Online Health Community (OHC) can help to reduce patients medical expenses, improve doctors service quality, and provide a channel for doctor to earn extra money. Therefore, OHC is widely accepted by doctors and patients, and become a typical application scenario of internet plus. Using data from Haodf.com, the largest Chinese online health community, and the website of Beijing Health Planning Commission, we explore the influence of penetration rate of online health service on quality and price of doctors online consulting service. Moreover, we investigate how such effects differ across different types of hospitals. The results suggest that online penetration rate positively affects the quality of doctors services and negatively affects the online service price. In addition, the online penetration rate has a bigger impact on the consulting price of doctors in specialized hospitals than that of doctors in general hospitals.
在线健康社区(Online Health Community, OHC)可以帮助患者减少医疗费用，提高医生的服务质量，并为医生提供一个赚取额外收入的渠道。因此，OHC被医生和患者广泛接受，成为互联网+的典型应用场景。利用中国最大的在线健康社区好医网和北京市卫计委网站的数据，探讨网络健康服务渗透率对医生在线咨询服务质量和价格的影响。此外，我们调查了这种影响在不同类型的医院之间的差异。结果表明，网络渗透率对医生服务质量有正向影响，对网络服务价格有负向影响。此外，网络渗透率对专科医院医生咨询价格的影响大于综合医院医生。
{"title":"The Impact of Penetration Rate of Online Health Service on Service Quality and Price: Evidence from Online Health Communities","authors":"Junwei Kuang, Lini Kuang, Zhijun Yan","doi":"10.1145/3265689.3265720","DOIUrl":"https://doi.org/10.1145/3265689.3265720","url":null,"abstract":"Online Health Community (OHC) can help to reduce patients medical expenses, improve doctors service quality, and provide a channel for doctor to earn extra money. Therefore, OHC is widely accepted by doctors and patients, and become a typical application scenario of internet plus. Using data from Haodf.com, the largest Chinese online health community, and the website of Beijing Health Planning Commission, we explore the influence of penetration rate of online health service on quality and price of doctors online consulting service. Moreover, we investigate how such effects differ across different types of hospitals. The results suggest that online penetration rate positively affects the quality of doctors services and negatively affects the online service price. In addition, the online penetration rate has a bigger impact on the consulting price of doctors in specialized hospitals than that of doctors in general hospitals.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"21 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126117430","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}
Yifan Du, Yuanlin Zhu, Shengjie Wu, Lihui Wang, Yuemin M. Zhu, Feng Yang
Myocardial segmentation plays an important role for quantitative evaluation of heart diseases and cardiac image processing and analysis. However, myocardial segmentation has always been a challenging task because gray scale intensities of the myocardium and tissues around the heart are very close and that significant differences exist in myocardial structure between different slices or slices at different times. Traditional segmentation algorithms are difficult to obtain accurate and robust segmentation results and are usually semi-automatic which require manual operations and extra workload. Therefore, the development of a fully automatic myocardial segmentation algorithm is an appealing research goal. In this paper, we propose an automatic myocardial segmentation algorithm based on fully convolutional neural networks. By building an end-to-end model, the segmentation speed has been improved without affecting the segmentation accuracy. Performance comparisons between the proposed HeartNet and state-of-art methods demonstrated the effectiveness of our algorithm, which achieved an average DSC of 90.48% by segmenting 144.9 frames per second.
{"title":"Automatic Segmentation of Left Myocardium in CMR Based on Fully Convolutional Networks","authors":"Yifan Du, Yuanlin Zhu, Shengjie Wu, Lihui Wang, Yuemin M. Zhu, Feng Yang","doi":"10.1145/3265689.3265710","DOIUrl":"https://doi.org/10.1145/3265689.3265710","url":null,"abstract":"Myocardial segmentation plays an important role for quantitative evaluation of heart diseases and cardiac image processing and analysis. However, myocardial segmentation has always been a challenging task because gray scale intensities of the myocardium and tissues around the heart are very close and that significant differences exist in myocardial structure between different slices or slices at different times. Traditional segmentation algorithms are difficult to obtain accurate and robust segmentation results and are usually semi-automatic which require manual operations and extra workload. Therefore, the development of a fully automatic myocardial segmentation algorithm is an appealing research goal. In this paper, we propose an automatic myocardial segmentation algorithm based on fully convolutional neural networks. By building an end-to-end model, the segmentation speed has been improved without affecting the segmentation accuracy. Performance comparisons between the proposed HeartNet and state-of-art methods demonstrated the effectiveness of our algorithm, which achieved an average DSC of 90.48% by segmenting 144.9 frames per second.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116727949","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}
With the advent of big data, data mining theories and methods face new challenges. This paper tries to find the impacts of big data on data mining research through 23377 data mining-related papers published in Chinese academic journals during 1996--2016. By utilization of various methods of bibliometrics, this study conducts three different levels of analysis to gradually dig deeper into the contents of literature. For the macro-level, paper amount analysis results show that big data-related research began in 2012 and has brought new growth to data mining area. For the meso-level, journal distribution analysis results indicate that many other disciplines, such as arts and agriculture science, began to apply data mining techniques with the wide spread of big data. For the micro-level, co-word-based research topic clustering results imply that new topics emerged due to the easy access of big data, such as 'clouding computing' and 'teaching and learning analysis'.
