Pub Date : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511706
Veaceslav Sprincean, Adrian Paladi, Vasili Andruh, Anton Danici, Petru Lozovanu, F. Paladi
Software application for computational modeling of environmental factors, in connection with U A V -based measuring station for environmental factors monitoring in realtime regime precise measurements [1], which facilitates the analysis and interpretation of the monitoring results, has been developed as an integrated mobile system for exact monitoring and computational modeling of environmental factors. This paper deals with the second stage related to the drone-dedicated system developed at the Moldova State University (MSU) in the research laboratory Environmental Physics and Modeling Complex Systems (MSU ePhysMCS Lab) for the observation and support of the air analysis for pollution, chemical and radiological contaminations [2]. The exact data are used in modeling of the impact of biotic and abiotic factors during the real-time environmental monitoring process.
{"title":"UAV-based Measuring Station for Monitoring and Computational Modeling of Environmental Factors","authors":"Veaceslav Sprincean, Adrian Paladi, Vasili Andruh, Anton Danici, Petru Lozovanu, F. Paladi","doi":"10.1109/MetroAeroSpace51421.2021.9511706","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511706","url":null,"abstract":"Software application for computational modeling of environmental factors, in connection with U A V -based measuring station for environmental factors monitoring in realtime regime precise measurements [1], which facilitates the analysis and interpretation of the monitoring results, has been developed as an integrated mobile system for exact monitoring and computational modeling of environmental factors. This paper deals with the second stage related to the drone-dedicated system developed at the Moldova State University (MSU) in the research laboratory Environmental Physics and Modeling Complex Systems (MSU ePhysMCS Lab) for the observation and support of the air analysis for pollution, chemical and radiological contaminations [2]. The exact data are used in modeling of the impact of biotic and abiotic factors during the real-time environmental monitoring process.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115690841","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 : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511689
G. Boscheri, A. Saverino, C. Lobascio
In situ food production capability is a key achievement required to enable long term human space exploration. Making food production sustainable in space is not only a matter of increasing crop yields while reducing necessary consumables, power consumption and buffers, coping with the microgravity or planetary space environment. Safety, reliability, repeatability, maintainability, logistics, failures management, biocontamination control are the key enabling aspects for sustainable food production technologies. Starting from the experience gained in Thales Alenia Space Italia from multiple studies in the ASI, ESA and EC framework, as well as from internal research activities, the lessons learnt concerning these key enabling aspects were analyzed. A path toward sustainable food production in space emerged from this analysis, impacting the currently ongoing ESA PFPU projects. This path runs along with analog applications for a sustainable future on Earth.
{"title":"Sustainable Food Production To Enable Long Term Human Space Exploration","authors":"G. Boscheri, A. Saverino, C. Lobascio","doi":"10.1109/MetroAeroSpace51421.2021.9511689","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511689","url":null,"abstract":"In situ food production capability is a key achievement required to enable long term human space exploration. Making food production sustainable in space is not only a matter of increasing crop yields while reducing necessary consumables, power consumption and buffers, coping with the microgravity or planetary space environment. Safety, reliability, repeatability, maintainability, logistics, failures management, biocontamination control are the key enabling aspects for sustainable food production technologies. Starting from the experience gained in Thales Alenia Space Italia from multiple studies in the ASI, ESA and EC framework, as well as from internal research activities, the lessons learnt concerning these key enabling aspects were analyzed. A path toward sustainable food production in space emerged from this analysis, impacting the currently ongoing ESA PFPU projects. This path runs along with analog applications for a sustainable future on Earth.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123402392","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 : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511695
G. Gugliandolo, M. T. Caccamo, G. Castorina, Domenica Letizia Chillemi, F. Famoso, G. Munaò, M. Raffaele, Valeria Schifilliti, Agostino Semprebello, S. Magazù
Among the issues affecting the aeronautical field, it is worth highlighting the impact that volcanic eruptions have on airport infrastructures. Such events can lead to delays and flights cancellations. In addition, airports may need to be shut down in order to restore the runway conditions with an important financial impact on the airport and airline companies as well as inconveniences for travelers. Moreover, volcanic ashes suspended in air represent a significant hazard for aircraft in flight: they limit the visibility and can seriously affect both mechanical parts and electronic components. The scope of this work is to develop a machine learning-based model able to predict such events in order to optimize the airport management in case of such extreme and uncontrollable phenomenon.
