Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278619
Mücahit Fındık, Seyma Yilmaz, Mehmet Köseoglu
One of the fundamental problems in the development of prosthetic fingers is the recognition of finger movements using surface electrocardiogram (EMG) data. Most of the previous studies have proposed the classification of EMG signals using features curated using expert knowledge. We here consider automatic generation and selection of EMG signal features without relying on domain knowledge. We then develop a classification method based on random forests. Our results show that the proposed method achieves 97.5% accuracy. We also present a discussion of the features which are important in distinguishing finger movements.
{"title":"Random Forest Classification of Finger Movements using Electromyogram (EMG) Signals","authors":"Mücahit Fındık, Seyma Yilmaz, Mehmet Köseoglu","doi":"10.1109/SENSORS47125.2020.9278619","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278619","url":null,"abstract":"One of the fundamental problems in the development of prosthetic fingers is the recognition of finger movements using surface electrocardiogram (EMG) data. Most of the previous studies have proposed the classification of EMG signals using features curated using expert knowledge. We here consider automatic generation and selection of EMG signal features without relying on domain knowledge. We then develop a classification method based on random forests. Our results show that the proposed method achieves 97.5% accuracy. We also present a discussion of the features which are important in distinguishing finger movements.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131006900","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 : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278673
A. Gueddida, Y. Pennec, S. Hémon, F. Lucklum, M. Vellekoop, N. Mukhin, R. Lucklum, B. Bonello, B. Djafari-Rouhani
We present a theoretical investigation of the dispersion and transmission properties of a tubular phononic crystal for sensing application. We show the existence of modes confined in a cavity with displacement field spreading over both the solid and fluid parts. Therefore, the frequency of the transmission peak associated to this mode should be sensitive to the sound velocity of the fluid filling the tube.
{"title":"Numerical Analysis of a Tubular Phononic Crystal Sensor","authors":"A. Gueddida, Y. Pennec, S. Hémon, F. Lucklum, M. Vellekoop, N. Mukhin, R. Lucklum, B. Bonello, B. Djafari-Rouhani","doi":"10.1109/SENSORS47125.2020.9278673","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278673","url":null,"abstract":"We present a theoretical investigation of the dispersion and transmission properties of a tubular phononic crystal for sensing application. We show the existence of modes confined in a cavity with displacement field spreading over both the solid and fluid parts. Therefore, the frequency of the transmission peak associated to this mode should be sensitive to the sound velocity of the fluid filling the tube.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130866365","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 : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278865
Matthew J. Vincie, T. Laurvick, Hengky Chandrahalim, Richard Cobb, J. Sattler
Despite the discovery of secondary electron emission over a century ago, repeatability in secondary electron emission measurements remains challenging. This work discusses the transient effects associated with sensing low-level currents during SEY measurements. Operations in the low-level range are shown to be prone to long settling times, transmission line effects, and capacitive coupling between isolated circuits. By programming our measurement system to avoid transients, our system was able to perform SEY measurements with currents as low as 140 fA.
{"title":"Avoiding Transients in Low-level Sensing of Secondary Electron Yield","authors":"Matthew J. Vincie, T. Laurvick, Hengky Chandrahalim, Richard Cobb, J. Sattler","doi":"10.1109/SENSORS47125.2020.9278865","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278865","url":null,"abstract":"Despite the discovery of secondary electron emission over a century ago, repeatability in secondary electron emission measurements remains challenging. This work discusses the transient effects associated with sensing low-level currents during SEY measurements. Operations in the low-level range are shown to be prone to long settling times, transmission line effects, and capacitive coupling between isolated circuits. By programming our measurement system to avoid transients, our system was able to perform SEY measurements with currents as low as 140 fA.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128198777","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 : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278616
Hossein Darvishi, D. Ciuonzo, Eivind Rosón Eide, P. Rossi
In this paper, we propose a novel sensor validation architecture, which performs sensor fault detection, isolation and accommodation (SFDIA). More specifically, a machine-learning based architecture is presented to detect faults in sensors measurements within the system, identify the faulty ones and replace them with estimated values. In our proposed architecture, sensor estimators based on neural networks are constructed for each sensor node in order to accommodate faulty measurements along with a classifier to determine the failure detection and isolation. Finally, numerical results are presented to confirm the effectiveness of the proposed architecture on a publicly-available air quality (AQ) chemical multi-sensor data-set.
