Pub Date : 2022-12-18DOI: 10.1109/IEIR56323.2022.10050062
Huihui Sun, Xinguo Yu
The function learning, as a major focus of attention for the mathematics education research community for several decades, requires humanized tutoring. Recently, several intelligent tutoring systems for mathematics learning have been proposed, which are relying on expert design and hand-crafted worked examples. However, there exists a strong need for a humanized intelligent tutoring platform for function learning, because (i) the function problems being tutored should not be limited by the worked examples, and (ii) it must be able to handle step-wise tutoring and instant feedback in response to a learner's answer. In order to achieve this goal, a relationcentric solving algorithm to support the above needs is proposed, allowing students to provide unrestricted input to the ITSFL platform and providing humanized tutoring service. Results from several empirical studies suggest that the proposed platform can be used in function learning effectively.
{"title":"Research on Solving Text-Diagram Function Problems and Its Application in Tutoring System","authors":"Huihui Sun, Xinguo Yu","doi":"10.1109/IEIR56323.2022.10050062","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050062","url":null,"abstract":"The function learning, as a major focus of attention for the mathematics education research community for several decades, requires humanized tutoring. Recently, several intelligent tutoring systems for mathematics learning have been proposed, which are relying on expert design and hand-crafted worked examples. However, there exists a strong need for a humanized intelligent tutoring platform for function learning, because (i) the function problems being tutored should not be limited by the worked examples, and (ii) it must be able to handle step-wise tutoring and instant feedback in response to a learner's answer. In order to achieve this goal, a relationcentric solving algorithm to support the above needs is proposed, allowing students to provide unrestricted input to the ITSFL platform and providing humanized tutoring service. Results from several empirical studies suggest that the proposed platform can be used in function learning effectively.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128111411","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 : 2022-12-18DOI: 10.1109/IEIR56323.2022.10050074
Wei Deng, Meijuan Liu, Minyu Shen, Xiangmiao Cong
This study uses a physical programming course to explore the development of children’s multiple intelligences. The process includes the design of teaching objectives, course design, course implementation and evaluation of effectiveness. A graphic multiple intelligences test scale was designed to measure children’s multiple intelligences. The study was conducted as a controlled experiment and the implementation of the courses showed that the physical programming coursess had a significant effect on the development of children’s natural observation, visual-spatial and mathematical-logical intelligences compared to the traditional courses.
{"title":"Design and application of a physical programming course for the development of multiple intelligences in children","authors":"Wei Deng, Meijuan Liu, Minyu Shen, Xiangmiao Cong","doi":"10.1109/IEIR56323.2022.10050074","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050074","url":null,"abstract":"This study uses a physical programming course to explore the development of children’s multiple intelligences. The process includes the design of teaching objectives, course design, course implementation and evaluation of effectiveness. A graphic multiple intelligences test scale was designed to measure children’s multiple intelligences. The study was conducted as a controlled experiment and the implementation of the courses showed that the physical programming coursess had a significant effect on the development of children’s natural observation, visual-spatial and mathematical-logical intelligences compared to the traditional courses.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126757184","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}
For developing a math word problem (MWP) solver, the problem text is usually modeled as a word sequence to put into a recursive neural network to capture the quantity relationships presented by the text. Recently, more and more researchers leverage graph-based models for problem representation learning and significant improvements are claimed to have achieved. To explore the potential effectiveness of presentation learning methods on diverse characteristics of benchmark datasets, a comparative analysis of problem representation learning is conducted in this paper. The framework of typical representation learning methods are studied and comparative experiments are implemented to reveal the performance variations in solving different types of math word problems. Experimental results show that, compared to sequence-based problem learning, there is no significant performance improvement after applying graphbased learning methods.
