Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174259
Shouvik Ganguly, Lele Wang, Young-Han Kim
Codes are developed for two-user multiple access and broadcast channels starting from Gelfand-Pinsker codes with known block lengths, rates, and error performances. Guarantees are provided on the block error rates of the MAC and BC codes in terms of the parameters of the constituent Gelfand- Pinsker codes. These guarantees hold as long as the constituent codes satisfy the assumed properties on rate, codeword weights, and performances, irrespective of the basic structure and other properties.
{"title":"A Functional Construction of Codes for Multiple Access and Broadcast Channels","authors":"Shouvik Ganguly, Lele Wang, Young-Han Kim","doi":"10.1109/ISIT44484.2020.9174259","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174259","url":null,"abstract":"Codes are developed for two-user multiple access and broadcast channels starting from Gelfand-Pinsker codes with known block lengths, rates, and error performances. Guarantees are provided on the block error rates of the MAC and BC codes in terms of the parameters of the constituent Gelfand- Pinsker codes. These guarantees hold as long as the constituent codes satisfy the assumed properties on rate, codeword weights, and performances, irrespective of the basic structure and other properties.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133631919","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 : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174356
Tyler Sypherd, Mario Díaz, L. Sankar, Gautam Dasarathy
We analyze the optimization landscape of a recently introduced tunable class of loss functions called α-loss, α ∈ (0, ∞], in the logistic model. This family encapsulates the exponential loss (α = 1/2), the log-loss (α = 1), and the 0-1 loss (α = ∞) and contains compelling properties that enable the practitioner to discern among a host of operating conditions relevant to emerging learning methods. Specifically, we study the evolution of the optimization landscape of α-loss with respect to α using tools drawn from the study of strictly-locally-quasi-convex functions in addition to geometric techniques. We interpret these results in terms of optimization complexity via normalized gradient descent.
{"title":"On the α-loss Landscape in the Logistic Model","authors":"Tyler Sypherd, Mario Díaz, L. Sankar, Gautam Dasarathy","doi":"10.1109/ISIT44484.2020.9174356","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174356","url":null,"abstract":"We analyze the optimization landscape of a recently introduced tunable class of loss functions called α-loss, α ∈ (0, ∞], in the logistic model. This family encapsulates the exponential loss (α = 1/2), the log-loss (α = 1), and the 0-1 loss (α = ∞) and contains compelling properties that enable the practitioner to discern among a host of operating conditions relevant to emerging learning methods. Specifically, we study the evolution of the optimization landscape of α-loss with respect to α using tools drawn from the study of strictly-locally-quasi-convex functions in addition to geometric techniques. We interpret these results in terms of optimization complexity via normalized gradient descent.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134526658","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 : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174071
Alex Dytso, H. Poor, S. Shamai
This paper provides a general derivative identity for the conditional mean estimator of an arbitrary vector signal in Gaussian noise with an arbitrary covariance matrix. This new identity is used to recover and generalize many known identities in the literature and derive some new identities. For example, a new identity is discovered, which shows that an arbitrary higher-order conditional moment is completely determined by the first conditional moment.Several applications of the identities are shown. For instance, by using one of the identities, a simple proof of the uniqueness of the conditional mean estimator as a function of the distribution of the signal is shown. Moreover, one of the identities is used to extend the notion of empirical Bayes to higher-order conditional moments. Specifically, based on a random sample of noisy observations, a consistent estimator for a conditional expectation of any order is derived.
