Pub Date : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156383
Min Shih, Yubo Zhang, K. Ma
The benefits of using advanced illumination models in volume visualization have been demonstrated by many researchers. Interactive volume rendering incorporated with advanced lighting has been achieved with GPU acceleration for regular-grid volume data, making volume visualization even more appealing as a tool for 3D data exploration. This paper presents an interactive illumination strategy, which is specially designed and optimized for volume visualization of unstructured-grid data. The basis of the design is a partial differential equation based illumination model to simulate the light propagation, absorption, and scattering within the volumetric medium. In particular, a two-level scheme is introduced to overcome the challenges presented by unstructured grids. Test results show that the added illumination effects such as global shadowing and multiple scattering not only lead to more visually pleasing visualization, but also greatly enhance the perception of the depth information and complex spatial relationships for features of interest in the volume data. This volume visualization enhancement is introduced at a time when unstructured grids are becoming increasingly popular for a variety of scientific simulation applications.
{"title":"Advanced lighting for unstructured-grid data visualization","authors":"Min Shih, Yubo Zhang, K. Ma","doi":"10.1109/PACIFICVIS.2015.7156383","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156383","url":null,"abstract":"The benefits of using advanced illumination models in volume visualization have been demonstrated by many researchers. Interactive volume rendering incorporated with advanced lighting has been achieved with GPU acceleration for regular-grid volume data, making volume visualization even more appealing as a tool for 3D data exploration. This paper presents an interactive illumination strategy, which is specially designed and optimized for volume visualization of unstructured-grid data. The basis of the design is a partial differential equation based illumination model to simulate the light propagation, absorption, and scattering within the volumetric medium. In particular, a two-level scheme is introduced to overcome the challenges presented by unstructured grids. Test results show that the added illumination effects such as global shadowing and multiple scattering not only lead to more visually pleasing visualization, but also greatly enhance the perception of the depth information and complex spatial relationships for features of interest in the volume data. This volume visualization enhancement is introduced at a time when unstructured grids are becoming increasingly popular for a variety of scientific simulation applications.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114656523","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 : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156381
Ayan Biswas, D. Thompson, Wenbin He, Qi Deng, Chun-Ming Chen, Han-Wei Shen, R. Machiraju, Anand Rangarajan
Although vortex analysis and detection have been extensively investigated in the past, none of the existing techniques are able to provide fully robust and reliable identification results. Local vortex detection methods are popular as they are efficient and easy to implement, and produce binary outputs based on a user-specified, hard threshold. However, vortices are global features, which present challenges for local detectors. On the other hand, global detectors are computationally intensive and require considerable user input. In this work, we propose a consensus-based uncertainty model and introduce spatial proximity to enhance vortex detection results obtained using point-based methods. We use four existing local vortex detectors and convert their outputs into fuzzy possibility values using a sigmoid-based soft-thresholding approach. We apply a majority voting scheme that enables us to identify candidate vortex regions with a higher degree of confidence. Then, we introduce spatial proximity- based analysis to discern the final vortical regions. Thus, by using spatial proximity coupled with fuzzy inputs, we propose a novel uncertainty analysis approach for vortex detection. We use expert's input to better estimate the system parameters and results from two real-world data sets demonstrate the efficacy of our method.