{"title":"Comparative Analysis of Problem Representation Learning in Math Word Problem Solving","authors":"Bin He, Guanghua Liang, Shengnan Chen, Kewen Pan, Zhangwen Miao, Litian Huang","doi":"10.1109/IEIR56323.2022.10050067","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050067","url":null,"abstract":"For developing a math word problem (MWP) solver, the problem text is usually modeled as a word sequence to put into a recursive neural network to capture the quantity relationships presented by the text. Recently, more and more researchers leverage graph-based models for problem representation learning and significant improvements are claimed to have achieved. To explore the potential effectiveness of presentation learning methods on diverse characteristics of benchmark datasets, a comparative analysis of problem representation learning is conducted in this paper. The framework of typical representation learning methods are studied and comparative experiments are implemented to reveal the performance variations in solving different types of math word problems. Experimental results show that, compared to sequence-based problem learning, there is no significant performance improvement after applying graphbased learning methods.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114914644","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 : 2022-12-18DOI: 10.1109/IEIR56323.2022.10050038
Litian Huang, Xinguo Yu, Bin He
The first step in solving geometry problems is to understand problems, and automatic understanding of geometry problems by computers has always been a challenge due to the massive advanced knowledge implied in the text and diagram. This paper proposes a method for geometry problem understanding based on vectorized Syntax-Semantics (S2) model. The proposed method divides the understanding of geometry problems into three parts. Firstly, we modified and optimized vectorized S2 model for understanding explicit arithmetic word problems, and applied it to the text understanding of geometry problems to extract basic geometric relations. Then, based on the idea that a diagram is an extension of problem text, we designed vectorized S2 model of diagram understanding according to the same framework as that of text understanding. All geometry diagrams are transformed into vectors for understanding in a uniform way. Finally, we designed a derived relations generation model based on the diagramet theory to extract derived geometric relations from the basic relations. Experimental results show that the proposed method is effective in understanding geometry problems with diagrams.
{"title":"A Novel Geometry Problem Understanding Method based on Uniform Vectorized Syntax-Semantics Model","authors":"Litian Huang, Xinguo Yu, Bin He","doi":"10.1109/IEIR56323.2022.10050038","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050038","url":null,"abstract":"The first step in solving geometry problems is to understand problems, and automatic understanding of geometry problems by computers has always been a challenge due to the massive advanced knowledge implied in the text and diagram. This paper proposes a method for geometry problem understanding based on vectorized Syntax-Semantics (S2) model. The proposed method divides the understanding of geometry problems into three parts. Firstly, we modified and optimized vectorized S2 model for understanding explicit arithmetic word problems, and applied it to the text understanding of geometry problems to extract basic geometric relations. Then, based on the idea that a diagram is an extension of problem text, we designed vectorized S2 model of diagram understanding according to the same framework as that of text understanding. All geometry diagrams are transformed into vectors for understanding in a uniform way. Finally, we designed a derived relations generation model based on the diagramet theory to extract derived geometric relations from the basic relations. Experimental results show that the proposed method is effective in understanding geometry problems with diagrams.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"84 Pt 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129038938","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 : 2022-12-18DOI: 10.1109/IEIR56323.2022.10050049
Wan Shuo, Chen Zengzhao, Wang Mengke, Shi Yawen, Zhu Shenghu
Teachers’ attention plays an important role in guiding students’ attention and communicating with students. It is a challenging task to measure teachers’ attention non intrusively. This paper first gives the definition of this task, and proposes a specific method to measure teachers’ attention in a given video based on head pose estimation. This method obtains the head posture information by inputting the head image information in the video into the Hopenet, determines the gaze point constant based on the tangent function of the pitch angle, and calculates the teacher’s attention based on the line of gaze and the gaze point range. The experimental results show that the method has high accuracy and is close to human recognition level.
{"title":"Teacher Attention Measurement Based on Head Pose Estimation","authors":"Wan Shuo, Chen Zengzhao, Wang Mengke, Shi Yawen, Zhu Shenghu","doi":"10.1109/IEIR56323.2022.10050049","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050049","url":null,"abstract":"Teachers’ attention plays an important role in guiding students’ attention and communicating with students. It is a challenging task to measure teachers’ attention non intrusively. This paper first gives the definition of this task, and proposes a specific method to measure teachers’ attention in a given video based on head pose estimation. This method obtains the head posture information by inputting the head image information in the video into the Hopenet, determines the gaze point constant based on the tangent function of the pitch angle, and calculates the teacher’s attention based on the line of gaze and the gaze point range. The experimental results show that the method has high accuracy and is close to human recognition level.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121121866","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 : 2022-12-18DOI: 10.1109/IEIR56323.2022.10050071
Yumin Zheng, Chaowang Shang, Cheng Feng, Han Yue
5E Online learning is the main form of integrated teaching, and the emotional experience of 5E online learning is an important embodiment of learners’ learning input. Based on the Ekman theoretical model, this paper designs and develops a cloud model of 5E online learning emotional experience with the six dimensions of “happy, relaxed, anxious, surprised, sad, and boredom which takes the area of the cloud as the main parameter. It determines the characteristic vectors and observation functions that characterize the learner’s emotional experience and evaluates the learner’s 5E online learning emotional experience. Otherwise, it promotes the learner’s 5E online learning ability and optimizes the evaluation of the online teaching process. Taking MOOCS as an example, this paper applies the cloud model to evaluate students’ emotions and verifies its effectiveness through specific data. This method enriches the methods of emotion calculation and characterization for online learners and provides a reference for the current multi-modal sentiment analysis research.
