Pub Date : 2019-10-01DOI: 10.1109/ISNE.2019.8896549
Yi Liang, Dedong Han, Wen Yu, Junchen Dong, Huijin Li, Yi Wang
Fully transparent indium gallium zinc oxide thin film transistors (IGZO TFTs) on glass substrate were fabricated by radio frequency magnetron sputtering at room temperature. The influence of oxygen plasma treatment technology on the characteristics of IGZO TFTs were analyzed. Before growing the source/drain electrodes, different power of oxygen plasma were used to treat the surface of the source/drain region. The experiment results suggest that the plasma treatment can improve the performance of device. Compared with the control group, the TFTs with O2 plasma treatment for 10 seconds and power of 150W show a better performance. The Ion/Ioff ratio was increased by an order of magnitude from 2.67×104 to 2.1×105, and the saturation mobility (μsat) was doubled from 0.54 cm2 V-1 s-1 to 1.1cm2 V-1 s-1. The sub-threshold swing (SS) is 0.42V/dec, and Ion/Ioff ratio is 2.1×105.
{"title":"Influence of Oxygen Plasma Treatment on the Amorphous IGZO Thin Film Transistors","authors":"Yi Liang, Dedong Han, Wen Yu, Junchen Dong, Huijin Li, Yi Wang","doi":"10.1109/ISNE.2019.8896549","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896549","url":null,"abstract":"Fully transparent indium gallium zinc oxide thin film transistors (IGZO TFTs) on glass substrate were fabricated by radio frequency magnetron sputtering at room temperature. The influence of oxygen plasma treatment technology on the characteristics of IGZO TFTs were analyzed. Before growing the source/drain electrodes, different power of oxygen plasma were used to treat the surface of the source/drain region. The experiment results suggest that the plasma treatment can improve the performance of device. Compared with the control group, the TFTs with O2 plasma treatment for 10 seconds and power of 150W show a better performance. The Ion/Ioff ratio was increased by an order of magnitude from 2.67×104 to 2.1×105, and the saturation mobility (μsat) was doubled from 0.54 cm2 V-1 s-1 to 1.1cm2 V-1 s-1. The sub-threshold swing (SS) is 0.42V/dec, and Ion/Ioff ratio is 2.1×105.","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116483154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ISNE.2019.8896438
Mingyao Zheng, Y. Tie, L. Qi, Shengnan Jiang
Gesture recognition is applied in various intelligent scenes. In this paper, we propose the multi-modality fusion temporal segment networks (MMFTSN) model to solve dynamic gestures recognition. Three gesture modalities: RGB, Depth and Optical flow (OF) video data are equally segmented and randomly sampled. Then, the sampling frames are classified using convolutional neural network. Finally, fusing three kinds of modality classification results. MMFTSN is used to obtain the recognition accuracy of 60.2% on the gesture database Chalearn LAP IsoGD, which is better than the result of related algorithms. The results show that the improved performance of our MMFTSN model.
手势识别应用于各种智能场景中。本文提出了多模态融合时间段网络(MMFTSN)模型来解决动态手势识别问题。三种手势模式:RGB，深度和光流(OF)视频数据等分割和随机采样。然后，利用卷积神经网络对采样帧进行分类。最后，将三种情态分类结果进行融合。利用MMFTSN在手势数据库Chalearn LAP IsoGD上获得60.2%的识别准确率，优于相关算法的识别结果。结果表明，我们的MMFTSN模型的性能得到了改善。
{"title":"Dynamic Gesture Recognition Based on the Multimodality Fusion Temporal Segment Networks","authors":"Mingyao Zheng, Y. Tie, L. Qi, Shengnan Jiang","doi":"10.1109/ISNE.2019.8896438","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896438","url":null,"abstract":"Gesture recognition is applied in various intelligent scenes. In this paper, we propose the multi-modality fusion temporal segment networks (MMFTSN) model to solve dynamic gestures recognition. Three gesture modalities: RGB, Depth and Optical flow (OF) video data are equally segmented and randomly sampled. Then, the sampling frames are classified using convolutional neural network. Finally, fusing three kinds of modality classification results. MMFTSN is used to obtain the recognition accuracy of 60.2% on the gesture database Chalearn LAP IsoGD, which is better than the result of related algorithms. The results show that the improved performance of our MMFTSN model.","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"527 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133437493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ISNE.2019.8896388
Benqing Guo, Jun Chen, Yao Wang
A CMOS fully differential current-mode frontend for SAW-less receivers is proposed. The noise-cancelling LNTA has a main path of the common-gate (CG) stage and an auxiliary path of the inverter stage. A current mirror is used to combine the signals from the main and auxiliary paths in current-mode domain. The stacked nMOS/pMOS configurations improve their power efficiency. Traditional stacked tri-state inverter as D-latch replaced by the discrete inverter and transmission gate enables a reduced supply voltage of divider core. LO generator based on the improved divider provides quarter LO signals to drive the proposed LNTA-shared receiver front-end. Simulation results in 180 nm CMOS indicate that the integrated receiver front-end provides a NF of 2.4 dB, and a maximum gain of 45 dB from 0.2 to 3.3 GHz. The inband and out-of-band IIP3 of 2.5 dBm and 4 dBm, are obtained, respectively.