{"title":"A General Derivative Identity for the Conditional Mean Estimator in Gaussian Noise and Some Applications","authors":"Alex Dytso, H. Poor, S. Shamai","doi":"10.1109/ISIT44484.2020.9174071","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174071","url":null,"abstract":"This paper provides a general derivative identity for the conditional mean estimator of an arbitrary vector signal in Gaussian noise with an arbitrary covariance matrix. This new identity is used to recover and generalize many known identities in the literature and derive some new identities. For example, a new identity is discovered, which shows that an arbitrary higher-order conditional moment is completely determined by the first conditional moment.Several applications of the identities are shown. For instance, by using one of the identities, a simple proof of the uniqueness of the conditional mean estimator as a function of the distribution of the signal is shown. Moreover, one of the identities is used to extend the notion of empirical Bayes to higher-order conditional moments. Specifically, based on a random sample of noisy observations, a consistent estimator for a conditional expectation of any order is derived.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130365254","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 : 2020-06-01DOI: 10.1109/ISIT44484.2020.9173987
Hang Liu, Xiaojun Yuan, Y. Zhang
In this paper, we study the channel acquisition problem in a reconfigurable intelligent surface (RIS) assisted multiuser multiple-input multiple-output (MIMO) system, where an RIS with fully passive phase-shift elements is deployed to assist the MIMO communication. The state-of-the-art channel acquisition approach in such a system estimates the cascaded transmitter-to-RIS and RIS-to-receiver channels by adopting excessively long training sequences. To estimate the cascaded channels with an affordable training overhead, we formulate the channel estimation problem as a matrix-calibration based matrix factorization task. By exploiting the information on the slow-varying channel components and the hidden channel sparsity, we propose a novel message-passing based algorithm to factorize the cascaded channels.
{"title":"Message-Passing Based Channel Estimation for Reconfigurable Intelligent Surface Assisted MIMO","authors":"Hang Liu, Xiaojun Yuan, Y. Zhang","doi":"10.1109/ISIT44484.2020.9173987","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9173987","url":null,"abstract":"In this paper, we study the channel acquisition problem in a reconfigurable intelligent surface (RIS) assisted multiuser multiple-input multiple-output (MIMO) system, where an RIS with fully passive phase-shift elements is deployed to assist the MIMO communication. The state-of-the-art channel acquisition approach in such a system estimates the cascaded transmitter-to-RIS and RIS-to-receiver channels by adopting excessively long training sequences. To estimate the cascaded channels with an affordable training overhead, we formulate the channel estimation problem as a matrix-calibration based matrix factorization task. By exploiting the information on the slow-varying channel components and the hidden channel sparsity, we propose a novel message-passing based algorithm to factorize the cascaded channels.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133726333","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 : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174261
Maciej Obremski, M. Skorski
Estimating entropy of random processes is one of the fundamental problems of machine learning and property testing. It has numerous applications to anything from DNA testing and predictability of human behaviour to modeling neural activity and cryptography. We investigate the problem of Renyi entropy estimation for sources that form Markov chains.Kamath and Verd (ISIT’16) showed that good mixing properties are essential for that task. We prove that even with very good mixing time, estimation of entropy of order α > 1 requires Ω(K2−1/α) samples, where K is the size of the alphabet; particularly min-entropy requires Ω(K2) sample size and collision entropy requires Ω(K3/2) samples. Our results hold both in asymptotic and non-asymptotic regimes (under mild restrictions). The analysis is completed by the upper complexity bound of O(K2) for the standard plug-in estimator. This leads to an interesting open question how to improve upon a plugin estimator, which looks much more challenging than for IID sources (which tensorize nicely).We achieve the results by applying Le Cam’s method to two Markov chains which differ by an appropriately chosen sparse perturbation; the discrepancy between these chains is estimated with help of perturbation theory. Our techniques might be of independent interest.
{"title":"Complexity of Estimating Rényi Entropy of Markov Chains","authors":"Maciej Obremski, M. Skorski","doi":"10.1109/ISIT44484.2020.9174261","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174261","url":null,"abstract":"Estimating entropy of random processes is one of the fundamental problems of machine learning and property testing. It has numerous applications to anything from DNA testing and predictability of human behaviour to modeling neural activity and cryptography. We investigate the problem of Renyi entropy estimation for sources that form Markov chains.Kamath and Verd (ISIT’16) showed that good mixing properties are essential for that task. We prove that even with very good mixing time, estimation of entropy of order α > 1 requires Ω(K2−1/α) samples, where K is the size of the alphabet; particularly min-entropy requires Ω(K2) sample size and collision entropy requires Ω(K3/2) samples. Our results hold both in asymptotic and non-asymptotic regimes (under mild restrictions). The analysis is completed by the upper complexity bound of O(K2) for the standard plug-in estimator. This leads to an interesting open question how to improve upon a plugin estimator, which looks much more challenging than for IID sources (which tensorize nicely).We achieve the results by applying Le Cam’s method to two Markov chains which differ by an appropriately chosen sparse perturbation; the discrepancy between these chains is estimated with help of perturbation theory. Our techniques might be of independent interest.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"59 1-3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120992410","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 : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174375
Shuowen Zhang, Rui Zhang
Intelligent reflecting surface (IRS) is a promising solution to enhance the wireless communication capacity both cost-effectively and energy-efficiently, by properly altering the signal propagation via tuning a large number of passive reflecting units. In this paper, we aim to characterize the fundamental capacity limit of IRS-aided point-to-point multiple-input multiple-output (MIMO) communication systems with multi-antenna transmitter and receiver in general, by jointly optimizing the IRS reflection coefficients and the MIMO transmit covariance matrix. We consider narrowband transmission under frequency-flat fading channels, and develop an efficient alternating optimization algorithm to find a locally optimal solution by iteratively optimizing the transmit covariance matrix or one of the reflection coefficients with the others being fixed. Numerical results show that our proposed algorithm achieves substantially increased capacity compared to traditional MIMO channels without the IRS, and also outperforms various benchmark schemes.
