Pub Date : 2019-10-31DOI: 10.12783/dteees/iceee2019/31645
Y. Fan, J. Klemeš
Transportation is one of the significant contributors of GHG and air pollutants, from both the tank to well and well to wheel cycle. This study aims to introduce a graphical approach to mapping the circumstances where the energy transition offers a lower emission. The proposed method is demonstrated by a case study of the EU condition (EU-28, Latvia and Sweden). Assessed energy sources to power transportation are electricity, compressed natural gas, liquefied natural gas, diesel and biodiesel. This approach facilitates the transport mode selection (road, rail, sea) and the understanding of how electricity mix or renewable energies influence the energy transition. The environmental oriented approach can be improved in a future study by integrating the economic perspective.
{"title":"Energy Transition for Sustainable Transportation System: Graphical Approach","authors":"Y. Fan, J. Klemeš","doi":"10.12783/dteees/iceee2019/31645","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31645","url":null,"abstract":"Transportation is one of the significant contributors of GHG and air pollutants, from both the tank to well and well to wheel cycle. This study aims to introduce a graphical approach to mapping the circumstances where the energy transition offers a lower emission. The proposed method is demonstrated by a case study of the EU condition (EU-28, Latvia and Sweden). Assessed energy sources to power transportation are electricity, compressed natural gas, liquefied natural gas, diesel and biodiesel. This approach facilitates the transport mode selection (road, rail, sea) and the understanding of how electricity mix or renewable energies influence the energy transition. The environmental oriented approach can be improved in a future study by integrating the economic perspective.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77598902","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 : 2019-10-31DOI: 10.12783/dteees/iceee2019/31821
Liu Boyu, Zheng Xinzhu, Z. Qi
With the increasing competition for limited metal ore resources, the impact of capital formation on nations’ metal footprints have been studied broadly. However, the driving forces and pathways of metal footprint change still haven’t been fully understood. Therefore, in the present study, the additive structural decomposition analysis is adopted to decompose the world metal footprint from 1995 to 2013 into five major driving factors. The obtained results indicate that: i) the modern production structure has been becoming increasingly dependent upon metal resources; ii)the production structure effect and consumption volume effect are dominant factors driving the metal footprint increase, yet the intensity effect is the main force offsetting this inclining trend; iii) all the driving factors in developing countries tend to be more divergent comparing with developed countries consistent with their economic growth characteristics. The findings of this study are significant for policy makers to understand the deep causes for domestic metal footprint change and propose proper relevant polices.
{"title":"Structural Decomposition Analysis of Global Metal Footprint Change, 1995–2013","authors":"Liu Boyu, Zheng Xinzhu, Z. Qi","doi":"10.12783/dteees/iceee2019/31821","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31821","url":null,"abstract":"With the increasing competition for limited metal ore resources, the impact of capital formation on nations’ metal footprints have been studied broadly. However, the driving forces and pathways of metal footprint change still haven’t been fully understood. Therefore, in the present study, the additive structural decomposition analysis is adopted to decompose the world metal footprint from 1995 to 2013 into five major driving factors. The obtained results indicate that: i) the modern production structure has been becoming increasingly dependent upon metal resources; ii)the production structure effect and consumption volume effect are dominant factors driving the metal footprint increase, yet the intensity effect is the main force offsetting this inclining trend; iii) all the driving factors in developing countries tend to be more divergent comparing with developed countries consistent with their economic growth characteristics. The findings of this study are significant for policy makers to understand the deep causes for domestic metal footprint change and propose proper relevant polices.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77795950","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 : 2019-10-31DOI: 10.12783/dteees/iceee2019/31807
Jiahuan Lu, Xinggang Li, Hao Lei, Yonggang Liu, R. Xiong
Predicting battery remaining useful life (RUL) is used for early warning of battery aging failure and providing instructions of battery maintenance and recycling. The existing RUL prediction focus too much on decreasing the dependence of aging tests, neglecting the value of test data. In this regard, a battery RUL prediction method driven by multi-source data is proposed for EVs to make full use of the aging test data from other cells. Six lithium-ion batteries were used to verify the effectiveness of the method. The results show that the prediction error is less than only 1 cycle in the case of capacity ‘diving’. In conclusion, the proposed method effectively improves the performance of RUL prediction by using multi-source data, and provides a solution for battery management in the era of big data.
