Pub Date : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463343
Wu Jian Kang, L. Dong, X. Chen, W. Yeoh, I. Pek
A system for Ambulatory Examination and Management of Cardiovascular disease patients (AEMC) is presented. The system continuously collects vital signals as well as context (activity and environment) information, and then fuses them to obtain the heart status in terms of cardiovascular fitness. Technical details for activity classification, Electrocardiogram (ECG) signal processing and data fusion are described. The system has reached the stage of medical trial.
{"title":"Ambulatory Examination and Management of CVD Patients","authors":"Wu Jian Kang, L. Dong, X. Chen, W. Yeoh, I. Pek","doi":"10.1109/BIOCAS.2007.4463343","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463343","url":null,"abstract":"A system for Ambulatory Examination and Management of Cardiovascular disease patients (AEMC) is presented. The system continuously collects vital signals as well as context (activity and environment) information, and then fuses them to obtain the heart status in terms of cardiovascular fitness. Technical details for activity classification, Electrocardiogram (ECG) signal processing and data fusion are described. The system has reached the stage of medical trial.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116803132","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 : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463325
Xiwen Zhang, Hoi Lee
This paper presents a dc-dc conversion system consisting of a switched-capacitor voltage tripler and a low-dropout regulator (LDO) for transcutaneous-powered cochlear implants. Break-before-make mechanism is developed in the tripler to improve the power efficiency and reduces the output glitch. The current-buffer compensated LDO as a post-regulator of the tripler not only removes the glitch from the tripler, but also maintains a constant and stable output voltage irrespective of the change in different load currents. The accuracy of the output voltage is thus significantly enhanced. In a standard 0.35-mum CMOS, results show that the proposed system can deliver up to 60 mA load current and achieve the peak power efficiency of 88%. The maximum output voltage variation is only 0.6% of the nominal output of 4.84 V under full load current change of 60 mA.
{"title":"An 88%-Power-Efficiency Accuracy-Enhanced DC-DC Conversion System for Transcutaneous-Powered Cochlear Implants","authors":"Xiwen Zhang, Hoi Lee","doi":"10.1109/BIOCAS.2007.4463325","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463325","url":null,"abstract":"This paper presents a dc-dc conversion system consisting of a switched-capacitor voltage tripler and a low-dropout regulator (LDO) for transcutaneous-powered cochlear implants. Break-before-make mechanism is developed in the tripler to improve the power efficiency and reduces the output glitch. The current-buffer compensated LDO as a post-regulator of the tripler not only removes the glitch from the tripler, but also maintains a constant and stable output voltage irrespective of the change in different load currents. The accuracy of the output voltage is thus significantly enhanced. In a standard 0.35-mum CMOS, results show that the proposed system can deliver up to 60 mA load current and achieve the peak power efficiency of 88%. The maximum output voltage variation is only 0.6% of the nominal output of 4.84 V under full load current change of 60 mA.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128310288","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 : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463335
Yanhong Liu, B. Veeravalli
In this paper, we propose novel low-energy static and dynamic scheduling algorithms for the heterogeneous Body Area Network (BAN) systems, where task graphs have deadlines (timing constraints) and precedence relationships to satisfy. Our proposed algorithms, with low computational complexities, use the novel "path information track-and-update" scheme to distribute slack over tasks such that the overall energy consumption is minimized, and an observer mechanism to guarantee the application constraints. Our dynamic scheduling algorithm utilizes the results from the static scheduling algorithm and attempts to aggressively reduce the energy consumption. Simulations for the task graph for a typical BAN application show that our scheduling algorithms achieve better energy savings with less than 5% of the computational time, compared with the recent heterogenous multiprocessor scheduling algorithms.
