Mass gathering events (MGEs) attracting local, national, or international crowds presented particular challenges in the context of the coronavirus disease 2019 (COVID-19) pandemic. Sporting, religious, music and other cultural events held during the early months of the pandemic, without social distancing or other safeguards, have been regarded as so-called ‘super spreader’ events. By the summer of 2020, MGEs were generally banned or subject to severe restrictions. Regular European sporting fixtures such as England’s Football Association and Germany’s Bundesliga matches began to return in the autumn with protective measures in place, such as matches initially held behind closed doors, and later with sub-capacity crowd limits and mandatory social distancing [1, 2, 3, 4, 5]. With protective measures in place, and proof of COVID-19 vaccination or recovery required for entry, a series of six sporting MGEs, ‘the All-Ireland Finals’ were held in the Republic of Ireland’s largest stadium, Croke Park in Dublin, during August-September 2021. This study draws on a high-resolution human population mobility dataset to quantify journeys to/from the stadium area on MGE days by destination. The anonymised, aggregated, data used is based on mobile phone usage, and consists of a series of fine-grained geographical origin-destination matrices presenting daily estimates of area to area journey numbers. With mobility from the stadium area serving as a proxy for MGE attendance, this study explores associations between MGE attendance numbers and local COVID-19 infections over subsequent five week periods. No evidence was found of association between attendance at any of the six 2021 All-Ireland MGEs and COVID-19 infections over subsequent five week periods. This finding contrasts with studies of comparable MGEs in 2020, such as English Association Football matches held during spring 2020, and German Bundesliga football matches held during autumn 2020. These differing outcomes may point to the effectiveness of transmission mitigation policies and behaviours.
{"title":"Assessing pandemic era stadium events and infections using mobile phone based population mobility data: An exploratory study from Ireland, 2021","authors":"A. Condron, G. McGrath, J. Madden","doi":"10.3233/sji-220045","DOIUrl":"https://doi.org/10.3233/sji-220045","url":null,"abstract":"Mass gathering events (MGEs) attracting local, national, or international crowds presented particular challenges in the context of the coronavirus disease 2019 (COVID-19) pandemic. Sporting, religious, music and other cultural events held during the early months of the pandemic, without social distancing or other safeguards, have been regarded as so-called ‘super spreader’ events. By the summer of 2020, MGEs were generally banned or subject to severe restrictions. Regular European sporting fixtures such as England’s Football Association and Germany’s Bundesliga matches began to return in the autumn with protective measures in place, such as matches initially held behind closed doors, and later with sub-capacity crowd limits and mandatory social distancing [1, 2, 3, 4, 5]. With protective measures in place, and proof of COVID-19 vaccination or recovery required for entry, a series of six sporting MGEs, ‘the All-Ireland Finals’ were held in the Republic of Ireland’s largest stadium, Croke Park in Dublin, during August-September 2021. This study draws on a high-resolution human population mobility dataset to quantify journeys to/from the stadium area on MGE days by destination. The anonymised, aggregated, data used is based on mobile phone usage, and consists of a series of fine-grained geographical origin-destination matrices presenting daily estimates of area to area journey numbers. With mobility from the stadium area serving as a proxy for MGE attendance, this study explores associations between MGE attendance numbers and local COVID-19 infections over subsequent five week periods. No evidence was found of association between attendance at any of the six 2021 All-Ireland MGEs and COVID-19 infections over subsequent five week periods. This finding contrasts with studies of comparable MGEs in 2020, such as English Association Football matches held during spring 2020, and German Bundesliga football matches held during autumn 2020. These differing outcomes may point to the effectiveness of transmission mitigation policies and behaviours.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47444937","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}
{"title":"Interview with Javier Carranza, director of the NGO GeoCensos’ about the decision to dissolve DIGESTYC El Salvador","authors":"","doi":"10.3233/sji-220104","DOIUrl":"https://doi.org/10.3233/sji-220104","url":null,"abstract":"","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42537108","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}
Collecting consumption and expenditure data might result in some measurement problems, such as potential recall bias. In addition, the respondent burden is another issue as a consequence of the interview lasting for hours. Consumption and expenditure data in Indonesia is collected through the National Socioeconomic Survey (Susenas). Indonesia is a country with many factors that can influence how long an interview may take, especially when collecting consumption and expenditure data, so deliberate sub-sampling and imputation need to be considered. The focus of this study is to look at the possibility of using sub-sampling of expenditure data and imputing the deliberately missing data using a standard method of missing data imputation (mice), a multilevel approach (jomo), and two machine learning approaches (missRanger and miceRanger). The results show that only mice with reasonable imputation results, in particular when breaking down by some categories. Although missRanger is the fastest, it has a large bias compared to the actual data.
