Pub Date : 1995-05-29DOI: 10.1109/INBS.1995.404291
D. Searls
Formal grammars can be used to model general forms of intramolecular structure, such as secondary structure of nucleic acids. A new formalism, called cut grammar, is shown to model intermolecular assemblages such as hybridization products, as well. Formal grammars themselves can be modelled by sets of oligonucleotides, and derivations from any context-free grammar can in theory be simulated by hybridization experiments.<>
{"title":"Formal grammars for intermolecular structure","authors":"D. Searls","doi":"10.1109/INBS.1995.404291","DOIUrl":"https://doi.org/10.1109/INBS.1995.404291","url":null,"abstract":"Formal grammars can be used to model general forms of intramolecular structure, such as secondary structure of nucleic acids. A new formalism, called cut grammar, is shown to model intermolecular assemblages such as hybridization products, as well. Formal grammars themselves can be modelled by sets of oligonucleotides, and derivations from any context-free grammar can in theory be simulated by hybridization experiments.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134039608","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 : 1995-05-29DOI: 10.1109/INBS.1995.404268
J. Hilke, J. Reggia, R. Navarro‐González, J. Lohn
An important stage in the development of living systems on Earth was the formation of RNA-like molecules capable of self-transcripting and self-replicating. In this paper, the authors attempt to develop a simple, flexible and accurate computer model of nucleotide interactions that lead to the non-enzymatic transcription of an oligonucleotide that acts as a template to catalyze the formation of a suite of oligonucleotides. The authors' computer model is cellular automata based and allows nucleotides to experience random movement and interact locally to associate with a template and/or oligomerize with other nucleotides according to a set of rules. To test the simulation method, results were compared to specific laboratory experimental results. The hypotheses were that the best set of rules developed would be able to produce results which were: 1. More similar to the laboratory experiment's results than random rules; 2. More similar to the laboratory experiment's results than a set of rules which is chemically realistic but has random probabilities; and 3. Statistically similar to the laboratory experiment's results. The test for determining whether the results were statistically similar was done using a regression analysis. At the a=0.05 level: the first two hypothesis were supported, and the third hypothesis has not yet been statistically supported.<>
{"title":"A modified cellular automata model of nucleotide interactions and non-enzymatic transcription of DNA","authors":"J. Hilke, J. Reggia, R. Navarro‐González, J. Lohn","doi":"10.1109/INBS.1995.404268","DOIUrl":"https://doi.org/10.1109/INBS.1995.404268","url":null,"abstract":"An important stage in the development of living systems on Earth was the formation of RNA-like molecules capable of self-transcripting and self-replicating. In this paper, the authors attempt to develop a simple, flexible and accurate computer model of nucleotide interactions that lead to the non-enzymatic transcription of an oligonucleotide that acts as a template to catalyze the formation of a suite of oligonucleotides. The authors' computer model is cellular automata based and allows nucleotides to experience random movement and interact locally to associate with a template and/or oligomerize with other nucleotides according to a set of rules. To test the simulation method, results were compared to specific laboratory experimental results. The hypotheses were that the best set of rules developed would be able to produce results which were: 1. More similar to the laboratory experiment's results than random rules; 2. More similar to the laboratory experiment's results than a set of rules which is chemically realistic but has random probabilities; and 3. Statistically similar to the laboratory experiment's results. The test for determining whether the results were statistically similar was done using a regression analysis. At the a=0.05 level: the first two hypothesis were supported, and the third hypothesis has not yet been statistically supported.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126628149","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 : 1995-05-29DOI: 10.1109/INBS.1995.404262
Rudolf Freund
The notion of splicing systems has been introduced by Tom Head (1987) in order to model the recombinational behaviors of double-stranded DNA molecules under the simultaneous influence of specified classes of restriction enzymes. Yet for modelling complex: (bio)chemical processes of three-dimensional (macro)molecules in the three-dimensional space strings turn out to be more or less inadequate objects. Hence in this paper the author suggests graphs as more suitable objects for modelling such processes and introduces graph splicing systems. An illustrating example from the area of DNA splicing is elaborated in order to show the suitability of the new approach. The author exhibits the relation between regular graph splicing systems on graphs and splicing systems on strings and shows that his new model allows him to describe splicing systems on strings as well as on circular strings within a uniform framework.<>
