Pub Date : 2014-12-20DOI: 10.5183/JJSCS.1405001_211
Asanao Shimokawa, Y. Kawasaki, E. Miyaoka
Analysis based on interval-valued symbolic variables, which are given as p-dimensional hyperrectangles in R, is considered appropriate in some scenarios. However, the methods analyzing these variables are not as well studied as those for classical variables, which are given as single points in R. The regression tree, which is constructed using the CART algorithm, is one such example, and we consider it in this paper. To construct a regression tree based on interval-valued symbolic variables, several models are considered. Our proposed model is different from the other models, because, in this model, a concept can be included in several terminal nodes in a tree. If we want to construct a regression tree using the proposed model, several problems such as the representation method of predictive models in each node and searching an optimal splitting point in interval values, should be addressed. We address these problems and present an application of this model in reference to the study of HIV-1-infected patients’ data.
{"title":"CONSTRUCTION OF REGRESSION TREES ON INTERVAL-VALUED SYMBOLIC VARIABLES","authors":"Asanao Shimokawa, Y. Kawasaki, E. Miyaoka","doi":"10.5183/JJSCS.1405001_211","DOIUrl":"https://doi.org/10.5183/JJSCS.1405001_211","url":null,"abstract":"Analysis based on interval-valued symbolic variables, which are given as p-dimensional hyperrectangles in R, is considered appropriate in some scenarios. However, the methods analyzing these variables are not as well studied as those for classical variables, which are given as single points in R. The regression tree, which is constructed using the CART algorithm, is one such example, and we consider it in this paper. To construct a regression tree based on interval-valued symbolic variables, several models are considered. Our proposed model is different from the other models, because, in this model, a concept can be included in several terminal nodes in a tree. If we want to construct a regression tree using the proposed model, several problems such as the representation method of predictive models in each node and searching an optimal splitting point in interval values, should be addressed. We address these problems and present an application of this model in reference to the study of HIV-1-infected patients’ data.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134517936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-20DOI: 10.5183/JJSCS.1309001_207
S. Usami
Novel simulation studies are performed to investigate the performance of likelihood-based and entropy-based information criteria for estimating the number of classes in latent growth curve mixture models, considering influences of true model complexity and model misspecification. Simulation results can be summarized as (1) Increased model complexity worsens the performance of all criteria, and this is salient in Bayesian Information Criteria (BIC) and Consistent Akaike Information Criteria (CAIC). (2) The classification likelihood information criterion (CLC) and integrated completed likelihood criterion with BIC approximation (ICL.BIC) frequently underestimate the number of classes. (3) Entropy-based criteria correctly estimate the number of classes more frequently. (4) When a normal mixture is incorrectly fit to non-normal data including outliers, although this seriously worsens the performance of many criteria, BIC, CAIC, and ICL.BIC are relatively robust. Additionally, overextracted classes with trivially small mixture proportions can be detected when the sample size is large. (5) When there is an upper bound of measurement, although this worsens the performance of almost all criteria, entropy-based criteria are robust. (6) Although no single criterion is always best, ICL.BIC shows better performance on average.
{"title":"PERFORMANCE OF INFORMATION CRITERIA FOR MODEL SELECTION IN A LATENT GROWTH CURVE MIXTURE MODEL","authors":"S. Usami","doi":"10.5183/JJSCS.1309001_207","DOIUrl":"https://doi.org/10.5183/JJSCS.1309001_207","url":null,"abstract":"Novel simulation studies are performed to investigate the performance of likelihood-based and entropy-based information criteria for estimating the number of classes in latent growth curve mixture models, considering influences of true model complexity and model misspecification. Simulation results can be summarized as (1) Increased model complexity worsens the performance of all criteria, and this is salient in Bayesian Information Criteria (BIC) and Consistent Akaike Information Criteria (CAIC). (2) The classification likelihood information criterion (CLC) and integrated completed likelihood criterion with BIC approximation (ICL.BIC) frequently underestimate the number of classes. (3) Entropy-based criteria correctly estimate the number of classes more frequently. (4) When a normal mixture is incorrectly fit to non-normal data including outliers, although this seriously worsens the performance of many criteria, BIC, CAIC, and ICL.BIC are relatively robust. Additionally, overextracted classes with trivially small mixture proportions can be detected when the sample size is large. (5) When there is an upper bound of measurement, although this worsens the performance of almost all criteria, entropy-based criteria are robust. (6) Although no single criterion is always best, ICL.BIC shows better performance on average.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131495668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-20DOI: 10.5183/JJSCS.1312001_209
Kenichi Hayashi
{"title":"BIAS REDUCTION IN ESTIMATING A CONCORDANCE FOR CENSORED TIME-TO-EVENT RESPONSES","authors":"Kenichi Hayashi","doi":"10.5183/JJSCS.1312001_209","DOIUrl":"https://doi.org/10.5183/JJSCS.1312001_209","url":null,"abstract":"","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130236469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-20DOI: 10.5183/JJSCS.1308001_206
Masanari Iida, N. Niki
In each SIMD (Single Instruction, Multiple Data) group, called a ‘warp’ of a GPU (Graphics Processing Unit), all the (cid:12)xed number of threads execute the same instruction concurrently at each unit period of time. We consider a class of probabilistic algorithms designed for use on GPUs, including a wide variety of Monte Carlo methods, such that each thread contains a loop iterated stochastically variable times, and that the life-cycle of a warp ends when the slowest thread completes its requested task. A run-time model is proposed in order to explain the distributions of execution time observed in SIMD parallel computations using the algorithms of this class. Asymptotic properties of those distributions are also presented.
