Pub Date : 2020-04-01DOI: 10.7763/ijmo.2020.v10.745
Xing Yee Leong, N. Jajo, S. Peiris
Medical professionals and patients have struggled with long elective surgery waiting line for decades. Hospitals across the world, especially in countries with universal healthcare, struggle with balancing the heavy demand from elective surgery waiting line and allocating enough resources for emergency patients. Patients must rely on private hospitals or going abroad to get faster health care, but poorer patients do not have this privilege. In this research, we investigate whether moving surgeons across hospitals within a local health district can improve the elective surgery waiting line. For the scope of this research, only 3 types of surgeries, Urology, Ophthalmology, and Orthodontics, are considered. In order to implement the simulation process, 3000 dummy patients, 2000 old and 1000 new patients, were created for each urgency type in each surgery category. The data was fed into a new model in the Arena Simulation model as input. Poisson and Triangular distribution were applied in this model for assigning the surgery and observation duration. Our model scenario contains 2 large hospitals and 1 small hospital. In the experiment model, one surgeon was moved from both large hospitals to the designated small hospital, and we analyzed the 90 percentile of the output. We noticed that the 90 percentile duration in the waiting line decreased for both small and large hospitals after moving one surgeon from each large hospital. Therefore, we can conclude that temporarily transferring surgeons from one hospital to another can be beneficial to the elective surgery wait line. By moving surgeons instead of patients, patients can also choose a hospital nearer to their home for their elective surgery.
{"title":"Discrete Simulation on Elective Surgery Wait Line Using Arena Simulation Software","authors":"Xing Yee Leong, N. Jajo, S. Peiris","doi":"10.7763/ijmo.2020.v10.745","DOIUrl":"https://doi.org/10.7763/ijmo.2020.v10.745","url":null,"abstract":"Medical professionals and patients have struggled with long elective surgery waiting line for decades. Hospitals across the world, especially in countries with universal healthcare, struggle with balancing the heavy demand from elective surgery waiting line and allocating enough resources for emergency patients. Patients must rely on private hospitals or going abroad to get faster health care, but poorer patients do not have this privilege. In this research, we investigate whether moving surgeons across hospitals within a local health district can improve the elective surgery waiting line. For the scope of this research, only 3 types of surgeries, Urology, Ophthalmology, and Orthodontics, are considered. In order to implement the simulation process, 3000 dummy patients, 2000 old and 1000 new patients, were created for each urgency type in each surgery category. The data was fed into a new model in the Arena Simulation model as input. Poisson and Triangular distribution were applied in this model for assigning the surgery and observation duration. Our model scenario contains 2 large hospitals and 1 small hospital. In the experiment model, one surgeon was moved from both large hospitals to the designated small hospital, and we analyzed the 90 percentile of the output. We noticed that the 90 percentile duration in the waiting line decreased for both small and large hospitals after moving one surgeon from each large hospital. Therefore, we can conclude that temporarily transferring surgeons from one hospital to another can be beneficial to the elective surgery wait line. By moving surgeons instead of patients, patients can also choose a hospital nearer to their home for their elective surgery.","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115845357","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 : 2020-04-01DOI: 10.7763/ijmo.2020.v10.748
A. Olaru, S. Olaru, Niculae Mihai, N. Šmídová
Multi objectives optimization in Robotics is one of the most difficult problem to be solved. In the paper will be shown the matrix form of the resistive and active forces and the proper algorithm to establish the best case between all studied cases. The mathematical matrix form of the active forces equations was transposed to the virtual LabVIEW instrumentation with the goals to obtain some characteristics of the active forces in each joints of the robot variation vs. time in the case when were changed some functional or constructive parameters. By using proper algorithm was choose the best solution between the studied cases for down movements of the robot’s arm. The applied method, the algorithm and the proper virtual instrumentation solve one small part of the complex problems of the optimisation in robotics.