{"title":"Splicing systems on graphs","authors":"Rudolf Freund","doi":"10.1109/INBS.1995.404262","DOIUrl":"https://doi.org/10.1109/INBS.1995.404262","url":null,"abstract":"The notion of splicing systems has been introduced by Tom Head (1987) in order to model the recombinational behaviors of double-stranded DNA molecules under the simultaneous influence of specified classes of restriction enzymes. Yet for modelling complex: (bio)chemical processes of three-dimensional (macro)molecules in the three-dimensional space strings turn out to be more or less inadequate objects. Hence in this paper the author suggests graphs as more suitable objects for modelling such processes and introduces graph splicing systems. An illustrating example from the area of DNA splicing is elaborated in order to show the suitability of the new approach. The author exhibits the relation between regular graph splicing systems on graphs and splicing systems on strings and shows that his new model allows him to describe splicing systems on strings as well as on circular strings within a uniform framework.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"427 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123405993","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 : 1995-05-29DOI: 10.1109/INBS.1995.404280
J. Collado-Vides
The integration of large amounts of information on the regulation of gene expression requires conceptual frameworks which should facilitate the discovery of general principles underlying different mechanisms of gene regulation. An exhaustive database of /spl sigma//sup 70/ and /spl sigma//sup 54/ promoters in E. Coli has supported the construction of a grammatical model of the /spl sigma//sup 70/ type of promoters. This grammar generates all and only those regulatory arrangements of the collection, as well as new ones which are consistent with the biological principles of the collection. In this paper, some ideas towards a unified model of the /spl sigma//sup 70/ and the /spl sigma//sup 54/ bacterial promoters are presented. This model should reflect the biological differences on the possible regulatory mechanisms of these collections. The /spl sigma//sup 54/ class represents an intermediate step between the 7/sup 0/ promoters and those present in higher organisms. Based on the biology of these bacterial promoters a hypothesis is proposed which stipulates that in principle it is feasible to activate /spl sigma//sup 70/ promoters at a distance, an exclusive property of the /spl sigma//sup 54/ class shared with promoters from higher organisms. Assuming this hypothesis is correct, some a ideas supporting a unique "universal" grammar for the /spl sigma//sup 70/ and /spl sigma//sup 54/ promoters are presented.<>
{"title":"Some ideas towards a grammatical model of the /spl sigma//sup 54/ bacterial promoters","authors":"J. Collado-Vides","doi":"10.1109/INBS.1995.404280","DOIUrl":"https://doi.org/10.1109/INBS.1995.404280","url":null,"abstract":"The integration of large amounts of information on the regulation of gene expression requires conceptual frameworks which should facilitate the discovery of general principles underlying different mechanisms of gene regulation. An exhaustive database of /spl sigma//sup 70/ and /spl sigma//sup 54/ promoters in E. Coli has supported the construction of a grammatical model of the /spl sigma//sup 70/ type of promoters. This grammar generates all and only those regulatory arrangements of the collection, as well as new ones which are consistent with the biological principles of the collection. In this paper, some ideas towards a unified model of the /spl sigma//sup 70/ and the /spl sigma//sup 54/ bacterial promoters are presented. This model should reflect the biological differences on the possible regulatory mechanisms of these collections. The /spl sigma//sup 54/ class represents an intermediate step between the 7/sup 0/ promoters and those present in higher organisms. Based on the biology of these bacterial promoters a hypothesis is proposed which stipulates that in principle it is feasible to activate /spl sigma//sup 70/ promoters at a distance, an exclusive property of the /spl sigma//sup 54/ class shared with promoters from higher organisms. Assuming this hypothesis is correct, some a ideas supporting a unique \"universal\" grammar for the /spl sigma//sup 70/ and /spl sigma//sup 54/ promoters are presented.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126584804","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 : 1995-05-29DOI: 10.1109/INBS.1995.404271
Lipo Wang
We clarify that the only essential difference between the two major "categories" of unsupervised learning rules discussed in theories of artificial neural networks-the competitive learning and the Hebbian learning rules-is that lateral inhibition is present in the former and is absent in the later. We demonstrate analytically that a competitive learning neural network, which has synaptically localized memory, shows better tolerance over noise in training patterns in comparison with the Hopfield neural network, which uses a Hebbian-type learning rule without any lateral inhibition and has synaptically distributed memory.<>
{"title":"Synaptically distributed memory vs. synaptically localized memory","authors":"Lipo Wang","doi":"10.1109/INBS.1995.404271","DOIUrl":"https://doi.org/10.1109/INBS.1995.404271","url":null,"abstract":"We clarify that the only essential difference between the two major \"categories\" of unsupervised learning rules discussed in theories of artificial neural networks-the competitive learning and the Hebbian learning rules-is that lateral inhibition is present in the former and is absent in the later. We demonstrate analytically that a competitive learning neural network, which has synaptically localized memory, shows better tolerance over noise in training patterns in comparison with the Hopfield neural network, which uses a Hebbian-type learning rule without any lateral inhibition and has synaptically distributed memory.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"9 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134599034","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 : 1995-05-29DOI: 10.1109/INBS.1995.404258