{"title":"LIFESPAN DISTRIBUTION OF SIMD GROUPS ON A GPU ENGAGED IN A CLASS OF PROBABILISTIC COMPUTATION","authors":"Masanari Iida, N. Niki","doi":"10.5183/JJSCS.1308001_206","DOIUrl":"https://doi.org/10.5183/JJSCS.1308001_206","url":null,"abstract":"In each SIMD (Single Instruction, Multiple Data) group, called a ‘warp’ of a GPU (Graphics Processing Unit), all the (cid:12)xed number of threads execute the same instruction concurrently at each unit period of time. We consider a class of probabilistic algorithms designed for use on GPUs, including a wide variety of Monte Carlo methods, such that each thread contains a loop iterated stochastically variable times, and that the life-cycle of a warp ends when the slowest thread completes its requested task. A run-time model is proposed in order to explain the distributions of execution time observed in SIMD parallel computations using the algorithms of this class. Asymptotic properties of those distributions are also presented.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126702634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-20DOI: 10.5183/JJSCS.1311001_208
Y. Takeda, Mituaki Huzii, N. Watanabe, T. Kamakura
Rukhin et al. (2010) proposed the non-overlapping template matching test as one of methods for statistical testing of randomness in cryptographic applications. This test is the very interesting, but statistical properties of this test and any methods on setting the template have not been shown. Our new contribution in this paper is to propose a modified version of this test including the setting of the template and to show how this modified test works effectively by some simulation studies.
Rukhin et al.(2010)提出了非重叠模板匹配检验作为密码学应用中随机性统计检验的方法之一。这个测试非常有趣，但是这个测试的统计属性和设置模板的任何方法都没有显示。我们在本文中的新贡献是提出了该测试的修改版本，包括模板的设置，并通过一些模拟研究显示了修改后的测试如何有效地工作。
{"title":"MODIFIED NON-OVERLAPPING TEMPLATE MATCHING TEST AND PROPOSAL ON SETTING TEMPLATE","authors":"Y. Takeda, Mituaki Huzii, N. Watanabe, T. Kamakura","doi":"10.5183/JJSCS.1311001_208","DOIUrl":"https://doi.org/10.5183/JJSCS.1311001_208","url":null,"abstract":"Rukhin et al. (2010) proposed the non-overlapping template matching test as one of methods for statistical testing of randomness in cryptographic applications. This test is the very interesting, but statistical properties of this test and any methods on setting the template have not been shown. Our new contribution in this paper is to propose a modified version of this test including the setting of the template and to show how this modified test works effectively by some simulation studies.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131510323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-12-20DOI: 10.5183/JJSCS.1212002_204
Yiping Tang
In analyzing complicated data, we are often unwilling or not confident to impose a parametric model for the data-generating structure. One important example is data analysis for proportional or count data with overdispersion. The obvious advantage of assuming full parametric models is that one can resort to likelihood analyses, for instance, to use AIC or BIC to choose the most appropriate regression models. For overdispersed proportional data, possible parametric models include the Beta-binomial models, the double exponential models, etc. In this paper, we extend the generalized linear models by replacing the full parametric models with a finite number of moment restrictions on both the data and the structural parameters. For such semiparametric statistical models, we propose a method for selecting the best possible regression model in the semiparametric model class. We will apply the proposed model selection technique to overdispersed data. We will demonstrate the use of the proposed semiparametric information criterion using the well-known data on germination of Orobanche.