{"title":"Imputation for sub-sampling in Indonesian National Socioeconomic Survey","authors":"Atika Nashirah Hasyyati, T. Lumley","doi":"10.3233/sji-220085","DOIUrl":"https://doi.org/10.3233/sji-220085","url":null,"abstract":"Collecting consumption and expenditure data might result in some measurement problems, such as potential recall bias. In addition, the respondent burden is another issue as a consequence of the interview lasting for hours. Consumption and expenditure data in Indonesia is collected through the National Socioeconomic Survey (Susenas). Indonesia is a country with many factors that can influence how long an interview may take, especially when collecting consumption and expenditure data, so deliberate sub-sampling and imputation need to be considered. The focus of this study is to look at the possibility of using sub-sampling of expenditure data and imputing the deliberately missing data using a standard method of missing data imputation (mice), a multilevel approach (jomo), and two machine learning approaches (missRanger and miceRanger). The results show that only mice with reasonable imputation results, in particular when breaking down by some categories. Although missRanger is the fastest, it has a large bias compared to the actual data.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46960781","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}
There are at least two sources of health insurance coverage estimates in the United States: the Behavioral Risk Factor Surveillance System (BRFSS) and the Small Area Health Insurance Estimates (SAHIE) program. This paper addresses the integration of BRFSS and SAHIE data using multilevel models that account for the different levels of aggregation at which data are available and for the different errors to which data are subject to. The uncertainty in the initial state-level estimates available from BRFSS and SAHIE is improved by borrowing information from both sources and across geographies. County-level model estimates are produced on both BRFSS and SAHIE scales, improving the usability of the BRFSS public-use data and inspiring possible extensions to estimation of BRFSS quantities other than health insurance coverage. The application uses 2018 public-use data. Parallels to small area estimation models and measurement error models are briefly discussed.
{"title":"Statistical data integration models to bridge health official statistics","authors":"Andreea L. Erciulescu","doi":"10.3233/sji-220089","DOIUrl":"https://doi.org/10.3233/sji-220089","url":null,"abstract":"There are at least two sources of health insurance coverage estimates in the United States: the Behavioral Risk Factor Surveillance System (BRFSS) and the Small Area Health Insurance Estimates (SAHIE) program. This paper addresses the integration of BRFSS and SAHIE data using multilevel models that account for the different levels of aggregation at which data are available and for the different errors to which data are subject to. The uncertainty in the initial state-level estimates available from BRFSS and SAHIE is improved by borrowing information from both sources and across geographies. County-level model estimates are produced on both BRFSS and SAHIE scales, improving the usability of the BRFSS public-use data and inspiring possible extensions to estimation of BRFSS quantities other than health insurance coverage. The application uses 2018 public-use data. Parallels to small area estimation models and measurement error models are briefly discussed.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46267230","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}
L. Barreñada, Juan Carlos Gálvez Sainz de Cueto, Jorge Fernández Calatrava
The modernisation of the production of official statistics should make use not only of new data sources but also of novel statistical methods applied to traditional survey and administrative data. This improves the traditional quality standards. Here we present an application of statistical learning algorithms to improve the timeliness under a controlled compromise of accuracy of the Spanish Industrial Turnover Index (ITI). The methodology has been developed based on a modular and standardized approach that could be easily extended to other surveys. Our advanced index allows us to predict the ITI 31 days before publication with a median error of 0.5 points over the period Mar 2016–Apr 21, in an index with large oscillations. The results are promising and support the idea of the use of these techniques in improving the quality dimension of timeliness while accuracy is kept under control.
{"title":"Timeliness reduction on industrial turnover index based on machine learning algorithms","authors":"L. Barreñada, Juan Carlos Gálvez Sainz de Cueto, Jorge Fernández Calatrava","doi":"10.3233/sji-220086","DOIUrl":"https://doi.org/10.3233/sji-220086","url":null,"abstract":"The modernisation of the production of official statistics should make use not only of new data sources but also of novel statistical methods applied to traditional survey and administrative data. This improves the traditional quality standards. Here we present an application of statistical learning algorithms to improve the timeliness under a controlled compromise of accuracy of the Spanish Industrial Turnover Index (ITI). The methodology has been developed based on a modular and standardized approach that could be easily extended to other surveys. Our advanced index allows us to predict the ITI 31 days before publication with a median error of 0.5 points over the period Mar 2016–Apr 21, in an index with large oscillations. The results are promising and support the idea of the use of these techniques in improving the quality dimension of timeliness while accuracy is kept under control.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43736127","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}
The aim of this research is to interpret the relationship between indicators of education, human development, economy and justice based on current indicators measured by international independent organizations. The coverage of this study was composed of 41 countries. Statistical evidence was collected that countries were divided into two clusters according to 15 indicators as education, law, human development and economy. The relationships between the average year of schooling in developed countries with the global competition; income inequality and freedom of the press; the rate of investment in basic education and freedom of the press; PISA-reading comprehension and judicial independence; PISA-reading comprehension average score and judicial independence; income inequality and fundamental rights; the rate of investment in basic education and fundamental rights; the rate of investment in basic education and the rule of law; income inequality and investment in basic education; investment rate in basic education and gender inequality, income inequality and rule of law were found to be statistically significant. However, it was observed that the correlation coefficients between the same indicators were not statistically significant for developing countries.
