Pub Date : 2020-12-14DOI: 10.1109/WSC48552.2020.9384053
R. D. Tordecilla, Javier Panadero, A. Juan, C. L. Quintero-Araújo, J. Montoya-Torres
Location routing is a well known problem in which decisions about facility location and vehicle routing must be made. Traditionally, a fixed size or capacity is assigned to an open facility as the input parameter to the problem. However, real-world cases show that decision-makers usually have a set of size options. If this size is selected accurately according to the demand of allocated customers, then location decisions and routing activities would raise smaller cost. Nevertheless, choosing this size implies additional variables that make an already NP-hard problem even more challenging. In addition, considering stochastic demands contributes to making the optimization problem more difficult to solve. Hence, a simheuristic algorithm is proposed in this work. It combines the efficiency of metaheuristics and the capabilities of simulation to deal with uncertainty. A series of computational experiments show that our approach can efficiently deal with medium-large instances.
{"title":"A Simheuristic Algorithm for the Location Routing Problem with Facility Sizing Decisions and Stochastic Demands","authors":"R. D. Tordecilla, Javier Panadero, A. Juan, C. L. Quintero-Araújo, J. Montoya-Torres","doi":"10.1109/WSC48552.2020.9384053","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384053","url":null,"abstract":"Location routing is a well known problem in which decisions about facility location and vehicle routing must be made. Traditionally, a fixed size or capacity is assigned to an open facility as the input parameter to the problem. However, real-world cases show that decision-makers usually have a set of size options. If this size is selected accurately according to the demand of allocated customers, then location decisions and routing activities would raise smaller cost. Nevertheless, choosing this size implies additional variables that make an already NP-hard problem even more challenging. In addition, considering stochastic demands contributes to making the optimization problem more difficult to solve. Hence, a simheuristic algorithm is proposed in this work. It combines the efficiency of metaheuristics and the capabilities of simulation to deal with uncertainty. A series of computational experiments show that our approach can efficiently deal with medium-large instances.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"245 1","pages":"1265-1275"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74120998","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9384112
David King, David Jacques, Jeremy Gray, Katherine Cheney
The implementation and testing of autonomous and cooperative unmanned systems is challenging due to the inherent design complexity, infinite test spaces, and lack of autonomy specific measures. Simulation provides a low cost alternative to flight tests, allowing researchers to rapidly iterate on the design before fielding. To expedite this process, an Autonomous System Reference Architecture allows researchers to utilize existing software modules to rapidly develop algorithms for autonomous systems and test them in included simulation environments. In this paper, we implement ASRA on a cooperative wide area search scenario as a test bed to study ASRA’s utility for rapid prototyping and evaluation of autonomous and cooperative systems. Through a face centered cubic design of experiments, selected autonomy metrics are studied to provide a response surface model to characterize the system and provide a tool to optimize mission control parameters and maximize mission performance.
{"title":"Design and Simulation of a Wide Area Search Mission: An Implementation of an Autonomous Systems Reference Architecture","authors":"David King, David Jacques, Jeremy Gray, Katherine Cheney","doi":"10.1109/WSC48552.2020.9384112","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384112","url":null,"abstract":"The implementation and testing of autonomous and cooperative unmanned systems is challenging due to the inherent design complexity, infinite test spaces, and lack of autonomy specific measures. Simulation provides a low cost alternative to flight tests, allowing researchers to rapidly iterate on the design before fielding. To expedite this process, an Autonomous System Reference Architecture allows researchers to utilize existing software modules to rapidly develop algorithms for autonomous systems and test them in included simulation environments. In this paper, we implement ASRA on a cooperative wide area search scenario as a test bed to study ASRA’s utility for rapid prototyping and evaluation of autonomous and cooperative systems. Through a face centered cubic design of experiments, selected autonomy metrics are studied to provide a response surface model to characterize the system and provide a tool to optimize mission control parameters and maximize mission performance.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"129 1","pages":"540-551"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76560172","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9384079
K. P. White, R. G. Ingalls
Simulation is experimentation with a model. The behavior of the model imitates some salient aspect of the behavior of the system under study and the user experiments with the model to infer this behavior. This general framework has proven a powerful adjunct to learning, problem solving, design, and control. In this tutorial, we focus principally on discrete-event simulation – its underlying concepts, structure, and application.