{"title":"A Data-Driven Architecture for Sensor Validation Based on Neural Networks","authors":"Hossein Darvishi, D. Ciuonzo, Eivind Rosón Eide, P. Rossi","doi":"10.1109/SENSORS47125.2020.9278616","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278616","url":null,"abstract":"In this paper, we propose a novel sensor validation architecture, which performs sensor fault detection, isolation and accommodation (SFDIA). More specifically, a machine-learning based architecture is presented to detect faults in sensors measurements within the system, identify the faulty ones and replace them with estimated values. In our proposed architecture, sensor estimators based on neural networks are constructed for each sensor node in order to accommodate faulty measurements along with a classifier to determine the failure detection and isolation. Finally, numerical results are presented to confirm the effectiveness of the proposed architecture on a publicly-available air quality (AQ) chemical multi-sensor data-set.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124357721","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 : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278607
Andreas Erbslöh, R. Viga, K. Seidl, R. Kokozinski
The aim of this research is to investigate low-power circuit concepts for the hardware implementation of adaptive stimulation for future retinal implants. Especially for retinal implants, the circuit complexity must be low while increasing functionality. This paper presents the implementation of an analog spike detection circuit to perform electrode individual firing-rate measurements in a spatially high-density electrode array, which has a reduced circuit complexity compared to the wide-used nonlinear energy operator (NEO) and allows stronger suppression of local oscillations due to the retinal remodeling. This recording-unit is integrated in an eight-channel closed-loop-neurostimulator prototype. This recording unit dissipates 13.8 µW and requires an area of 0.066 mm2 by using a 350 nm CMOS process.
{"title":"Artefact-Suppressing Analog Spike Detection Circuit for Firing-Rate Measurements in Closed-Loop Retinal Neurostimulators","authors":"Andreas Erbslöh, R. Viga, K. Seidl, R. Kokozinski","doi":"10.1109/SENSORS47125.2020.9278607","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278607","url":null,"abstract":"The aim of this research is to investigate low-power circuit concepts for the hardware implementation of adaptive stimulation for future retinal implants. Especially for retinal implants, the circuit complexity must be low while increasing functionality. This paper presents the implementation of an analog spike detection circuit to perform electrode individual firing-rate measurements in a spatially high-density electrode array, which has a reduced circuit complexity compared to the wide-used nonlinear energy operator (NEO) and allows stronger suppression of local oscillations due to the retinal remodeling. This recording-unit is integrated in an eight-channel closed-loop-neurostimulator prototype. This recording unit dissipates 13.8 µW and requires an area of 0.066 mm2 by using a 350 nm CMOS process.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125830320","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 : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278822
Paul Marsh, Fatemeh Mohseni, J. Chiao, H. Cao
This paper explores a potential performance control strategy for the uses of a self-calibrating, remotely-accessible, electrodeposited iridium oxide-based (IrOx) pH sensing system. Previous works have investigated deposition parameters, onboard thick film reference electrodes, and embedded applications for electrodeposited IrOx pH sensors on flexible and biocompatible polyimide substrates as applied to passive wireless systems. As complete devices have been demonstrated, the logical next step is to investigate performance improvements. To that end, a self-calibration scheme is investigated herein to enhance longevity and performance, where potentiostatic control is used to return the thin film to a specific material state. This method can be coupled with the aforementioned passive wireless system, to be miniaturized and applied to a variety of applications. The method investigated provides design methodologies towards the ultimate goal of a long-term, self-calibrating IrOx pH sensing system, operated and monitored remotely.
