C. Bengel, Leon Dixius, R. Waser, D. Wouters, S. Menzel
Abstract Computation-in-Memory accelerators based on resistive switching devices represent a promising approach to realize future information processing systems. These architectures promise orders of magnitudes lower energy consumption for certain tasks, while also achieving higher throughputs than other special purpose hardware such as GPUs, due to their analog computation nature. Due to device variability issues, however, a single resistive switching cell usually does not achieve the resolution required for the considered applications. To overcome this challenge, many of the proposed architectures use an approach called bit slicing, where generally multiple low-resolution components are combined to realize higher resolution blocks. In this paper, we will present an analog accelerator architecture on the circuit level, which can be used to perform Vector-Matrix-Multiplications or Matrix-Matrix-Multiplications. The architecture consists of the 1T1R crossbar array, the optimized select circuitry and an ADC. The components are designed to handle the variability of the resistive switching cells, which is verified through our verified and physical compact model. We then use this architecture to compare different bit slicing approaches and discuss their tradeoffs.
{"title":"Bit slicing approaches for variability aware ReRAM CIM macros","authors":"C. Bengel, Leon Dixius, R. Waser, D. Wouters, S. Menzel","doi":"10.1515/itit-2023-0018","DOIUrl":"https://doi.org/10.1515/itit-2023-0018","url":null,"abstract":"Abstract Computation-in-Memory accelerators based on resistive switching devices represent a promising approach to realize future information processing systems. These architectures promise orders of magnitudes lower energy consumption for certain tasks, while also achieving higher throughputs than other special purpose hardware such as GPUs, due to their analog computation nature. Due to device variability issues, however, a single resistive switching cell usually does not achieve the resolution required for the considered applications. To overcome this challenge, many of the proposed architectures use an approach called bit slicing, where generally multiple low-resolution components are combined to realize higher resolution blocks. In this paper, we will present an analog accelerator architecture on the circuit level, which can be used to perform Vector-Matrix-Multiplications or Matrix-Matrix-Multiplications. The architecture consists of the 1T1R crossbar array, the optimized select circuitry and an ADC. The components are designed to handle the variability of the resistive switching cells, which is verified through our verified and physical compact model. We then use this architecture to compare different bit slicing approaches and discuss their tradeoffs.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43977932","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}
Abstract Computer programs, so-called solvers, for solving the well-known Boolean satisfiability problem (S at ) have been improving for decades. Among the reasons, why these solvers are so fast, is the implicit usage of the formula’s structural properties during solving. One of such structural indicators is the so-called treewidth, which tries to measure how close a formula instance is to being easy (tree-like). This work focuses on logic-based problems and treewidth-based methods and tools for solving them. Many of these problems are also relevant for knowledge representation and reasoning (KR) as well as artificial intelligence (AI) in general. We present a new type of problem reduction, which is referred to by decomposition-guided ( DG ). This reduction type forms the basis to solve a problem for quantified Boolean formulas (QBFs) of bounded treewidth that has been open since 2004. The solution of this problem then gives rise to a new methodology for proving precise lower bounds for a range of further formalisms in logic, KR, and AI. Despite the established lower bounds, we implement an algorithm for solving extensions of S at efficiently, by directly using treewidth. Our implementation is based on finding abstractions of instances, which are then incrementally refined in the process. Thereby, our observations confirm that treewidth is an important measure that should be considered in the design of modern solvers.
