Pub Date : 2022-05-10DOI: 10.1080/17445760.2022.2070748
Salvador Robles Herrera, M. Ceberio, V. Kreinovich
In many practical situations, deep neural networks work better than the traditional ‘shallow’ ones; however, in some cases, the shallow neural networks lead to better results. At present, deciding which type of neural networks will work better is mostly done by trial and error. It is therefore desirable to come up with some criterion of when deep learning is better and when shallow is better. In this paper, we argue that this depends on whether the corresponding situation has natural symmetries: if it does, we expect deep learning to work better, otherwise we expect shallow learning to be more effective. Our general qualitative arguments are strengthened by the fact that in the simplest case, the connection between symmetries and effectiveness of deep learning can be theoretically proven.
{"title":"When is deep learning better and when is shallow learning better: qualitative analysis","authors":"Salvador Robles Herrera, M. Ceberio, V. Kreinovich","doi":"10.1080/17445760.2022.2070748","DOIUrl":"https://doi.org/10.1080/17445760.2022.2070748","url":null,"abstract":"In many practical situations, deep neural networks work better than the traditional ‘shallow’ ones; however, in some cases, the shallow neural networks lead to better results. At present, deciding which type of neural networks will work better is mostly done by trial and error. It is therefore desirable to come up with some criterion of when deep learning is better and when shallow is better. In this paper, we argue that this depends on whether the corresponding situation has natural symmetries: if it does, we expect deep learning to work better, otherwise we expect shallow learning to be more effective. Our general qualitative arguments are strengthened by the fact that in the simplest case, the connection between symmetries and effectiveness of deep learning can be theoretically proven.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"37 1","pages":"589 - 595"},"PeriodicalIF":1.1,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41749336","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 : 2022-05-04DOI: 10.1080/17445760.2022.2052871
K. Morita
In this paper, we give a survey on the problem of how a Fredkin gate, a universal reversible logic gate, is realised in various reversible cellular automata (RCAs). Models of RCAs considered here are two kinds of square partitioned cellular automata (SPCAs), and four kinds of elementary triangular partitioned cellular automata (ETPCAs). These six RCAs are very simple, in particular, ETPCAs are extremely simple, yet they are computationally universal in the sense any reversible Turing machine, which is composed of Fredkin gates, can be embedded in them. There are three key points for implementing a Fredkin gate in an RCA: (1) realising a signal, (2) routeing a signal, and (3) interacting two signals. We shall see that depending on the properties of the RCAs, different techniques are used to realise the above three functions. Based on these techniques, complete configurations of Fredkin gates in the six RCAs are given.
{"title":"Fredkin gates in simple reversible cellular automata","authors":"K. Morita","doi":"10.1080/17445760.2022.2052871","DOIUrl":"https://doi.org/10.1080/17445760.2022.2052871","url":null,"abstract":"In this paper, we give a survey on the problem of how a Fredkin gate, a universal reversible logic gate, is realised in various reversible cellular automata (RCAs). Models of RCAs considered here are two kinds of square partitioned cellular automata (SPCAs), and four kinds of elementary triangular partitioned cellular automata (ETPCAs). These six RCAs are very simple, in particular, ETPCAs are extremely simple, yet they are computationally universal in the sense any reversible Turing machine, which is composed of Fredkin gates, can be embedded in them. There are three key points for implementing a Fredkin gate in an RCA: (1) realising a signal, (2) routeing a signal, and (3) interacting two signals. We shall see that depending on the properties of the RCAs, different techniques are used to realise the above three functions. Based on these techniques, complete configurations of Fredkin gates in the six RCAs are given.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"37 1","pages":"249 - 272"},"PeriodicalIF":1.1,"publicationDate":"2022-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44556376","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 : 2022-04-20DOI: 10.1080/17445760.2022.2066102
Mohamad Abdallah, E. Cheng
ABSTRACT The strong matching preclusion number of a graph is the minimum number of vertices and edges whose deletion results in a graph that has neither perfect matchings nor almost-perfect matchings. Park and Ihm introduced the problem of strong matching preclusion under the condition that no isolated vertex is created as a result of faults. In this article, we find the conditional strong matching preclusion number for the pancake graph.
