Recently,pre-trained language representation models such as bidirec-tional encoder representations from transformers(BERT)have been performing well in commonsense question answering(CSQA).However,there is a problem th...Recently,pre-trained language representation models such as bidirec-tional encoder representations from transformers(BERT)have been performing well in commonsense question answering(CSQA).However,there is a problem that the models do not directly use explicit information of knowledge sources existing outside.To augment this,additional methods such as knowledge-aware graph network(KagNet)and multi-hop graph relation network(MHGRN)have been proposed.In this study,we propose to use the latest pre-trained language model a lite bidirectional encoder representations from transformers(ALBERT)with knowledge graph information extraction technique.We also propose to applying the novel method,schema graph expansion to recent language models.Then,we analyze the effect of applying knowledge graph-based knowledge extraction techniques to recent pre-trained language models and confirm that schema graph expansion is effective in some extent.Furthermore,we show that our proposed model can achieve better performance than existing KagNet and MHGRN models in CommonsenseQA dataset.展开更多
The aim of this study was to determine the relationship between phenotypic antimicrobial susceptibility patterns and extended-spectrum,carbapenem-resistance genes.A total of 109 clinical Staphilococcus aureus strains ...The aim of this study was to determine the relationship between phenotypic antimicrobial susceptibility patterns and extended-spectrum,carbapenem-resistance genes.A total of 109 clinical Staphilococcus aureus strains were subjected to 19 antimicrobial susceptibility tests.Resistance to methicillin(mecA),penicillin(blaTEM),and tetracycline(tetM)was detected.We compared the presence of the blaTEM genes with extended-spectrum,carbapenem-related genes and identified the types of SCCmec genes.Of 109 clinical S.aureus strains,62(56.88%)had methicillin resistance and 60 strains carried mecA.The prevalence of blaTEM and tetM genes was 81.65%and 37.61%,respectively.The most predominant SCCmec type was SCCmec type Ⅱ 28/60(46.67%),in 60 mecA-positive methicillin-resistant S.aureus(MRSA)isolates.The SCCmec prevalence rates were type ⅣA 30.00%(18/60),type Ⅳb 8.33%(5/60),type Ⅳd 6.67%(4/60),and non-typable 8.33%(5/60).Sixty of the 109(55.05%)MRSA isolates were positive for extended-spectrum carbapenems(31/60)(51.67%),cephalosporins 40/60(66.67%)and carbapenems 31/60(51.67%).The predominant SCCmec type II demonstrated more carbapenem-resistance than the ⅣA,Ⅳb and Ⅳd types.展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)(No.2020R1G1A1100493).
文摘Recently,pre-trained language representation models such as bidirec-tional encoder representations from transformers(BERT)have been performing well in commonsense question answering(CSQA).However,there is a problem that the models do not directly use explicit information of knowledge sources existing outside.To augment this,additional methods such as knowledge-aware graph network(KagNet)and multi-hop graph relation network(MHGRN)have been proposed.In this study,we propose to use the latest pre-trained language model a lite bidirectional encoder representations from transformers(ALBERT)with knowledge graph information extraction technique.We also propose to applying the novel method,schema graph expansion to recent language models.Then,we analyze the effect of applying knowledge graph-based knowledge extraction techniques to recent pre-trained language models and confirm that schema graph expansion is effective in some extent.Furthermore,we show that our proposed model can achieve better performance than existing KagNet and MHGRN models in CommonsenseQA dataset.
基金supported by a human resources exchange program in scientific technology through the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(No.NRF-2018H1D2A2076169)the Technology Development Program of MSS(S2660881)funded by the Ministry of SMEs and Startups(MSS,Korea).
文摘The aim of this study was to determine the relationship between phenotypic antimicrobial susceptibility patterns and extended-spectrum,carbapenem-resistance genes.A total of 109 clinical Staphilococcus aureus strains were subjected to 19 antimicrobial susceptibility tests.Resistance to methicillin(mecA),penicillin(blaTEM),and tetracycline(tetM)was detected.We compared the presence of the blaTEM genes with extended-spectrum,carbapenem-related genes and identified the types of SCCmec genes.Of 109 clinical S.aureus strains,62(56.88%)had methicillin resistance and 60 strains carried mecA.The prevalence of blaTEM and tetM genes was 81.65%and 37.61%,respectively.The most predominant SCCmec type was SCCmec type Ⅱ 28/60(46.67%),in 60 mecA-positive methicillin-resistant S.aureus(MRSA)isolates.The SCCmec prevalence rates were type ⅣA 30.00%(18/60),type Ⅳb 8.33%(5/60),type Ⅳd 6.67%(4/60),and non-typable 8.33%(5/60).Sixty of the 109(55.05%)MRSA isolates were positive for extended-spectrum carbapenems(31/60)(51.67%),cephalosporins 40/60(66.67%)and carbapenems 31/60(51.67%).The predominant SCCmec type II demonstrated more carbapenem-resistance than the ⅣA,Ⅳb and Ⅳd types.
