Pub Date : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709578
Bo Yu, T. Mak, Xiangyu Li, Fei Xia, A. Yakovlev, Yihe Sun, C. Poon
Rapid advances in multi-channel microelectrode neural recording technologies in recent years have spawned broad applications in implantable neuroprosthetic and rehabilitation systems. The dramatic increases in data bandwidth and data volume associated with multichannel recording also come with a large computational load which presents major design challenges for implantable systems in terms of power dissipation and hardware area. In this paper, we present a new design methodology that utilizes Hebbian learning for real-time neural signal processing. A stream-based technique is proposed that can effectively approximate the hardware learning kernel while significantly reducing hardware area and power. The proposed method is validated using benchmark problems including spike sorting and population decoding. Experimental results show that the stream-based approach can achieve up to 98% and 43.4% reduction in equivalent slice look-up table and power of Xilinx Spartan6 Low Power FPGA.
{"title":"A stream-based Hebbian eigenfilter for real-time neurophysiological signal processing","authors":"Bo Yu, T. Mak, Xiangyu Li, Fei Xia, A. Yakovlev, Yihe Sun, C. Poon","doi":"10.1109/BIOCAS.2010.5709578","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709578","url":null,"abstract":"Rapid advances in multi-channel microelectrode neural recording technologies in recent years have spawned broad applications in implantable neuroprosthetic and rehabilitation systems. The dramatic increases in data bandwidth and data volume associated with multichannel recording also come with a large computational load which presents major design challenges for implantable systems in terms of power dissipation and hardware area. In this paper, we present a new design methodology that utilizes Hebbian learning for real-time neural signal processing. A stream-based technique is proposed that can effectively approximate the hardware learning kernel while significantly reducing hardware area and power. The proposed method is validated using benchmark problems including spike sorting and population decoding. Experimental results show that the stream-based approach can achieve up to 98% and 43.4% reduction in equivalent slice look-up table and power of Xilinx Spartan6 Low Power FPGA.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124653475","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709589
W. S. W. Zain, T. Prodromakis, C. Toumazou
In this work the concept of the chemical mixer for comparing the pH of two aqueous solutions is introduced. Ionic concentrations are sensed via a pair of ISFETs, which are then translated into signals with frequencies that correspond to the pH values of the solutions. Using the bulk-driven single balanced topology, the number of transistors is significantly reduced, making it suitable for applications where a low supply voltage and low power consumption are essential. Finally, it is demonstrated that the output frequency of the mixer depends on the ΔpH of the solutions under test.
{"title":"A bulk-driven ISFET-based chemical mixer","authors":"W. S. W. Zain, T. Prodromakis, C. Toumazou","doi":"10.1109/BIOCAS.2010.5709589","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709589","url":null,"abstract":"In this work the concept of the chemical mixer for comparing the pH of two aqueous solutions is introduced. Ionic concentrations are sensed via a pair of ISFETs, which are then translated into signals with frequencies that correspond to the pH values of the solutions. Using the bulk-driven single balanced topology, the number of transistors is significantly reduced, making it suitable for applications where a low supply voltage and low power consumption are essential. Finally, it is demonstrated that the output frequency of the mixer depends on the ΔpH of the solutions under test.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125827942","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709567
W. Juffali, Jamil El-Imad, A. Eftekhar, C. Toumazou
This work presents a novel algorithmic method based on an ngram approach and applies it ECoG and deep brain neural data for analysis of epileptic seizures. This is part of a project (WiNAM) to design an analysis framework suitable for analysing brain dynamical changes. By first exploring the ngram model and its traditional use we describe how to apply it to biological data for pattern recognition. We then use this methodology and apply it to neurological data to show good sensitivity to seizure onset. Through these tests we explore the parameters used when computing the ngram to evaluate what is needed to maintain this sensitivity. Additionally, we present the analysis framework (an online system) that is being developed to carry out the ngram analysis and database the data and results.
