Genetic algorithm is one of the most important mathematical models to simulate biological evolution and recommend the best judgment for the development of things. It is widely used in many fields, such as engineering construction, medical diagnosis, economic management, daily management and so on. Therefore, the fitness running optimization program of middle school students based on genetic algorithm model was studied in this paper. The main process and structure of the genetic algorithm model were described. Based on the analysis of the model structure, the method of improving the genetic algorithm was proposed. Under the background of the rapid development of the Internet, big data, computer information technology and artificial intelligence, the improved algorithm was introduced to establish the optimized genetic algorithm model, so as to promote the fitness running optimization program more targeted and effective. Finally, the fitness running optimization scheme was tested and verified by genetic algorithm, so as to prove that the research has good practicability.
{"title":"Construction of Genetic Algorithm Model for Fitness Program Optimization of Middle School Students","authors":"Weibo Zhou","doi":"10.1145/3448748.3448778","DOIUrl":"https://doi.org/10.1145/3448748.3448778","url":null,"abstract":"Genetic algorithm is one of the most important mathematical models to simulate biological evolution and recommend the best judgment for the development of things. It is widely used in many fields, such as engineering construction, medical diagnosis, economic management, daily management and so on. Therefore, the fitness running optimization program of middle school students based on genetic algorithm model was studied in this paper. The main process and structure of the genetic algorithm model were described. Based on the analysis of the model structure, the method of improving the genetic algorithm was proposed. Under the background of the rapid development of the Internet, big data, computer information technology and artificial intelligence, the improved algorithm was introduced to establish the optimized genetic algorithm model, so as to promote the fitness running optimization program more targeted and effective. Finally, the fitness running optimization scheme was tested and verified by genetic algorithm, so as to prove that the research has good practicability.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121748264","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 this paper a two-stage automatic summarization model is proposed, which combines traditional method with deep learning method. In the first stage, this paper uses improved TextRank algorithm which combines with sentence weight to extract key sentences from multiple documents. In the second stage, a summary sentence is generated from the key sentences sequence based on the Seq2seq model. The experiments on LCSTS and self-constructed corpus show that the scores of the model in this paper of Rouge are all improved with character level input, which shows the effectiveness of the proposed method of this paper.
{"title":"Research on Chinese multi-documents automatic summarizations method based on improved TextRank algorithm and seq2seq","authors":"Weijian Qiu, Yujin Shu, Yongjin Xu","doi":"10.1145/3448748.3448779","DOIUrl":"https://doi.org/10.1145/3448748.3448779","url":null,"abstract":"In this paper a two-stage automatic summarization model is proposed, which combines traditional method with deep learning method. In the first stage, this paper uses improved TextRank algorithm which combines with sentence weight to extract key sentences from multiple documents. In the second stage, a summary sentence is generated from the key sentences sequence based on the Seq2seq model. The experiments on LCSTS and self-constructed corpus show that the scores of the model in this paper of Rouge are all improved with character level input, which shows the effectiveness of the proposed method of this paper.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125585658","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 rapid development of the Internet, more and more donation-based crowdfunding information is published and forwarded on Internet platforms such as Weibo and Moments. How can funders quickly obtain the content they need from the text information of donation-based crowdfunding. How sponsors can obtain financial support has become a very urgent need. This article uses deep learning methods to process the titles of donation-based crowdfunding, and realizes the classification of donation-based crowdfunding texts in different language styles. Research has found that the BERT+CNN-based donation-based crowdfunding title classification model can more accurately classify titles, and is superior to other models in various evaluation indicators. The research results have practical significance for the research in the field of text classification.
{"title":"Donation-Based Crowdfunding Title Classification Based on BERT+CNN","authors":"Gang Zhou","doi":"10.1145/3448748.3448795","DOIUrl":"https://doi.org/10.1145/3448748.3448795","url":null,"abstract":"With the rapid development of the Internet, more and more donation-based crowdfunding information is published and forwarded on Internet platforms such as Weibo and Moments. How can funders quickly obtain the content they need from the text information of donation-based crowdfunding. How sponsors can obtain financial support has become a very urgent need. This article uses deep learning methods to process the titles of donation-based crowdfunding, and realizes the classification of donation-based crowdfunding texts in different language styles. Research has found that the BERT+CNN-based donation-based crowdfunding title classification model can more accurately classify titles, and is superior to other models in various evaluation indicators. The research results have practical significance for the research in the field of text classification.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129184680","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}
Fuzzy resource constrained project scheduling problem (FRCPSP) is an extended problem of RCPSP considering uncertainty. It is a very important research issue, as a NP-hard combinatorial optimization problem and actual application of project scheduling. This paper proposes a hybrid genetic algorithm that combines a non-random initialization, a neighborhood search-based mutation, and two local search strategies. Fuzzy RCPSP uses fuzzy set method to describe uncertainty. It assumes that the activities with random duration changed in an interval, which is composed of optimistic time, pessimistic time and possible time. This paper innovatively converts the interval into 3 optimization objectives, reformulates FRCPSP into a multiobjective optimization model, and designs a hybrid multiobjective genetic algorithm based on NSGA-II for solving this FRCPSP. Finally, benchmarks of RCPSP and extended datasets with fuzzy processing time are adopted to test our approach. Computational results show that our approach performs better than the existing state-of-the-art methods.