{"title":"A machine learning-based predictive model for risk assessment in airport areas","authors":"G. Gugliandolo, M. T. Caccamo, G. Castorina, Domenica Letizia Chillemi, F. Famoso, G. Munaò, M. Raffaele, Valeria Schifilliti, Agostino Semprebello, S. Magazù","doi":"10.1109/MetroAeroSpace51421.2021.9511695","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511695","url":null,"abstract":"Among the issues affecting the aeronautical field, it is worth highlighting the impact that volcanic eruptions have on airport infrastructures. Such events can lead to delays and flights cancellations. In addition, airports may need to be shut down in order to restore the runway conditions with an important financial impact on the airport and airline companies as well as inconveniences for travelers. Moreover, volcanic ashes suspended in air represent a significant hazard for aircraft in flight: they limit the visibility and can seriously affect both mechanical parts and electronic components. The scope of this work is to develop a machine learning-based model able to predict such events in order to optimize the airport management in case of such extreme and uncontrollable phenomenon.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123635608","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 : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511729
A. Lerro, A. Brandl, P. Gili, M. Pisani
In this work, the SAIFE project is presented highlighting its main innovative aspects and the verification strategy up to TRL 6. In fact, the SAIFE project is born to demonstrate in operative environment a synthetic solution to estimate the aircraft flow angles, angle-of-attack and angle-of-sideslip. The flow angle synthetic solution is based on a model-free scheme named ASSE and it is briefly described. The SAIFE solution is suitable for modern aircraft or it can be adopted on board drones and urban mobility air vehicles. The SAIFE project is introduced and its main advantages with respect to the state-of-the-art are presented. The SAIFE demonstrator is designed and manufactured to be verified first in laboratory and later validated during flight tests.
{"title":"The SAIFE Project: Demonstration of a Model-Free Synthetic Sensor for Flow Angle Estimation","authors":"A. Lerro, A. Brandl, P. Gili, M. Pisani","doi":"10.1109/MetroAeroSpace51421.2021.9511729","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511729","url":null,"abstract":"In this work, the SAIFE project is presented highlighting its main innovative aspects and the verification strategy up to TRL 6. In fact, the SAIFE project is born to demonstrate in operative environment a synthetic solution to estimate the aircraft flow angles, angle-of-attack and angle-of-sideslip. The flow angle synthetic solution is based on a model-free scheme named ASSE and it is briefly described. The SAIFE solution is suitable for modern aircraft or it can be adopted on board drones and urban mobility air vehicles. The SAIFE project is introduced and its main advantages with respect to the state-of-the-art are presented. The SAIFE demonstrator is designed and manufactured to be verified first in laboratory and later validated during flight tests.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129917585","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 : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511747
E. I. Trombetta, Iris David Du Mutel de Pierrepont Frauzetti, D. Carminati, M. Scanavino, E. Capello
Autonomous mobile robots rely on the environment features to operate. In a framework in which agents operate autonomously from each other and only use their on-board sensors and computing power, an accurate simulation environment has to be set up. Accuracy is increased by producing a good model of the robot agent itself. In this paper, a data-driven identification method is exploited to design a black-box model for numerical simulations. A MATLAB/Simulink-ROS-Unity3D hybrid environment is considered as simulation scenario, to be easily connected to the on-board real hardware.