{"title":"A 0.2-3.3 GHz 2.4 dB NF 45 dB Gain Current-Mode Front-End for SAW-less Receivers in 180 nm CMOS","authors":"Benqing Guo, Jun Chen, Yao Wang","doi":"10.1109/ISNE.2019.8896388","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896388","url":null,"abstract":"A CMOS fully differential current-mode frontend for SAW-less receivers is proposed. The noise-cancelling LNTA has a main path of the common-gate (CG) stage and an auxiliary path of the inverter stage. A current mirror is used to combine the signals from the main and auxiliary paths in current-mode domain. The stacked nMOS/pMOS configurations improve their power efficiency. Traditional stacked tri-state inverter as D-latch replaced by the discrete inverter and transmission gate enables a reduced supply voltage of divider core. LO generator based on the improved divider provides quarter LO signals to drive the proposed LNTA-shared receiver front-end. Simulation results in 180 nm CMOS indicate that the integrated receiver front-end provides a NF of 2.4 dB, and a maximum gain of 45 dB from 0.2 to 3.3 GHz. The inband and out-of-band IIP3 of 2.5 dBm and 4 dBm, are obtained, respectively.","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134329439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ISNE.2019.8896449
N. Prabhu, Desmond Loy Jia Jun, P. Dananjaya, E. Toh, W. Lew, N. Raghavan
In this work, the quantitative impact of variability in the low and high resistance state distributions of Hafnium oxide based RRAM on the prediction accuracy of deep learning neural networks is explored over a wide range of current compliance ranging from 2 to 500micro Ampere. The device power versus prediction accuracy trade-off trend is examined for such a wide range of compliance for the first time. The weights of one of the layers of the convolutional neural network (CNN) are represented by the floating point binary representation where the binary bits are configured using the RRAM resistance distribution data on an AlexNet platform.
{"title":"Exploring the Power – Prediction Accuracy Trade-Off in a Deep Learning Neural Network using Wide Compliance RRAM Device","authors":"N. Prabhu, Desmond Loy Jia Jun, P. Dananjaya, E. Toh, W. Lew, N. Raghavan","doi":"10.1109/ISNE.2019.8896449","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896449","url":null,"abstract":"In this work, the quantitative impact of variability in the low and high resistance state distributions of Hafnium oxide based RRAM on the prediction accuracy of deep learning neural networks is explored over a wide range of current compliance ranging from 2 to 500micro Ampere. The device power versus prediction accuracy trade-off trend is examined for such a wide range of compliance for the first time. The weights of one of the layers of the convolutional neural network (CNN) are represented by the floating point binary representation where the binary bits are configured using the RRAM resistance distribution data on an AlexNet platform.","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134068298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ISNE.2019.8896397
Zeheng Wang, Shengji Wang, Yuanzhe Yao
In this letter, a high-performance electrically adjust-able current regulator is proposed on the LED-compatible AlGaN/GaN platform. The regulator features an electrical controlled gate and an integrated sensor, which could effectively feedback the cathode potential into the channel near the gate. Therefore, a large adjustable range of current regulating, more than 300 mA/mm, is achieved with a maximum ripple of 34.4 mA/mm. Compared with the conventional devices that just own sensor or p-GaN gate, the proposed regulator exhibits reasonable operation point and low current ripple in addition to the large-range electrically adjustable functionality. These features render the proposed regulator's notable potential in commercialization of high-density integrated LED components, charging stations and so on.
