Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622244
Dilruba Showkat, M. Kabir
Multi-objective optimization plays a significant role in optimizing many real life problems, where we desire to optimize more than one objective. Numerous multi-objective optimization algorithm exists in research. NSGA-II and SPEA2 are widely used multi-objective optimization algorithms. SPEA2+ algorithm performs better than the other multi-objective optimization algorithms in terms of searching and maintaining diversity in the optimal solution. In this research, to reconstruct the gene regulatory network we have proposed a new Hybrid SPEA2+ algorithm based inference method. We have proposed a new objective function to obtain sparse gene network structure more precisely. To reverse engineer the gene regulatory network we have used linear time variant model. The proposed approach is at first tested against synthetic noise free time series datasets. It has successfully inferred all the correct regulations from noise free time series datasets. Then it was applied on synthetic noisy time series datasets. Even with the presence of noise, the proposed method have correctly captured all the correct gene regulations successfully. The proposed reconstruction method has been further validated by analyzing the real gene expression datasets of SOS DNA repair system in Escherichia coli. Our proposed method have shown its potency in finding more correct regulations and this has been confirmed by comparing the obtained gene regulations with the results of other existing researches.
{"title":"Inference of genetic networks using multi-objective hybrid SPEA2+ from Microarray data","authors":"Dilruba Showkat, M. Kabir","doi":"10.1109/ICCI-CC.2013.6622244","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622244","url":null,"abstract":"Multi-objective optimization plays a significant role in optimizing many real life problems, where we desire to optimize more than one objective. Numerous multi-objective optimization algorithm exists in research. NSGA-II and SPEA2 are widely used multi-objective optimization algorithms. SPEA2+ algorithm performs better than the other multi-objective optimization algorithms in terms of searching and maintaining diversity in the optimal solution. In this research, to reconstruct the gene regulatory network we have proposed a new Hybrid SPEA2+ algorithm based inference method. We have proposed a new objective function to obtain sparse gene network structure more precisely. To reverse engineer the gene regulatory network we have used linear time variant model. The proposed approach is at first tested against synthetic noise free time series datasets. It has successfully inferred all the correct regulations from noise free time series datasets. Then it was applied on synthetic noisy time series datasets. Even with the presence of noise, the proposed method have correctly captured all the correct gene regulations successfully. The proposed reconstruction method has been further validated by analyzing the real gene expression datasets of SOS DNA repair system in Escherichia coli. Our proposed method have shown its potency in finding more correct regulations and this has been confirmed by comparing the obtained gene regulations with the results of other existing researches.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126375650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622221
Yingxu Wang
Semantics is the meaning of a language unit at the levels of word, phrase, sentence, paragraph, and essay. Cognitive linguistics focuses on cognitive semantics of sentences and its interaction with syntactic structures. A denotational mathematical framework of language semantics known as semantic algebra is developed in this paper. Semantic algebra reveals the nature of semantics by a general mathematical model. On the basis of the formal semantic structure, language semantics can be deductively manipulated by a set of algebraic operations at different levels of language units. According to semantic algebra, semantic interpretation and comprehension can be embodied as a process of formal semantic aggregation in cognitive linguistics from the bottom up. Applications of semantic algebra are illustrated in computational linguistics, computing with words, cognitive informatics, and cognitive computing.
{"title":"A semantic algebra for cognitive linguistics and cognitive computing","authors":"Yingxu Wang","doi":"10.1109/ICCI-CC.2013.6622221","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622221","url":null,"abstract":"Semantics is the meaning of a language unit at the levels of word, phrase, sentence, paragraph, and essay. Cognitive linguistics focuses on cognitive semantics of sentences and its interaction with syntactic structures. A denotational mathematical framework of language semantics known as semantic algebra is developed in this paper. Semantic algebra reveals the nature of semantics by a general mathematical model. On the basis of the formal semantic structure, language semantics can be deductively manipulated by a set of algebraic operations at different levels of language units. According to semantic algebra, semantic interpretation and comprehension can be embodied as a process of formal semantic aggregation in cognitive linguistics from the bottom up. Applications of semantic algebra are illustrated in computational linguistics, computing with words, cognitive informatics, and cognitive computing.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129154927","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}
Predictive display based on virtual environment models is an effective method of solving the problem of time delay in teleoperation. However, this method will not work well without the precise virtual environment model. Thus, it is of great significance that augmented reality with video feedback is introduced into teleoperation, instead of the virtual environment models. A teleoperation system platform based on augmented reality was developed to improve system stability and enhance system telepresence, facilitating the operator's observation and operation. The improved algorithm ARToolkit-based made the system adaptable to many types of lighting environments. This paper introduces system structure and the realization of key modules. Lots of experiments such as pressing the button, pulling the drawer and so on are also conducted to evaluate the system performance. The simulation results indicate that the proposed system can compensate the defect of prediction and improve teleoperation system reliability.
