Pub Date : 2020-12-14DOI: 10.1109/WSC48552.2020.9383923
Javier Panadero, A. Juan, Alfons Freixes, M. Grifoll, C. Serrat, Mohammad Dehghanimohamamdabadi
Efficient coordination of unmanned aerial vehicles (UAVs) requires the solving of challenging operational problems. One of them is the integrated team task assignment and orienteering problem (TAOP). The TAOP can be seen as an extension of the well-known team orienteering problem (TOP). In the classical TOP, a homogeneous fleet of UAVs has to select and visit a subset of customers in order to maximize, subject to a maximum travel time per route, the total reward obtained from these visits. In the TAOP, a number of different tasks (customer services) have to be assigned to a fleet of heterogeneous UAVs, while the best routing plan must also be determined to cover these services. Since factors such as weather conditions might influence travel times, these are modeled as random variables. Reliability issues are also considered, since random times might prevent a route from being successfully completed before a UAV runs out of battery.
{"title":"An Agile Simheuristic for the Stochastic Team Task Assignment and Orienteering Problem: Applications to Unmanned Aerial Vehicles","authors":"Javier Panadero, A. Juan, Alfons Freixes, M. Grifoll, C. Serrat, Mohammad Dehghanimohamamdabadi","doi":"10.1109/WSC48552.2020.9383923","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383923","url":null,"abstract":"Efficient coordination of unmanned aerial vehicles (UAVs) requires the solving of challenging operational problems. One of them is the integrated team task assignment and orienteering problem (TAOP). The TAOP can be seen as an extension of the well-known team orienteering problem (TOP). In the classical TOP, a homogeneous fleet of UAVs has to select and visit a subset of customers in order to maximize, subject to a maximum travel time per route, the total reward obtained from these visits. In the TAOP, a number of different tasks (customer services) have to be assigned to a fleet of heterogeneous UAVs, while the best routing plan must also be determined to cover these services. Since factors such as weather conditions might influence travel times, these are modeled as random variables. Reliability issues are also considered, since random times might prevent a route from being successfully completed before a UAV runs out of battery.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"10 1","pages":"1324-1335"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82595717","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/WSC48552.2020.9383865
Xingyu Wang, C. Rhee
In this paper we address the problem of rare-event simulation for heavy-tailed Lévy processes with infinite activities. We propose a strongly efficient importance sampling algorithm that builds upon the sample path large deviations for heavy-tailed Lévy processes, stick-breaking approximation of extrema of Lévy processes, and the randomized debiasing Monte Carlo scheme. The proposed importance sampling algorithm can be applied to a broad class of Lévy processes and exhibits significant improvements in efficiency when compared to crude Monte-Carlo method in our numerical experiments.
{"title":"Rare-Event Simulation for Multiple Jump Events in Heavy-Tailed Lévy Processes with Infinite Activities","authors":"Xingyu Wang, C. Rhee","doi":"10.1109/WSC48552.2020.9383865","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383865","url":null,"abstract":"In this paper we address the problem of rare-event simulation for heavy-tailed Lévy processes with infinite activities. We propose a strongly efficient importance sampling algorithm that builds upon the sample path large deviations for heavy-tailed Lévy processes, stick-breaking approximation of extrema of Lévy processes, and the randomized debiasing Monte Carlo scheme. The proposed importance sampling algorithm can be applied to a broad class of Lévy processes and exhibits significant improvements in efficiency when compared to crude Monte-Carlo method in our numerical experiments.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"78 1","pages":"409-420"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82845539","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/WSC48552.2020.9384039
Gongbo Zhang, Haidong Li, Yijie Peng
We study a ranking and selection problem with exponential sampling distributions. Under a Bayesian framework, we derive the posterior distribution of the performance parameter, and provide a normal approximation for the posterior distribution based on a central limit theorem to efficiently learn about the performance parameter. We formulate dynamic sampling decision as a stochastic control problem, and propose a sequential sampling procedure, which maximizes a value function approximation one-step ahead and is proved to be consistent. Numerical results demonstrate the efficiency of the proposed method.