{"title":"The Basics of Simulation","authors":"K. P. White, R. G. Ingalls","doi":"10.1109/WSC48552.2020.9384079","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384079","url":null,"abstract":"Simulation is experimentation with a model. The behavior of the model imitates some salient aspect of the behavior of the system under study and the user experiments with the model to infer this behavior. This general framework has proven a powerful adjunct to learning, problem solving, design, and control. In this tutorial, we focus principally on discrete-event simulation – its underlying concepts, structure, and application.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"27 1","pages":"1087-1101"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80102613","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9384113
Andrew J. Collins, Sheida Etemadidavan, Pilar Pazos Lago
Agent-based modeling (ABM) provides a means to investigate the emergent phenomenon generated from interacting autonomous agents. However, there are some concerns with this modeling approach. One concern is how to integrate strategic group formation, into ABM, without imposing macro-level aggregation rules. Another concern is whether the computerized agents’ behavior is reflective of actual human behavior. Collins and Frydenlund developed a hybrid modeling approach to address the first concern in 2018. The focus of our paper is on the second concern, in the context of the hybrid model. An experiment was conducted to help determine whether a person’s experiences affect their behavior and whether their behavior is similar to those generated by the hybrid model. The experimental results confirmed these two assertions. Our experiment used a standard cooperative game-theoretic game, called the glove game, as its base scenario.
{"title":"A Human Experiment Using a Hybrid Agent-Based Model","authors":"Andrew J. Collins, Sheida Etemadidavan, Pilar Pazos Lago","doi":"10.1109/WSC48552.2020.9384113","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384113","url":null,"abstract":"Agent-based modeling (ABM) provides a means to investigate the emergent phenomenon generated from interacting autonomous agents. However, there are some concerns with this modeling approach. One concern is how to integrate strategic group formation, into ABM, without imposing macro-level aggregation rules. Another concern is whether the computerized agents’ behavior is reflective of actual human behavior. Collins and Frydenlund developed a hybrid modeling approach to address the first concern in 2018. The focus of our paper is on the second concern, in the context of the hybrid model. An experiment was conducted to help determine whether a person’s experiences affect their behavior and whether their behavior is similar to those generated by the hybrid model. The experimental results confirmed these two assertions. Our experiment used a standard cooperative game-theoretic game, called the glove game, as its base scenario.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"1 1","pages":"1016-1026"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83084580","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9384028
Cristina Ruiz Martin, Guillermo G. Trabes, Gabriel A. Wainer
Discrete Event Systems Specification (DEVS) is a well-known formalism to develop models using the discrete event approach. One advantage of DEVS is a clear separation between the modeling and simulation activities. The user only needs to develop models and general algorithms execute the simulations. The PDEVS simulation protocol is a well-know and widely accepted algorithm to execute DEVS simulations. However, when events are scheduled with time advance equal to zero, this algorithm handles them sequentially. Events that occur at the same time are processed one after the other. This may result in unwanted simulation results. In this work, we propose a new algorithm that assures that the output bag of a model is transmitted only when all the outputs corresponding to a given simulation time have been collected.
{"title":"A New Simulation Algorithm for PDEVS Models with Time Advance Zero","authors":"Cristina Ruiz Martin, Guillermo G. Trabes, Gabriel A. Wainer","doi":"10.1109/WSC48552.2020.9384028","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384028","url":null,"abstract":"Discrete Event Systems Specification (DEVS) is a well-known formalism to develop models using the discrete event approach. One advantage of DEVS is a clear separation between the modeling and simulation activities. The user only needs to develop models and general algorithms execute the simulations. The PDEVS simulation protocol is a well-know and widely accepted algorithm to execute DEVS simulations. However, when events are scheduled with time advance equal to zero, this algorithm handles them sequentially. Events that occur at the same time are processed one after the other. This may result in unwanted simulation results. In this work, we propose a new algorithm that assures that the output bag of a model is transmitted only when all the outputs corresponding to a given simulation time have been collected.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"36 1","pages":"2208-2220"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90772790","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9384066
B. Feng, Kai Liu
Variable annuities are long-term insurance products that offer a large variety of investment-linked benefits, which have gained much popularity in the last decade. Accurate valuation of large variable annuity portfolios is an essential task for insurers. However, these products often have complicated payoffs that depend on both of the policyholder’s mortality risk and the financial market risk. Consequently, their values are usually estimated by computationally intensive Monte Carlo simulation. Simulating large numbers of sample paths from complex dynamic asset models is often a computational bottleneck. In this study, we propose and analyze three Quasi-Monte Carlo path generation methods, Cholesky decomposition, Brownian Bridge, and Principal Component Analysis, for the valuation of large VA portfolios. Our numerical results indicate that all three PGMs produce more accurate estimates than the standard Monte Carlo simulation at both the contract and portfolio levels.