{"title":"Assisted Multi Objectives Research Optimization of the Arm Type Robot’s Forces","authors":"A. Olaru, S. Olaru, Niculae Mihai, N. Šmídová","doi":"10.7763/ijmo.2020.v10.748","DOIUrl":"https://doi.org/10.7763/ijmo.2020.v10.748","url":null,"abstract":"Multi objectives optimization in Robotics is one of the most difficult problem to be solved. In the paper will be shown the matrix form of the resistive and active forces and the proper algorithm to establish the best case between all studied cases. The mathematical matrix form of the active forces equations was transposed to the virtual LabVIEW instrumentation with the goals to obtain some characteristics of the active forces in each joints of the robot variation vs. time in the case when were changed some functional or constructive parameters. By using proper algorithm was choose the best solution between the studied cases for down movements of the robot’s arm. The applied method, the algorithm and the proper virtual instrumentation solve one small part of the complex problems of the optimisation in robotics.","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123585279","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 : 2020-02-01DOI: 10.7763/ijmo.2020.v10.740
B. D. Van Der Waaij, Groningen Dw Netherlands Tno, E. Lazovik, T. Albers
In modern data-driven analysis it becomes quite typical to process not only the datasets you own, but to collaborate with other organizations to receive data and analysis results from them as well. It is performed to achieve much more accurate analysis results, make better predictions, and be able to provide better decision-support mechanisms. However, to analyze data in a cross-organizational environment is not the same as to analyze your own data: there are many limitations and conditions from the collaborators to allow access to their data and/or analysis models. This paper presents a methodology called CO-ARCH dealing with the process of choosing the suitable data-driven architectures for collaboration on data analysis between different organizations having their own conditions and limitations.
{"title":"CO-ARCH: Methodology for COllaborative ARCHitectures for Cross-organizational Data Analysis","authors":"B. D. Van Der Waaij, Groningen Dw Netherlands Tno, E. Lazovik, T. Albers","doi":"10.7763/ijmo.2020.v10.740","DOIUrl":"https://doi.org/10.7763/ijmo.2020.v10.740","url":null,"abstract":"In modern data-driven analysis it becomes quite typical to process not only the datasets you own, but to collaborate with other organizations to receive data and analysis results from them as well. It is performed to achieve much more accurate analysis results, make better predictions, and be able to provide better decision-support mechanisms. However, to analyze data in a cross-organizational environment is not the same as to analyze your own data: there are many limitations and conditions from the collaborators to allow access to their data and/or analysis models. This paper presents a methodology called CO-ARCH dealing with the process of choosing the suitable data-driven architectures for collaboration on data analysis between different organizations having their own conditions and limitations.","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124871193","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 : 2020-02-01DOI: 10.7763/ijmo.2020.v10.738
Martin Maiwald, Linda Kosmol, C. Pieper, T. Schmidt
One approach to a more sustainable industry is the reuse of waste and by-products. In particular, the exchange of resources between companies and the reuse of energy are considered critical, as they are time-dependent and may require technical or organizational changes to the production system leading to new interdependencies between the companies. Simulation is a suitable tool for analyzing the dynamic behavior of production systems to identify and evaluate critical factors and risks with regard to compatibility or feasibility, necessary changes and their effects on the system. This paper presents a modeling and simulation approach for resource reuse and exchange in the context of industrial symbiosis. To distinguish the proposed method from related work, an overview of existing modeling and simulation approaches is presented. The suggested approach is based on the modeling language Modelica. A custom model library with reusable preconfigured model elements is developed to model and simulate different production systems and scenarios bottom-up and modularly and in order to investigate interactions between resource providers and consumers. The conceptual and mathematical development of the model components and their interaction principles are presented and demonstrated. Based on this, organizational interdependencies and their economic and ecological impacts can be analyzed.
{"title":"ESProNet: A Model Library for the Dynamic Simulation of Industrial Symbiosis","authors":"Martin Maiwald, Linda Kosmol, C. Pieper, T. Schmidt","doi":"10.7763/ijmo.2020.v10.738","DOIUrl":"https://doi.org/10.7763/ijmo.2020.v10.738","url":null,"abstract":"One approach to a more sustainable industry is the reuse of waste and by-products. In particular, the exchange of resources between companies and the reuse of energy are considered critical, as they are time-dependent and may require technical or organizational changes to the production system leading to new interdependencies between the companies. Simulation is a suitable tool for analyzing the dynamic behavior of production systems to identify and evaluate critical factors and risks with regard to compatibility or feasibility, necessary changes and their effects on the system. This paper presents a modeling and simulation approach for resource reuse and exchange in the context of industrial symbiosis. To distinguish the proposed method from related work, an overview of existing modeling and simulation approaches is presented. The suggested approach is based on the modeling language Modelica. A custom model library with reusable preconfigured model elements is developed to model and simulate different production systems and scenarios bottom-up and modularly and in order to investigate interactions between resource providers and consumers. The conceptual and mathematical development of the model components and their interaction principles are presented and demonstrated. Based on this, organizational interdependencies and their economic and ecological impacts can be analyzed.","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114529295","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 : 2020-02-01DOI: 10.7763/ijmo.2020.v10.743
Kanon Sujaree
In this research study, a novel metaheuristic approach using nanotechnology is proposed, known as Artificial Carbon Nanotube Synthesis Optimization (ACNSO), in order to develop a vaccine cold chain network in north of Thailand. The scope of the study emphasizes Area 1 of the Office Disease Prevention and Control in the Chiang Mai region. Vaccines must be transported both to the Provincial Health Offices and hospitals in the region. This study seeks to arrange the transportation routes involved in order to achieve the shortest possible total distance. The algorithm must first of all assess the travel conditions between each point in the network, and then generate the starting solution. Efficient solutions to this problem will cut the total processing time. The study then made a comparison between the results produced by ACNSO algorithm and those of other algorithms used in earlier studies. Full factorial design was the statistical approach used to evaluate the optimal parameters for the algorithm. The experiment was designed to examine the various factors which influence the algorithm performance. The results showed that ACNSO algorithm found the best solution in experimental algorithms and 3 processing time.