{"title":"MODEL SELECTION BASED ON QUASI-LIKELIHOOD WITH APPLICATION TO OVERDISPERSED DATA","authors":"Yiping Tang","doi":"10.5183/JJSCS.1212002_204","DOIUrl":"https://doi.org/10.5183/JJSCS.1212002_204","url":null,"abstract":"In analyzing complicated data, we are often unwilling or not confident to impose a parametric model for the data-generating structure. One important example is data analysis for proportional or count data with overdispersion. The obvious advantage of assuming full parametric models is that one can resort to likelihood analyses, for instance, to use AIC or BIC to choose the most appropriate regression models. For overdispersed proportional data, possible parametric models include the Beta-binomial models, the double exponential models, etc. In this paper, we extend the generalized linear models by replacing the full parametric models with a finite number of moment restrictions on both the data and the structural parameters. For such semiparametric statistical models, we propose a method for selecting the best possible regression model in the semiparametric model class. We will apply the proposed model selection technique to overdispersed data. We will demonstrate the use of the proposed semiparametric information criterion using the well-known data on germination of Orobanche.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121960720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-12-20DOI: 10.5183/JJSCS.1206001_199
Joji Mori, Y. Kano
Since a latent trait θ can not be directly observed in item response theory models, it is difficult to specify an item response function (IRF). Many mathematical models have been proposed, among which the two-parameter logistic model (2PLM) is often included. In this article, we will propose a new parametric model, namely, a finite mixture of logistic models (MLM). The MLM has different mixing weights per item, and can model a plateau in the learning curve, which is a well-known phenomenon in education and psychology. It is also known that finite mixtures have some problems with estimating item parameters. Therefore, we develop a new useful estimation algorithm for item parameters and present simulation studies which show that this estimation algorithm works well. In fact, when the MLM was applied to analyze real data, we also found that the MLM makes it possible to distinguish whether or not a plateau appears in an IRF, whereas the 2PLM does not have this capability.
{"title":"ITEM RESPONSE THEORY USING A FINITE MIXTURE OF LOGISTIC MODELS WITH ITEM-SPECIFIC MIXING WEIGHTS","authors":"Joji Mori, Y. Kano","doi":"10.5183/JJSCS.1206001_199","DOIUrl":"https://doi.org/10.5183/JJSCS.1206001_199","url":null,"abstract":"Since a latent trait θ can not be directly observed in item response theory models, it is difficult to specify an item response function (IRF). Many mathematical models have been proposed, among which the two-parameter logistic model (2PLM) is often included. In this article, we will propose a new parametric model, namely, a finite mixture of logistic models (MLM). The MLM has different mixing weights per item, and can model a plateau in the learning curve, which is a well-known phenomenon in education and psychology. It is also known that finite mixtures have some problems with estimating item parameters. Therefore, we develop a new useful estimation algorithm for item parameters and present simulation studies which show that this estimation algorithm works well. In fact, when the MLM was applied to analyze real data, we also found that the MLM makes it possible to distinguish whether or not a plateau appears in an IRF, whereas the 2PLM does not have this capability.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132165053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-12-20DOI: 10.5183/JJSCS.1208002_201
K. Adachi
An algorithm for the constrained least squares problem is proposed in which the upper bound of the condition number of a parameter matrix is predetermined. In the algorithm, the parameter matrix to be obtained is reparameterized using its singular value decomposition, and the loss function is minimized alternately over the singular vector matrices and the singular values with condition number constraint. It was demonstrated that the algorithm recovered full rank matrices in simulated reverse component analysis, in which the matrices were estimated from their reduced rank counterparts. The proposed algorithm is useful for avoiding degenerate solutions in which parameter matrices become rank de(cid:12)cient, which is illustrated in its application to generalized oblique Procrustes rotation and three-mode Parafac component analysis.
{"title":"A RESTRAINED CONDITION NUMBER LEAST SQUARES TECHNIQUE WITH ITS APPLICATIONS TO AVOIDING RANK DEFICIENCY","authors":"K. Adachi","doi":"10.5183/JJSCS.1208002_201","DOIUrl":"https://doi.org/10.5183/JJSCS.1208002_201","url":null,"abstract":"An algorithm for the constrained least squares problem is proposed in which the upper bound of the condition number of a parameter matrix is predetermined. In the algorithm, the parameter matrix to be obtained is reparameterized using its singular value decomposition, and the loss function is minimized alternately over the singular vector matrices and the singular values with condition number constraint. It was demonstrated that the algorithm recovered full rank matrices in simulated reverse component analysis, in which the matrices were estimated from their reduced rank counterparts. The proposed algorithm is useful for avoiding degenerate solutions in which parameter matrices become rank de(cid:12)cient, which is illustrated in its application to generalized oblique Procrustes rotation and three-mode Parafac component analysis.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132926303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-12-20DOI: 10.5183/JJSCS.1211001_202
Sho Takahashi, Masashi Hyodo, T. Nishiyama, T. Pavlenko
This paper analyzes whether procedures for multiple comparison derived in Hyodo et al. (2012) work for an unbalanced case and under non-normality. We focus on pairwise multiple comparisons and comparison with a control among mean vectors, and show that the asymptotic properties of these procedures remain valid in unbalanced high-dimensional setting. We also numerically justify that the derived procedures are robust under non-normality, i.e., the coverage probability of these procedures can be controlled with or without the assumption of normality of the data.