{"title":"Conditional strong matching preclusion of the pancake graph","authors":"Mohamad Abdallah, E. Cheng","doi":"10.1080/17445760.2022.2066102","DOIUrl":"https://doi.org/10.1080/17445760.2022.2066102","url":null,"abstract":"ABSTRACT The strong matching preclusion number of a graph is the minimum number of vertices and edges whose deletion results in a graph that has neither perfect matchings nor almost-perfect matchings. Park and Ihm introduced the problem of strong matching preclusion under the condition that no isolated vertex is created as a result of faults. In this article, we find the conditional strong matching preclusion number for the pancake graph.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"38 1","pages":"1 - 13"},"PeriodicalIF":1.1,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44026847","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 : 2022-04-11DOI: 10.1080/17445760.2022.2060976
A. Zaenchkovski, A. Lazarev, Dmitrii Tukaev, V. Epifanov
One of modern industrial systems key features is the special role of information in their creation and operation. On the one hand, being a source of innovative ideas, it stimulates the transformation of production processes in a strategic perspective, on the other hand – it significantly expands capabilities of individual enterprises. Implementation of information interaction are currently carried out using IPv4 streaming, which is a common and traditional way of communicating distributed devices. However, this protocol has a number of critical vulnerabilities. To solve this problem, the multiplatform information flow management system for industrial enterprises devices based on neural network data addressing version 6 of the IP protocol was developed. GRAPHICAL ABSTRACT
{"title":"Intelligent information flow management system in innovative scientific and industrial clusters","authors":"A. Zaenchkovski, A. Lazarev, Dmitrii Tukaev, V. Epifanov","doi":"10.1080/17445760.2022.2060976","DOIUrl":"https://doi.org/10.1080/17445760.2022.2060976","url":null,"abstract":"One of modern industrial systems key features is the special role of information in their creation and operation. On the one hand, being a source of innovative ideas, it stimulates the transformation of production processes in a strategic perspective, on the other hand – it significantly expands capabilities of individual enterprises. Implementation of information interaction are currently carried out using IPv4 streaming, which is a common and traditional way of communicating distributed devices. However, this protocol has a number of critical vulnerabilities. To solve this problem, the multiplatform information flow management system for industrial enterprises devices based on neural network data addressing version 6 of the IP protocol was developed. GRAPHICAL ABSTRACT","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"37 1","pages":"303 - 317"},"PeriodicalIF":1.1,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41861758","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 : 2022-04-11DOI: 10.1080/17445760.2022.2061484
Jiawei Sun, Salimur Choudhury, K. Salomaa
Fog computing is a complementary computing paradigm to the existing cloud computing. A fundamental problem of fog computing is how to allocate the computing resources of fog nodes when scheduling tasks that arrive in an online manner. Other than task completion speed metrics, fairness of resource allocation between competing users is also an important metric to consider. One such metric is Dominant Resource Fairness (DRF), a fairness scheme that guarantees four key qualities: incentivised sharing, strategy-proof, Pareto-efficiency, and envy free. This paper examines the multi-resource, multi-server, and heterogeneous task resource allocation problem from a DRF perspective. Four different types of tasks are considered: ordered/unordered and splittable/unsplittable. Three low complexity heuristics are proposed to maximise fairness between users. Results show that the proposed heuristics are at least comparable to three baseline scheduling algorithms in terms of task completion speed while achieving higher fairness between users.
{"title":"An online fair resource allocation solution for fog computing","authors":"Jiawei Sun, Salimur Choudhury, K. Salomaa","doi":"10.1080/17445760.2022.2061484","DOIUrl":"https://doi.org/10.1080/17445760.2022.2061484","url":null,"abstract":"Fog computing is a complementary computing paradigm to the existing cloud computing. A fundamental problem of fog computing is how to allocate the computing resources of fog nodes when scheduling tasks that arrive in an online manner. Other than task completion speed metrics, fairness of resource allocation between competing users is also an important metric to consider. One such metric is Dominant Resource Fairness (DRF), a fairness scheme that guarantees four key qualities: incentivised sharing, strategy-proof, Pareto-efficiency, and envy free. This paper examines the multi-resource, multi-server, and heterogeneous task resource allocation problem from a DRF perspective. Four different types of tasks are considered: ordered/unordered and splittable/unsplittable. Three low complexity heuristics are proposed to maximise fairness between users. Results show that the proposed heuristics are at least comparable to three baseline scheduling algorithms in terms of task completion speed while achieving higher fairness between users.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"37 1","pages":"456 - 477"},"PeriodicalIF":1.1,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41340608","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 : 2022-04-06DOI: 10.1080/17445760.2022.2060977
E. Cheng, Y. Mao, K. Qiu, Z. Shen
We generalise an approach to deriving diagnosability results of various interconnection networks in terms of the popular g-good-neighbour and g-extra fault-tolerant models, as well as mainstream diagnostic models such as the PMC and the MM* models. As demonstrative examples, we show how to follow this constructive, and effective, process to derive the g-extra diagnosabilities of the hypercube, the -star, and the arrangement graph. These results agree with those achieved individually, without duplicating structure independent technical details. Some of them come with a larger applicable range than those already known, and the result for the arrangement graph in terms of the MM* model is new.