{"title":"An Analysis Method of 5E Online Learning Emotional Experience based on Cloud Model","authors":"Yumin Zheng, Chaowang Shang, Cheng Feng, Han Yue","doi":"10.1109/IEIR56323.2022.10050071","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050071","url":null,"abstract":"5E Online learning is the main form of integrated teaching, and the emotional experience of 5E online learning is an important embodiment of learners’ learning input. Based on the Ekman theoretical model, this paper designs and develops a cloud model of 5E online learning emotional experience with the six dimensions of “happy, relaxed, anxious, surprised, sad, and boredom which takes the area of the cloud as the main parameter. It determines the characteristic vectors and observation functions that characterize the learner’s emotional experience and evaluates the learner’s 5E online learning emotional experience. Otherwise, it promotes the learner’s 5E online learning ability and optimizes the evaluation of the online teaching process. Taking MOOCS as an example, this paper applies the cloud model to evaluate students’ emotions and verifies its effectiveness through specific data. This method enriches the methods of emotion calculation and characterization for online learners and provides a reference for the current multi-modal sentiment analysis research.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128407965","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 : 2022-12-18DOI: 10.1109/IEIR56323.2022.10050076
Wenbin Liu, L. Niu, Jinhua Zhao
The development of artificial intelligence technology has proudly enhanced the quality of life and education of students. The outbreak of COVID-19 in early 2020 dealt a huge blow to the world economy and workplace environment, therefore planning a career path before graduation is a primary and core task for undergraduate students to succeed in this era. This paper introduces the framework design of an intelligent career recommendation system, which is based on the analysis of the required career ability and students’ individual ability to achieve accurate career recommendations.
{"title":"Framework Design of Intelligent Career Recommendation System for Undergraduates","authors":"Wenbin Liu, L. Niu, Jinhua Zhao","doi":"10.1109/IEIR56323.2022.10050076","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050076","url":null,"abstract":"The development of artificial intelligence technology has proudly enhanced the quality of life and education of students. The outbreak of COVID-19 in early 2020 dealt a huge blow to the world economy and workplace environment, therefore planning a career path before graduation is a primary and core task for undergraduate students to succeed in this era. This paper introduces the framework design of an intelligent career recommendation system, which is based on the analysis of the required career ability and students’ individual ability to achieve accurate career recommendations.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134096741","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 : 2022-12-18DOI: 10.1109/IEIR56323.2022.10050041
A. Yousef, Ahmed M. Abd El-Haleem, M. M. Elmesalawy
To prevent the spread of the Covid-19 pandemic, governments have been forced to stop offering educational services directly on campus. Thus, education has moved towards a new path; homes have been transformed into online educational classes through Learning Management Systems (LMS). Despite the many advantages of LMS such as availability, accessibility, and usability, which helps to monitor student learning and manage synchronous and asynchronous learning tools, there are many challenges facing students of applied disciplines such as sciences, engineering, and technology. Among these challenges are the following: how can laboratory experiments be conducted from a distance? How can students’ achievement be measured while conducting their scientific experiment tasks? The current study aimed to reach design criteria for a new system for managing a virtual learning laboratory system (LLS). The Delphi method was used to obtain the opinions of experts and those interested in the field of e-learning design. The responses of (31) experts were analyzed using NVivo software, then the results were analyzed using statistical methods to rank them according to importance through three rounds. The results revealed that the criteria for applying artificial intelligence mechanisms, content management systems through virtual machine, assessment, and accessibility through cloud computing are among the key criteria for designing LLS for science, engineering, and technology disciplines.