{"title":"Path Generation Methods for Valuation of Large Variable Annuities Portfolio using Quasi-Monte Carlo Simulation","authors":"B. Feng, Kai Liu","doi":"10.1109/WSC48552.2020.9384066","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384066","url":null,"abstract":"Variable annuities are long-term insurance products that offer a large variety of investment-linked benefits, which have gained much popularity in the last decade. Accurate valuation of large variable annuity portfolios is an essential task for insurers. However, these products often have complicated payoffs that depend on both of the policyholder’s mortality risk and the financial market risk. Consequently, their values are usually estimated by computationally intensive Monte Carlo simulation. Simulating large numbers of sample paths from complex dynamic asset models is often a computational bottleneck. In this study, we propose and analyze three Quasi-Monte Carlo path generation methods, Cholesky decomposition, Brownian Bridge, and Principal Component Analysis, for the valuation of large VA portfolios. Our numerical results indicate that all three PGMs produce more accurate estimates than the standard Monte Carlo simulation at both the contract and portfolio levels.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"34 1","pages":"481-491"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78748910","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9384020
J. Surdu, Dirk Harrington, Jason Black, Tony Lynch, Wyatt Schmitz, Jordan Bracken
The Army has a significant training gap for Stinger gunners and teams. In particular, there is no solution that enables Stinger teams to get credit for successful engagements in large force-on-force exercises if the aircraft are not equipped with MILES detectors, which is apparently usually the case. This paper describes the development of a surrogate Stinger missile that facilitates both home station and deployed force-on-force training. The effort described in this paper resulted in a single device that addresses the training previously addressed by the three other devices, all of which are aging and often irreplaceable. This paper describes the design of the Low Altitude Air Defense Training System (LAADTS), the implementation of the prototype and results, and the future work.
{"title":"Low Altitude Air Defense Training System","authors":"J. Surdu, Dirk Harrington, Jason Black, Tony Lynch, Wyatt Schmitz, Jordan Bracken","doi":"10.1109/WSC48552.2020.9384020","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384020","url":null,"abstract":"The Army has a significant training gap for Stinger gunners and teams. In particular, there is no solution that enables Stinger teams to get credit for successful engagements in large force-on-force exercises if the aircraft are not equipped with MILES detectors, which is apparently usually the case. This paper describes the development of a surrogate Stinger missile that facilitates both home station and deployed force-on-force training. The effort described in this paper resulted in a single device that addresses the training previously addressed by the three other devices, all of which are aging and often irreplaceable. This paper describes the design of the Low Altitude Air Defense Training System (LAADTS), the implementation of the prototype and results, and the future work.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"11 1","pages":"1974-1982"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90819332","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9383945
Natalie Gentner, A. Kyek, Yao Yang, Mattia Carletti, Gian Antonio Susto
One of the main challenges in developing Machine Learning-based solutions for Semiconductor Manufacturing is the high number of machines in the production and their differences, even when considering chambers of the same machine; this poses a challenge in the scalability of Machine Learning-based solutions in this context, since the development of chamber-specific models for all equipment in the fab is unsustainable. In this work, we present a domain adaptation approach for Virtual Metrology (VM), one of the most successful Machine Learning-based technology in this context. The approach provides a common VM model for two identical-in-design chambers whose data follow different distributions. The approach is based on Domain-Adversarial Neural Networks and it has the merit of exploiting raw trace data, avoiding the loss of information that typically affects VM modules based on features. The effectiveness of the approach is demonstrated on real-world Etching.