{"title":"On the Capacity of Intelligent Reflecting Surface Aided MIMO Communication","authors":"Shuowen Zhang, Rui Zhang","doi":"10.1109/ISIT44484.2020.9174375","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174375","url":null,"abstract":"Intelligent reflecting surface (IRS) is a promising solution to enhance the wireless communication capacity both cost-effectively and energy-efficiently, by properly altering the signal propagation via tuning a large number of passive reflecting units. In this paper, we aim to characterize the fundamental capacity limit of IRS-aided point-to-point multiple-input multiple-output (MIMO) communication systems with multi-antenna transmitter and receiver in general, by jointly optimizing the IRS reflection coefficients and the MIMO transmit covariance matrix. We consider narrowband transmission under frequency-flat fading channels, and develop an efficient alternating optimization algorithm to find a locally optimal solution by iteratively optimizing the transmit covariance matrix or one of the reflection coefficients with the others being fixed. Numerical results show that our proposed algorithm achieves substantially increased capacity compared to traditional MIMO channels without the IRS, and also outperforms various benchmark schemes.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116637845","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 : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174145
Jinwen Shi, Cong Ling, O. Simeone, J. Kliewer
The uplink of a Cloud Radio Access Network (C-RAN) architecture is studied, where decoding in the cloud takes place at distributed decoding processors. To mitigate the impact of straggling decoders in the cloud, the cloud re-encodes the received frames via a linear code before distributing them to the decoding processors, which estimate linear combinations of the codewords. Focusing on Gaussian channels, and assuming the use of lattice codes at the users, we derive the computational rates and frame error probabilities at the cloud. The approach differs from Compute-and-Forward in that the combination of codewords is not caused by the channel but purposefully created in the cloud by encoding the received signals to reduce the decoding delay.
{"title":"Coded Computation Against Straggling Channel Decoders in the Cloud for Gaussian Channels","authors":"Jinwen Shi, Cong Ling, O. Simeone, J. Kliewer","doi":"10.1109/ISIT44484.2020.9174145","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174145","url":null,"abstract":"The uplink of a Cloud Radio Access Network (C-RAN) architecture is studied, where decoding in the cloud takes place at distributed decoding processors. To mitigate the impact of straggling decoders in the cloud, the cloud re-encodes the received frames via a linear code before distributing them to the decoding processors, which estimate linear combinations of the codewords. Focusing on Gaussian channels, and assuming the use of lattice codes at the users, we derive the computational rates and frame error probabilities at the cloud. The approach differs from Compute-and-Forward in that the combination of codewords is not caused by the channel but purposefully created in the cloud by encoding the received signals to reduce the decoding delay.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114802806","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 : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174461
Hanxu Hou, P. Lee, Y. Han
Modern data centers often organize storage nodes in racks, in which the cross-rack communication cost is typically much higher than the intra-rack communication cost. Rack-aware regenerating codes have recently been proposed to achieve the optimal trade-off between storage redundancy and cross-rack repair bandwidth, subject to the condition that the original data can be reconstructed from a sufficient number of any non-failed nodes. In this paper, we present a coding framework that transforms any minimum-storage regenerating (MSR) code to a minimum-storage rack-aware regenerating (MSRR) code, such that the cross-rack repair bandwidth is minimized subject to the minimum storage redundancy. To this end, we can construct a family of exact-repair constructions for the MSRR codes for all admissible parameters. Furthermore, our constructions achieve low sub-packetization, which is critical for mitigating the I/O overhead during repair.