{"title":"Design and implementation of the teleoperation platform based on augmented reality","authors":"Huan Hu, Xin Gao, Hanxu Sun, Q. Jia, Yanheng Zhang","doi":"10.1109/ICCI-CC.2013.6622234","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622234","url":null,"abstract":"Predictive display based on virtual environment models is an effective method of solving the problem of time delay in teleoperation. However, this method will not work well without the precise virtual environment model. Thus, it is of great significance that augmented reality with video feedback is introduced into teleoperation, instead of the virtual environment models. A teleoperation system platform based on augmented reality was developed to improve system stability and enhance system telepresence, facilitating the operator's observation and operation. The improved algorithm ARToolkit-based made the system adaptable to many types of lighting environments. This paper introduces system structure and the realization of key modules. Lots of experiments such as pressing the button, pulling the drawer and so on are also conducted to evaluate the system performance. The simulation results indicate that the proposed system can compensate the defect of prediction and improve teleoperation system reliability.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128270270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622218
A. R. Rao
Summary form only given. Technological advances over the past five years have led to an unprecedented level of volume and detail in the acquisition of neuroscientific data relating to the mammalian brain. However, this creates significant challenges in the processing and interpretation of the data. We will adopt a network-centric approach to tackle this, as it matches the physical structure of the brain. We present methods to extract functional brain networks from spatio-temporal time series that describe neural activity, such as in functional magnetic resonance imaging (fMRI). These networks capture intrinsic brain dynamics. We describe computational methods to extract topological regularities in such networks, including motifs and cycles. We analyze the relations hip between the structure of the network, as represented by its motifs, and its function. For instance, example hub neurons in the hippocampus promote synchrony and shortest loops act as pacemakers of neural activity. We demonstrate the relevance of the network analysis techniques in understanding specific brain-related disorders such as schizophrenia and autism. For instance, the disruption of cortical networks involved in synchronization may be a contributor to autism and schizophrenic patients which have been shown to have higher connectivity within the default mode network.
{"title":"The measurement and analysis of cortical networks","authors":"A. R. Rao","doi":"10.1109/ICCI-CC.2013.6622218","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622218","url":null,"abstract":"Summary form only given. Technological advances over the past five years have led to an unprecedented level of volume and detail in the acquisition of neuroscientific data relating to the mammalian brain. However, this creates significant challenges in the processing and interpretation of the data. We will adopt a network-centric approach to tackle this, as it matches the physical structure of the brain. We present methods to extract functional brain networks from spatio-temporal time series that describe neural activity, such as in functional magnetic resonance imaging (fMRI). These networks capture intrinsic brain dynamics. We describe computational methods to extract topological regularities in such networks, including motifs and cycles. We analyze the relations hip between the structure of the network, as represented by its motifs, and its function. For instance, example hub neurons in the hippocampus promote synchrony and shortest loops act as pacemakers of neural activity. We demonstrate the relevance of the network analysis techniques in understanding specific brain-related disorders such as schizophrenia and autism. For instance, the disruption of cortical networks involved in synchronization may be a contributor to autism and schizophrenic patients which have been shown to have higher connectivity within the default mode network.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123657673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-16DOI: 10.4018/IJCINI.2014040104
A. Abe
In this paper, first I review the basic theories-concept and computational realization of abduction. Then I brefly review chance discovery which focuses on rare and novel events. In addition I briefly review the concept of affordance porposed by Gibson. By using the above concepts and techniques, a dementia care system inspired by affordance is proposed and discussed Finally I introduce chance discovery based curation proposed by me. The dementia care system is discussed from the aspect of communication and chance discovery based curation.