{"title":"Determining Critical Success Factors for an Online Laboratory Learning System Using Delphi Method","authors":"A. Yousef, Ahmed M. Abd El-Haleem, M. M. Elmesalawy","doi":"10.1109/IEIR56323.2022.10050041","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050041","url":null,"abstract":"To prevent the spread of the Covid-19 pandemic, governments have been forced to stop offering educational services directly on campus. Thus, education has moved towards a new path; homes have been transformed into online educational classes through Learning Management Systems (LMS). Despite the many advantages of LMS such as availability, accessibility, and usability, which helps to monitor student learning and manage synchronous and asynchronous learning tools, there are many challenges facing students of applied disciplines such as sciences, engineering, and technology. Among these challenges are the following: how can laboratory experiments be conducted from a distance? How can students’ achievement be measured while conducting their scientific experiment tasks? The current study aimed to reach design criteria for a new system for managing a virtual learning laboratory system (LLS). The Delphi method was used to obtain the opinions of experts and those interested in the field of e-learning design. The responses of (31) experts were analyzed using NVivo software, then the results were analyzed using statistical methods to rank them according to importance through three rounds. The results revealed that the criteria for applying artificial intelligence mechanisms, content management systems through virtual machine, assessment, and accessibility through cloud computing are among the key criteria for designing LLS for science, engineering, and technology disciplines.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"474 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117011682","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 : 2022-12-18DOI: 10.1109/IEIR56323.2022.10050069
Tai Wang, Cheng Chen
With the innovation and progress of AI technology, research on AI empowered education has gradually become a hot spot in the education field. However, through the research on the trend of publication in recent years, the research on AI empowered pedagogy has declined. Using the literature visualization software CiteSpace, we collected data from 2012 to August 2022 and analyzed the keywords of AI empowered pedagogy over the past decade. For the relative burst keywords, we analyzed the publication trends for 11 quarters between 2020 and September 2022. We found three types of trends (Attenuation type, Bottleneck type, Growth type) and analyzed the possible causes of the trend. Finally, the paper discusses the possible future research directions.
{"title":"Is the Research on AI Empowered Pedagogy in China Decaying?","authors":"Tai Wang, Cheng Chen","doi":"10.1109/IEIR56323.2022.10050069","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050069","url":null,"abstract":"With the innovation and progress of AI technology, research on AI empowered education has gradually become a hot spot in the education field. However, through the research on the trend of publication in recent years, the research on AI empowered pedagogy has declined. Using the literature visualization software CiteSpace, we collected data from 2012 to August 2022 and analyzed the keywords of AI empowered pedagogy over the past decade. For the relative burst keywords, we analyzed the publication trends for 11 quarters between 2020 and September 2022. We found three types of trends (Attenuation type, Bottleneck type, Growth type) and analyzed the possible causes of the trend. Finally, the paper discusses the possible future research directions.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114422422","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 : 2022-12-18DOI: 10.1109/IEIR56323.2022.10050087
Dan Xia, Yu Zhang, Tongjing Qiu
This study examines how augmented reality (AR) technology can be integrated into educational games to help students learn English. An AR game system was designed and developed for helping students memorize the English vocabulary by providing interesting pictures and impressive surroundings. The system framework, as well as the design and development process of the game were presented in this paper. A case study of the application and evaluation of the game was implemented. In detail, a questionnaire was designed according to the general evaluation methodology of educational games. In this study, the questions of the questionnaire were classified into five aspects: game information, multimedia, interface design, content and feedback. The evaluation results of the game show that the students can memorize the English vocabulary while playing this AR educational game happily. Obviously, the game could increase the learning interests of the students with the aid of the AR technology.
{"title":"The Development and Application of Augmented Reality Educational Game in English Learning","authors":"Dan Xia, Yu Zhang, Tongjing Qiu","doi":"10.1109/IEIR56323.2022.10050087","DOIUrl":"https://doi.org/10.1109/IEIR56323.2022.10050087","url":null,"abstract":"This study examines how augmented reality (AR) technology can be integrated into educational games to help students learn English. An AR game system was designed and developed for helping students memorize the English vocabulary by providing interesting pictures and impressive surroundings. The system framework, as well as the design and development process of the game were presented in this paper. A case study of the application and evaluation of the game was implemented. In detail, a questionnaire was designed according to the general evaluation methodology of educational games. In this study, the questions of the questionnaire were classified into five aspects: game information, multimedia, interface design, content and feedback. The evaluation results of the game show that the students can memorize the English vocabulary while playing this AR educational game happily. Obviously, the game could increase the learning interests of the students with the aid of the AR technology.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130723414","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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