{"title":"Fuzzy Resource Constrained Project Scheduling Optimization with Hybrid Multiobjective Genetic Algorithm","authors":"Hang Yang, Yisong Yuan, S. Ye, Lin Lin","doi":"10.1145/3448748.3448793","DOIUrl":"https://doi.org/10.1145/3448748.3448793","url":null,"abstract":"Fuzzy resource constrained project scheduling problem (FRCPSP) is an extended problem of RCPSP considering uncertainty. It is a very important research issue, as a NP-hard combinatorial optimization problem and actual application of project scheduling. This paper proposes a hybrid genetic algorithm that combines a non-random initialization, a neighborhood search-based mutation, and two local search strategies. Fuzzy RCPSP uses fuzzy set method to describe uncertainty. It assumes that the activities with random duration changed in an interval, which is composed of optimistic time, pessimistic time and possible time. This paper innovatively converts the interval into 3 optimization objectives, reformulates FRCPSP into a multiobjective optimization model, and designs a hybrid multiobjective genetic algorithm based on NSGA-II for solving this FRCPSP. Finally, benchmarks of RCPSP and extended datasets with fuzzy processing time are adopted to test our approach. Computational results show that our approach performs better than the existing state-of-the-art methods.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133372130","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}
A Brain-Computer Interface (BCI) aims at providing a way for controlling external devices through the utilization of brain signals. One of the challenges in electroencephalography (EEG)-based BCI is to adjust the brain signal decoder to detect a user's intention as accurately and efficiently as possible, as EEG signals are non-stationary. Therefore, adaptive classification, an approach to adapt to the changes of the EEG signals, would be effective in overcoming this problem. This paper provides a review of the representative adaptive classifiers used in BCI, and it can be divided into four categories: adaptive linear discriminant analysis, adaptive support vector machine, adaptive Bayesian classifiers and adaptive Riemannian Geometry-based classifiers. Besides, the pros and cons of these adaptive classification algorithms are further described.
{"title":"A Review on Adaptive Classifiers for BCI Classification","authors":"Yu-Ze Su","doi":"10.1145/3448748.3448797","DOIUrl":"https://doi.org/10.1145/3448748.3448797","url":null,"abstract":"A Brain-Computer Interface (BCI) aims at providing a way for controlling external devices through the utilization of brain signals. One of the challenges in electroencephalography (EEG)-based BCI is to adjust the brain signal decoder to detect a user's intention as accurately and efficiently as possible, as EEG signals are non-stationary. Therefore, adaptive classification, an approach to adapt to the changes of the EEG signals, would be effective in overcoming this problem. This paper provides a review of the representative adaptive classifiers used in BCI, and it can be divided into four categories: adaptive linear discriminant analysis, adaptive support vector machine, adaptive Bayesian classifiers and adaptive Riemannian Geometry-based classifiers. Besides, the pros and cons of these adaptive classification algorithms are further described.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131944987","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}
Weifeng Zheng, Wentao Zhang, Yuqin Wang, Yinglin Cui
Objective: This paper is to explore the clinical effect of combined use of Jiawei Yiqi Congming Decoction and acupuncture treatment in the treatment of patients with cervical vertigo due to deficiency of qi and blood. Methods: This research work was selected to be carried out in Henan Provincial Hospital of Traditional Chinese Medicine, and the time was from October 2019 to October 2020. The patients were treated in our hospital during this period with cervical vertigo due to deficiency of qi and blood. The number of patients was 100. They were randomly divided into two groups. One group was given pure acupuncture and moxibustion treatment and named the control group, and the other group was given Jiawei Yiqi Congming Decoction combined with acupuncture and moxibustion treatment, and named the experimental group. The treatment effects of the two groups were observed and compared. Results: Before treatment, there was no significant difference in the clinical symptom scores between the two groups, P>0.05. After treatment intervention, the dizziness scores of the experimental group were significantly higher, and the levels of various indicators were significantly lower than those of the control group. The effective rates of treatment for patients were 94.00% and 76.00%. The experimental group is more effective, and the differences in various data indicate P<0.05, and the experimental group has a better treatment effect. Conclusion: In the treatment of patients with cervical vertigo due to deficiency of qi and blood, the combined use of Jiawei Yiqi Congming Decoction and acupuncture treatment has a significant effect, which can improve the clinical symptoms of patients and promote the recovery of patients, which has positive significance for clinical development.