{"title":"Impacts of Big Data on Data Mining Research: An Empirical Study of Chinese Journals","authors":"Yue Huang","doi":"10.1145/3265689.3265706","DOIUrl":"https://doi.org/10.1145/3265689.3265706","url":null,"abstract":"With the advent of big data, data mining theories and methods face new challenges. This paper tries to find the impacts of big data on data mining research through 23377 data mining-related papers published in Chinese academic journals during 1996--2016. By utilization of various methods of bibliometrics, this study conducts three different levels of analysis to gradually dig deeper into the contents of literature. For the macro-level, paper amount analysis results show that big data-related research began in 2012 and has brought new growth to data mining area. For the meso-level, journal distribution analysis results indicate that many other disciplines, such as arts and agriculture science, began to apply data mining techniques with the wide spread of big data. For the micro-level, co-word-based research topic clustering results imply that new topics emerged due to the easy access of big data, such as 'clouding computing' and 'teaching and learning analysis'.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134079419","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}
Since 2015, Robotic Process Automation (RPA), the software robot, imitate human behaviors to take complicated tasks is more and more popular in various industry. The current references are mainly concepts the case studiess that focused on the dedicated enterprise, however, less of generalization. For the goal of stepping out and going further of find the genera key factors about RPA-Business alignment, researchers will use multi-valued qualitative comparative (mvQCA) method and IT-Business alignment theory. The general factors of IT-Business alignment can also affect RPA-Business. Second, there are two ways to accelerate the RPA-business alignment and six ways to slow down RPA-business alignment from the calculation results. The positive and negative have different configurations. With this research result, other mvQCA requirements could take the most of the positive factors of RPA-Business alignment. Meanwhile, the negative factors can avoid in advance. The essence of RPA is information technology.
{"title":"The Key Factors Affecting RPA-business Alignment","authors":"Ning Zhang, Bo Liu","doi":"10.1145/3265689.3265699","DOIUrl":"https://doi.org/10.1145/3265689.3265699","url":null,"abstract":"Since 2015, Robotic Process Automation (RPA), the software robot, imitate human behaviors to take complicated tasks is more and more popular in various industry. The current references are mainly concepts the case studiess that focused on the dedicated enterprise, however, less of generalization. For the goal of stepping out and going further of find the genera key factors about RPA-Business alignment, researchers will use multi-valued qualitative comparative (mvQCA) method and IT-Business alignment theory. The general factors of IT-Business alignment can also affect RPA-Business. Second, there are two ways to accelerate the RPA-business alignment and six ways to slow down RPA-business alignment from the calculation results. The positive and negative have different configurations. With this research result, other mvQCA requirements could take the most of the positive factors of RPA-Business alignment. Meanwhile, the negative factors can avoid in advance. The essence of RPA is information technology.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124048578","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}
Gamification is a promising approach to enhance user experience in many contexts. Taking a motivational perspective and using the motivational affordances theory as a guiding framework, this paper presents a literature analysis of 60 journal articles that study motivational influences of gamification in information technology design. Our results reveal that four types of game design features and eight basic human needs are studied in this pool of literature. Correspondence analysis indicates some interesting associations between game design features and basic human needs. We discuss the findings and suggest potential directions for future investigations.
{"title":"Gamification and Basic Human Needs in Information Technology Design: A Literature Analysis","authors":"Jian Tang, Ping Zhang","doi":"10.1145/3265689.3265695","DOIUrl":"https://doi.org/10.1145/3265689.3265695","url":null,"abstract":"Gamification is a promising approach to enhance user experience in many contexts. Taking a motivational perspective and using the motivational affordances theory as a guiding framework, this paper presents a literature analysis of 60 journal articles that study motivational influences of gamification in information technology design. Our results reveal that four types of game design features and eight basic human needs are studied in this pool of literature. Correspondence analysis indicates some interesting associations between game design features and basic human needs. We discuss the findings and suggest potential directions for future investigations.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122653613","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}
Product reviews in the network shopping platform provide references to customs' purchase decision. However, existing researches on opinion objects mainly focus on explicit features, and few of scholars take implicit features into consideration. In this paper, based on Chinese online comments data preprocessing. We proposed a Fuzzy C-means algorithm based on Simulated Annealing (SA-FCM) to cluster the explicit comment sentences into 9 classes. And put each class of comment sentences into a document set. Then association rules between opinion words and opinion objects in every document set are mined and build an association rules table among classes, opinion targets and opinion words. The implicit features are discovered according to the opinion words in the association rule table. Finally, the implicit features excavate method proposed in this paper can effectively improve the accuracy of the extraction effect through an experiment verification.