{"title":"The WiNAM project: Neural data analysis with applications to epilespy","authors":"W. Juffali, Jamil El-Imad, A. Eftekhar, C. Toumazou","doi":"10.1109/BIOCAS.2010.5709567","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709567","url":null,"abstract":"This work presents a novel algorithmic method based on an ngram approach and applies it ECoG and deep brain neural data for analysis of epileptic seizures. This is part of a project (WiNAM) to design an analysis framework suitable for analysing brain dynamical changes. By first exploring the ngram model and its traditional use we describe how to apply it to biological data for pattern recognition. We then use this methodology and apply it to neurological data to show good sensitivity to seizure onset. Through these tests we explore the parameters used when computing the ngram to evaluate what is needed to maintain this sensitivity. Additionally, we present the analysis framework (an online system) that is being developed to carry out the ngram analysis and database the data and results.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125687440","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709590
T. Yamazaki, T. Ikeda, M. Futagawa, F. Dasai, M. Ishida, K. Sawada
We have designed and fabricated a 2×4 electrochemical image sensor with CMOS signal processing circuits integrated on a single chip. Using a well-studied ferricyanide solution, a clear cyclic voltammetry curve was obtained from each working electrode of the array sensor. The external components used include a data generator and a data recorder. This sensor chip is an early prototype of a fully integrated system of a fast-scan electrochemical image sensor that uses microelectrodes.
{"title":"An electrochemical array sensor with CMOS signal processing circuits integrated on a single chip","authors":"T. Yamazaki, T. Ikeda, M. Futagawa, F. Dasai, M. Ishida, K. Sawada","doi":"10.1109/BIOCAS.2010.5709590","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709590","url":null,"abstract":"We have designed and fabricated a 2×4 electrochemical image sensor with CMOS signal processing circuits integrated on a single chip. Using a well-studied ferricyanide solution, a clear cyclic voltammetry curve was obtained from each working electrode of the array sensor. The external components used include a data generator and a data recorder. This sensor chip is an early prototype of a fully integrated system of a fast-scan electrochemical image sensor that uses microelectrodes.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125111901","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709581
N. Joye, A. Schmid, Y. Leblebici
An innovative readout channel, based on analog amplitude modulation of the signals recorded by each sensing site, is developed for high-density CMOS-based microelectrode arrays. A single amplification stage simultaneously records the neural activity acquired from several sensors. A theoretical analysis has demonstrated that a major physical limitation of the readout architecture relates to the summation of the thermal noise of each recorded signal at the input node of the front-end amplification stage. After implementation of the proposed readout architecture in a UMC 0.18 μm CMOS technology, it has been shown that the maximum number of sensors which can simultaneously be recorded depends on the electrical characteristics of the recorded extracellular voltages, which depend on the experimental setup. Considering a typical case encountered during electrophysiological experiments, the maximum number of sensors which can simultaneously be recorded is approximately in the range of 5–10.
{"title":"Extracellular recording system based on amplitude modulation for CMOS microelectrode arrays","authors":"N. Joye, A. Schmid, Y. Leblebici","doi":"10.1109/BIOCAS.2010.5709581","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709581","url":null,"abstract":"An innovative readout channel, based on analog amplitude modulation of the signals recorded by each sensing site, is developed for high-density CMOS-based microelectrode arrays. A single amplification stage simultaneously records the neural activity acquired from several sensors. A theoretical analysis has demonstrated that a major physical limitation of the readout architecture relates to the summation of the thermal noise of each recorded signal at the input node of the front-end amplification stage. After implementation of the proposed readout architecture in a UMC 0.18 μm CMOS technology, it has been shown that the maximum number of sensors which can simultaneously be recorded depends on the electrical characteristics of the recorded extracellular voltages, which depend on the experimental setup. Considering a typical case encountered during electrophysiological experiments, the maximum number of sensors which can simultaneously be recorded is approximately in the range of 5–10.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127196180","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709591
O. Bulteel, N. Van Overstraeten-Schlogel, P. Dupuis, D. Flandre
In this paper, we describe a complete microsystem allowing the measurement of DNA concentration based on ultraviolet (UV) absorption. The system includes an ultraviolet light-emitting diode (LED) as light source and a silicon-on-insulator (SOI) lateral PIN diode as photodetector. After demonstrating the feasibility of the system with a quartz container, measurements are performed on DNA samples in PCR tubes by direct trans-mittance. The measurement of the sample in the tubes implies no waste neither manipulation of the samples. We study the impact of variation of the different parameters of the system, i.e. the wavelength of the LED, the light power reaching the samples and the bias of the photosensor. We are able to measure responses for DNA concentrations in the range from 400 ng/μL to 4 pg/μL and correlate bacteria concentrations to the induced photocurrent of the diode from 6.1011 spores/mL to 6.107 spores/mL. The system features a present precision of current measurements of 2%. In the optimal case, a limit of detection (LOD) of 0.02 ng/μL has been estimated.