{"title":"Advanced tools and methods for treewidth-based problem solving","authors":"Markus Hecher","doi":"10.1515/itit-2023-0004","DOIUrl":"https://doi.org/10.1515/itit-2023-0004","url":null,"abstract":"Abstract Computer programs, so-called solvers, for solving the well-known Boolean satisfiability problem (S at ) have been improving for decades. Among the reasons, why these solvers are so fast, is the implicit usage of the formula’s structural properties during solving. One of such structural indicators is the so-called treewidth, which tries to measure how close a formula instance is to being easy (tree-like). This work focuses on logic-based problems and treewidth-based methods and tools for solving them. Many of these problems are also relevant for knowledge representation and reasoning (KR) as well as artificial intelligence (AI) in general. We present a new type of problem reduction, which is referred to by decomposition-guided ( DG ). This reduction type forms the basis to solve a problem for quantified Boolean formulas (QBFs) of bounded treewidth that has been open since 2004. The solution of this problem then gives rise to a new methodology for proving precise lower bounds for a range of further formalisms in logic, KR, and AI. Despite the established lower bounds, we implement an algorithm for solving extensions of S at efficiently, by directly using treewidth. Our implementation is based on finding abstractions of instances, which are then incrementally refined in the process. Thereby, our observations confirm that treewidth is an important measure that should be considered in the design of modern solvers.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136131845","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}
Abstract Boundaries at different scales or in different cultural contexts vary in permeability, fuzziness, and continuity. The contribution of methods from the Geographical Information Systems (GIS) toolbox used in archaeology for the understanding of boundaries is explored in a case study based on known boundaries that are located in a hilly region east of Cologne, Germany. The known political and religious boundaries date back to the 16th and early 17th century. Furthermore, a linguistic boundary traversing the study area is well-known. A classification of the reliability of the political boundaries is presented based on evidence from different sources including archaeological sites. A traditional GIS method for delimiting territories is Voronoi polygon generation, also known as Thiessen polygons. A variant uses least-cost distances, accounting for costs of movement. A site catchment of a settlement consists of all locations that can be reached by expending a given cost limit. Both the initial Voronoi computations as well as the site catchments failed to reconstruct a significant proportion of the known past boundaries. Therefore, the association of the known boundaries with rivers, ridges, and modern parish boundaries was tested and found significant. In contrast, poor soils and voids identified by least-cost Kernel Density Estimation (LC-KDE) of 16th century settlement locations are no preferred locations of past boundaries. Boundaries of Voronoi polygons based on modified cost models taking the association of past boundaries with ridges, rivers, and modern boundaries into account reconstructed about 27 % of the confirmed past political boundaries successfully. The association of the linguistic boundary with the features mentioned above is insignificant. Diagnostic place names are the traits forming the basis of Voronoi diagrams and LC-KDE applied in archaeological studies for reconstructing boundaries. Considering the uneven distribution and fairly low number of traits, the results of these two approaches are satisfactory.
{"title":"Computational approaches towards the understanding of past boundaries: A case study based on archaeological and historical data in a hilly region in Germany","authors":"I. Herzog","doi":"10.1515/itit-2022-0010","DOIUrl":"https://doi.org/10.1515/itit-2022-0010","url":null,"abstract":"Abstract Boundaries at different scales or in different cultural contexts vary in permeability, fuzziness, and continuity. The contribution of methods from the Geographical Information Systems (GIS) toolbox used in archaeology for the understanding of boundaries is explored in a case study based on known boundaries that are located in a hilly region east of Cologne, Germany. The known political and religious boundaries date back to the 16th and early 17th century. Furthermore, a linguistic boundary traversing the study area is well-known. A classification of the reliability of the political boundaries is presented based on evidence from different sources including archaeological sites. A traditional GIS method for delimiting territories is Voronoi polygon generation, also known as Thiessen polygons. A variant uses least-cost distances, accounting for costs of movement. A site catchment of a settlement consists of all locations that can be reached by expending a given cost limit. Both the initial Voronoi computations as well as the site catchments failed to reconstruct a significant proportion of the known past boundaries. Therefore, the association of the known boundaries with rivers, ridges, and modern parish boundaries was tested and found significant. In contrast, poor soils and voids identified by least-cost Kernel Density Estimation (LC-KDE) of 16th century settlement locations are no preferred locations of past boundaries. Boundaries of Voronoi polygons based on modified cost models taking the association of past boundaries with ridges, rivers, and modern boundaries into account reconstructed about 27 % of the confirmed past political boundaries successfully. The association of the linguistic boundary with the features mentioned above is insignificant. Diagnostic place names are the traits forming the basis of Voronoi diagrams and LC-KDE applied in archaeological studies for reconstructing boundaries. Considering the uneven distribution and fairly low number of traits, the results of these two approaches are satisfactory.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43953755","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}
S. Karl, Peter Houska, S. Lengauer, Jessica Haring, E. Trinkl, R. Preiner
Abstract Rapid progress in digitisation and computer techniques have enabled noteworthy new pottery analysis applications in recent decades. We focus on analytical techniques directed specifically at archaeological pottery research in this survey and review the specific benefits these have brought in the field. We consider techniques based on heterogeneous sources such as drawings, photographs, 3D scans and CT volume data. The various approaches and methods are structured according to the main steps in pottery processing in archaeology: documentation, classification and retrieval. Within these categories we review the most relevant papers and identify their advantages and limitations. We evaluate both freely and commercially available analysis tools and databases. Finally, we discuss open problems and future challenges in the field of pottery analysis.