J. Gattiker, D. Wilson
A genetic system that uses a radically epistatic mapping from genotype to phenotype is defined. This system is proposed in order to study the population dynamics rather than create a new system for function optimization. Two behaviors not found in traditional genetic systems are explored: first, although the genetic system uses only simple generational recombination and fitness scaling, it is capable of distributing a population of solutions on a number of non-adjacent phenotype peaks. This capability is analyzed and empirically explored. Second, the genetic system is shown to have the capability of tracking an environment where the adaptive peaks are changed in a recurrent manner.<>
{"title":"Population dynamics in a radically epistatic genetic system","authors":"J. Gattiker, D. Wilson","doi":"10.1109/INBS.1995.404258","DOIUrl":"https://doi.org/10.1109/INBS.1995.404258","url":null,"abstract":"A genetic system that uses a radically epistatic mapping from genotype to phenotype is defined. This system is proposed in order to study the population dynamics rather than create a new system for function optimization. Two behaviors not found in traditional genetic systems are explored: first, although the genetic system uses only simple generational recombination and fitness scaling, it is capable of distributing a population of solutions on a number of non-adjacent phenotype peaks. This capability is analyzed and empirically explored. Second, the genetic system is shown to have the capability of tracking an environment where the adaptive peaks are changed in a recurrent manner.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122634857","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 : 1995-05-29DOI: 10.1109/INBS.1995.404260
D. Yeung, Hing-Yip Chan, Y. C. Lau
The objective of this paper is to propose a modified neocognitron with production rules embedded for handwritten character recognition. Structured information about the basic features in a character is stored in the production rules constructed by users. A mapping scheme is used to map these rules into the connection weights of the neocognitron. The ability to represent structured information for characters using production rules provides some insights into how this structured information or knowledge can be processed by the network for its character recognition or refinement in the case where a character is misrecognized. The whole process can be controlled by users by analyzing the results of the recognition by refining the production rules to improve the recognition rate. It is much more flexible, and can be used as tools to build a rapid prototype of a pattern recognizer with fault diagnosis capability.<>
{"title":"A neocognitron synthesized by production rule for handwritten character recognition","authors":"D. Yeung, Hing-Yip Chan, Y. C. Lau","doi":"10.1109/INBS.1995.404260","DOIUrl":"https://doi.org/10.1109/INBS.1995.404260","url":null,"abstract":"The objective of this paper is to propose a modified neocognitron with production rules embedded for handwritten character recognition. Structured information about the basic features in a character is stored in the production rules constructed by users. A mapping scheme is used to map these rules into the connection weights of the neocognitron. The ability to represent structured information for characters using production rules provides some insights into how this structured information or knowledge can be processed by the network for its character recognition or refinement in the case where a character is misrecognized. The whole process can be controlled by users by analyzing the results of the recognition by refining the production rules to improve the recognition rate. It is much more flexible, and can be used as tools to build a rapid prototype of a pattern recognizer with fault diagnosis capability.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128300066","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 : 1995-05-29DOI: 10.1109/INBS.1995.404278
Stéphane Avner
In this paper, we introduce a system that extracts comprehensible symbolic rules from a multilayer perceptron. Once the network has been trained in the usual manner, the training set is presented again, and the actual activations of the units recorded. Logical rules, corresponding to the logical combinations of the incoming signals, are extracted at each activated unit. This procedure is used for all examples belonging to the training set. Thus we obtain a set of rules which account for all logical steps taken by the network to process all known input patterns. Furthermore, we show that if some symbolic meaning were associated to every input unit, then the hidden units, which have formed concepts in order to deal with recurrent features in the input data, possess some symbolic meaning tool. Our algorithm allows the recognition or the understandability of these concepts: they are found to be reducible to conjunctions and negations of the human input concepts. Our rules can also be recombined in different ways, thus constituting some limited but sound generalization of the training set. Neural networks could learn concepts about domains where little theory was known but where many examples were available. Yet, because their knowledge was stored in the synaptic strengths under numerical form, it was difficult to comprehend what they had discovered. This system therefore provides some means of accessing the information contained inside the network.<>
