applications in the field of astronomy.Traditional methods of extracting knowledge entities from texts face numerous challenging obstacles that are difficult to overcome.Consequently,there is a pressing need for improved methods to efficiently extract them.This study explores the potential of pre-trained Large Language Models(LLMs)to perform astronomical knowledge entity extraction(KEE)task from astrophysical journal articles using prompts.We propose a prompting strategy called PromptKEE,which includes five prompt elements,and design eight combination prompts based on them.We select four representative LLMs(Llama-2-70B,GPT-3.5,GPT-4,and Claude 2)and attempt to extract the most typical astronomical knowledge entities,celestial object identifiers and telescope names,from astronomical journal articles using these eight combination prompts.To accommodate their token limitations,we construct two data sets:the full texts and paragraph collections of 30 articles.Leveraging the eight prompts,we test on full texts with GPT-4and Claude 2,on paragraph collections with all LLMs.The experimental results demonstrate that pre-trained LLMs show significant potential in performing KEE tasks,but their performance varies on the two data sets.Furthermore,we analyze some important factors that influence the performance of LLMs in entity extraction and provide insights for future KEE tasks in astrophysical articles using LLMs.Finally,compared to other methods of KEE,LLMs exhibit strong competitiveness in multiple aspects.
基金supported by the National Natural Science Foundation of China(U1431227)Guangzhou Science and Technology Planning Project(201604010037)
文摘The usage of a subset of observed stars in a CCD image to find their corresponding matched stars in a stellar catalog is an important issue in astronomical research. Subgraph isomorphic-based algorithms are the most widely used methods in star catalog matching. When more subgraph features are provided, the CCD images are recognized better. However, when the navigation feature database is large, the method requires more time to match the observing model. To solve this problem, this study investigates further and improves subgraph isomorphic matching algorithms. We present an algorithm based on a locality-sensitive hashing technique, which allocates quadrilateral models in the navigation feature database into different hash buckets and reduces the search range to the bucket in which the observed quadrilateral model is located. Experimental results indicate the effectivity of our method.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51327803 and 51406041)the Fundamental Research Funds for the Central Universities (Grant No. HIT. NSRIF.2014090)
文摘Considering features of stellar spectral radiation and sky surveys, we established a computational model for stellar effective temperatures, detected angular parameters and gray rates. Using known stellar flux data in some bands, we estimated stellar effective temperatures and detected angular parameters using stochastic particle swarm optimization （SPSO）. We first verified the reliability of SPSO, and then determined reasonable parameters that produced highly accurate estimates under certain gray deviation levels. Finally, we calculated 177 860 stellar effective temperatures and detected angular parameters using data from the Midcourse Space Experiment （MSX） catalog. These derived stellar effective temperatures were accurate when we compared them to known values from literatures. This research makes full use of catalog data and presents an original technique for studying stellar characteristics. It proposes a novel method for calculating stellar effective temperatures and detecting angular parameters, and provides theoretical and practical data for finding information about radiation in any band.
文摘There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers' ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.
基金the Science&Engineering Research Board(SERB),a statutory body of Department of Science&Technology(DST),Government of India,for funding our research under grant number CRG/2019/005380the Center for Research,CHRIST(Deemed to be University),Bangalore,India,for funding our research under the grant number MRP DSC-1932。
文摘We present a catalog of 3339 hot emission-line stars(ELSs)identified from 451695 O,B and A type spectra,provided by LAMOST Data Release 5(DR5).We developed an automated Python routine that identified 5437 spectra having a peak between 6561 and 6568.False detections and bad spectra were removed,leaving 4138 good emission-line spectra of 3339 unique ELSs.We re-estimated the spectral types of 3307 spectra as the LAMOST Stellar Parameter Pipeline(LASP)did not provide accurate spectral types for these emission-line spectra.As Herbig Ae/Be stars exhibit higher excess in near-infrared and mid-infrared wavelengths than classical Ae/Be stars,we relied on 2 MASS and WISE photometry to distinguish them.Finally,we report 1089 classical Be,233 classical Ae and 56 Herbig Ae/Be stars identified from LAMOST DR5.In addition,928 B[em]/A[em]stars and 240 CAe/CBe potential candidates are identified.From our sample of 3339 hot ELSs,2716 ELSs identified in this work do not have any record in the SIMBAD database and they can be considered as new detections.Identification of such a large homogeneous set of emission-line spectra will help the community study the emission phenomenon in detail without worrying about the inherent biases when compiling from various sources.
基金Supported by the National Natural Science Foundation of China.
文摘We compare the performance of Bayesian Belief Networks （BBN）, Multilayer Perception （MLP） networks and Alternating Decision Trees （ADtree） on separating quasars from stars with the database from the 2MASS and FIRST survey catalogs. Having a training sample of sources of known object types, the classifiers are trained to separate quasars from stars. By the statistical properties of the sample, the features important for classifica- tion are selected. We compare the classification results with and without feature selection. Experiments show that the results with feature selection are better than those without feature selection. From the high accuracy found, it is concluded that these automated methods are robust and effective for classifying point sources. They may all be applied to large survey projects （e.g. selecting input catalogs） and for other astronomical issues, such as the parameter measurement of stars and the redshift estimation of galaxies and quasars.