{"title":"Advances in digital pottery analysis","authors":"S. Karl, Peter Houska, S. Lengauer, Jessica Haring, E. Trinkl, R. Preiner","doi":"10.1515/itit-2022-0006","DOIUrl":"https://doi.org/10.1515/itit-2022-0006","url":null,"abstract":"Abstract Rapid progress in digitisation and computer techniques have enabled noteworthy new pottery analysis applications in recent decades. We focus on analytical techniques directed specifically at archaeological pottery research in this survey and review the specific benefits these have brought in the field. We consider techniques based on heterogeneous sources such as drawings, photographs, 3D scans and CT volume data. The various approaches and methods are structured according to the main steps in pottery processing in archaeology: documentation, classification and retrieval. Within these categories we review the most relevant papers and identify their advantages and limitations. We evaluate both freely and commercially available analysis tools and databases. Finally, we discuss open problems and future challenges in the field of pottery analysis.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47766450","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}
S. Lengauer, Peter Houska, R. Preiner, E. Trinkl, S. Karl, I. Sipiran, Benjamin Bustos, T. Schreck
Abstract In Greek art, the phase from 900 to 700 BCE is referred to as the Geometric period due to the characteristically simple geometry-like ornamentations appearing on painted pottery surfaces during this era. Distinctive geometric patterns are typical for specific periods, regions, workshops as well as painters and are an important cue for archaeological tasks, such as dating and attribution. To date, these analyses are mostly conducted with the support of information technology. The primitives of an artefact’s ornamentation can be generally classified into a set of distinguishable pattern classes, which also appear in a similar fashion on other objects. Although a taxonomy of known pattern classes is given in subject-specific publications, the automatic detection and classification of surface patterns from object depictions poses a non-trivial challenge. Our long-term goal is to provide this classification functionality using a specifically designed and trained neural network. This, however, requires a large amount of labelled training data, which at this point does not exist for this domain context. In this work, we propose an effective annotation system, which allows a domain expert to interactively segment and label parts of digitized vessel surfaces. These user inputs are constantly fed back to a Convolutional Neural Network (CNN), enabling the prediction of pattern classes for a given surface area with ever increasing precision. Our work paves the way for a fully automatic classification and analysis of large surface pattern collections, which, with the help of suitable visual analysis techniques, can answer research questions like pattern variability or change over time. While the capability of our proposed annotation pipeline is demonstrated at the example of two characteristic Greek pottery artefacts from the Geometric period, the proposed methods can be readily adopted for the patternation in any other chronological periods as well as for stamped motifs.