{"title":"Cognitive Chance Discovery: From abduction to affordance and curation","authors":"A. Abe","doi":"10.4018/IJCINI.2014040104","DOIUrl":"https://doi.org/10.4018/IJCINI.2014040104","url":null,"abstract":"In this paper, first I review the basic theories-concept and computational realization of abduction. Then I brefly review chance discovery which focuses on rare and novel events. In addition I briefly review the concept of affordance porposed by Gibson. By using the above concepts and techniques, a dementia care system inspired by affordance is proposed and discussed Finally I introduce chance discovery based curation proposed by me. The dementia care system is discussed from the aspect of communication and chance discovery based curation.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132016799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622243
Pedro Valero-Lara, F. Pelayo
Nowadays, due to massively parallel characteristics of current many-core architectures, these devices are not only being used in order to exploit data-parallelism and to minimize the execution time in a single problem, but, they are beginning to be used in order both to execute and to increase the performances when executing more than one application simultaneously. In this work, we provide a performance analysis on the use of current many-core architectures for this new purpose; this performance analysis has been carried out over two different many-core architectures. Furthermore, two different programming approaches to tackle this new role have been tested. The results so obtained show that a increase in the computational requirements implies an important fall in performance. The main objective of this paper is to explain the reasons for this behavior, and afterwards, to propose a set of alternatives to deal with these disadvantages previously mentioned.
{"title":"Analysis in performance and new model for multiple kernels executions on many-core architectures","authors":"Pedro Valero-Lara, F. Pelayo","doi":"10.1109/ICCI-CC.2013.6622243","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622243","url":null,"abstract":"Nowadays, due to massively parallel characteristics of current many-core architectures, these devices are not only being used in order to exploit data-parallelism and to minimize the execution time in a single problem, but, they are beginning to be used in order both to execute and to increase the performances when executing more than one application simultaneously. In this work, we provide a performance analysis on the use of current many-core architectures for this new purpose; this performance analysis has been carried out over two different many-core architectures. Furthermore, two different programming approaches to tackle this new role have been tested. The results so obtained show that a increase in the computational requirements implies an important fall in performance. The main objective of this paper is to explain the reasons for this behavior, and afterwards, to propose a set of alternatives to deal with these disadvantages previously mentioned.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132876722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622236
Du Zhang
It is a grand challenge to build intelligent agent systems that can improve their problem-solving performance through perpetual learning. In our previous work, we have proposed a special type of perpetual learning paradigm called inconsistency-induced learning, or i2Learning, along with several inconsistency-specific learning algorithms. i2Learning is a step toward meeting the challenge. The work reported in this paper is a continuation of the ongoing research with i2Learning. We describe two more learning algorithms for incompatible inconsistency and anti-subsumption inconsistency in the context of i2Learning. The results will be incorporated into empirical studies as part of future work.
{"title":"Learning through overcoming incompatible and anti-subsumption inconsistencies","authors":"Du Zhang","doi":"10.1109/ICCI-CC.2013.6622236","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622236","url":null,"abstract":"It is a grand challenge to build intelligent agent systems that can improve their problem-solving performance through perpetual learning. In our previous work, we have proposed a special type of perpetual learning paradigm called inconsistency-induced learning, or i2Learning, along with several inconsistency-specific learning algorithms. i2Learning is a step toward meeting the challenge. The work reported in this paper is a continuation of the ongoing research with i2Learning. We describe two more learning algorithms for incompatible inconsistency and anti-subsumption inconsistency in the context of i2Learning. The results will be incorporated into empirical studies as part of future work.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130647363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622229
L. Reynoso, Marcelo Amaolo, Claudio Vaucheret, Mabel Álvarez
Different authors from literature had argued that measures for ontologies can help: to select a suitable ontology for the user needs, to improve dynamic web service composition and to predict the completed system's overall quality. However, the majority of the ontologies' measures go no further than their definitions. We have compared a set of 51 measures according to minimal criteria that a measure must fulfill. In order to do a coherent comparison of their definitions and their intents we have formalized the measures using Object Constraint Language (OCL) upon the Ontology Definition Model (ODM). The formalization of the measures help to avoid the misunderstanding and misinterpretation introduced when measures are informally defined using natural language. The formal definitions upon a OMD metamodel assure that measures capture the concepts they intend for and could facilitate the implementation of measures extraction tools.