{"title":"Minimum Storage Rack-Aware Regenerating Codes with Exact Repair and Small Sub-Packetization","authors":"Hanxu Hou, P. Lee, Y. Han","doi":"10.1109/ISIT44484.2020.9174461","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174461","url":null,"abstract":"Modern data centers often organize storage nodes in racks, in which the cross-rack communication cost is typically much higher than the intra-rack communication cost. Rack-aware regenerating codes have recently been proposed to achieve the optimal trade-off between storage redundancy and cross-rack repair bandwidth, subject to the condition that the original data can be reconstructed from a sufficient number of any non-failed nodes. In this paper, we present a coding framework that transforms any minimum-storage regenerating (MSR) code to a minimum-storage rack-aware regenerating (MSRR) code, such that the cross-rack repair bandwidth is minimized subject to the minimum storage redundancy. To this end, we can construct a family of exact-repair constructions for the MSRR codes for all admissible parameters. Furthermore, our constructions achieve low sub-packetization, which is critical for mitigating the I/O overhead during repair.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115334617","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 : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174100
Wei Zhao, K. Shum, Shenghao Yang
A locally repairable code (LRC) with locality r allows for the recovery of any erased symbol of a codeword by accessing only r other symbols of the same codeword. The LRCs achieving the Singleton-like bound are said to be optimal. In this paper, we completely characterize the locality of any constacyclic codes of length ps over finite fields. Using this characterization, we determine all the optimal constacyclic LRCs of prime power lengths over finite fields, i.e., there are no other optimal constacyclic LRCs of prime power length except for those we characterized in this paper. We classify all the optimal constacyclic LRCs into seven classes. The first six classes of constacyclic LRCs classified in this paper have unbounded length, and can achieve smaller locality comparing to those codes constructed by Luo, Xing and Yuan, which also provide unbounded length.
{"title":"Optimal Locally Repairable Constacyclic Codes of Prime Power Lengths","authors":"Wei Zhao, K. Shum, Shenghao Yang","doi":"10.1109/ISIT44484.2020.9174100","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174100","url":null,"abstract":"A locally repairable code (LRC) with locality r allows for the recovery of any erased symbol of a codeword by accessing only r other symbols of the same codeword. The LRCs achieving the Singleton-like bound are said to be optimal. In this paper, we completely characterize the locality of any constacyclic codes of length ps over finite fields. Using this characterization, we determine all the optimal constacyclic LRCs of prime power lengths over finite fields, i.e., there are no other optimal constacyclic LRCs of prime power length except for those we characterized in this paper. We classify all the optimal constacyclic LRCs into seven classes. The first six classes of constacyclic LRCs classified in this paper have unbounded length, and can achieve smaller locality comparing to those codes constructed by Luo, Xing and Yuan, which also provide unbounded length.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116147795","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 : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174496
Shohei Satake, Yujie Gu
Complex codebooks with small inner-product correlation have many applications such as in code-division multiple access communications and compressed sensing. It is desirable but difficult to construct optimal codebooks achieving the well-known Welch bound. In this paper, complex codebooks are investigated from a graph theoretic perspective. A connection between codebooks and Cayley sum graphs is established. Based on this, many infinite families of complex codebooks are explicitly constructed, which are asymptotically optimal with respect to the Welch bound. These constructions not only include some known constructions as special cases but also provide flexible new parameters.
{"title":"Constructions of Complex Codebooks Asymptotically Meeting the Welch Bound: A Graph Theoretic Approach","authors":"Shohei Satake, Yujie Gu","doi":"10.1109/ISIT44484.2020.9174496","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174496","url":null,"abstract":"Complex codebooks with small inner-product correlation have many applications such as in code-division multiple access communications and compressed sensing. It is desirable but difficult to construct optimal codebooks achieving the well-known Welch bound. In this paper, complex codebooks are investigated from a graph theoretic perspective. A connection between codebooks and Cayley sum graphs is established. Based on this, many infinite families of complex codebooks are explicitly constructed, which are asymptotically optimal with respect to the Welch bound. These constructions not only include some known constructions as special cases but also provide flexible new parameters.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116571557","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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