{"title":"A LED-Compatible Current Regulator with Integrated Electrically Adjustable Sensor","authors":"Zeheng Wang, Shengji Wang, Yuanzhe Yao","doi":"10.1109/ISNE.2019.8896397","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896397","url":null,"abstract":"In this letter, a high-performance electrically adjust-able current regulator is proposed on the LED-compatible AlGaN/GaN platform. The regulator features an electrical controlled gate and an integrated sensor, which could effectively feedback the cathode potential into the channel near the gate. Therefore, a large adjustable range of current regulating, more than 300 mA/mm, is achieved with a maximum ripple of 34.4 mA/mm. Compared with the conventional devices that just own sensor or p-GaN gate, the proposed regulator exhibits reasonable operation point and low current ripple in addition to the large-range electrically adjustable functionality. These features render the proposed regulator's notable potential in commercialization of high-density integrated LED components, charging stations and so on.","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123790676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ISNE.2019.8896530
T. Gao, Hongtao Shi, Zhongnan Jiang, Shiyu Du, Shuli Jia
Neural network attracts more and more attention in many research fields. However, neural network prediction is scarce in determining the hidden layer. In this paper an algorithm for rapidly discovering hidden layer nodes in neural networks is proposed. Establish a neural network to predict future wind power. Weather forecast information is used as an input data set for neural networks. Then two test sites in the hidden layer are identified by traditional methods. The fitting degree of the two test points is compared through the fitting judgment. BP NNW is founded base on the weather-report data, and the prediction of future wind power is finally completed
{"title":"An Optimization Algorithm Based On Fitting and Center Approximation Principle For Wind Power Prediction","authors":"T. Gao, Hongtao Shi, Zhongnan Jiang, Shiyu Du, Shuli Jia","doi":"10.1109/ISNE.2019.8896530","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896530","url":null,"abstract":"Neural network attracts more and more attention in many research fields. However, neural network prediction is scarce in determining the hidden layer. In this paper an algorithm for rapidly discovering hidden layer nodes in neural networks is proposed. Establish a neural network to predict future wind power. Weather forecast information is used as an input data set for neural networks. Then two test sites in the hidden layer are identified by traditional methods. The fitting degree of the two test points is compared through the fitting judgment. BP NNW is founded base on the weather-report data, and the prediction of future wind power is finally completed","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116152045","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}
Uneven illumination phenomenon and the cloud are common factors in lower quality aerial images, which will lead to the ground cover image, tonal change, distribution of color and brightness in RS images. This paper presents a technique to eliminate the cloud of the RS images, which uses filter dodging and information compensation to the processed images, in order to achieve a clear representation of the ground cover information.
{"title":"A Technique to Eliminate Cloud of RS Images","authors":"Youwei Zhang, Xiaoqing Zhu, Fangli Ge, Yafei Liu, Bing Xue, Xuekai Sun","doi":"10.1109/ISNE.2019.8896673","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896673","url":null,"abstract":"Uneven illumination phenomenon and the cloud are common factors in lower quality aerial images, which will lead to the ground cover image, tonal change, distribution of color and brightness in RS images. This paper presents a technique to eliminate the cloud of the RS images, which uses filter dodging and information compensation to the processed images, in order to achieve a clear representation of the ground cover information.","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130010266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ISNE.2019.8896415
Chuang Ding, Y. Tie, L. Qi
Multi-modal methods play an important role on action recognition. Each modal can extract different features to analyze the same motion classification. But numbers of researches always separate the one task from the others, which cause the unreasonable utilization of complementary information in the multi-modality data. Skeleton is robust to the variation of illumination, backgrounds and viewpoints, while RGB has better performance in some circumstances when there are other objects that have great effect on recognition of action, such as drinking water and eating snacks. In this paper, we propose a novel Multi-information Complementarity Neural Network (MiCNN) for human action recognition to address this problem. The proposed MiCNN can learn the features from both skeleton and RGB data to ensure the abundance of information. Besides, we design a weighted fusion block to distribute the weights reasonably, which can make each modal draw on their respective strengths. The experiments on NTU RGB-D datasets demonstrate the excellent performance of our scheme, which are superior to other methods that we have ever known.