{"title":"Reflections of the relationship between education indicators and economic, law and human development indicators","authors":"T. Acar","doi":"10.3233/sji-220955","DOIUrl":"https://doi.org/10.3233/sji-220955","url":null,"abstract":"The aim of this research is to interpret the relationship between indicators of education, human development, economy and justice based on current indicators measured by international independent organizations. The coverage of this study was composed of 41 countries. Statistical evidence was collected that countries were divided into two clusters according to 15 indicators as education, law, human development and economy. The relationships between the average year of schooling in developed countries with the global competition; income inequality and freedom of the press; the rate of investment in basic education and freedom of the press; PISA-reading comprehension and judicial independence; PISA-reading comprehension average score and judicial independence; income inequality and fundamental rights; the rate of investment in basic education and fundamental rights; the rate of investment in basic education and the rule of law; income inequality and investment in basic education; investment rate in basic education and gender inequality, income inequality and rule of law were found to be statistically significant. However, it was observed that the correlation coefficients between the same indicators were not statistically significant for developing countries.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42914896","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}
Dilshanie Deepawansa, P. Dunusinghe, P. Lahiri, R. Gunatilaka
This paper presents a new approach to measure multidimensional poverty, combining the strengths of the Fuzzy Set method and the Alkire and Foster method, and addresses some of their limitations. The approach applies the Fuzzy Set method to resolve the discontinuity problem that arises when the latter is used in the Alkire and Foster method to identify the multidimensionally poor people. The resultant process satisfies poverty axioms of a good poverty measure. It also incorporates some s statistical techniques in selecting indicators and computing weights for the membership function. The empirical assessment is done to primary data, collected from the Uva province of Sri Lanka, an economically, neglected comprising of people representing various socio-economic backgrounds. This study examines poverty under three main dimensions; material, social dimensions and human capital. The results reveal that, 42.3 percent of people in the Uva province have a propensity to poverty. The incidence of multidimensional poverty is 56 percent and the intensity is 48.6 percent. The adjusted fuzzy headcount index is 27.2 percent. Interestingly, the highest contribution to overall poverty comes from deprivation by social dimensions. The application of the this method undoubtedly would encourage the analysis of further research on multidimensional poverty.
{"title":"An innovative approach to measure measuring multidimensional poverty: A synthesis method","authors":"Dilshanie Deepawansa, P. Dunusinghe, P. Lahiri, R. Gunatilaka","doi":"10.3233/sji-220036","DOIUrl":"https://doi.org/10.3233/sji-220036","url":null,"abstract":"This paper presents a new approach to measure multidimensional poverty, combining the strengths of the Fuzzy Set method and the Alkire and Foster method, and addresses some of their limitations. The approach applies the Fuzzy Set method to resolve the discontinuity problem that arises when the latter is used in the Alkire and Foster method to identify the multidimensionally poor people. The resultant process satisfies poverty axioms of a good poverty measure. It also incorporates some s statistical techniques in selecting indicators and computing weights for the membership function. The empirical assessment is done to primary data, collected from the Uva province of Sri Lanka, an economically, neglected comprising of people representing various socio-economic backgrounds. This study examines poverty under three main dimensions; material, social dimensions and human capital. The results reveal that, 42.3 percent of people in the Uva province have a propensity to poverty. The incidence of multidimensional poverty is 56 percent and the intensity is 48.6 percent. The adjusted fuzzy headcount index is 27.2 percent. Interestingly, the highest contribution to overall poverty comes from deprivation by social dimensions. The application of the this method undoubtedly would encourage the analysis of further research on multidimensional poverty.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48322267","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}
H. Asatryan, V.S. Aleksanyan, L. Azatyan, Meri Manucharyan
The use of regression analysis is a common method for quantifying the impact of various factors on economic phenomena. This article presents the dynamics of the development of viticulture in Republic of Armenia. In particular, by applying econometric analysis, the impact of the “Prices” factor on viticulture development was singled out. The nature of its impact was studied and a regression model was constructed. In addition, references were made to the studies of various researchers relating to viticulture development. The relevance of the research lies in the fact that it is the first of its kind. There have been no studies, which will give a quantitative assessment of the factors that influence the development of viticulture of Republic of Armenia. By using results of this analysis, we can assess the dynamics of viticulture indicators in future depending on changes of price factor. This can be a basis for policy makers to make scientifically sound decisions.