{"title":"An uncertainty-driven approach to vortex analysis using oracle consensus and spatial proximity","authors":"Ayan Biswas, D. Thompson, Wenbin He, Qi Deng, Chun-Ming Chen, Han-Wei Shen, R. Machiraju, Anand Rangarajan","doi":"10.1109/PACIFICVIS.2015.7156381","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156381","url":null,"abstract":"Although vortex analysis and detection have been extensively investigated in the past, none of the existing techniques are able to provide fully robust and reliable identification results. Local vortex detection methods are popular as they are efficient and easy to implement, and produce binary outputs based on a user-specified, hard threshold. However, vortices are global features, which present challenges for local detectors. On the other hand, global detectors are computationally intensive and require considerable user input. In this work, we propose a consensus-based uncertainty model and introduce spatial proximity to enhance vortex detection results obtained using point-based methods. We use four existing local vortex detectors and convert their outputs into fuzzy possibility values using a sigmoid-based soft-thresholding approach. We apply a majority voting scheme that enables us to identify candidate vortex regions with a higher degree of confidence. Then, we introduce spatial proximity- based analysis to discern the final vortical regions. Thus, by using spatial proximity coupled with fuzzy inputs, we propose a novel uncertainty analysis approach for vortex detection. We use expert's input to better estimate the system parameters and results from two real-world data sets demonstrate the efficacy of our method.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125590687","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 : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156368
F. Wang, A. Sallaberry, Karsten Klein, M. Takatsuka, Mathieu Roche
In this work, we introduce SentiCompass for exploring and comparing the sentiments of time-varying Twitter data. Our visualization design combines 2D psychology model of affect (i.e. emotion) with a time tunnel representation. To illustrate our visualization design, two case studies are conducted. They demonstrate the effectiveness of SentiCompass in achieving various tasks related to temporal sentiment and affective analysis of tweets. The interactive demo of our system is available at: http://youtu.be/ZaMF6VNO7tA.
{"title":"SentiCompass: Interactive visualization for exploring and comparing the sentiments of time-varying twitter data","authors":"F. Wang, A. Sallaberry, Karsten Klein, M. Takatsuka, Mathieu Roche","doi":"10.1109/PACIFICVIS.2015.7156368","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156368","url":null,"abstract":"In this work, we introduce SentiCompass for exploring and comparing the sentiments of time-varying Twitter data. Our visualization design combines 2D psychology model of affect (i.e. emotion) with a time tunnel representation. To illustrate our visualization design, two case studies are conducted. They demonstrate the effectiveness of SentiCompass in achieving various tasks related to temporal sentiment and affective analysis of tweets. The interactive demo of our system is available at: http://youtu.be/ZaMF6VNO7tA.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126605092","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 : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156366
K. Kucher, A. Kerren
Text visualization has become a growing and increasingly important subfield of information visualization. Thus, it is getting harder for researchers to look for related work with specific tasks or visual metaphors in mind. In this paper, we present an interactive visual survey of text visualization techniques that can be used for the purposes of search for related work, introduction to the subfield and gaining insight into research trends. We describe the taxonomy used for categorization of text visualization techniques and compare it to approaches employed in several other surveys. Finally, we present results of analyses performed on the entries data.
{"title":"Text visualization techniques: Taxonomy, visual survey, and community insights","authors":"K. Kucher, A. Kerren","doi":"10.1109/PACIFICVIS.2015.7156366","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156366","url":null,"abstract":"Text visualization has become a growing and increasingly important subfield of information visualization. Thus, it is getting harder for researchers to look for related work with specific tasks or visual metaphors in mind. In this paper, we present an interactive visual survey of text visualization techniques that can be used for the purposes of search for related work, introduction to the subfield and gaining insight into research trends. We describe the taxonomy used for categorization of text visualization techniques and compare it to approaches employed in several other surveys. Finally, we present results of analyses performed on the entries data.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127703549","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 : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156349
Xin Tong, Chun-Ming Chen, Han-Wei Shen, P. C. Wong
Occlusion presents a major challenge in visualizing 3D flow fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. A more ideal streamline exploration approach is to visually manipulate the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized deformation algorithm and an interactive visualization tool to minimize visual cluttering. The algorithm is able to maintain the overall integrity of the flow field and expose the previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the flow field freely.