{"title":"Heuristic-Path and Observer based Low-Energy Scheduling Algorithms for Body Area Network Systems","authors":"Yanhong Liu, B. Veeravalli","doi":"10.1109/BIOCAS.2007.4463335","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463335","url":null,"abstract":"In this paper, we propose novel low-energy static and dynamic scheduling algorithms for the heterogeneous Body Area Network (BAN) systems, where task graphs have deadlines (timing constraints) and precedence relationships to satisfy. Our proposed algorithms, with low computational complexities, use the novel \"path information track-and-update\" scheme to distribute slack over tasks such that the overall energy consumption is minimized, and an observer mechanism to guarantee the application constraints. Our dynamic scheduling algorithm utilizes the results from the static scheduling algorithm and attempts to aggressively reduce the energy consumption. Simulations for the task graph for a typical BAN application show that our scheduling algorithms achieve better energy savings with less than 5% of the computational time, compared with the recent heterogenous multiprocessor scheduling algorithms.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122433477","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 : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463346
Fei Zhang, Y. Lian
Existing wavelet transform methods usually realize the QRS detection by sourcing for two modulus maxima with opposite sign and locating the zero crossing point between them at high decomposition scale. However high scale wavelet transform is often contaminated with severe baseline drift. In addition, common sense indicates that detecting zero crossing is not an easy task compared to the detection of maximum point. In this paper, a novel algorithm based on continuous wavelet transform (CWT) is proposed to accurately detect QRS. It employs a first-order derivative-based differentiator to suppress noise and baseline drift and uses high scale continuous wavelet transform to peak the zero crossing R point produced by differentiator to ease the task of QRS detection. It is shown by simulation that the proposed algorithm outperforms many existing methods and achieves an average detection rate of 99.69%, a sensitivity of 99.87%, and a positive prediction of 99.82% against the lead II of study records from the MIT-BIH Arrhythmia database.
{"title":"Novel QRS Detection by CWT for ECG Sensor","authors":"Fei Zhang, Y. Lian","doi":"10.1109/BIOCAS.2007.4463346","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463346","url":null,"abstract":"Existing wavelet transform methods usually realize the QRS detection by sourcing for two modulus maxima with opposite sign and locating the zero crossing point between them at high decomposition scale. However high scale wavelet transform is often contaminated with severe baseline drift. In addition, common sense indicates that detecting zero crossing is not an easy task compared to the detection of maximum point. In this paper, a novel algorithm based on continuous wavelet transform (CWT) is proposed to accurately detect QRS. It employs a first-order derivative-based differentiator to suppress noise and baseline drift and uses high scale continuous wavelet transform to peak the zero crossing R point produced by differentiator to ease the task of QRS detection. It is shown by simulation that the proposed algorithm outperforms many existing methods and achieves an average detection rate of 99.69%, a sensitivity of 99.87%, and a positive prediction of 99.82% against the lead II of study records from the MIT-BIH Arrhythmia database.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127270891","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 : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463301
Yang Liu, A. Gore, S. Chakrabartty, E. Alocilja
One of the important factors determining the sensitivity of any biosensing system is successful integration of bio- molecular transducers with peripheral signal processing circuitry. In this paper we present an architecture of a multi-array biosensor that integrates molecular bio-wires based immunosensor with a multi-channel potentiostat array. The biosensor operates by converting binding events between antigen and antibody into a measurable electrical signal using polyaniline nanowires as a transducer. The electrical signal is measured using a multichannel potentiostat where each channel comprises of a semi- synchronous SigmaDelta modulator. Measured results using a fabricated potentiostat array demonstrate sensitivity down to 50 femtoampere range which makes it ideal for detecting pathogens at low concentration levels. Experiments using the biosensor array specific to Bacillus Cereus bacterium validate the functionality of the platform in detecting the pathogen at different concentration levels.
{"title":"A Molecular bio-wire based multi-array biosensor with integrated potentiostat","authors":"Yang Liu, A. Gore, S. Chakrabartty, E. Alocilja","doi":"10.1109/BIOCAS.2007.4463301","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463301","url":null,"abstract":"One of the important factors determining the sensitivity of any biosensing system is successful integration of bio- molecular transducers with peripheral signal processing circuitry. In this paper we present an architecture of a multi-array biosensor that integrates molecular bio-wires based immunosensor with a multi-channel potentiostat array. The biosensor operates by converting binding events between antigen and antibody into a measurable electrical signal using polyaniline nanowires as a transducer. The electrical signal is measured using a multichannel potentiostat where each channel comprises of a semi- synchronous SigmaDelta modulator. Measured results using a fabricated potentiostat array demonstrate sensitivity down to 50 femtoampere range which makes it ideal for detecting pathogens at low concentration levels. Experiments using the biosensor array specific to Bacillus Cereus bacterium validate the functionality of the platform in detecting the pathogen at different concentration levels.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123752090","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 : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463302
P. Weerakoon, K. Klemic, F. Sigworth, E. Culurciello
This paper presents an evaluation of electrical noise sources and signal-to-noise limitations in a fabricated integrated patch-clamp amplifier. We also present numerical calculation of the theoretical noise of the patch-clamp system. Our fabricated device was measured to have less than 4pA of rms noise at 10 kHz bandwidth, similar in performance to commercial bench- top systems. The integrated patch-clamp can accurately measure nano-Amperes of current and is intended for a high-throughput system that can screen a large number of cells in parallel. The fabricated device consumes 1480 by 1300 mum of silicon area and 3.2 mW at 3.3 V of power. The device was fabricated using AMI 0.5 mA Micron technology.