{"title":"Sequential Sampling for a Ranking and Selection Problem with Exponential Sampling Distributions","authors":"Gongbo Zhang, Haidong Li, Yijie Peng","doi":"10.1109/WSC48552.2020.9384039","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384039","url":null,"abstract":"We study a ranking and selection problem with exponential sampling distributions. Under a Bayesian framework, we derive the posterior distribution of the performance parameter, and provide a normal approximation for the posterior distribution based on a central limit theorem to efficiently learn about the performance parameter. We formulate dynamic sampling decision as a stochastic control problem, and propose a sequential sampling procedure, which maximizes a value function approximation one-step ahead and is proved to be consistent. Numerical results demonstrate the efficiency of the proposed method.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"11 1","pages":"2984-2995"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81141614","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/WSC48552.2020.9383878
Philipp Gabriel Mazur, No-San Lee, D. Schoder
In the air cargo context, pallet loading faces substantial constraints and item heterogeneity. The stability constraint in the pallet loading problem is highly important due to its impact on the efficiency, security, and resulting costs of an air cargo company. In information systems that support pallet loading, physical simulations provide a realistic approximation of a pallet’s stability. However, current approaches neglect the opportunity to integrate physical simulations in underlying solvers. In this research, we propose and compare two approaches for integrating a physical simulation as a fixed component of the problem-solving heuristic and include irregular shapes. Our results achieve runtimes that meet air cargo requirements; therefore, assumptions about the cargo, e.g., shape assumptions, can be relaxed.
{"title":"Integration of Physical Simulations in Static Stability Assessments for Pallet Loading in Air Cargo","authors":"Philipp Gabriel Mazur, No-San Lee, D. Schoder","doi":"10.1109/WSC48552.2020.9383878","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383878","url":null,"abstract":"In the air cargo context, pallet loading faces substantial constraints and item heterogeneity. The stability constraint in the pallet loading problem is highly important due to its impact on the efficiency, security, and resulting costs of an air cargo company. In information systems that support pallet loading, physical simulations provide a realistic approximation of a pallet’s stability. However, current approaches neglect the opportunity to integrate physical simulations in underlying solvers. In this research, we propose and compare two approaches for integrating a physical simulation as a fixed component of the problem-solving heuristic and include irregular shapes. Our results achieve runtimes that meet air cargo requirements; therefore, assumptions about the cargo, e.g., shape assumptions, can be relaxed.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"20 1","pages":"1312-1323"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90323558","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/WSC48552.2020.9383919
Jake Martin, Pushpendra Singh, A. Cohn, Jakob Kiel-Locey, K. Shehadeh, S. Saini, Jacob E. Kurlander
Colonoscopy procedures are key to reducing colorectal cancer incidence and improving outcomes. For this reason, it is important that clinics be designed to maximize access to care and to use clinic time effectively. This paper presents a simulation tool that analyzes different scheduling policies to see how they impact overall clinic operations. By simultaneously simulating both scheduling and operations, the tool can account for more variability and better predict actual outcomes. This tool can be used to inform clinics on what scheduling policies work best for their clinic and help analyze what the trade-offs will be between different policies.
{"title":"Integrated Simulation Tool to Analyze Patient Access to and Flow During Colonoscopy Appointments","authors":"Jake Martin, Pushpendra Singh, A. Cohn, Jakob Kiel-Locey, K. Shehadeh, S. Saini, Jacob E. Kurlander","doi":"10.1109/WSC48552.2020.9383919","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383919","url":null,"abstract":"Colonoscopy procedures are key to reducing colorectal cancer incidence and improving outcomes. For this reason, it is important that clinics be designed to maximize access to care and to use clinic time effectively. This paper presents a simulation tool that analyzes different scheduling policies to see how they impact overall clinic operations. By simultaneously simulating both scheduling and operations, the tool can account for more variability and better predict actual outcomes. This tool can be used to inform clinics on what scheduling policies work best for their clinic and help analyze what the trade-offs will be between different policies.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"9 11","pages":"934-943"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91425039","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/WSC48552.2020.9383947
Yagmur S. Gök, M. Tomasella, Daniel Guimarans, Cemalettin Ozturk
The problem of developing robust daily schedules for the teams turning around aircraft at airports has recently been approached through an efficient combination of project scheduling and vehicle routing models, and solved jointly by constraint programming and mixed integer programming solvers, organized in a matheuristic approach based on large neighborhood search. Therein, robustness is achieved through optimally allocating time windows to tasks, as well as allocating slack times to the routes to be followed by each team throughout their working shift. We enhance that approach by integrating discrete event simulation within a simheuristic scheme, whereby results from simulation provide constructive feedback to improve the overall robustness of the plan. This is achieved as a trade-off between the interests of each separate turnaround service provider and that of the airport as a whole. Numerical experiments show the applicability of the developed approach as a decision support mechanism at any airport.