{"title":"A general approach to deriving diagnosability results of interconnection networks*","authors":"E. Cheng, Y. Mao, K. Qiu, Z. Shen","doi":"10.1080/17445760.2022.2060977","DOIUrl":"https://doi.org/10.1080/17445760.2022.2060977","url":null,"abstract":"We generalise an approach to deriving diagnosability results of various interconnection networks in terms of the popular g-good-neighbour and g-extra fault-tolerant models, as well as mainstream diagnostic models such as the PMC and the MM* models. As demonstrative examples, we show how to follow this constructive, and effective, process to derive the g-extra diagnosabilities of the hypercube, the -star, and the arrangement graph. These results agree with those achieved individually, without duplicating structure independent technical details. Some of them come with a larger applicable range than those already known, and the result for the arrangement graph in terms of the MM* model is new.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"37 1","pages":"369 - 397"},"PeriodicalIF":1.1,"publicationDate":"2022-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43663873","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 : 2022-03-21DOI: 10.1080/17445760.2022.2047678
Jordi Vallverdú
Self-adaptive behavior can be defined as the behavior that allows an agent to adapt to a context using her/his/its resources. The property of being ‘self-adaptive’ implies considering some preliminary sources or elicitors for such skill. In the case of machine learning, all the learning or self-adaptive behavior mechanisms are related to algorithmic models of mathematical nature, while in the case of humans more subtle neurochemical and symbolic processes (logical and linguistic) are present. The purpose of this paper is to offer a theoretical analysis of the basic mechanisms related to learning processes, always oriented towards the creation of artificial cognitive systems which can implement such bioinspired mechanisms. Parafunctionality is the key innovative concept we introduce for applying bioinspired cognition to machine learning exploring a real mechanism still unexplored.
{"title":"Para-functional engineering: cognitive challenges","authors":"Jordi Vallverdú","doi":"10.1080/17445760.2022.2047678","DOIUrl":"https://doi.org/10.1080/17445760.2022.2047678","url":null,"abstract":"Self-adaptive behavior can be defined as the behavior that allows an agent to adapt to a context using her/his/its resources. The property of being ‘self-adaptive’ implies considering some preliminary sources or elicitors for such skill. In the case of machine learning, all the learning or self-adaptive behavior mechanisms are related to algorithmic models of mathematical nature, while in the case of humans more subtle neurochemical and symbolic processes (logical and linguistic) are present. The purpose of this paper is to offer a theoretical analysis of the basic mechanisms related to learning processes, always oriented towards the creation of artificial cognitive systems which can implement such bioinspired mechanisms. Parafunctionality is the key innovative concept we introduce for applying bioinspired cognition to machine learning exploring a real mechanism still unexplored.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"37 1","pages":"292 - 302"},"PeriodicalIF":1.1,"publicationDate":"2022-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48105957","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 : 2022-03-01DOI: 10.1080/17445760.2022.2042535
A. Sadhu, S. Mukhopadhyaya
This paper addresses the partition problem under the continuous domain in swarm robotics. In this problem, a swarm of n robots, randomly deployed over a rectangular workspace, are required to form K size-balanced groups within a finite amount of time. We aim to look into the problem in the presence of horizontal line obstacles. The obstacles are scattered randomly over the bounded region, and their positions remain unaltered throughout the process. In the proposed solutions, the robots are assumed to be identical, autonomous, and do not have any direct communication among themselves. The robots are memoryless, except they retain only the information of the two parameters n and K throughout the process and their states among three possible ones. Two different partition algorithms are proposed assuming full-compass axis agreement and half-compass axis agreement among the local coordinate systems of the robots. In the first case, the proposed algorithm works for both synchronous and semi-synchronous models, whereas, in the second case, the robots are assumed to be synchronous. As a pre-processing step of the partition algorithms, an assembling algorithm for the half-compass axis agreement model has also been proposed for synchronous and semi-synchronous robots. GRAPHICAL ABSTRACT
{"title":"Partition of a swarm of robots into size-balanced groups in presence of line obstacles","authors":"A. Sadhu, S. Mukhopadhyaya","doi":"10.1080/17445760.2022.2042535","DOIUrl":"https://doi.org/10.1080/17445760.2022.2042535","url":null,"abstract":"This paper addresses the partition problem under the continuous domain in swarm robotics. In this problem, a swarm of n robots, randomly deployed over a rectangular workspace, are required to form K size-balanced groups within a finite amount of time. We aim to look into the problem in the presence of horizontal line obstacles. The obstacles are scattered randomly over the bounded region, and their positions remain unaltered throughout the process. In the proposed solutions, the robots are assumed to be identical, autonomous, and do not have any direct communication among themselves. The robots are memoryless, except they retain only the information of the two parameters n and K throughout the process and their states among three possible ones. Two different partition algorithms are proposed assuming full-compass axis agreement and half-compass axis agreement among the local coordinate systems of the robots. In the first case, the proposed algorithm works for both synchronous and semi-synchronous models, whereas, in the second case, the robots are assumed to be synchronous. As a pre-processing step of the partition algorithms, an assembling algorithm for the half-compass axis agreement model has also been proposed for synchronous and semi-synchronous robots. GRAPHICAL ABSTRACT","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"37 1","pages":"344 - 368"},"PeriodicalIF":1.1,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44081252","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 : 2022-02-28DOI: 10.1080/17445760.2022.2042536