{"title":"Multi-information Complementarity Neural Networks for Multi-Modal Action Recognition","authors":"Chuang Ding, Y. Tie, L. Qi","doi":"10.1109/ISNE.2019.8896415","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896415","url":null,"abstract":"Multi-modal methods play an important role on action recognition. Each modal can extract different features to analyze the same motion classification. But numbers of researches always separate the one task from the others, which cause the unreasonable utilization of complementary information in the multi-modality data. Skeleton is robust to the variation of illumination, backgrounds and viewpoints, while RGB has better performance in some circumstances when there are other objects that have great effect on recognition of action, such as drinking water and eating snacks. In this paper, we propose a novel Multi-information Complementarity Neural Network (MiCNN) for human action recognition to address this problem. The proposed MiCNN can learn the features from both skeleton and RGB data to ensure the abundance of information. Besides, we design a weighted fusion block to distribute the weights reasonably, which can make each modal draw on their respective strengths. The experiments on NTU RGB-D datasets demonstrate the excellent performance of our scheme, which are superior to other methods that we have ever known.","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"351 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124446573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ISNE.2019.8896379
Guancong Liu, Xia Xiao, Haiyang Qi, Hang Song, Shuming Zhao, Derong Cao
In the new green Eco-toilet, the temperature of the reaction chamber plays a crucial role in the effective decomposition and utilization of human excreta. In this paper, an FPGA-based reaction chamber thermal control system is proposed. The system combines with explosion-proof temperature sensor and DC water pump, which can control and keep the temperature of reaction chamber in a proper range. The experimental results show the efficacy of the system, demonstrating that the proposed system can promote the development of new green Eco-toilet.
{"title":"FPGA-based Thermal Control System of Reaction Chamber of Photovolatic powerd Eco-toilet","authors":"Guancong Liu, Xia Xiao, Haiyang Qi, Hang Song, Shuming Zhao, Derong Cao","doi":"10.1109/ISNE.2019.8896379","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896379","url":null,"abstract":"In the new green Eco-toilet, the temperature of the reaction chamber plays a crucial role in the effective decomposition and utilization of human excreta. In this paper, an FPGA-based reaction chamber thermal control system is proposed. The system combines with explosion-proof temperature sensor and DC water pump, which can control and keep the temperature of reaction chamber in a proper range. The experimental results show the efficacy of the system, demonstrating that the proposed system can promote the development of new green Eco-toilet.","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124747650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ISNE.2019.8896442
Yongquan Xia, Xiwang Xie, Xinwen Wu, Jun Zhi, Sihai Qiao
Liver region extraction in abdominal CT images is a very important research field, a method of liver segmentation based on region growing for automatic selection of seed points is proposed in this paper. Firstly, the original image is binarized, and the initial area of the liver is extracted by the maximum area measurement method; After that, the improved region growth algorithm was used to segment the liver, and the location of seed points was automatically obtained by finding the center of the maximum inscribed circle locked in the initial liver area, which was used as the basis for the selection of seed points; Finally, the segmented liver region is treated by morphological methods. The experimental results show that the approach effectively solves the problem of manually selecting seed points for regional growth, and can improve the efficiency and accuracy of seed point selection, which avoids the selection of seed points at the wrong positions such as edges or noise due to subjective factors.
{"title":"An Approach of Automatically Selecting Seed Point Based on Region Growing for Liver Segmentation","authors":"Yongquan Xia, Xiwang Xie, Xinwen Wu, Jun Zhi, Sihai Qiao","doi":"10.1109/ISNE.2019.8896442","DOIUrl":"https://doi.org/10.1109/ISNE.2019.8896442","url":null,"abstract":"Liver region extraction in abdominal CT images is a very important research field, a method of liver segmentation based on region growing for automatic selection of seed points is proposed in this paper. Firstly, the original image is binarized, and the initial area of the liver is extracted by the maximum area measurement method; After that, the improved region growth algorithm was used to segment the liver, and the location of seed points was automatically obtained by finding the center of the maximum inscribed circle locked in the initial liver area, which was used as the basis for the selection of seed points; Finally, the segmented liver region is treated by morphological methods. The experimental results show that the approach effectively solves the problem of manually selecting seed points for regional growth, and can improve the efficiency and accuracy of seed point selection, which avoids the selection of seed points at the wrong positions such as edges or noise due to subjective factors.","PeriodicalId":405565,"journal":{"name":"2019 8th International Symposium on Next Generation Electronics (ISNE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124793761","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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