{"title":"Interactive streamline exploration and manipulation using deformation","authors":"Xin Tong, Chun-Ming Chen, Han-Wei Shen, P. C. Wong","doi":"10.1109/PACIFICVIS.2015.7156349","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156349","url":null,"abstract":"Occlusion presents a major challenge in visualizing 3D flow fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. A more ideal streamline exploration approach is to visually manipulate the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized deformation algorithm and an interactive visualization tool to minimize visual cluttering. The algorithm is able to maintain the overall integrity of the flow field and expose the previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the flow field freely.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"153 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126107152","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 : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156377
Arindam Bhattacharya, C. Heinzl, A. Amirkhanov, J. Kastner, R. Wenger
This work introduces MetaTracts, a novel method for extracting and visualizing individual fiber bundles and weaving patterns from X-ray computed tomography (XCT) scans of endless carbon fiber reinforced polymers (CFRP). The proposed work flow is designed to analyze unit cells of CFRP materials integrating the recurring weaving pattern. It is designed to handle XCT scans of low resolution, in which individual fibers are not visible or are barely visible. First, a coarse version of integral curves is used to trace subsections of the individual fiber bundles in the woven CFRP materials. We call these sections MetaTracts. In the second step, these extracted fiber bundle sections (MetaTracts) are clustered using a two-step approach: first by orientation, then by proximity. The tool can generate volumetric representations as well as surface models of the extracted fiber bundles to be exported for further analysis. We evaluate the proposed work flow on a number of real world datasets and demonstrate that MetaTracts effectively and robustly identifies and separates different fiber bundles.
{"title":"MetaTracts - A method for robust extraction and visualization of carbon fiber bundles in fiber reinforced composites","authors":"Arindam Bhattacharya, C. Heinzl, A. Amirkhanov, J. Kastner, R. Wenger","doi":"10.1109/PACIFICVIS.2015.7156377","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156377","url":null,"abstract":"This work introduces MetaTracts, a novel method for extracting and visualizing individual fiber bundles and weaving patterns from X-ray computed tomography (XCT) scans of endless carbon fiber reinforced polymers (CFRP). The proposed work flow is designed to analyze unit cells of CFRP materials integrating the recurring weaving pattern. It is designed to handle XCT scans of low resolution, in which individual fibers are not visible or are barely visible. First, a coarse version of integral curves is used to trace subsections of the individual fiber bundles in the woven CFRP materials. We call these sections MetaTracts. In the second step, these extracted fiber bundle sections (MetaTracts) are clustered using a two-step approach: first by orientation, then by proximity. The tool can generate volumetric representations as well as surface models of the extracted fiber bundles to be exported for further analysis. We evaluate the proposed work flow on a number of real world datasets and demonstrate that MetaTracts effectively and robustly identifies and separates different fiber bundles.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"14 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114007473","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 : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156350
R. Bujack, Jens Kasten, I. Hotz, G. Scheuermann, E. Hitzer
We generalize the framework of moments and introduce a definition of invariants for three-dimensional vector fields. To do so, we use the method of moment normalization that has been shown to be useful in the two dimensions. Using invariant moments, we show how to search for patterns in these fields independent from their position, orientation and scale. From the first order vector moment tensor, we construct a complete and independent set of descriptors. We test the invariants in queries on synthetic and real world flow fields.
{"title":"Moment invariants for 3D flow fields via normalization","authors":"R. Bujack, Jens Kasten, I. Hotz, G. Scheuermann, E. Hitzer","doi":"10.1109/PACIFICVIS.2015.7156350","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156350","url":null,"abstract":"We generalize the framework of moments and introduce a definition of invariants for three-dimensional vector fields. To do so, we use the method of moment normalization that has been shown to be useful in the two dimensions. Using invariant moments, we show how to search for patterns in these fields independent from their position, orientation and scale. From the first order vector moment tensor, we construct a complete and independent set of descriptors. We test the invariants in queries on synthetic and real world flow fields.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122654938","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 : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156359
A. Meidiana, Seok-Hee Hong
Modern-day social networks are often dynamic and multi-relational, however there is currently little being studied on how to incorporate both aspects simultaneously to support visual analytic tasks for such complex social networks. We present a visual analytic framework for dynamic multi-relational networks and a prototype implementation, called the MultiStory system, which includes two new visualisation methods, AlterCluster and InterArc, designed for dynamic networks with multiple relations. The system is evaluated with two case studies using social networks from the MIT Reality Commons to demonstrate the effectiveness of the system to support a variety of visual analytical tasks on dynamic multi-relational networks.