{"title":"Electrical Noise Analysis of an Integrated Patch-Clamp Amplifier","authors":"P. Weerakoon, K. Klemic, F. Sigworth, E. Culurciello","doi":"10.1109/BIOCAS.2007.4463302","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463302","url":null,"abstract":"This paper presents an evaluation of electrical noise sources and signal-to-noise limitations in a fabricated integrated patch-clamp amplifier. We also present numerical calculation of the theoretical noise of the patch-clamp system. Our fabricated device was measured to have less than 4pA of rms noise at 10 kHz bandwidth, similar in performance to commercial bench- top systems. The integrated patch-clamp can accurately measure nano-Amperes of current and is intended for a high-throughput system that can screen a large number of cells in parallel. The fabricated device consumes 1480 by 1300 mum of silicon area and 3.2 mW at 3.3 V of power. The device was fabricated using AMI 0.5 mA Micron technology.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"279 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123168922","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 : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463350
A. Malatesta, L. R. Quitadamo, M. Abbafati, L. Bianchi, M. Marciani, G. Cardarilli
Brain computer interface (BCI) systems implement a communication path between human users and the external environment by translating physiological signals directly acquired from the brain into commands toward external peripherals. A lot of protocols have been implemented in the BCI field and a lot of analytical techniques and algorithms on the signals have been tested to improve the reliability of the information extracted from signals and then the performances of BCI systems. Independent component analysis (ICA) revealed to be a useful tool for analyzing data as it allows the separation of the signals in some independent sources which carry information about the different components of the signals themselves. However ICA is computationally expensive and some efforts should be done in order to maximize its results in terms of time spent for the analysis. A hardware implementation is now discussed which makes the ICA more useful for the online analysis typical of BCI systems.
{"title":"Moving Towards a Hardware Implementation of the Independent Component Analysis for Brain Computer Interfaces","authors":"A. Malatesta, L. R. Quitadamo, M. Abbafati, L. Bianchi, M. Marciani, G. Cardarilli","doi":"10.1109/BIOCAS.2007.4463350","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463350","url":null,"abstract":"Brain computer interface (BCI) systems implement a communication path between human users and the external environment by translating physiological signals directly acquired from the brain into commands toward external peripherals. A lot of protocols have been implemented in the BCI field and a lot of analytical techniques and algorithms on the signals have been tested to improve the reliability of the information extracted from signals and then the performances of BCI systems. Independent component analysis (ICA) revealed to be a useful tool for analyzing data as it allows the separation of the signals in some independent sources which carry information about the different components of the signals themselves. However ICA is computationally expensive and some efforts should be done in order to maximize its results in terms of time spent for the analysis. A hardware implementation is now discussed which makes the ICA more useful for the online analysis typical of BCI systems.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130585137","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 : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463353
Chiung-An Chen, Ho-Yin Lee, Shih-Lun Chen, Hong-Yi Huang, C. Luo
There is a low power wireless transceiver system for healthcare monitoring applications in wireless sensor network (WSN). Technical advancements in micro-sensors, micro electromechanical system (MEMS) devices, low-power electronics, and radio frequency (RF) circuits and systems have enabled both design and development of such highly integrated system. In this paper, we present a wireless transceiver for wireless sensor network system, which is considering the link budget for low power design. This hierarchical architecture will make it possible to reconfigurable map application to the WSN system. The accurate pipeline control will advance the performance efficiently, and the adaptive low-power system design will reduce lots of power consumptions. In order to confirm the system, the temperature is regard as the input signals for system performance measurement.