{"title":"Complete microsystem using SOI photodiode for DNA concentration measurement","authors":"O. Bulteel, N. Van Overstraeten-Schlogel, P. Dupuis, D. Flandre","doi":"10.1109/BIOCAS.2010.5709591","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709591","url":null,"abstract":"In this paper, we describe a complete microsystem allowing the measurement of DNA concentration based on ultraviolet (UV) absorption. The system includes an ultraviolet light-emitting diode (LED) as light source and a silicon-on-insulator (SOI) lateral PIN diode as photodetector. After demonstrating the feasibility of the system with a quartz container, measurements are performed on DNA samples in PCR tubes by direct trans-mittance. The measurement of the sample in the tubes implies no waste neither manipulation of the samples. We study the impact of variation of the different parameters of the system, i.e. the wavelength of the LED, the light power reaching the samples and the bias of the photosensor. We are able to measure responses for DNA concentrations in the range from 400 ng/μL to 4 pg/μL and correlate bacteria concentrations to the induced photocurrent of the diode from 6.1011 spores/mL to 6.107 spores/mL. The system features a present precision of current measurements of 2%. In the optimal case, a limit of detection (LOD) of 0.02 ng/μL has been estimated.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126039203","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709599
A. Basu, P. Hasler
This paper introduces the use of the concept of small signal analysis, commonly used in circuit design, for understanding neural models. We show that neural models, varying in complexity from Hodgkin-Huxley to Integrate and fire have similar small signal models when their corresponding differential equations are close to the same bifurcation with respect to input current. The small signal model allows circuit designers to intuitively understand the behavior of complicated differential equations in a simple way. We use small-signal models for deriving parameters for a simple neural model (like resonate and fire) from a more complicated but biophysically relevant one like Morris-Lecar. We show similarity in the sub threshold behavior of the simple and complicated model when they are close to a Hopf bifurcation and a Saddle-node bifurcation. Hence, this is useful to correctly tune simple neural models for large scale cortical simulations.
{"title":"Small-signal neural models and its application to determining model parameters","authors":"A. Basu, P. Hasler","doi":"10.1109/BIOCAS.2010.5709599","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709599","url":null,"abstract":"This paper introduces the use of the concept of small signal analysis, commonly used in circuit design, for understanding neural models. We show that neural models, varying in complexity from Hodgkin-Huxley to Integrate and fire have similar small signal models when their corresponding differential equations are close to the same bifurcation with respect to input current. The small signal model allows circuit designers to intuitively understand the behavior of complicated differential equations in a simple way. We use small-signal models for deriving parameters for a simple neural model (like resonate and fire) from a more complicated but biophysically relevant one like Morris-Lecar. We show similarity in the sub threshold behavior of the simple and complicated model when they are close to a Hopf bifurcation and a Saddle-node bifurcation. Hence, this is useful to correctly tune simple neural models for large scale cortical simulations.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126698403","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709603
Andre Harrison, R. Ozgun, Joseph H. Lin, A. Andreou, R. Etienne-Cummings
Spike based imagers commonly use either time-to-first spike (TTFS) or spike rate encoding exclusively. In this paper we discuss the benefits of using a mixed-mode encoding scheme backed by theoretical analysis and SPICE simulations. The mixed-mode readout uses both TTFS and spike rate information to estimate the illumination for each pixel, which lessens the maximum spike rate and timing clock speeds required for a given level of accuracy. We intend to test this methodology on a generic spike based imager chip we have designed and submitted for fabrication in a 0.13μm 3D SOI CMOS process. The imager is capable of both TTFS and spike rate encoding and should allow us to fully validate our theory.