{"title":"Data-Driven Identification Method and Simulation Modeling of a Ground Robot","authors":"E. I. Trombetta, Iris David Du Mutel de Pierrepont Frauzetti, D. Carminati, M. Scanavino, E. Capello","doi":"10.1109/MetroAeroSpace51421.2021.9511747","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511747","url":null,"abstract":"Autonomous mobile robots rely on the environment features to operate. In a framework in which agents operate autonomously from each other and only use their on-board sensors and computing power, an accurate simulation environment has to be set up. Accuracy is increased by producing a good model of the robot agent itself. In this paper, a data-driven identification method is exploited to design a black-box model for numerical simulations. A MATLAB/Simulink-ROS-Unity3D hybrid environment is considered as simulation scenario, to be easily connected to the on-board real hardware.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121159363","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 : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511660
Ilija Jovanovic, Shaghayegh Khodabakhshian Khonsari, J. Enright
Effective calibration of sensors with fine-scale irregularities in their residual space requires large and dense calibration datasets. For the case of biaxial electrolytic inclinometers, these irregularities are not evenly distributed and concentrate in small regions that drive data resolution requirements. Using evenly spaced sampling for look up tables results in less irregular regions being over-sampled, burdening the calibration process. Artificial neural networks have the capability to optimally distribute a limited number of trainable parameters to minimize the residuals. This can have the benefit of reducing data collection requirements as well as reducing memory requirements. In this paper, we compare the residual model accuracy of a neural networks and look up tables for biaxial inclinometers with temperature variability. We control for neural network size by equating trainable parameters to lookup table data and control for data acquisition by the number of sample points. To avoid biasing the neural network, we introduce random perturbation to otherwise uniform data sampling locations. For temperature dependent validation, we found that the neural network reduced the difference in performance between the orthogonal measurement channels by 99% as compared to a look up table.
{"title":"Artificial Neural Network Calibration of Wide Range of Motion Biaxial Inclinometers","authors":"Ilija Jovanovic, Shaghayegh Khodabakhshian Khonsari, J. Enright","doi":"10.1109/MetroAeroSpace51421.2021.9511660","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511660","url":null,"abstract":"Effective calibration of sensors with fine-scale irregularities in their residual space requires large and dense calibration datasets. For the case of biaxial electrolytic inclinometers, these irregularities are not evenly distributed and concentrate in small regions that drive data resolution requirements. Using evenly spaced sampling for look up tables results in less irregular regions being over-sampled, burdening the calibration process. Artificial neural networks have the capability to optimally distribute a limited number of trainable parameters to minimize the residuals. This can have the benefit of reducing data collection requirements as well as reducing memory requirements. In this paper, we compare the residual model accuracy of a neural networks and look up tables for biaxial inclinometers with temperature variability. We control for neural network size by equating trainable parameters to lookup table data and control for data acquisition by the number of sample points. To avoid biasing the neural network, we introduce random perturbation to otherwise uniform data sampling locations. For temperature dependent validation, we found that the neural network reduced the difference in performance between the orthogonal measurement channels by 99% as compared to a look up table.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121350419","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 : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511714
Lorenzo Frezza, Paolo Marzioli, Niccolò Picci, Andrea Gianfermo, Emanuele Bedetti, Diego Amadio, F. Curianò, F. Santoni
While Electro-Magnetic Compatibility testing is not often considered for CubeSat projects, the increasing complexity of nano-satellite platforms is suggesting to include such tests in their standard verification processes. This paper reports the followed approach and measurements set-up for an EMC anomaly regarding the LEDSAT 1U CubeSat Proto-Flight Model on-board GPS antenna. The anomaly was discovered and solved during functional testing campaign in 2020 and the satellite has been successfully qualified for flight.
{"title":"LEDSAT 1U CubeSat GPS receiver Electro-Magnetic Interference (EMI) analysis","authors":"Lorenzo Frezza, Paolo Marzioli, Niccolò Picci, Andrea Gianfermo, Emanuele Bedetti, Diego Amadio, F. Curianò, F. Santoni","doi":"10.1109/MetroAeroSpace51421.2021.9511714","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511714","url":null,"abstract":"While Electro-Magnetic Compatibility testing is not often considered for CubeSat projects, the increasing complexity of nano-satellite platforms is suggesting to include such tests in their standard verification processes. This paper reports the followed approach and measurements set-up for an EMC anomaly regarding the LEDSAT 1U CubeSat Proto-Flight Model on-board GPS antenna. The anomaly was discovered and solved during functional testing campaign in 2020 and the satellite has been successfully qualified for flight.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116440310","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 : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511759
G. Galanopoulos, Dimitrios P Milanoski, A.A.R. Broer, D. Zarouchas, T. Loutas
In order to reduce aircraft downtimes Condition-Based-Maintenance (CBM) is a topic gaining increased popularity in recent years. However, to apply such maintenance policies reliable health monitoring techniques should be implemented. Two state of the art monitoring techniques, namely Fiber Bragg Gratings (FBG) and Acoustic Emission (AE) are used to monitor the fatigue behavior of single stiffened composite panels (SSCPs) subjected to variable amplitude compression-compression (C-C) fatigue. Advanced features, called Health indicators (HIs) are extracted from the raw sensor data to monitor the degradation behavior. It is crucial to have robust and reliable HIs that capture the degradation of the structures. This work focuses on providing capable HIs for monitoring degradation of composite structures.