{"title":"Low-Power 2.4-GHz Transceiver in Wireless Sensor Network for Bio-medical Applications","authors":"Chiung-An Chen, Ho-Yin Lee, Shih-Lun Chen, Hong-Yi Huang, C. Luo","doi":"10.1109/BIOCAS.2007.4463353","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463353","url":null,"abstract":"There is a low power wireless transceiver system for healthcare monitoring applications in wireless sensor network (WSN). Technical advancements in micro-sensors, micro electromechanical system (MEMS) devices, low-power electronics, and radio frequency (RF) circuits and systems have enabled both design and development of such highly integrated system. In this paper, we present a wireless transceiver for wireless sensor network system, which is considering the link budget for low power design. This hierarchical architecture will make it possible to reconfigurable map application to the WSN system. The accurate pipeline control will advance the performance efficiently, and the adaptive low-power system design will reduce lots of power consumptions. In order to confirm the system, the temperature is regard as the input signals for system performance measurement.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130635984","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 : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463315
S. Mitra, G. Indiveri, Stefano Fusi
We demonstrate robust classification of correlated patterns of mean firing rates, using a VLSI network of spiking neurons and spike-driven plastic synapses. The synapses have bistable weights over long time-scales and the transitions from one stable state to the other are driven by the pre and postsynaptic spiking activity. Learning is supervised by a teacher signal which provides an extra current to the output neurons during the training phase. This current steers the activity of the neurons toward the desired value, and the synaptic weights are modified only if the current generated by the plastic synapses does not match the one provided by the teacher signal. If the neuron's response matches the desired output, the synaptic updates are blocked. Such a feature allows the neurons to classify spatial patterns of mean firing rates, even when they have significant correlations. If synaptic updates are stochastic, as in the case of random Poisson input spike trains, the classification performance can be further improved by combining the outcome of multiple neurons together.
{"title":"Robust classification of correlated patterns with a neuromorphic VLSI network of spiking neurons","authors":"S. Mitra, G. Indiveri, Stefano Fusi","doi":"10.1109/BIOCAS.2007.4463315","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463315","url":null,"abstract":"We demonstrate robust classification of correlated patterns of mean firing rates, using a VLSI network of spiking neurons and spike-driven plastic synapses. The synapses have bistable weights over long time-scales and the transitions from one stable state to the other are driven by the pre and postsynaptic spiking activity. Learning is supervised by a teacher signal which provides an extra current to the output neurons during the training phase. This current steers the activity of the neurons toward the desired value, and the synaptic weights are modified only if the current generated by the plastic synapses does not match the one provided by the teacher signal. If the neuron's response matches the desired output, the synaptic updates are blocked. Such a feature allows the neurons to classify spatial patterns of mean firing rates, even when they have significant correlations. If synaptic updates are stochastic, as in the case of random Poisson input spike trains, the classification performance can be further improved by combining the outcome of multiple neurons together.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131006091","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 : 2007-11-01DOI: 10.1109/BIOCAS.2007.4463313
F. Folowosele, R. J. Vogelstein, R. Etienne-Cummings
Complex cells in the visual cortex utilize a maximum (MAX) operation to pool the outputs of simple cells to achieve feature specificity and invariance. We demonstrate a biologically-plausible MAX network for nonlinear pooling in hardware, using a reconfigurable multichip address event representation based VLSI system. With this implementation we have shown that we can implement simple and advanced stages of visual processing on the same chip and are one step closer to constructing an autonomous, continuous-time, biologically- plausible hierarchical model of visual information processing using large-scale arrays of identical silicon neurons.
{"title":"Spike-Based MAX Networks for Nonlinear Pooling in Hierarchical Vision Processing","authors":"F. Folowosele, R. J. Vogelstein, R. Etienne-Cummings","doi":"10.1109/BIOCAS.2007.4463313","DOIUrl":"https://doi.org/10.1109/BIOCAS.2007.4463313","url":null,"abstract":"Complex cells in the visual cortex utilize a maximum (MAX) operation to pool the outputs of simple cells to achieve feature specificity and invariance. We demonstrate a biologically-plausible MAX network for nonlinear pooling in hardware, using a reconfigurable multichip address event representation based VLSI system. With this implementation we have shown that we can implement simple and advanced stages of visual processing on the same chip and are one step closer to constructing an autonomous, continuous-time, biologically- plausible hierarchical model of visual information processing using large-scale arrays of identical silicon neurons.","PeriodicalId":273819,"journal":{"name":"2007 IEEE Biomedical Circuits and Systems Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134628272","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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