{"title":"Remaining Useful Life Prediction Driven by Multi-source Data for Batteries in Electric Vehicles","authors":"Jiahuan Lu, Xinggang Li, Hao Lei, Yonggang Liu, R. Xiong","doi":"10.12783/dteees/iceee2019/31807","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31807","url":null,"abstract":"Predicting battery remaining useful life (RUL) is used for early warning of battery aging failure and providing instructions of battery maintenance and recycling. The existing RUL prediction focus too much on decreasing the dependence of aging tests, neglecting the value of test data. In this regard, a battery RUL prediction method driven by multi-source data is proposed for EVs to make full use of the aging test data from other cells. Six lithium-ion batteries were used to verify the effectiveness of the method. The results show that the prediction error is less than only 1 cycle in the case of capacity ‘diving’. In conclusion, the proposed method effectively improves the performance of RUL prediction by using multi-source data, and provides a solution for battery management in the era of big data.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91454810","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 : 2019-10-31DOI: 10.12783/dteees/iceee2019/31725
Ying Yang, Zhen Wang
The study simplifies the application of the electrochemical model of lithium-ion battery in battery experiments and applies it to the battery management system (BMS), which can improve the validity and accuracy of the BMS for battery state estimation. Based on the charge-discharge experiments of 18650 lithium-ion battery, two simplified models are established, namely single-particle model (SP) and extended single-particle model (ESP). The research process consists of three parts: (1) the characteristics of lithium batteries under different discharge rate conditions are tested. (2) Based on the experimental results, the parameters of the two simplified models are estimated with particle swarm optimization (PSO). (3) Two simplified models are analyzed and compared using MATLAB. The results demonstrate that both simplified models can accurately predict the experimental results of 18650 lithium-ion batteries, but the effect of the ESP model is better.
{"title":"Analysis of Simplified Electrochemical Model for Lithium Battery in Electric Vehicles","authors":"Ying Yang, Zhen Wang","doi":"10.12783/dteees/iceee2019/31725","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31725","url":null,"abstract":"The study simplifies the application of the electrochemical model of lithium-ion battery in battery experiments and applies it to the battery management system (BMS), which can improve the validity and accuracy of the BMS for battery state estimation. Based on the charge-discharge experiments of 18650 lithium-ion battery, two simplified models are established, namely single-particle model (SP) and extended single-particle model (ESP). The research process consists of three parts: (1) the characteristics of lithium batteries under different discharge rate conditions are tested. (2) Based on the experimental results, the parameters of the two simplified models are estimated with particle swarm optimization (PSO). (3) Two simplified models are analyzed and compared using MATLAB. The results demonstrate that both simplified models can accurately predict the experimental results of 18650 lithium-ion batteries, but the effect of the ESP model is better.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87365757","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 : 2019-10-31DOI: 10.12783/dteees/iceee2019/31763
C. Xue, Yifeng Zhao, Zeyu Chen, Bo Zhang
State of charge (SOC) estimation is a key function of battery management system. This study examines the possibility of estimating the battery SOC under a certain short time External short circuit (ESC) process. Active short time ESC is sometimes useful in special applications that may not cause serious outcomes. The following contents are introduced in this papery. Firstly, ESC of cell experiment is designed under different SOC and temperatures. Then, genetic algorithm (GA) is used to identify model parameter, and SOC is estimated based adaptive extended Kalman filter (AEKF). It is illustrated that the presented SOC estimation can be well used in active ESC process with error less than 0.2%.
{"title":"AEKF-based Method of SOC Estimation for Batteries under the Active Short-time External Short Circuit","authors":"C. Xue, Yifeng Zhao, Zeyu Chen, Bo Zhang","doi":"10.12783/dteees/iceee2019/31763","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31763","url":null,"abstract":"State of charge (SOC) estimation is a key function of battery management system. This study examines the possibility of estimating the battery SOC under a certain short time External short circuit (ESC) process. Active short time ESC is sometimes useful in special applications that may not cause serious outcomes. The following contents are introduced in this papery. Firstly, ESC of cell experiment is designed under different SOC and temperatures. Then, genetic algorithm (GA) is used to identify model parameter, and SOC is estimated based adaptive extended Kalman filter (AEKF). It is illustrated that the presented SOC estimation can be well used in active ESC process with error less than 0.2%.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82442856","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 : 2019-10-31DOI: 10.12783/dteees/iceee2019/31805
Haiyang Lin, Yu Fu, Qie Sun, R. Wennersten
The idea that electric vehicles (EVs) can connect to the grid to serve as energy storage energy devices is compelling, especially in situations where traditional forms of storage, back-up energy supply is unavailable or expensive, or considering the volatility of frequency. So far, the viability and reliability of vehicle-grid integration, which represents smart charging (SC) and vehicle to grid (V2G) of electric vehicles, has become a very popular research topic. Previous studies mainly focused on the maximum potential of SC and V2G capacity on account of too many assumptions, which, however, is usually unrealistic to achieve. The charging and V2G flexibility of EVs are estimated from both adjustable power and adjustable amount aspects with model derived from real-world data. Overall, the EVs at home locations have the largest charging and V2G flexibility under the uncontrolled charging (UC) strategy, only in the regular working time, the maximum adjustable charging power at home location is smaller than that at work locations. Meanwhile, the V2G flexibility, is generally larger than charging flexibility at work and public locations.