基于尖峰的成像仪通常只使用第一个尖峰时间(TTFS)或尖峰率编码。在本文中，我们讨论了使用混合模式编码方案的好处，支持理论分析和SPICE模拟。混合模式读出使用TTFS和尖峰率信息来估计每个像素的照明，这降低了给定精度级别所需的最大尖峰率和定时时钟速度。我们打算在我们设计并提交的用于0.13μm 3D SOI CMOS工艺制造的通用脉冲成像芯片上测试该方法。成像仪能够TTFS和峰值速率编码，应该允许我们完全验证我们的理论。
{"title":"A spike based 3D imager chip using a mixed mode encoding readout","authors":"Andre Harrison, R. Ozgun, Joseph H. Lin, A. Andreou, R. Etienne-Cummings","doi":"10.1109/BIOCAS.2010.5709603","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709603","url":null,"abstract":"Spike based imagers commonly use either time-to-first spike (TTFS) or spike rate encoding exclusively. In this paper we discuss the benefits of using a mixed-mode encoding scheme backed by theoretical analysis and SPICE simulations. The mixed-mode readout uses both TTFS and spike rate information to estimate the illumination for each pixel, which lessens the maximum spike rate and timing clock speeds required for a given level of accuracy. We intend to test this methodology on a generic spike based imager chip we have designed and submitted for fabrication in a 0.13μm 3D SOI CMOS process. The imager is capable of both TTFS and spike rate encoding and should allow us to fully validate our theory.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115367834","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709628
J. Ramos, J. L. Ausín, J. F. Duque-Carrillo, G. Torelli
In this paper, a limiting/logarithmic amplifier (LLA) for high dynamic range wideband bioelectrical impedance measurements is presented. The amplifier is composed of eight cascaded gain stages with a folded diode-connected transistor as a load that attain wide bandwidth performance with limited power consumption. The logarithmic conversion of the input variable is carried out with the aid of nine detectors. A prototype in standard 0.35-μm CMOS technology occupies 0.06 mm2 of silicon area and dissipates 2.2 mW from a single 2-V supply. Post-layout results show that the LLA is capable of processing a 65-dB input dynamic range over a frequency interval from 1 kHz to 1 MHz with an accuracy within ± 0.7 dB.
{"title":"Design of limiting/logarithmic amplifier for wideband bioimpedance measuring devices","authors":"J. Ramos, J. L. Ausín, J. F. Duque-Carrillo, G. Torelli","doi":"10.1109/BIOCAS.2010.5709628","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709628","url":null,"abstract":"In this paper, a limiting/logarithmic amplifier (LLA) for high dynamic range wideband bioelectrical impedance measurements is presented. The amplifier is composed of eight cascaded gain stages with a folded diode-connected transistor as a load that attain wide bandwidth performance with limited power consumption. The logarithmic conversion of the input variable is carried out with the aid of nine detectors. A prototype in standard 0.35-μm CMOS technology occupies 0.06 mm2 of silicon area and dissipates 2.2 mW from a single 2-V supply. Post-layout results show that the LLA is capable of processing a 65-dB input dynamic range over a frequency interval from 1 kHz to 1 MHz with an accuracy within ± 0.7 dB.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116677615","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709604
Liang Guo, I. Clements, Dustin Li, R. Bellamkonda, S. DeWeerth
A high-resolution PDMS-based conformable microelectrode array (cMEA) with integrated electronics is implemented. The cMEA is incorporated into individual layers of a nanofiber-based nerve regeneration scaffold to create a novel regenerative electrode scaffold (RES) capable of establishing a stable, high-resolution peripheral nerve interface. The device features a compact size with an enhanced signal-to-noise ratio (SNR), as required by implantation applications. Preliminary characterizations of the device are performed using in vitro experimentations, including impedance spectroscopy and neural culturing.
{"title":"A conformable microelectrode array (cMEA) with integrated electronics for peripheral nerve interfacing","authors":"Liang Guo, I. Clements, Dustin Li, R. Bellamkonda, S. DeWeerth","doi":"10.1109/BIOCAS.2010.5709604","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709604","url":null,"abstract":"A high-resolution PDMS-based conformable microelectrode array (cMEA) with integrated electronics is implemented. The cMEA is incorporated into individual layers of a nanofiber-based nerve regeneration scaffold to create a novel regenerative electrode scaffold (RES) capable of establishing a stable, high-resolution peripheral nerve interface. The device features a compact size with an enhanced signal-to-noise ratio (SNR), as required by implantation applications. Preliminary characterizations of the device are performed using in vitro experimentations, including impedance spectroscopy and neural culturing.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"366 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121729122","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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