{"title":"A Simheuristic Approach for Robust Scheduling of Airport Turnaround Teams","authors":"Yagmur S. Gök, M. Tomasella, Daniel Guimarans, Cemalettin Ozturk","doi":"10.1109/WSC48552.2020.9383947","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383947","url":null,"abstract":"The problem of developing robust daily schedules for the teams turning around aircraft at airports has recently been approached through an efficient combination of project scheduling and vehicle routing models, and solved jointly by constraint programming and mixed integer programming solvers, organized in a matheuristic approach based on large neighborhood search. Therein, robustness is achieved through optimally allocating time windows to tasks, as well as allocating slack times to the routes to be followed by each team throughout their working shift. We enhance that approach by integrating discrete event simulation within a simheuristic scheme, whereby results from simulation provide constructive feedback to improve the overall robustness of the plan. This is achieved as a trade-off between the interests of each separate turnaround service provider and that of the airport as a whole. Numerical experiments show the applicability of the developed approach as a decision support mechanism at any airport.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"6 1","pages":"1336-1347"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72873285","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/WSC48552.2020.9384089
N. Feldkamp, S. Bergmann, S. Strassburger
Modular production systems aim to supersede the traditional line production in the automobile industry. The idea here is that highly customized products can move dynamically and autonomously through a system of flexible workstations without fixed production cycles. This approach has challenging demands regarding planning and organization of such systems. Since each product can define its way through the system freely and individually, implementing rules and heuristics that leverage the flexibility in the system in order to increase performance can be difficult in this dynamic environment. Transport tasks are usually carried out by automated guided vehicles (AGVs). Therefore, integration of AI-based control logics offer a promising alternative to manually implemented decision rules for operating the AGVs. This paper presents an approach for using reinforcement learning (RL) in combination with simulation in order to control AGVs in modular production systems. We present a case study and compare our approach to heuristic rules.
{"title":"Simulation-Based Deep Reinforcement Learning For Modular Production Systems","authors":"N. Feldkamp, S. Bergmann, S. Strassburger","doi":"10.1109/WSC48552.2020.9384089","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9384089","url":null,"abstract":"Modular production systems aim to supersede the traditional line production in the automobile industry. The idea here is that highly customized products can move dynamically and autonomously through a system of flexible workstations without fixed production cycles. This approach has challenging demands regarding planning and organization of such systems. Since each product can define its way through the system freely and individually, implementing rules and heuristics that leverage the flexibility in the system in order to increase performance can be difficult in this dynamic environment. Transport tasks are usually carried out by automated guided vehicles (AGVs). Therefore, integration of AI-based control logics offer a promising alternative to manually implemented decision rules for operating the AGVs. This paper presents an approach for using reinforcement learning (RL) in combination with simulation in order to control AGVs in modular production systems. We present a case study and compare our approach to heuristic rules.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"10 1","pages":"1596-1607"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81867415","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/WSC48552.2020.9383995
C. Kuhlman, S. Ravi, Gizem Korkmaz, F. Vega-Redondo
Protest is a collective action problem and can be modeled as a coordination game in which people take an action with the potential to achieve shared mutual benefits. In game-theoretic contexts, successful coordination requires that people know each others’ willingness to participate, and that this information is common knowledge among a sufficient number of people. We develop an agent-based model of collective action that was the first to combine social structure and individual incentives. Another novel aspect of the model is that a social network increases in density (i.e., new graph edges are formed) over time. The model studies the formation of common knowledge through local interactions and the characterizing social network structures. We use four real-world, data-mined social networks (Facebook, Wikipedia, email, and peer-to-peer networks) and one scale-free network, and conduct computational experiments to study contagion dynamics under different conditions.