{"title":"Artificial Carbon Nanotube Synthesis Optimization to Address the Vaccine Cold Chain Network Problem","authors":"Kanon Sujaree","doi":"10.7763/ijmo.2020.v10.743","DOIUrl":"https://doi.org/10.7763/ijmo.2020.v10.743","url":null,"abstract":"In this research study, a novel metaheuristic approach using nanotechnology is proposed, known as Artificial Carbon Nanotube Synthesis Optimization (ACNSO), in order to develop a vaccine cold chain network in north of Thailand. The scope of the study emphasizes Area 1 of the Office Disease Prevention and Control in the Chiang Mai region. Vaccines must be transported both to the Provincial Health Offices and hospitals in the region. This study seeks to arrange the transportation routes involved in order to achieve the shortest possible total distance. The algorithm must first of all assess the travel conditions between each point in the network, and then generate the starting solution. Efficient solutions to this problem will cut the total processing time. The study then made a comparison between the results produced by ACNSO algorithm and those of other algorithms used in earlier studies. Full factorial design was the statistical approach used to evaluate the optimal parameters for the algorithm. The experiment was designed to examine the various factors which influence the algorithm performance. The results showed that ACNSO algorithm found the best solution in experimental algorithms and 3 processing time.","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114731590","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 : 2020-02-01DOI: 10.7763/ijmo.2020.v10.741
Can Zhang, Mingyuan Zang, Ying Yan
Internet traffic is predicted to increase fast over the next years. A large portion of it will be generated by mobile video services. Such a data explosion puts higher requirements on the capacity of the mobile network. Deploying more bandwidth resources to increase the network capacity is one solution, but it also means high cost. Mobile Edge Caching (MEC) is a new solution put forward these years to deal with the drastic growth of video data by bringing the video resources close to users at the edge cache. Researches have been done on the design of MEC, and implementing it in an emulator is one of the ways to verify the design. An emulator can provide real-case protocol implementation and more credible results compared with simulator. This paper studies the LTE emulators available in the market and proposes an MEC testbed based on the OpenAirInterface platform. Two use cases of the testbed are demonstrated and their performances are evaluated separately.
{"title":"Design and Evaluation on Mobile Edge Caching Testbed","authors":"Can Zhang, Mingyuan Zang, Ying Yan","doi":"10.7763/ijmo.2020.v10.741","DOIUrl":"https://doi.org/10.7763/ijmo.2020.v10.741","url":null,"abstract":"Internet traffic is predicted to increase fast over the next years. A large portion of it will be generated by mobile video services. Such a data explosion puts higher requirements on the capacity of the mobile network. Deploying more bandwidth resources to increase the network capacity is one solution, but it also means high cost. Mobile Edge Caching (MEC) is a new solution put forward these years to deal with the drastic growth of video data by bringing the video resources close to users at the edge cache. Researches have been done on the design of MEC, and implementing it in an emulator is one of the ways to verify the design. An emulator can provide real-case protocol implementation and more credible results compared with simulator. This paper studies the LTE emulators available in the market and proposes an MEC testbed based on the OpenAirInterface platform. Two use cases of the testbed are demonstrated and their performances are evaluated separately.","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131975344","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 : 2020-02-01DOI: 10.7763/ijmo.2020.v10.739
Vaughn H. Standley, Frank G. Nuño, Jacob W. Sharpe
A prolonged campaign of peaceful interstate competition is an ideal strategic application of artificial intelligence. Monte Carlo simulation, based on validated war analytics, must be at the heart of this capability. Otherwise the system will not know how to assess the potential consequences of failed solutions, chief among them combat fatalities resulting from interstate war. Although the power law has been used since 1960 to model the statistical distribution of deaths resulting from violent conflict, it is not a valid candidate for use in Monte Carlo simulation because it is mathematically divergent for the case of interstate war. Probing Correlates of War Project data, investigators found that combat fatalities in interstate war follow log-gamma or log-normal distributions, depending on whether a state is attacking or defending. Both distributions are valid for use in Monte Carlo simulations. Moreover, they are strong quantitative evidence that war should be modeled as a zero-sum, non-cooperative, high-risk game.