{"title":"Investigation of the Self-Calibration Function for IrOx-based pH Sensors","authors":"Paul Marsh, Fatemeh Mohseni, J. Chiao, H. Cao","doi":"10.1109/SENSORS47125.2020.9278822","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278822","url":null,"abstract":"This paper explores a potential performance control strategy for the uses of a self-calibrating, remotely-accessible, electrodeposited iridium oxide-based (IrOx) pH sensing system. Previous works have investigated deposition parameters, onboard thick film reference electrodes, and embedded applications for electrodeposited IrOx pH sensors on flexible and biocompatible polyimide substrates as applied to passive wireless systems. As complete devices have been demonstrated, the logical next step is to investigate performance improvements. To that end, a self-calibration scheme is investigated herein to enhance longevity and performance, where potentiostatic control is used to return the thin film to a specific material state. This method can be coupled with the aforementioned passive wireless system, to be miniaturized and applied to a variety of applications. The method investigated provides design methodologies towards the ultimate goal of a long-term, self-calibrating IrOx pH sensing system, operated and monitored remotely.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126361781","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 : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278939
Jacob Dawes, Jinwon Kim, M. Johnston
Recent developments in impedance-based flow cytometry have shown it to be a promising alternative to conventional optical approaches for point-of-care (POC) applications. While analysis tools such as finite element analysis provide unique insight for designers of such systems, they provide limited utility for system-level design and are computationally prohibitive for large design space explorations. In this work, an electrical model is presented for resistive impedance-based cytometry to inform system-level design choices such as bandwidth requirements and to provide a flexible way of simulating particle transits for arbitrary arrangements of particles and electrodes. The model is validated using measured results from a microfluidic flow cell.
{"title":"Modeling and Design Considerations for Resistive Impedance-Based Flow Cytometry","authors":"Jacob Dawes, Jinwon Kim, M. Johnston","doi":"10.1109/SENSORS47125.2020.9278939","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278939","url":null,"abstract":"Recent developments in impedance-based flow cytometry have shown it to be a promising alternative to conventional optical approaches for point-of-care (POC) applications. While analysis tools such as finite element analysis provide unique insight for designers of such systems, they provide limited utility for system-level design and are computationally prohibitive for large design space explorations. In this work, an electrical model is presented for resistive impedance-based cytometry to inform system-level design choices such as bandwidth requirements and to provide a flexible way of simulating particle transits for arbitrary arrangements of particles and electrodes. The model is validated using measured results from a microfluidic flow cell.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126306814","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 : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278600
Wanlin Li, Y. Noh, A. Alomainy, I. Vitanov, Yu Zheng, Peng Qi, K. Althoefer
We present an innovative concept for a sensor design that can simultaneously measure multi-axis force information and acquire geometry information with the use of a vision-based technique. The sensor is named F-TOUCH (force and tactile optically unified coherent haptics) which is originally inspired by the GelSight tactile sensor. However, the GelSight tactile sensor uses numerous markers painted between the coating layer and the elastomer base, and it can not well generalize the force-related information from the GelSight images [1]. The F-TOUCH sensor is enhanced with a three-axis force measurement capability by virtue of an internal elastic structure placed underneath the entire elastomer layer, as well as using a conventional force sensor calibration method. The proposed sensor uses a camera to concurrently record the mechanical deformation of the elastic structure (for normal and shear forces measurement) and the surface distortion of the elastomer layer (for geometry observation). Results show that the F-TOUCH sensor is effective in generalizing the force-related information from the images and performing brilliant multi-axis force measurements (comparing with a commercial force sensor), as well as capturing the object’s geometry at the same time.
{"title":"F-TOUCH Sensor for Three-Axis Forces Measurement and Geometry Observation","authors":"Wanlin Li, Y. Noh, A. Alomainy, I. Vitanov, Yu Zheng, Peng Qi, K. Althoefer","doi":"10.1109/SENSORS47125.2020.9278600","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278600","url":null,"abstract":"We present an innovative concept for a sensor design that can simultaneously measure multi-axis force information and acquire geometry information with the use of a vision-based technique. The sensor is named F-TOUCH (force and tactile optically unified coherent haptics) which is originally inspired by the GelSight tactile sensor. However, the GelSight tactile sensor uses numerous markers painted between the coating layer and the elastomer base, and it can not well generalize the force-related information from the GelSight images [1]. The F-TOUCH sensor is enhanced with a three-axis force measurement capability by virtue of an internal elastic structure placed underneath the entire elastomer layer, as well as using a conventional force sensor calibration method. The proposed sensor uses a camera to concurrently record the mechanical deformation of the elastic structure (for normal and shear forces measurement) and the surface distortion of the elastomer layer (for geometry observation). Results show that the F-TOUCH sensor is effective in generalizing the force-related information from the images and performing brilliant multi-axis force measurements (comparing with a commercial force sensor), as well as capturing the object’s geometry at the same time.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126677311","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 : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278754
Sebastian A. Schober, C. Carbonelli, A. Roth, Alexander Zoepfl, R. Wille
Due to environmental conditions as well as internal processes, the lack of long-term stability of electrochemical gas sensors poses a severe problem with respect to their applications, e.g. in tracking air quality on a large scale. Thus far, the development of suitable algorithms to face these problems relies on long-term datasets obtained from sufficiently good reference devices. Since such measurements on actual sensor systems are not always available, especially in the development phase of them, simulated approaches would be a great benefit for algorithm development and the further analysis of the sensors. Those simulators, however, require proper models to capture the general principles of the functionalized materials in such sensor arrays. In this work, we propose a stochastic model that can be used for this purpose, i.e. that allows for simulating the behavior of graphene-based electrochemical gas sensors in particular. The proposed approach allows to properly map different material-related microscopic effects on the sensor surface to a signal output. Evaluations show that the proposed model is able to capture the drift dynamics of such sensors in particular when comparing the results to real measurement data.