{"title":"Effect of Jiawei Yiqi Congming Decoction Combined with Acupuncture on Cervical Vertigo with Deficiency of Qi and Blood","authors":"Weifeng Zheng, Wentao Zhang, Yuqin Wang, Yinglin Cui","doi":"10.1145/3448748.3448771","DOIUrl":"https://doi.org/10.1145/3448748.3448771","url":null,"abstract":"Objective: This paper is to explore the clinical effect of combined use of Jiawei Yiqi Congming Decoction and acupuncture treatment in the treatment of patients with cervical vertigo due to deficiency of qi and blood. Methods: This research work was selected to be carried out in Henan Provincial Hospital of Traditional Chinese Medicine, and the time was from October 2019 to October 2020. The patients were treated in our hospital during this period with cervical vertigo due to deficiency of qi and blood. The number of patients was 100. They were randomly divided into two groups. One group was given pure acupuncture and moxibustion treatment and named the control group, and the other group was given Jiawei Yiqi Congming Decoction combined with acupuncture and moxibustion treatment, and named the experimental group. The treatment effects of the two groups were observed and compared. Results: Before treatment, there was no significant difference in the clinical symptom scores between the two groups, P>0.05. After treatment intervention, the dizziness scores of the experimental group were significantly higher, and the levels of various indicators were significantly lower than those of the control group. The effective rates of treatment for patients were 94.00% and 76.00%. The experimental group is more effective, and the differences in various data indicate P<0.05, and the experimental group has a better treatment effect. Conclusion: In the treatment of patients with cervical vertigo due to deficiency of qi and blood, the combined use of Jiawei Yiqi Congming Decoction and acupuncture treatment has a significant effect, which can improve the clinical symptoms of patients and promote the recovery of patients, which has positive significance for clinical development.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128391031","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}
Alzheimer's disease is a typical brain cognitive dysfunction disease that seriously affects the work and life of patients. How to diagnose this disease early has always been a concentration and it is also a meaningful field to study. Recently, novel biomarkers has been a topic worthy discussing. Here we summarize the knowledge on Electroencephalography biomarkers for Alzheimer's disease and Event-Related Potentials biomarkers with respect to their importance in the diagnosis of Alzheimer's disease. In addition to that, the focus of the review is about mismatch negativity and its utilization to detect early Alzheimer's disease and Mild cognitive impairment.
{"title":"Review on Early Biomarkers for Alzheimer's Disease Based on Electroencephalography (EEG) and Event-Related Potentials (ERP's)","authors":"Chenyu Zhang","doi":"10.1145/3448748.3448764","DOIUrl":"https://doi.org/10.1145/3448748.3448764","url":null,"abstract":"Alzheimer's disease is a typical brain cognitive dysfunction disease that seriously affects the work and life of patients. How to diagnose this disease early has always been a concentration and it is also a meaningful field to study. Recently, novel biomarkers has been a topic worthy discussing. Here we summarize the knowledge on Electroencephalography biomarkers for Alzheimer's disease and Event-Related Potentials biomarkers with respect to their importance in the diagnosis of Alzheimer's disease. In addition to that, the focus of the review is about mismatch negativity and its utilization to detect early Alzheimer's disease and Mild cognitive impairment.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125301688","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 Google Hadoop platform Map/Reduce task scheduling and distribution mechanism of the Hadoop distributed computing framework applied to cloud computing and big data. The Quartz open source job scheduler regularly crawls into the websites of different tourist attractions, and stores the tourist attractions prices calculated by the price comparison algorithm to the Database HBase distribution Computing System. When the user enters the planned departure place, departure date, tourist attractions and other specific conditions, the cloud platform price comparison strategy system will display tourist routes according to certain logic, and generate price comparison data for tourist attractions, from the travel start point to the travel destination. The price comparison strategy of clothing, food, housing, transportation and consumption generates cost prices, recommends the best travel planning plan for customers, helps users choose the most economical tourist attractions and tourist routes to make quick choices, and obtain satisfactory returns for short vacations or holidays to avoid delay in decision-making time.