{"title":"Extracting Implicit Features Based on Association Rules","authors":"Zhishuo Liu, Qianhui Shen, Jingmiao Ma","doi":"10.1145/3265689.3265707","DOIUrl":"https://doi.org/10.1145/3265689.3265707","url":null,"abstract":"Product reviews in the network shopping platform provide references to customs' purchase decision. However, existing researches on opinion objects mainly focus on explicit features, and few of scholars take implicit features into consideration. In this paper, based on Chinese online comments data preprocessing. We proposed a Fuzzy C-means algorithm based on Simulated Annealing (SA-FCM) to cluster the explicit comment sentences into 9 classes. And put each class of comment sentences into a document set. Then association rules between opinion words and opinion objects in every document set are mined and build an association rules table among classes, opinion targets and opinion words. The implicit features are discovered according to the opinion words in the association rule table. Finally, the implicit features excavate method proposed in this paper can effectively improve the accuracy of the extraction effect through an experiment verification.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127610190","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}
An adaptive and intelligent prototype of knowledge construction for college students, information to Intelligence(itoI), is proposed in this paper. During the process of knowledge construction, the system records all kinds of online study performance of each student, and then interdisciplinary coursework is automatically assigned to the right students. Both the student and the system improve their knowledge level and intelligence level adaptively. Through the random survey on college student of Shandong Normal University, the results show that it is useful for guiding the process of online learning.
本文提出了一种面向大学生的自适应智能知识构建原型——信息到智能(information to Intelligence, itoI)。在知识构建的过程中，系统记录每个学生的各种在线学习表现，然后自动将跨学科的课程分配给合适的学生。学生和系统都能自适应地提高自己的知识水平和智力水平。通过对山东师范大学大学生的随机调查，结果表明该方法对指导在线学习的过程是有益的。
{"title":"information to Intelligence(itoI): An Adaptive and Intelligent Prototype of Knowledge Construction for College Student","authors":"Li Sun, Hua-lei Wang, Yongxin Zhang, Yinggang Liu, Hongchen Wu, Yanhui Ding, Jinghuan Zhang","doi":"10.1145/3265689.3265691","DOIUrl":"https://doi.org/10.1145/3265689.3265691","url":null,"abstract":"An adaptive and intelligent prototype of knowledge construction for college students, information to Intelligence(itoI), is proposed in this paper. During the process of knowledge construction, the system records all kinds of online study performance of each student, and then interdisciplinary coursework is automatically assigned to the right students. Both the student and the system improve their knowledge level and intelligence level adaptively. Through the random survey on college student of Shandong Normal University, the results show that it is useful for guiding the process of online learning.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126222616","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}
Crowd Funding is a behavior that raises funds for projects or venture capital by generating a small amount of money from a large number of people. It started late in China, but has rapidly been developeing. At present, the research on crowdfunding in China is still at an early stage and lacks deep-level exploration Those researches mostly focus on the meaning, characteristics, and operating methods of crowd Funding. Therefore, this paper takes crowd Funding literature as the research object, using CiteSpace to map, describe and counts the related keywords and cited references in the target domain. Starting with the cited relations among the existing studies of core database, focusing on weighted documents, this papaer analyzes the relationship of cooccurrence in crowd funding papers, and conductes research hotspots, trends and knowledge structures in the "Crowd Funding" field. The results show that the business economy is the largest research category in crowdfunding, followed by computer science and government laws and regulations, and there are also studies about crowdfunding from the perspective of the environmental ecology science, public management and social science.