{"title":"Dynamics of the development of viticulture in RA: The econometric case study","authors":"H. Asatryan, V.S. Aleksanyan, L. Azatyan, Meri Manucharyan","doi":"10.3233/sji-220948","DOIUrl":"https://doi.org/10.3233/sji-220948","url":null,"abstract":"The use of regression analysis is a common method for quantifying the impact of various factors on economic phenomena. This article presents the dynamics of the development of viticulture in Republic of Armenia. In particular, by applying econometric analysis, the impact of the “Prices” factor on viticulture development was singled out. The nature of its impact was studied and a regression model was constructed. In addition, references were made to the studies of various researchers relating to viticulture development. The relevance of the research lies in the fact that it is the first of its kind. There have been no studies, which will give a quantitative assessment of the factors that influence the development of viticulture of Republic of Armenia. By using results of this analysis, we can assess the dynamics of viticulture indicators in future depending on changes of price factor. This can be a basis for policy makers to make scientifically sound decisions.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46207964","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}
The Hellenic Statistical Authority (ELSTAT) worked towards the introduction of a designated Law governing the 2021 General Censuses in Greece. It was the first time that the General Censuses were conducted by virtue of a legal act which underwent extensive deliberations and legal scrutiny. This kind of strengthening of the statistical legislation demonstrates the wide recognition of the professional independence ELSTAT has established and it provided a solid basis for the Hellenic Statistical System (ELSS) to be able to adequately respond to both current and future challenges. These straightforward institutional arrangements ensured ELSTAT’s ability to effectively conduct the Censuses in accordance with the International Recommendations and Standards, while, at the same time, strengthened its capacity to an immediate response to arising needs and challenges. It was then no mystery how ELSTAT was able to immediately adapt to the developing operational conditions by creating a plan for a hybrid census system for all households. At the same time the legal instruments used laid the foundations for the establishment and maintenance of Statistical Registers for Population and Buildings, introducing two unique identifiers (“keys”) in the Census variables and creating the institutional infrastructure for linkage to other administrative registers.
{"title":"Institutional challenges and prospects regarding the 2021 Population-Housing Census in Greece","authors":"Vassiliki Benaki-Kyprioti, Apostolos Kasapis","doi":"10.3233/sji-220083","DOIUrl":"https://doi.org/10.3233/sji-220083","url":null,"abstract":"The Hellenic Statistical Authority (ELSTAT) worked towards the introduction of a designated Law governing the 2021 General Censuses in Greece. It was the first time that the General Censuses were conducted by virtue of a legal act which underwent extensive deliberations and legal scrutiny. This kind of strengthening of the statistical legislation demonstrates the wide recognition of the professional independence ELSTAT has established and it provided a solid basis for the Hellenic Statistical System (ELSS) to be able to adequately respond to both current and future challenges. These straightforward institutional arrangements ensured ELSTAT’s ability to effectively conduct the Censuses in accordance with the International Recommendations and Standards, while, at the same time, strengthened its capacity to an immediate response to arising needs and challenges. It was then no mystery how ELSTAT was able to immediately adapt to the developing operational conditions by creating a plan for a hybrid census system for all households. At the same time the legal instruments used laid the foundations for the establishment and maintenance of Statistical Registers for Population and Buildings, introducing two unique identifiers (“keys”) in the Census variables and creating the institutional infrastructure for linkage to other administrative registers.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45693151","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}
Data are an integral part of the normative world and therefore ethics. With the advent of big data and data science, increased attention has been given to the ethics of artificial intelligence. However, data ethics is broader than that and must now be considered on its own as a field of ethics. In this paper, we make the case for the importance of data ethics and propose a general framework to support organizations in adopting ethical data practices. We provide the examples of statistics and standards as two contexts within which data ethics can be advanced and where advancements have already been made.
{"title":"A data ethics framework for responsible responsive organizations in the digital world","authors":"Inbal Marcovitch, E. Rancourt","doi":"10.3233/sji-220067","DOIUrl":"https://doi.org/10.3233/sji-220067","url":null,"abstract":"Data are an integral part of the normative world and therefore ethics. With the advent of big data and data science, increased attention has been given to the ethics of artificial intelligence. However, data ethics is broader than that and must now be considered on its own as a field of ethics. In this paper, we make the case for the importance of data ethics and propose a general framework to support organizations in adopting ethical data practices. We provide the examples of statistics and standards as two contexts within which data ethics can be advanced and where advancements have already been made.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44570144","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：