{"title":"Interactive annotation of geometric ornamentation on painted pottery assisted by deep learning","authors":"S. Lengauer, Peter Houska, R. Preiner, E. Trinkl, S. Karl, I. Sipiran, Benjamin Bustos, T. Schreck","doi":"10.1515/itit-2022-0007","DOIUrl":"https://doi.org/10.1515/itit-2022-0007","url":null,"abstract":"Abstract In Greek art, the phase from 900 to 700 BCE is referred to as the Geometric period due to the characteristically simple geometry-like ornamentations appearing on painted pottery surfaces during this era. Distinctive geometric patterns are typical for specific periods, regions, workshops as well as painters and are an important cue for archaeological tasks, such as dating and attribution. To date, these analyses are mostly conducted with the support of information technology. The primitives of an artefact’s ornamentation can be generally classified into a set of distinguishable pattern classes, which also appear in a similar fashion on other objects. Although a taxonomy of known pattern classes is given in subject-specific publications, the automatic detection and classification of surface patterns from object depictions poses a non-trivial challenge. Our long-term goal is to provide this classification functionality using a specifically designed and trained neural network. This, however, requires a large amount of labelled training data, which at this point does not exist for this domain context. In this work, we propose an effective annotation system, which allows a domain expert to interactively segment and label parts of digitized vessel surfaces. These user inputs are constantly fed back to a Convolutional Neural Network (CNN), enabling the prediction of pattern classes for a given surface area with ever increasing precision. Our work paves the way for a fully automatic classification and analysis of large surface pattern collections, which, with the help of suitable visual analysis techniques, can answer research questions like pattern variability or change over time. While the capability of our proposed annotation pipeline is demonstrated at the example of two characteristic Greek pottery artefacts from the Geometric period, the proposed methods can be readily adopted for the patternation in any other chronological periods as well as for stamped motifs.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41652158","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 : 2022-08-24DOI: 10.25932/PUBLISHUP-51251
Markus Hecher
Abstract Computer programs, so-called solvers, for solving the well-known Boolean satisfiability problem (Sat) have been improving for decades. Among the reasons, why these solvers are so fast, is the implicit usage of the formula’s structural properties during solving. One of such structural indicators is the so-called treewidth, which tries to measure how close a formula instance is to being easy (tree-like). This work focuses on logic-based problems and treewidth-based methods and tools for solving them. Many of these problems are also relevant for knowledge representation and reasoning (KR) as well as artificial intelligence (AI) in general. We present a new type of problem reduction, which is referred to by decomposition-guided (DG). This reduction type forms the basis to solve a problem for quantified Boolean formulas (QBFs) of bounded treewidth that has been open since 2004. The solution of this problem then gives rise to a new methodology for proving precise lower bounds for a range of further formalisms in logic, KR, and AI. Despite the established lower bounds, we implement an algorithm for solving extensions of Sat efficiently, by directly using treewidth. Our implementation is based on finding abstractions of instances, which are then incrementally refined in the process. Thereby, our observations confirm that treewidth is an important measure that should be considered in the design of modern solvers.
{"title":"Advanced tools and methods for treewidth-based problem solving","authors":"Markus Hecher","doi":"10.25932/PUBLISHUP-51251","DOIUrl":"https://doi.org/10.25932/PUBLISHUP-51251","url":null,"abstract":"Abstract Computer programs, so-called solvers, for solving the well-known Boolean satisfiability problem (Sat) have been improving for decades. Among the reasons, why these solvers are so fast, is the implicit usage of the formula’s structural properties during solving. One of such structural indicators is the so-called treewidth, which tries to measure how close a formula instance is to being easy (tree-like). This work focuses on logic-based problems and treewidth-based methods and tools for solving them. Many of these problems are also relevant for knowledge representation and reasoning (KR) as well as artificial intelligence (AI) in general. We present a new type of problem reduction, which is referred to by decomposition-guided (DG). This reduction type forms the basis to solve a problem for quantified Boolean formulas (QBFs) of bounded treewidth that has been open since 2004. The solution of this problem then gives rise to a new methodology for proving precise lower bounds for a range of further formalisms in logic, KR, and AI. Despite the established lower bounds, we implement an algorithm for solving extensions of Sat efficiently, by directly using treewidth. Our implementation is based on finding abstractions of instances, which are then incrementally refined in the process. Thereby, our observations confirm that treewidth is an important measure that should be considered in the design of modern solvers.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45118379","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}
Johannes Zagermann, Sebastian Hubenschmid, Priscilla Balestrucci, Tiare M. Feuchtner, Sven Mayer, M. Ernst, Albrecht Schmidt, Harald Reiterer
Abstract With increasing complexity in visual computing tasks, a single device may not be sufficient to adequately support the user’s workflow. Here, we can employ multi-device ecologies such as cross-device interaction, where a workflow can be split across multiple devices, each dedicated to a specific role. But what makes these multi-device ecologies compelling? Based on insights from our research, each device or interface component must contribute a complementary characteristic to increase the quality of interaction and further support users in their current activity. We establish the term complementary interfaces for such meaningful combinations of devices and modalities and provide an initial set of challenges. In addition, we demonstrate the value of complementarity with examples from within our own research.