{"title":"The Charging and Vehicle to Grid Flexibility of Electric Vehicles at Different Locations","authors":"Haiyang Lin, Yu Fu, Qie Sun, R. Wennersten","doi":"10.12783/dteees/iceee2019/31805","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31805","url":null,"abstract":"The idea that electric vehicles (EVs) can connect to the grid to serve as energy storage energy devices is compelling, especially in situations where traditional forms of storage, back-up energy supply is unavailable or expensive, or considering the volatility of frequency. So far, the viability and reliability of vehicle-grid integration, which represents smart charging (SC) and vehicle to grid (V2G) of electric vehicles, has become a very popular research topic. Previous studies mainly focused on the maximum potential of SC and V2G capacity on account of too many assumptions, which, however, is usually unrealistic to achieve. The charging and V2G flexibility of EVs are estimated from both adjustable power and adjustable amount aspects with model derived from real-world data. Overall, the EVs at home locations have the largest charging and V2G flexibility under the uncontrolled charging (UC) strategy, only in the regular working time, the maximum adjustable charging power at home location is smaller than that at work locations. Meanwhile, the V2G flexibility, is generally larger than charging flexibility at work and public locations.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73489717","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}
In this paper, the technology of traffic sign recognition based on machine vision is studied, and the recognition results are analyzed. Firstly, aiming at the problem of image color distortion, the input image is grayed, and the OTSU method is applied to image segmentation to extract the marking target. Then, aiming at the imbalance of image data, the OCR function is applied to train and recognize the target. Finally, the test result shows that traffic signs can be accurately identified in different environments and have good engineering application.
{"title":"Research of Traffic Sign Recognition Technology Based on Machine Vision","authors":"Aijuan Li, Zhenghong Chen, Shaohua Li, Jiaqi Chen, Xuyun Qiu, Wei Hu","doi":"10.12783/dteees/iceee2019/31777","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31777","url":null,"abstract":"In this paper, the technology of traffic sign recognition based on machine vision is studied, and the recognition results are analyzed. Firstly, aiming at the problem of image color distortion, the input image is grayed, and the OTSU method is applied to image segmentation to extract the marking target. Then, aiming at the imbalance of image data, the OCR function is applied to train and recognize the target. Finally, the test result shows that traffic signs can be accurately identified in different environments and have good engineering application.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75841203","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 : 2019-10-31DOI: 10.12783/dteees/iceee2019/31810
A. Flamos
Existing climate targets suggest energy transitions that fundamentally re-envisage the electricity system. To this end, increasing shares of renewable energy sources (RES) and reducing total demand are of paramount importance. However, one of the main challenges of a transition based on a high RES penetration is integrating these variable energy sources without jeopardizing the security and the reliability of the electricity system. Key solutions forward include the introduction of demand-side management (DSM) and flexibility functions, to absorb increased shares of dispatchable RES. However, so far DSM modeling at the building sector has been proven challenging, as the distributed and fluctuating nature of the consumption behavior can lead to misleading modeling assumptions. Addressing that, this paper presents a new Dynamic high-Resolution dEmand-sidE Management (DREEM) model. The novelty of the model lies mainly in its modularity, as its integrated structure allows for the model components’ output variables to be appropriately correlated.