{"title":"A Bibliometric Analysis of Crowdfunding Related Research: Current trends and Future Prospect","authors":"Wei Zhang, Yan-chun Zhu, Xiao-Lin Wu","doi":"10.1145/3265689.3265702","DOIUrl":"https://doi.org/10.1145/3265689.3265702","url":null,"abstract":"Crowd Funding is a behavior that raises funds for projects or venture capital by generating a small amount of money from a large number of people. It started late in China, but has rapidly been developeing. At present, the research on crowdfunding in China is still at an early stage and lacks deep-level exploration Those researches mostly focus on the meaning, characteristics, and operating methods of crowd Funding. Therefore, this paper takes crowd Funding literature as the research object, using CiteSpace to map, describe and counts the related keywords and cited references in the target domain. Starting with the cited relations among the existing studies of core database, focusing on weighted documents, this papaer analyzes the relationship of cooccurrence in crowd funding papers, and conductes research hotspots, trends and knowledge structures in the \"Crowd Funding\" field. The results show that the business economy is the largest research category in crowdfunding, followed by computer science and government laws and regulations, and there are also studies about crowdfunding from the perspective of the environmental ecology science, public management and social science.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"599 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134435377","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 rapid development of the sharing economy has brought positive effects to many people, but it has also led to some negative consequences. Among them, the negative externalities to society caused by disorderly development of the sharing economy are particularly evident. This paper uses the qualitative comparative analysis (QCA) method to study the sources of negative externality in the sharing economy, and puts forward three paths for the negative externality source. It is clear that the costs and benefits of individual behavior, convenience of behavior, and extent of public goods attribute, degree of separation of property rights, and restraint mechanisms contribute to these negative externalities. Findings reveal that negative externalities in the sharing economy come from the joint effect of the sharing degree of the product or service and the constraint mechanism, indicating that the current main modes of the shared economy increase the possibility of negative externalities.
{"title":"Study on the Source of Negative Externality in the Sharing Economy","authors":"Wenjun Jing, Baowen Sun","doi":"10.1145/3265689.3265701","DOIUrl":"https://doi.org/10.1145/3265689.3265701","url":null,"abstract":"The rapid development of the sharing economy has brought positive effects to many people, but it has also led to some negative consequences. Among them, the negative externalities to society caused by disorderly development of the sharing economy are particularly evident. This paper uses the qualitative comparative analysis (QCA) method to study the sources of negative externality in the sharing economy, and puts forward three paths for the negative externality source. It is clear that the costs and benefits of individual behavior, convenience of behavior, and extent of public goods attribute, degree of separation of property rights, and restraint mechanisms contribute to these negative externalities. Findings reveal that negative externalities in the sharing economy come from the joint effect of the sharing degree of the product or service and the constraint mechanism, indicating that the current main modes of the shared economy increase the possibility of negative externalities.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133227449","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}
In the present paper, we analyze electroencephalogram (EEG) signals recorded by a single frontal channel from 105 elderly subjects while they were responding to an attention-demanded task (Stroop color test). The first objective is to discover how post-cue frequency band oscillations of EEG, as neural index of attention, are correlated with elderly response time (RT), as behavioral index of attention. Furthermore, we aim to detect the most informative period of brain activity (EEG) in which the strongest correlations with reaction time exist. Our results show that 1) there is significant negative correlation between alpha gamma ratio (AGR) and response time (p<0.0001), 2) theta beta ratio (TBR) is positively correlated with subjects' response time (p<0.0001) and 3) these correlations are stronger in a 500ms period right after triggering the cue (question onset in Stroop test). Our study provides an insight into the research on analysis and prediction of subject behavior from EEG. Moreover, it has potential to be used in implementation of feasible and efficient single channel EEG-based brain computer interface (BCI) training systems for elderly.
{"title":"Neural Indexes of Attention Extracted from EEG Correlate with Elderly Reaction Time in response to an Attentional Task","authors":"Fatemeh Fahimi, Wooi-Boon Goh, Tih-Shih Lee, Cuntai Guan","doi":"10.1145/3265689.3265722","DOIUrl":"https://doi.org/10.1145/3265689.3265722","url":null,"abstract":"In the present paper, we analyze electroencephalogram (EEG) signals recorded by a single frontal channel from 105 elderly subjects while they were responding to an attention-demanded task (Stroop color test). The first objective is to discover how post-cue frequency band oscillations of EEG, as neural index of attention, are correlated with elderly response time (RT), as behavioral index of attention. Furthermore, we aim to detect the most informative period of brain activity (EEG) in which the strongest correlations with reaction time exist. Our results show that 1) there is significant negative correlation between alpha gamma ratio (AGR) and response time (p<0.0001), 2) theta beta ratio (TBR) is positively correlated with subjects' response time (p<0.0001) and 3) these correlations are stronger in a 500ms period right after triggering the cue (question onset in Stroop test). Our study provides an insight into the research on analysis and prediction of subject behavior from EEG. Moreover, it has potential to be used in implementation of feasible and efficient single channel EEG-based brain computer interface (BCI) training systems for elderly.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123728862","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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