{"title":"A Big Data Platform Tourism Price Strategy Method with Map/Reduce","authors":"Haiyan Lv, Zhiqiang Li, Baoqiang Wen, Chauan Wan","doi":"10.1145/3448748.3448989","DOIUrl":"https://doi.org/10.1145/3448748.3448989","url":null,"abstract":"The Google Hadoop platform Map/Reduce task scheduling and distribution mechanism of the Hadoop distributed computing framework applied to cloud computing and big data. The Quartz open source job scheduler regularly crawls into the websites of different tourist attractions, and stores the tourist attractions prices calculated by the price comparison algorithm to the Database HBase distribution Computing System. When the user enters the planned departure place, departure date, tourist attractions and other specific conditions, the cloud platform price comparison strategy system will display tourist routes according to certain logic, and generate price comparison data for tourist attractions, from the travel start point to the travel destination. The price comparison strategy of clothing, food, housing, transportation and consumption generates cost prices, recommends the best travel planning plan for customers, helps users choose the most economical tourist attractions and tourist routes to make quick choices, and obtain satisfactory returns for short vacations or holidays to avoid delay in decision-making time.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132337978","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}
Alzheimers disease (AD), the most common form of dementia, affects more than 50 million people worldwide, with no current treatment to halt the disease. The exact molecular mechanisms modulating disease progression remains elusive, even though numerous studies using mouse AD models have been done. In addition, as mouse models do not fully recapitulate human pathology, it is unclear to what extent results acquired from mouse models can be applied to treat humans. In this study, we conducted comprehensive bioinformatics analyses on transcriptomic profiles from mice bearing Abeta or tau pathology and human AD to identify differentially expressed genes (DEGs) and biological pathways shared among them. We identified the disease-associated microglia (DAM) signature and inflammatory pathways in both amyloid and tau mouse models compared to controls. Although GFAP was the only DEG shared by human AD and mouse AD models, pathways such as inflammatory response were identified in both human and mouse. Common pathways found in this study may modulate disease progression and provide new therapeutic targets.
{"title":"A Bioinformatics Analysis of Gene Expression Changes in Human Alzheimer's Disease and Mouse Models","authors":"Kai Xu, Yingyue Zhou","doi":"10.1145/3448748.3448755","DOIUrl":"https://doi.org/10.1145/3448748.3448755","url":null,"abstract":"Alzheimers disease (AD), the most common form of dementia, affects more than 50 million people worldwide, with no current treatment to halt the disease. The exact molecular mechanisms modulating disease progression remains elusive, even though numerous studies using mouse AD models have been done. In addition, as mouse models do not fully recapitulate human pathology, it is unclear to what extent results acquired from mouse models can be applied to treat humans. In this study, we conducted comprehensive bioinformatics analyses on transcriptomic profiles from mice bearing Abeta or tau pathology and human AD to identify differentially expressed genes (DEGs) and biological pathways shared among them. We identified the disease-associated microglia (DAM) signature and inflammatory pathways in both amyloid and tau mouse models compared to controls. Although GFAP was the only DEG shared by human AD and mouse AD models, pathways such as inflammatory response were identified in both human and mouse. Common pathways found in this study may modulate disease progression and provide new therapeutic targets.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128055320","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 mining plays an important role in all kinds of practical applications in modern society. In recent years, with the exponential growth trend of data produced and accumulated in various industries, data mining has attracted the attention of many researchers. Hadoop distributed software framework is the most commonly used framework to build cloud platform. This paper introduces the latest progress of parallel data mining applications in Hadoop platform, such as book management, cloud computing, industry, scientific research and water treatment, traffic management and other practical applications such as daily life management.
{"title":"Recent advances on the application of big data framework based on Hadoop platform","authors":"Xiao Zhang, H. Xu, Haiquan Wang, Xu Chen","doi":"10.1145/3448748.3448782","DOIUrl":"https://doi.org/10.1145/3448748.3448782","url":null,"abstract":"Data mining plays an important role in all kinds of practical applications in modern society. In recent years, with the exponential growth trend of data produced and accumulated in various industries, data mining has attracted the attention of many researchers. Hadoop distributed software framework is the most commonly used framework to build cloud platform. This paper introduces the latest progress of parallel data mining applications in Hadoop platform, such as book management, cloud computing, industry, scientific research and water treatment, traffic management and other practical applications such as daily life management.","PeriodicalId":115821,"journal":{"name":"Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129279877","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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