{"title":"Complementary interfaces for visual computing","authors":"Johannes Zagermann, Sebastian Hubenschmid, Priscilla Balestrucci, Tiare M. Feuchtner, Sven Mayer, M. Ernst, Albrecht Schmidt, Harald Reiterer","doi":"10.1515/itit-2022-0031","DOIUrl":"https://doi.org/10.1515/itit-2022-0031","url":null,"abstract":"Abstract With increasing complexity in visual computing tasks, a single device may not be sufficient to adequately support the user’s workflow. Here, we can employ multi-device ecologies such as cross-device interaction, where a workflow can be split across multiple devices, each dedicated to a specific role. But what makes these multi-device ecologies compelling? Based on insights from our research, each device or interface component must contribute a complementary characteristic to increase the quality of interaction and further support users in their current activity. We establish the term complementary interfaces for such meaningful combinations of devices and modalities and provide an initial set of challenges. In addition, we demonstrate the value of complementarity with examples from within our own research.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46133548","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}
Ying Zhang, Karsten Klein, O. Deussen, Theodor Gutschlag, Sabine Storandt
Abstract The analysis of movement trajectories plays a central role in many application areas, such as traffic management, sports analysis, and collective behavior research, where large and complex trajectory data sets are routinely collected these days. While automated analysis methods are available to extract characteristics of trajectories such as statistics on the geometry, movement patterns, and locations that might be associated with important events, human inspection is still required to interpret the results, derive parameters for the analysis, compare trajectories and patterns, and to further interpret the impact factors that influence trajectory shapes and their underlying movement processes. Every step in the acquisition and analysis pipeline might introduce artifacts or alterate trajectory features, which might bias the human interpretation or confound the automated analysis. Thus, visualization methods as well as the visualizations themselves need to take into account the corresponding factors in order to allow sound interpretation without adding or removing important trajectory features or putting a large strain on the analyst. In this paper, we provide an overview of the challenges arising in robust trajectory visualization tasks. We then discuss several methods that contribute to improved visualizations. In particular, we present practical algorithms for simplifying trajectory sets that take semantic and uncertainty information directly into account. Furthermore, we describe a complementary approach that allows to visualize the uncertainty along with the trajectories.
{"title":"Robust visualization of trajectory data","authors":"Ying Zhang, Karsten Klein, O. Deussen, Theodor Gutschlag, Sabine Storandt","doi":"10.1515/itit-2022-0036","DOIUrl":"https://doi.org/10.1515/itit-2022-0036","url":null,"abstract":"Abstract The analysis of movement trajectories plays a central role in many application areas, such as traffic management, sports analysis, and collective behavior research, where large and complex trajectory data sets are routinely collected these days. While automated analysis methods are available to extract characteristics of trajectories such as statistics on the geometry, movement patterns, and locations that might be associated with important events, human inspection is still required to interpret the results, derive parameters for the analysis, compare trajectories and patterns, and to further interpret the impact factors that influence trajectory shapes and their underlying movement processes. Every step in the acquisition and analysis pipeline might introduce artifacts or alterate trajectory features, which might bias the human interpretation or confound the automated analysis. Thus, visualization methods as well as the visualizations themselves need to take into account the corresponding factors in order to allow sound interpretation without adding or removing important trajectory features or putting a large strain on the analyst. In this paper, we provide an overview of the challenges arising in robust trajectory visualization tasks. We then discuss several methods that contribute to improved visualizations. In particular, we present practical algorithms for simplifying trajectory sets that take semantic and uncertainty information directly into account. Furthermore, we describe a complementary approach that allows to visualize the uncertainty along with the trajectories.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45338873","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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