{"title":"Discovery of comprehensible symbolic rules in a neural network","authors":"Stéphane Avner","doi":"10.1109/INBS.1995.404278","DOIUrl":"https://doi.org/10.1109/INBS.1995.404278","url":null,"abstract":"In this paper, we introduce a system that extracts comprehensible symbolic rules from a multilayer perceptron. Once the network has been trained in the usual manner, the training set is presented again, and the actual activations of the units recorded. Logical rules, corresponding to the logical combinations of the incoming signals, are extracted at each activated unit. This procedure is used for all examples belonging to the training set. Thus we obtain a set of rules which account for all logical steps taken by the network to process all known input patterns. Furthermore, we show that if some symbolic meaning were associated to every input unit, then the hidden units, which have formed concepts in order to deal with recurrent features in the input data, possess some symbolic meaning tool. Our algorithm allows the recognition or the understandability of these concepts: they are found to be reducible to conjunctions and negations of the human input concepts. Our rules can also be recombined in different ways, thus constituting some limited but sound generalization of the training set. Neural networks could learn concepts about domains where little theory was known but where many examples were available. Yet, because their knowledge was stored in the synaptic strengths under numerical form, it was difficult to comprehend what they had discovered. This system therefore provides some means of accessing the information contained inside the network.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131297990","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 : 1995-05-29DOI: 10.1109/INBS.1995.404266
R. Brause
Presents a framework for the self-organized formation of high level learning by a statistical preprocessing of features. The paper focuses first on the formation of the features in the context of layers of feature processing units as a kind of resource-restricted associative learning. The author claims that such an architecture must reach maturity by basic statistical proportions, optimizing the information processing capabilities of each layer. The final symbolic output is learned by pure association of features of different levels and kind of sensorial input. Finally, the author also shows that common error-correction learning can be accomplished by a kind of associative learning.<>
{"title":"Self-organized learning in multi-layer networks","authors":"R. Brause","doi":"10.1109/INBS.1995.404266","DOIUrl":"https://doi.org/10.1109/INBS.1995.404266","url":null,"abstract":"Presents a framework for the self-organized formation of high level learning by a statistical preprocessing of features. The paper focuses first on the formation of the features in the context of layers of feature processing units as a kind of resource-restricted associative learning. The author claims that such an architecture must reach maturity by basic statistical proportions, optimizing the information processing capabilities of each layer. The final symbolic output is learned by pure association of features of different levels and kind of sensorial input. Finally, the author also shows that common error-correction learning can be accomplished by a kind of associative learning.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114143375","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 : 1995-04-25DOI: 10.1109/INBS.1995.404272
M. Sahami
This paper investigates the generation of neural networks through the induction of binary trees of threshold logic units (TLUs). Initially, we describe the framework for our tree construction algorithm and show how it helps to bridge the gap between pure connectionist (neural network) and symbolic (decision tree) paradigms. We also show how the trees of threshold units that we induce can be transformed into an isomorphic neural network topology. Several methods for learning the linear discriminant functions at each node of the tree structure are examined and shown to produce accuracy results that are comparable to classical information theoretic methods for constructing decision trees (which use single feature tests at each node), but produce trees that are smaller and thus easier to understand. Moreover, our results also show that it is possible to simultaneously learn both the topology and weight settings of a neural network simply using the training data set that we are initially given.<>
{"title":"Generating neural networks through the induction of threshold logic unit trees","authors":"M. Sahami","doi":"10.1109/INBS.1995.404272","DOIUrl":"https://doi.org/10.1109/INBS.1995.404272","url":null,"abstract":"This paper investigates the generation of neural networks through the induction of binary trees of threshold logic units (TLUs). Initially, we describe the framework for our tree construction algorithm and show how it helps to bridge the gap between pure connectionist (neural network) and symbolic (decision tree) paradigms. We also show how the trees of threshold units that we induce can be transformed into an isomorphic neural network topology. Several methods for learning the linear discriminant functions at each node of the tree structure are examined and shown to produce accuracy results that are comparable to classical information theoretic methods for constructing decision trees (which use single feature tests at each node), but produce trees that are smaller and thus easier to understand. Moreover, our results also show that it is possible to simultaneously learn both the topology and weight settings of a neural network simply using the training data set that we are initially given.<<ETX>>","PeriodicalId":423954,"journal":{"name":"Proceedings First International Symposium on Intelligence in Neural and Biological Systems. INBS'95","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131481154","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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