{"title":"Health indicators for diagnostics and prognostics of composite aerospace structures","authors":"G. Galanopoulos, Dimitrios P Milanoski, A.A.R. Broer, D. Zarouchas, T. Loutas","doi":"10.1109/MetroAeroSpace51421.2021.9511759","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511759","url":null,"abstract":"In order to reduce aircraft downtimes Condition-Based-Maintenance (CBM) is a topic gaining increased popularity in recent years. However, to apply such maintenance policies reliable health monitoring techniques should be implemented. Two state of the art monitoring techniques, namely Fiber Bragg Gratings (FBG) and Acoustic Emission (AE) are used to monitor the fatigue behavior of single stiffened composite panels (SSCPs) subjected to variable amplitude compression-compression (C-C) fatigue. Advanced features, called Health indicators (HIs) are extracted from the raw sensor data to monitor the degradation behavior. It is crucial to have robust and reliable HIs that capture the degradation of the structures. This work focuses on providing capable HIs for monitoring degradation of composite structures.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126906664","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 : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511749
Paolo Marzioli, Lorenzo Frezza
Distributed architectures of hybrid sensors could greatly support the future launch vehicles navigation systems and avionics in the perspective of a significant increase of the space launches in the future years and decades. While the current architectures rely on high-TRL, costly, centralized sensors, similar performances could be reached by distributed networks of lower TRL, lower cost sensors. This paper introduces a concept for a hybrid network of sensors and will describe the prototypes and tests for several categories of implemented sensors.
{"title":"Distributed Hybrid Sensors Architectures for Launch Vehicle Avionics and Future Space Transportation Systems","authors":"Paolo Marzioli, Lorenzo Frezza","doi":"10.1109/MetroAeroSpace51421.2021.9511749","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511749","url":null,"abstract":"Distributed architectures of hybrid sensors could greatly support the future launch vehicles navigation systems and avionics in the perspective of a significant increase of the space launches in the future years and decades. While the current architectures rely on high-TRL, costly, centralized sensors, similar performances could be reached by distributed networks of lower TRL, lower cost sensors. This paper introduces a concept for a hybrid network of sensors and will describe the prototypes and tests for several categories of implemented sensors.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126484365","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 : 2021-06-23DOI: 10.1109/MetroAeroSpace51421.2021.9511723
G. Spagnolo, F. Leccese
Aircraft warning lights are a crucial element for flight safety. Currently, LEDs are used for aircraft warning lights (obstacle lights). Unfortunately, lights realized with this technology are not clearly visible to pilots using night vision goggles. To solve this drawback, infrared LEDs are added to the visible ones. Unluckily, the failure of the IR LED is not detectable visually. Therefore, the optoelectronic systems are fundamental to monitor the correct operation of these LEDs. In this paper, we will describe a system to check the correct light emission by the IR LEDs and to activate an alarm in case of incorrect operation.
{"title":"System to Monitor IR Radiation of LED Aircraft Warning Lights","authors":"G. Spagnolo, F. Leccese","doi":"10.1109/MetroAeroSpace51421.2021.9511723","DOIUrl":"https://doi.org/10.1109/MetroAeroSpace51421.2021.9511723","url":null,"abstract":"Aircraft warning lights are a crucial element for flight safety. Currently, LEDs are used for aircraft warning lights (obstacle lights). Unfortunately, lights realized with this technology are not clearly visible to pilots using night vision goggles. To solve this drawback, infrared LEDs are added to the visible ones. Unluckily, the failure of the IR LED is not detectable visually. Therefore, the optoelectronic systems are fundamental to monitor the correct operation of these LEDs. In this paper, we will describe a system to check the correct light emission by the IR LEDs and to activate an alarm in case of incorrect operation.","PeriodicalId":236783,"journal":{"name":"2021 IEEE 8th International Workshop on Metrology for AeroSpace (MetroAeroSpace)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122344266","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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