{"title":"MultiStory: Visual analytics of dynamic multi-relational networks","authors":"A. Meidiana, Seok-Hee Hong","doi":"10.1109/PACIFICVIS.2015.7156359","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156359","url":null,"abstract":"Modern-day social networks are often dynamic and multi-relational, however there is currently little being studied on how to incorporate both aspects simultaneously to support visual analytic tasks for such complex social networks. We present a visual analytic framework for dynamic multi-relational networks and a prototype implementation, called the MultiStory system, which includes two new visualisation methods, AlterCluster and InterArc, designed for dynamic networks with multiple relations. The system is evaluated with two case studies using social networks from the MIT Reality Commons to demonstrate the effectiveness of the system to support a variety of visual analytical tasks on dynamic multi-relational networks.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132915320","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 : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156378
Bongshin Lee, Greg Smith, N. Riche, Amy K. Karlson, Sheelagh Carpendale
In this work, we advance research efforts in combining the casual sketching approach of whiteboards with the machine's computing power. We present SketchInsight, a system that applies the familiar and collaborative features of a whiteboard interface to the accurate data exploration capabilities of interactive visualizations. SketchInsight enables data analysis with more fluid interaction, allowing people to visually explore their data by drawing simple charts and directly manipulating them. In addition, we report results from a qualitative study conducted to evaluate user experience in exploring data with SketchInsight, expanding our understanding on how people use a pen- and touch-enabled digital whiteboard for data exploration. We also discuss the challenges in building a working system that supports data analytic capabilities with pen and touch interaction and freeform annotation.
{"title":"SketchInsight: Natural data exploration on interactive whiteboards leveraging pen and touch interaction","authors":"Bongshin Lee, Greg Smith, N. Riche, Amy K. Karlson, Sheelagh Carpendale","doi":"10.1109/PACIFICVIS.2015.7156378","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156378","url":null,"abstract":"In this work, we advance research efforts in combining the casual sketching approach of whiteboards with the machine's computing power. We present SketchInsight, a system that applies the familiar and collaborative features of a whiteboard interface to the accurate data exploration capabilities of interactive visualizations. SketchInsight enables data analysis with more fluid interaction, allowing people to visually explore their data by drawing simple charts and directly manipulating them. In addition, we report results from a qualitative study conducted to evaluate user experience in exploring data with SketchInsight, expanding our understanding on how people use a pen- and touch-enabled digital whiteboard for data exploration. We also discuss the challenges in building a working system that supports data analytic capabilities with pen and touch interaction and freeform annotation.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133767707","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 : 2015-04-14DOI: 10.1109/PACIFICVIS.2015.7156386
V. Narayanan, Dilip Mathew Thomas, V. Natarajan
Scientific phenomena are often studied through collections of related scalar fields generated from different observations of the same phenomenon. Exploration of such data requires a robust distance measure to compare scalar fields for tasks such as identifying key events and establishing correspondence between features in the data. Towards this goal, we propose a topological data structure called the complete extremum graph and define a distance measure on it for comparing scalar fields in a feature-aware manner. We design an algorithm for computing the distance and show its applications in analysing time varying data.
{"title":"Distance between extremum graphs","authors":"V. Narayanan, Dilip Mathew Thomas, V. Natarajan","doi":"10.1109/PACIFICVIS.2015.7156386","DOIUrl":"https://doi.org/10.1109/PACIFICVIS.2015.7156386","url":null,"abstract":"Scientific phenomena are often studied through collections of related scalar fields generated from different observations of the same phenomenon. Exploration of such data requires a robust distance measure to compare scalar fields for tasks such as identifying key events and establishing correspondence between features in the data. Towards this goal, we propose a topological data structure called the complete extremum graph and define a distance measure on it for comparing scalar fields in a feature-aware manner. We design an algorithm for computing the distance and show its applications in analysing time varying data.","PeriodicalId":177381,"journal":{"name":"2015 IEEE Pacific Visualization Symposium (PacificVis)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122969937","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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