{"title":"Survey of measures for the structural dimension of ontologies","authors":"L. Reynoso, Marcelo Amaolo, Claudio Vaucheret, Mabel Álvarez","doi":"10.1109/ICCI-CC.2013.6622229","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622229","url":null,"abstract":"Different authors from literature had argued that measures for ontologies can help: to select a suitable ontology for the user needs, to improve dynamic web service composition and to predict the completed system's overall quality. However, the majority of the ontologies' measures go no further than their definitions. We have compared a set of 51 measures according to minimal criteria that a measure must fulfill. In order to do a coherent comparison of their definitions and their intents we have formalized the measures using Object Constraint Language (OCL) upon the Ontology Definition Model (ODM). The formalization of the measures help to avoid the misunderstanding and misinterpretation introduced when measures are informally defined using natural language. The formal definitions upon a OMD metamodel assure that measures capture the concepts they intend for and could facilitate the implementation of measures extraction tools.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114847946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622284
W. Ye, Yu-feng Peng, Xianrong Liu, Jun-ling Yang
Power switching components' dead time, voltage drop and the change in load introduce the distortion in the output of SPWM inverter. This kind of outputs will trigger a series of serious problems, like lowering the stability of running equipment, increasing the loss, etc. In this paper, based on the causes of different kinds of distortion, aiming at the dead-zone effect, a algorithm to minimize dead time and to reduce the output zero-crossing distortion is given; aiming at the change of model parameters and load, based on adaptive linear neural network, a algorithm about distortion detection and compensation is proposed. Finally,using STM32F103ZE6 (Cortex-M3 32-bit ARM microprocessor), single-phase SPWM inverter results show that the distortion of output is only 0.9%, lower than about 85% before compensation.
{"title":"Distortion suppression based on adaline for single-phase SPWM inverter","authors":"W. Ye, Yu-feng Peng, Xianrong Liu, Jun-ling Yang","doi":"10.1109/ICCI-CC.2013.6622284","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622284","url":null,"abstract":"Power switching components' dead time, voltage drop and the change in load introduce the distortion in the output of SPWM inverter. This kind of outputs will trigger a series of serious problems, like lowering the stability of running equipment, increasing the loss, etc. In this paper, based on the causes of different kinds of distortion, aiming at the dead-zone effect, a algorithm to minimize dead time and to reduce the output zero-crossing distortion is given; aiming at the change of model parameters and load, based on adaptive linear neural network, a algorithm about distortion detection and compensation is proposed. Finally,using STM32F103ZE6 (Cortex-M3 32-bit ARM microprocessor), single-phase SPWM inverter results show that the distortion of output is only 0.9%, lower than about 85% before compensation.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125458304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622219
D. Hsu
The advent of sensor technologies and imaging modalities has greatly increased our ability to map the brain structure and understand its cognitive function. In order for the acquired Big Data (with large volume, wide variety, and high velocity) to be valuable, innovative data-centric algorithms and systems in machine learning, data mining and artificial intelligence have been developed, designed and implemented. Due to the complexity of the brain system and its cognitive processes, new data-driven paradigm is needed to recognize patterns in Big Data, to fuse information from different sources (systems and sensors), and to extract useful knowledge for actionable decisions.
{"title":"Cognitive diversity in perceptive informatics and affective computing","authors":"D. Hsu","doi":"10.1109/ICCI-CC.2013.6622219","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622219","url":null,"abstract":"The advent of sensor technologies and imaging modalities has greatly increased our ability to map the brain structure and understand its cognitive function. In order for the acquired Big Data (with large volume, wide variety, and high velocity) to be valuable, innovative data-centric algorithms and systems in machine learning, data mining and artificial intelligence have been developed, designed and implemented. Due to the complexity of the brain system and its cognitive processes, new data-driven paradigm is needed to recognize patterns in Big Data, to fuse information from different sources (systems and sensors), and to extract useful knowledge for actionable decisions.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130252181","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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