本文分析了Hyodo et al.(2012)导出的多重比较程序是否适用于非平衡情况和非正态情况。我们重点研究了两两多重比较和均值向量间的控制比较，并证明了这些过程的渐近性质在不平衡高维环境下仍然有效。我们还在数值上证明了导出的程序在非正态性下是鲁棒的，即，这些程序的覆盖概率可以在假设数据正态性或不假设数据正态性的情况下控制。
{"title":"MULTIPLE COMPARISON PROCEDURES FOR HIGH-DIMENSIONAL DATA AND THEIR ROBUSTNESS UNDER NON-NORMALITY","authors":"Sho Takahashi, Masashi Hyodo, T. Nishiyama, T. Pavlenko","doi":"10.5183/JJSCS.1211001_202","DOIUrl":"https://doi.org/10.5183/JJSCS.1211001_202","url":null,"abstract":"This paper analyzes whether procedures for multiple comparison derived in Hyodo et al. (2012) work for an unbalanced case and under non-normality. We focus on pairwise multiple comparisons and comparison with a control among mean vectors, and show that the asymptotic properties of these procedures remain valid in unbalanced high-dimensional setting. We also numerically justify that the derived procedures are robust under non-normality, i.e., the coverage probability of these procedures can be controlled with or without the assumption of normality of the data.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133683082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-12-20DOI: 10.5183/JJSCS.1212001_203
Y. Yamaguchi, Wataru Sakamoto, S. Shirahata, M. Goto
Meta-analysis methods based on individual patient data (IPD) have attracted attention in estimating a treatment-covariate interaction effect. An existing metaregression approach, based on aggregate data (AD) such as a treatment effect estimate and its standard error, is used only for the inference of between-trial interaction which indicates a relationship between the treatment effect estimates and mean covariate values; in contrast, the use of IPD can achieve estimation of not only the between-trial interaction but also within-trial interaction which indicates a relationship between individual outcomes and individual covariate values. However, most of the IPD metaanalyses are often difficult to implement because practitioners cannot always collect the IPD from all trials involved. We propose a new meta-analysis method for estimating both the between-trial and the within-trial interaction, in which we assume an IPD meta-analysis model for the missing IPD and then marginalize its density with respect to the missing IPD. The proposed method allows one to estimate the withintrial interaction even when only AD are available, and has potential benefits for another meta-analytic situation where some trials provide IPD and the others provide only AD. Through simulation studies, we demonstrate how close estimates of the between-trial and the within-trial interaction from the proposed method are to those from the IPD meta-analysis.
{"title":"AN EVALUATION OF TREATMENT-COVARIATE INTERACTION IN META-ANALYSIS WITH MARGINALIZING OF MISSING INDIVIDUAL PATIENT DATA","authors":"Y. Yamaguchi, Wataru Sakamoto, S. Shirahata, M. Goto","doi":"10.5183/JJSCS.1212001_203","DOIUrl":"https://doi.org/10.5183/JJSCS.1212001_203","url":null,"abstract":"Meta-analysis methods based on individual patient data (IPD) have attracted attention in estimating a treatment-covariate interaction effect. An existing metaregression approach, based on aggregate data (AD) such as a treatment effect estimate and its standard error, is used only for the inference of between-trial interaction which indicates a relationship between the treatment effect estimates and mean covariate values; in contrast, the use of IPD can achieve estimation of not only the between-trial interaction but also within-trial interaction which indicates a relationship between individual outcomes and individual covariate values. However, most of the IPD metaanalyses are often difficult to implement because practitioners cannot always collect the IPD from all trials involved. We propose a new meta-analysis method for estimating both the between-trial and the within-trial interaction, in which we assume an IPD meta-analysis model for the missing IPD and then marginalize its density with respect to the missing IPD. The proposed method allows one to estimate the withintrial interaction even when only AD are available, and has potential benefits for another meta-analytic situation where some trials provide IPD and the others provide only AD. Through simulation studies, we demonstrate how close estimates of the between-trial and the within-trial interaction from the proposed method are to those from the IPD meta-analysis.","PeriodicalId":338719,"journal":{"name":"Journal of the Japanese Society of Computational Statistics","volume":"9 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132595758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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