R. Hes, Giacomo Gioroli
Large datasets pose a difficult challenge for clustering algorithms due to memory limitations and execution speed. Clustering is typically addressed with current popular techniques: K-Means and DBScan, which are inherently tightly coupled to all points in the data set. K-Means clustering is based on cluster centres and requires prior knowledge of the number of classes present in the dataset. DBScan relaxes this constraint but retains the need for a complete dataset during computation. In this paper, a novel ‘self’-learning primitive unsupervised technique is presented that addresses the tight coupling and is readily distributable. The technique follows the comparison to class averages similar to K-Means yet relaxes the constraint of prior knowledge of the number of classes, similar to DBScan. The algorithm competes well with the standardised K-Means and DBScan variants in the context of physically based observations where Gaussian noise can be presumed. An application of usage of the unsupervised technique is presented; the classification of unknown whale species in the cook strait of New Zealand is shown to perform well. GRAPHICAL ABSTRACT
{"title":"A distributed unsupervised learning algorithm and its suitability to physical based observation","authors":"R. Hes, Giacomo Gioroli","doi":"10.1080/17445760.2022.2042536","DOIUrl":"https://doi.org/10.1080/17445760.2022.2042536","url":null,"abstract":"Large datasets pose a difficult challenge for clustering algorithms due to memory limitations and execution speed. Clustering is typically addressed with current popular techniques: K-Means and DBScan, which are inherently tightly coupled to all points in the data set. K-Means clustering is based on cluster centres and requires prior knowledge of the number of classes present in the dataset. DBScan relaxes this constraint but retains the need for a complete dataset during computation. In this paper, a novel ‘self’-learning primitive unsupervised technique is presented that addresses the tight coupling and is readily distributable. The technique follows the comparison to class averages similar to K-Means yet relaxes the constraint of prior knowledge of the number of classes, similar to DBScan. The algorithm competes well with the standardised K-Means and DBScan variants in the context of physically based observations where Gaussian noise can be presumed. An application of usage of the unsupervised technique is presented; the classification of unknown whale species in the cook strait of New Zealand is shown to perform well. GRAPHICAL ABSTRACT","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"37 1","pages":"443 - 455"},"PeriodicalIF":1.1,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41925847","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 : 2022-01-31DOI: 10.5121/ijdps.2022.13102
Mamadou Diarra, Telesphore B. Tiendrebeogo
Big Data has introduced the challenge of storing and processing large volumes of data (text, images, and videos). The success of centralised exploitation of massive data on a node is outdated, leading to the emergence of distributed storage, parallel processing and hybrid distributed storage and parallel processing frameworks. The main objective of this paper is to evaluate the load balancing and task allocation strategy of our hybrid distributed storage and parallel processing framework CLOAK-Reduce. To achieve this goal, we first performed a theoretical approach of the architecture and operation of some DHT-MapReduce. Then, we compared the data collected from their load balancing and task allocation strategy by simulation. Finally, the simulation results show that CLOAK-Reduce C5R5 replication provides better load balancing efficiency, MapReduce job submission with 10% churn or no churn.
{"title":"Performance Evaluation of Big Data Processing of Cloak-Reduce","authors":"Mamadou Diarra, Telesphore B. Tiendrebeogo","doi":"10.5121/ijdps.2022.13102","DOIUrl":"https://doi.org/10.5121/ijdps.2022.13102","url":null,"abstract":"Big Data has introduced the challenge of storing and processing large volumes of data (text, images, and videos). The success of centralised exploitation of massive data on a node is outdated, leading to the emergence of distributed storage, parallel processing and hybrid distributed storage and parallel processing frameworks. The main objective of this paper is to evaluate the load balancing and task allocation strategy of our hybrid distributed storage and parallel processing framework CLOAK-Reduce. To achieve this goal, we first performed a theoretical approach of the architecture and operation of some DHT-MapReduce. Then, we compared the data collected from their load balancing and task allocation strategy by simulation. Finally, the simulation results show that CLOAK-Reduce C5R5 replication provides better load balancing efficiency, MapReduce job submission with 10% churn or no churn.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"380 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76107330","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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