{"title":"Modeling Interstate War Combat Deaths","authors":"Vaughn H. Standley, Frank G. Nuño, Jacob W. Sharpe","doi":"10.7763/ijmo.2020.v10.739","DOIUrl":"https://doi.org/10.7763/ijmo.2020.v10.739","url":null,"abstract":"A prolonged campaign of peaceful interstate competition is an ideal strategic application of artificial intelligence. Monte Carlo simulation, based on validated war analytics, must be at the heart of this capability. Otherwise the system will not know how to assess the potential consequences of failed solutions, chief among them combat fatalities resulting from interstate war. Although the power law has been used since 1960 to model the statistical distribution of deaths resulting from violent conflict, it is not a valid candidate for use in Monte Carlo simulation because it is mathematically divergent for the case of interstate war. Probing Correlates of War Project data, investigators found that combat fatalities in interstate war follow log-gamma or log-normal distributions, depending on whether a state is attacking or defending. Both distributions are valid for use in Monte Carlo simulations. Moreover, they are strong quantitative evidence that war should be modeled as a zero-sum, non-cooperative, high-risk game.","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125190307","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 : 2020-02-01DOI: 10.7763/ijmo.2020.v10.742
Alexandros Deligiannis, Charalampos Argyriou, D. Kourtesis
The goal of the research presented here is to describe an innovative approach to predicting the impact of a business messaging campaign, by estimating the percentage of message recipients who will engage with a message. The motivation is to facilitate business marketers to address the problem of estimating the return on investment coming from a potential messaging campaign. The presented solution relies on the processing of large scale business data, taking into account state-of-the-art predictive algorithms, GDPR compliance requirements, and the challenge of increased data security and availability. In this paper we discuss the design of the core functional components of a system that could make this possible, which encompasses predictive analytics, data mining and machine learning technologies in a cloud computing environment.
{"title":"Building a Cloud-based Regression Model to Predict Click-through Rate in Business Messaging Campaigns","authors":"Alexandros Deligiannis, Charalampos Argyriou, D. Kourtesis","doi":"10.7763/ijmo.2020.v10.742","DOIUrl":"https://doi.org/10.7763/ijmo.2020.v10.742","url":null,"abstract":"The goal of the research presented here is to describe an innovative approach to predicting the impact of a business messaging campaign, by estimating the percentage of message recipients who will engage with a message. The motivation is to facilitate business marketers to address the problem of estimating the return on investment coming from a potential messaging campaign. The presented solution relies on the processing of large scale business data, taking into account state-of-the-art predictive algorithms, GDPR compliance requirements, and the challenge of increased data security and availability. In this paper we discuss the design of the core functional components of a system that could make this possible, which encompasses predictive analytics, data mining and machine learning technologies in a cloud computing environment.","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124438469","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 : 2019-12-01DOI: 10.7763/ijmo.2019.v9.736
O. Stan, A. Manea
{"title":"Design and Implement a 6DOF Anthropomorphic Robotic Structure","authors":"O. Stan, A. Manea","doi":"10.7763/ijmo.2019.v9.736","DOIUrl":"https://doi.org/10.7763/ijmo.2019.v9.736","url":null,"abstract":"","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121589804","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 : 2019-12-01DOI: 10.7763/ijmo.2019.v9.735
S. Toyama, Uichi Nishizawa
The deep sea of the 4,000m grade is a treasure house of resources. However, there are no precise maps about the sea bottom shape. So, the authors have developed deep-sea drone with functions to make sensing marine bottom and make maps of the 4,000m depth grades. The drone shape durable in the deep sea is only a sphere. The authors have made a prototype of deep-sea drone by use of spherical ultrasonic motors. The authors have succeeded in driving it in underwater.
{"title":"Deep-sea Drone with Spherical Ultrasonic Motors","authors":"S. Toyama, Uichi Nishizawa","doi":"10.7763/ijmo.2019.v9.735","DOIUrl":"https://doi.org/10.7763/ijmo.2019.v9.735","url":null,"abstract":"The deep sea of the 4,000m grade is a treasure house of resources. However, there are no precise maps about the sea bottom shape. So, the authors have developed deep-sea drone with functions to make sensing marine bottom and make maps of the 4,000m depth grades. The drone shape durable in the deep sea is only a sphere. The authors have made a prototype of deep-sea drone by use of spherical ultrasonic motors. The authors have succeeded in driving it in underwater.","PeriodicalId":134487,"journal":{"name":"International Journal of Modeling and Optimization","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128503615","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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