{"title":"DREEM: A New Dynamic High-resolution Demand-side Management Model for Quantifying Benefits of Demand-flexibility in the Building Sector","authors":"A. Flamos","doi":"10.12783/dteees/iceee2019/31810","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31810","url":null,"abstract":"Existing climate targets suggest energy transitions that fundamentally re-envisage the electricity system. To this end, increasing shares of renewable energy sources (RES) and reducing total demand are of paramount importance. However, one of the main challenges of a transition based on a high RES penetration is integrating these variable energy sources without jeopardizing the security and the reliability of the electricity system. Key solutions forward include the introduction of demand-side management (DSM) and flexibility functions, to absorb increased shares of dispatchable RES. However, so far DSM modeling at the building sector has been proven challenging, as the distributed and fluctuating nature of the consumption behavior can lead to misleading modeling assumptions. Addressing that, this paper presents a new Dynamic high-Resolution dEmand-sidE Management (DREEM) model. The novelty of the model lies mainly in its modularity, as its integrated structure allows for the model components’ output variables to be appropriately correlated.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78847586","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}
Contactless slip-ring provide a safe, non-contact, high efficiency, wear-free and reliable power transfer solution with low maintenance for rotary applications. In this paper, a novel magnetic coupler of wireless power transfer (WPT) system for the space utilization is designed. Compared with the traditional slip ring power supply, it can be applied to the rotating condition. To realize light-weight and small-volume of the WPT, the magnetic coupler and circuit have been optimized from both compensation topology and coil configuration. Experimental results are demonstrating that transfer power is 280W at efficiency of 91.7%.
{"title":"A Rotation Face to Face Through-hole Wireless Power Transfer System for Space Applications","authors":"Liangyu Bai, Jianquan Zhang, Simin Peng, Yan-Min Liu, Xiang Li, Liangzhi Men","doi":"10.12783/dteees/iceee2019/31789","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31789","url":null,"abstract":"Contactless slip-ring provide a safe, non-contact, high efficiency, wear-free and reliable power transfer solution with low maintenance for rotary applications. In this paper, a novel magnetic coupler of wireless power transfer (WPT) system for the space utilization is designed. Compared with the traditional slip ring power supply, it can be applied to the rotating condition. To realize light-weight and small-volume of the WPT, the magnetic coupler and circuit have been optimized from both compensation topology and coil configuration. Experimental results are demonstrating that transfer power is 280W at efficiency of 91.7%.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81264275","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 : 2019-10-31DOI: 10.12783/dteees/iceee2019/31736
Jiang Zhu, Jun Yuan, Jian-min Duan
As the main mode of transportation for international trade, shipping has a large volume of transportation and low freight rate, but there are problems of large fuel consumption and large emissions. Therefore, it is necessary to take some mitigation measures to save energy and reduce emissions. Many mitigation measures have been proposed based on various factors affecting ship energy consumption. To assess the performance of these mitigation measures, the energy savings of these measures have to be evaluated. Due to the complexity of the ship energy system, these factors are of different importance and may be related each other. In this paper, several influencing factors have been chosen to assess the effects of different mitigation measures on ship energy consumption, including ship conditions (speed, draft, trim, cargo volume) and weather conditions (wind, wave). A chemical tanker is taken as the research object to analyze the ship energy system and an artificial neural network model is applied to predict and evaluate the energy consumption for different mitigation measures. Moreover, various adjustments are made to the neural network structure, and the accuracy of different structures is compared based on their prediction results. The optimal neural network structure is further identified for ship energy consumption’s prediction and evaluation.
{"title":"Ship Energy Consumption Evaluation for Mitigation Measures Using Back-Propagation Neural Network","authors":"Jiang Zhu, Jun Yuan, Jian-min Duan","doi":"10.12783/dteees/iceee2019/31736","DOIUrl":"https://doi.org/10.12783/dteees/iceee2019/31736","url":null,"abstract":"As the main mode of transportation for international trade, shipping has a large volume of transportation and low freight rate, but there are problems of large fuel consumption and large emissions. Therefore, it is necessary to take some mitigation measures to save energy and reduce emissions. Many mitigation measures have been proposed based on various factors affecting ship energy consumption. To assess the performance of these mitigation measures, the energy savings of these measures have to be evaluated. Due to the complexity of the ship energy system, these factors are of different importance and may be related each other. In this paper, several influencing factors have been chosen to assess the effects of different mitigation measures on ship energy consumption, including ship conditions (speed, draft, trim, cargo volume) and weather conditions (wind, wave). A chemical tanker is taken as the research object to analyze the ship energy system and an artificial neural network model is applied to predict and evaluate the energy consumption for different mitigation measures. Moreover, various adjustments are made to the neural network structure, and the accuracy of different structures is compared based on their prediction results. The optimal neural network structure is further identified for ship energy consumption’s prediction and evaluation.","PeriodicalId":11324,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76556758","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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