{"title":"An Agent-Based Model of Common Knowledge and Collective Action Dynamics on Social Networks","authors":"C. Kuhlman, S. Ravi, Gizem Korkmaz, F. Vega-Redondo","doi":"10.1109/WSC48552.2020.9383995","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383995","url":null,"abstract":"Protest is a collective action problem and can be modeled as a coordination game in which people take an action with the potential to achieve shared mutual benefits. In game-theoretic contexts, successful coordination requires that people know each others’ willingness to participate, and that this information is common knowledge among a sufficient number of people. We develop an agent-based model of collective action that was the first to combine social structure and individual incentives. Another novel aspect of the model is that a social network increases in density (i.e., new graph edges are formed) over time. The model studies the formation of common knowledge through local interactions and the characterizing social network structures. We use four real-world, data-mined social networks (Facebook, Wikipedia, email, and peer-to-peer networks) and one scale-free network, and conduct computational experiments to study contagion dynamics under different conditions.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"3 1","pages":"218-229"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75397615","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/WSC48552.2020.9383925
Jaume Figueras i Jové, A. Guasch, Josep Casanovas-García
Wildfire simulation tools focus on how fire spreads in the natural environment. Simulation of fire containment operations can provide managers with a tool that combine wildfire evolution with suppression operations. Combined simulation tools are useful to evaluate different strategies and tactics in firefighting wildfires. This paper presents the modelling and simulation of aerial containment operations integrated into a wildfire spread simulator. A continuous space wildfire spread simulator has been used for fire spread simulation. This simulator called GisFIRE integrates aerial operations and uses QGIS geographical information system to integrate both simulation tools with geographical information. The information system combines air facilities locations, usable bodies of water, and other relevant geo-information with the simulation procedures. Open source software is a requirement to allow integration of different software packages and usage of OGC standards to represent geographical information.
{"title":"Simulation of Aerial Supression Tasks in Wildfire Events Integrated with Gisfire Simulator","authors":"Jaume Figueras i Jové, A. Guasch, Josep Casanovas-García","doi":"10.1109/WSC48552.2020.9383925","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383925","url":null,"abstract":"Wildfire simulation tools focus on how fire spreads in the natural environment. Simulation of fire containment operations can provide managers with a tool that combine wildfire evolution with suppression operations. Combined simulation tools are useful to evaluate different strategies and tactics in firefighting wildfires. This paper presents the modelling and simulation of aerial containment operations integrated into a wildfire spread simulator. A continuous space wildfire spread simulator has been used for fire spread simulation. This simulator called GisFIRE integrates aerial operations and uses QGIS geographical information system to integrate both simulation tools with geographical information. The information system combines air facilities locations, usable bodies of water, and other relevant geo-information with the simulation procedures. Open source software is a requirement to allow integration of different software packages and usage of OGC standards to represent geographical information.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"1 1","pages":"736-746"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74905904","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/WSC48552.2020.9383957
Zhanyang Zhang, Michael E. Kress, Tobias Schäfer
The focus of our study is to investigate the feasibility and effectiveness of using Lattice Boltzmann Advection Diffusion Equation (LBM-ADE) to model and simulate ocean oil spill transport at the surface level. We present some preliminary results from a prototype model and simulation in limited scale (a sub area of Gulf of Mexico) with assimilation of real ocean current data from the Unified Wave Interface-Coupled Model (UWIN-CM). We validate our model in a benchmark study against GNOME, a tool developed and used by NOAA for ocean oil spill forecast, under two scenarios: (i) a Gaussian hill concentration using a linear ocean current with the analytical solution as a reference; (ii) a Gaussian hill concentration using real ocean current from (UWIN-CM). Our benchmark results in both cases show the LBM-ADE model solutions are very close to the targeted analytical and GNOME solutions with the same initial oil spill and location.
{"title":"A Lattice Boltzmann Advection Diffusion Model for Ocean Oil Spill Surface Transport Prediction","authors":"Zhanyang Zhang, Michael E. Kress, Tobias Schäfer","doi":"10.1109/WSC48552.2020.9383957","DOIUrl":"https://doi.org/10.1109/WSC48552.2020.9383957","url":null,"abstract":"The focus of our study is to investigate the feasibility and effectiveness of using Lattice Boltzmann Advection Diffusion Equation (LBM-ADE) to model and simulate ocean oil spill transport at the surface level. We present some preliminary results from a prototype model and simulation in limited scale (a sub area of Gulf of Mexico) with assimilation of real ocean current data from the Unified Wave Interface-Coupled Model (UWIN-CM). We validate our model in a benchmark study against GNOME, a tool developed and used by NOAA for ocean oil spill forecast, under two scenarios: (i) a Gaussian hill concentration using a linear ocean current with the analytical solution as a reference; (ii) a Gaussian hill concentration using real ocean current from (UWIN-CM). Our benchmark results in both cases show the LBM-ADE model solutions are very close to the targeted analytical and GNOME solutions with the same initial oil spill and location.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"30 1","pages":"680-691"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73886689","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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