{"title":"Enhancing Scalability of Virtual Metrology: A Deep Learning-Based Approach for Domain Adaptation","authors":"Natalie Gentner, A. Kyek, Yao Yang, Mattia Carletti, Gian Antonio Susto","doi":"10.1109/WSC48552.2020.9383945","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383945","url":null,"abstract":"One of the main challenges in developing Machine Learning-based solutions for Semiconductor Manufacturing is the high number of machines in the production and their differences, even when considering chambers of the same machine; this poses a challenge in the scalability of Machine Learning-based solutions in this context, since the development of chamber-specific models for all equipment in the fab is unsustainable. In this work, we present a domain adaptation approach for Virtual Metrology (VM), one of the most successful Machine Learning-based technology in this context. The approach provides a common VM model for two identical-in-design chambers whose data follow different distributions. The approach is based on Domain-Adversarial Neural Networks and it has the merit of exploiting raw trace data, avoiding the loss of information that typically affects VM modules based on features. The effectiveness of the approach is demonstrated on real-world Etching.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"32 1","pages":"1898-1909"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90872270","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9383908
Andreas Ruscheinski, Anja Wolpers, P. Henning, Tom Warnke, Fiete Haack, A. Uhrmacher
Particle-based simulation is a powerful approach for modeling systems and processes of entities interacting in continuous space. One way to validate a particle-based simulation is to check for the occurrence of spatio-temporal patterns formed by the particles, for example by statistical model checking. Whereas spatio-temporal logics for describing spatio-temporal patterns exist, they are defined on discrete rather than continuous space. We propose an approach to bridge this gap by automatically translating the output of continuous-space particle-based simulations into an input for discrete-space spatio-temporal logics. The translation is parameterized with information about relevant regions and their development in time. We demonstrate the utility of our approach with a case study in which we successfully apply statistical model-checking to a particle-based cell-biological model. A Java implementation of our approach is available under an open-source license.
{"title":"Pragmatic Logic-Based Spatio-Temporal Pattern Checking in Particle-Based Models","authors":"Andreas Ruscheinski, Anja Wolpers, P. Henning, Tom Warnke, Fiete Haack, A. Uhrmacher","doi":"10.1109/WSC48552.2020.9383908","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383908","url":null,"abstract":"Particle-based simulation is a powerful approach for modeling systems and processes of entities interacting in continuous space. One way to validate a particle-based simulation is to check for the occurrence of spatio-temporal patterns formed by the particles, for example by statistical model checking. Whereas spatio-temporal logics for describing spatio-temporal patterns exist, they are defined on discrete rather than continuous space. We propose an approach to bridge this gap by automatically translating the output of continuous-space particle-based simulations into an input for discrete-space spatio-temporal logics. The translation is parameterized with information about relevant regions and their development in time. We demonstrate the utility of our approach with a case study in which we successfully apply statistical model-checking to a particle-based cell-biological model. A Java implementation of our approach is available under an open-source license.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"37 1","pages":"2245-2256"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85062820","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 : 2020-12-14DOI: 10.1109/WSC48552.2020.9383915
Gerd Wagner
This tutorial article, which is extracted from (Wagner 2019), shows how to use UML Class Diagrams and Discrete Event Process Modeling Notation (DPMN) Process Diagrams for making simulation models of business processes with resource-constrained activities based on the DES paradigm of Object Event Modeling and Simulation. In this approach, the state structure of a business system is captured by a UML Class Diagram, which defines the types of objects, events and activities underlying a DPMN Process Diagram, which captures the causal regularities of the system in the form of a set of event rules. DPMN Process Diagrams extend the Event Graphs proposed by Schruben (1983) by adding elements from the Business Process Modeling Notation (BPMN), viz. data objects and activities, and, as its main innovation over BPMN, resource-dependent activity start arrows.
{"title":"Business Process Modeling And Simulation With DPMN: Resource-Constrained Activities","authors":"Gerd Wagner","doi":"10.1109/WSC48552.2020.9383915","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383915","url":null,"abstract":"This tutorial article, which is extracted from (Wagner 2019), shows how to use UML Class Diagrams and Discrete Event Process Modeling Notation (DPMN) Process Diagrams for making simulation models of business processes with resource-constrained activities based on the DES paradigm of Object Event Modeling and Simulation. In this approach, the state structure of a business system is captured by a UML Class Diagram, which defines the types of objects, events and activities underlying a DPMN Process Diagram, which captures the causal regularities of the system in the form of a set of event rules. DPMN Process Diagrams extend the Event Graphs proposed by Schruben (1983) by adding elements from the Business Process Modeling Notation (BPMN), viz. data objects and activities, and, as its main innovation over BPMN, resource-dependent activity start arrows.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"76 1","pages":"45-59"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85119396","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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