{"title":"Towards Drift Modeling of Graphene-Based Gas Sensors Using Stochastic Simulation Techniques","authors":"Sebastian A. Schober, C. Carbonelli, A. Roth, Alexander Zoepfl, R. Wille","doi":"10.1109/SENSORS47125.2020.9278754","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278754","url":null,"abstract":"Due to environmental conditions as well as internal processes, the lack of long-term stability of electrochemical gas sensors poses a severe problem with respect to their applications, e.g. in tracking air quality on a large scale. Thus far, the development of suitable algorithms to face these problems relies on long-term datasets obtained from sufficiently good reference devices. Since such measurements on actual sensor systems are not always available, especially in the development phase of them, simulated approaches would be a great benefit for algorithm development and the further analysis of the sensors. Those simulators, however, require proper models to capture the general principles of the functionalized materials in such sensor arrays. In this work, we propose a stochastic model that can be used for this purpose, i.e. that allows for simulating the behavior of graphene-based electrochemical gas sensors in particular. The proposed approach allows to properly map different material-related microscopic effects on the sensor surface to a signal output. Evaluations show that the proposed model is able to capture the drift dynamics of such sensors in particular when comparing the results to real measurement data.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126758062","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 : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278919
P. Stephanou, David Xu
This work introduces an ultrasound-based sensor for non-invasively detecting obstructions within low pressure gas-filled metallic pipeline. The combination of Lamb wave mode ultrasonic transducers and narrow-band passive ultrasonic isolators enables a break-beam approach to detecting solid obstructions within the enclosed cylindrical volume through the intervening solid-fluid boundaries. The approach has demonstrated the ability to transmit an ultrasound signal across 3/4 inch to 4 inch Schedule 40 steel pipeline containing methane at pressures as low as 0 psig. Moreover, operating over a band of frequencies between 300 kHz and 500 kHz accommodates a wide range of pipe wall thicknesses. The sensing technology has been put into practice within the context of an easy to use clamp-on instrument for quickly and safely detecting natural gas distribution pipeline inserted within retired steel pipeline, and the instrument has been tested extensively in the field at active job sites. This insert detector represents a lower cost, faster to use alternative to existing sensing approaches that employ radiographic testing or intrusive bolt-on saddle punch tees.
{"title":"Ultrasound-Based Sensor for Non-Invasively Detecting Obstructions Within Natural Gas Pipeline","authors":"P. Stephanou, David Xu","doi":"10.1109/SENSORS47125.2020.9278919","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278919","url":null,"abstract":"This work introduces an ultrasound-based sensor for non-invasively detecting obstructions within low pressure gas-filled metallic pipeline. The combination of Lamb wave mode ultrasonic transducers and narrow-band passive ultrasonic isolators enables a break-beam approach to detecting solid obstructions within the enclosed cylindrical volume through the intervening solid-fluid boundaries. The approach has demonstrated the ability to transmit an ultrasound signal across 3/4 inch to 4 inch Schedule 40 steel pipeline containing methane at pressures as low as 0 psig. Moreover, operating over a band of frequencies between 300 kHz and 500 kHz accommodates a wide range of pipe wall thicknesses. The sensing technology has been put into practice within the context of an easy to use clamp-on instrument for quickly and safely detecting natural gas distribution pipeline inserted within retired steel pipeline, and the instrument has been tested extensively in the field at active job sites. This insert detector represents a lower cost, faster to use alternative to existing sensing approaches that employ radiographic testing or intrusive bolt-on saddle punch tees.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"40 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126798393","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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