Digital Communications and Networks最新文献_第2页

Adversarial diffusion synthesis for specific emitter identification: multi-scale signal augmentation with cross-domain constraints 特定发射器识别的对抗扩散合成：跨域约束下的多尺度信号增强

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-09-01 Epub Date: 2026-07-16 DOI: 10.1016/j.dcan.2026.07.006

Yongsheng Duan, Junning Zhang, Lei Xue, Ying Xu, Linshuang Kang, Dongli Zhang

{"title":"Adversarial diffusion synthesis for specific emitter identification: multi-scale signal augmentation with cross-domain constraints","authors":"Yongsheng Duan, Junning Zhang, Lei Xue, Ying Xu, Linshuang Kang, Dongli Zhang","doi":"10.1016/j.dcan.2026.07.006","DOIUrl":"10.1016/j.dcan.2026.07.006","url":null,"abstract":"<div><div>Generative data augmentation offers a promising solution to data scarcity in Internet of Things(IoT) emitter identification, yet standard Denoising Diffusion Probabilistic Model (DDPM) often lacks semantic and structural control, hindering their capture of hierarchical signal features and cross-domain physical consistency. For this, this paper proposes a DDPM enhanced with a multi-scale hybrid attention mechanism, which jointly optimizes consistency across time-domain waveforms, frequency-domain modulation patterns, and sequential signal features. By integrating contrastive learning with autoregressive modeling, the proposed method captures long-range temporal dependencies and effectively represents complex signal interactions across multiple time scales. Then, we propose a multi-domain adversarial joint constraint to align the generated and real data distributions across physical layer signal, statistical, and semantic domains, significantly enhancing cross-domain feature consistency. The experimental results obtained show that, compared with the existing benchmark tests, our solution has increased the recognition accuracy by 7.91% in the case of small sample sizes, and also demonstrates stronger robustness even under low to moderate signal-to-noise ratio conditions.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 9","pages":"Pages 1384-1395"},"PeriodicalIF":6.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149203287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

S2F-GNN: A self-supervised robust encrypted traffic classification method based on dynamic heterogeneous graphs S2F-GNN：基于动态异构图的自监督鲁棒加密流量分类方法

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-09-01 Epub Date: 2026-05-20 DOI: 10.1016/j.dcan.2026.05.002

Jiangtao Zhai, Lejun Shen, Shuo Wu, Kai Chen, Guangjie Liu

{"title":"S2F-GNN: A self-supervised robust encrypted traffic classification method based on dynamic heterogeneous graphs","authors":"Jiangtao Zhai, Lejun Shen, Shuo Wu, Kai Chen, Guangjie Liu","doi":"10.1016/j.dcan.2026.05.002","DOIUrl":"10.1016/j.dcan.2026.05.002","url":null,"abstract":"<div><div>Encrypted traffic classification is a critical task in network security and management. However, existing methods often neglect the structural and multi-dimensional correlations of traffic. Furthermore, their heavy reliance on large-scale labeled data limits their generalization ability in dynamic networks. To address the above limitations, this paper proposes a novel few-shot encrypted traffic classification framework based on self-supervised learning (S<sup>2</sup>F-GNN). Firstly, we represent network sessions as dynamic heterogeneous graphs consisting of flow, time, and attribute nodes. This representation effectively captures the structural features and temporal evolution of traffic in a multi-dimensional space. Secondly, we design a multi-task self-supervised framework that synergizes masked autoencoder, graph structure prediction, clustering, and contrastive learning. This framework efficiently learns universal and robust traffic representations from large-scale unlabeled data. In addition, we design a Jensen-Shannon Divergence (JSD)-based feature selection mechanism to identify features that remain stable across changing environments. This further enhances the model’s adaptability in few-shot and dynamic scenarios. Experimental results demonstrate that S<sup>2</sup>F-GNN significantly outperforms the state-of-the-art methods on multiple public datasets. Especially in the few-shot scenarios with scarce labeled data, the average accuracy and F1-score are improved by 4.04% and 9.68%, respectively.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 9","pages":"Pages 1442-1460"},"PeriodicalIF":6.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149203285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Entropy Energy-Based Model: A neighborhood entropy energy-based model for high-dimensional data distribution estimation in intelligent communication networks 基于熵能的模型：基于邻域熵能的智能通信网络高维数据分布估计模型

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-08-01 Epub Date: 2026-04-28 DOI: 10.1016/j.dcan.2026.04.006

Naiyao Wang, Xirong Fu, Changdong Zhou, Houhua Shao, Jiahui Li, Zijian Li, Tony Q. S. Quek

{"title":"Entropy Energy-Based Model: A neighborhood entropy energy-based model for high-dimensional data distribution estimation in intelligent communication networks","authors":"Naiyao Wang, Xirong Fu, Changdong Zhou, Houhua Shao, Jiahui Li, Zijian Li, Tony Q. S. Quek","doi":"10.1016/j.dcan.2026.04.006","DOIUrl":"10.1016/j.dcan.2026.04.006","url":null,"abstract":"<div><div>Energy-based models have shown strong potential in unsupervised learning due to their flexibility in representing complex and uncertain distributions. However, for high-dimensional and locally non-uniform distributions that frequently occur in intelligent communication networks, traditional energy-based models face challenges such as the curse of dimensionality and data sparsity. In this paper, we propose a Neighborhood Entropy Energy-Based Model (NEEM), which estimates the non-uniform probability distribution of the <em>k</em>-Nearest Neighbor region around each sample point using a Local Gaussian. The energy function maps sample points to energy values for entropy estimation, enabling a more accurate representation of the data. NEEM is further applied to generative adversarial models to define the joint distributions of sample points, and its energy values are used for out-of-distribution detection. Experiments on benchmark datasets demonstrate the effectiveness of NEEM across seven evaluation metrics. The model achieves superior performance in diversity evaluation with a Fréchet Inception Distance of 28.88 and an Inception Score of 7.30. Results on out-of-distribution detection further show that NEEM outperforms five baseline models, highlighting its capability in high-dimensional probability distribution estimation and its potential for data analysis and anomaly detection in intelligent communication networks.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 8","pages":"Pages 1233-1246"},"PeriodicalIF":6.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148960976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Corrigendum to “Detecting conflict of heterogeneous access control policies” [Digit. Commun. Networks 8 (2022), 664–679] “检测异构访问控制策略冲突”的勘误表[数字。Commun。网络8 (2022),664-679]

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-08-01 Epub Date: 2026-07-31 DOI: 10.1016/j.dcan.2026.07.007

Mingjie Yu, Fenghua Li, Nenghai Yu, Xiao Wang, Yunchuan Guo

引用次数: 0

Joint design of beam pattern and multi-domain resource allocation for multi-satellite beam hopping systems 多卫星跳波束系统波束方向图联合设计与多域资源分配

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-08-01 Epub Date: 2026-06-27 DOI: 10.1016/j.dcan.2026.06.006

Zhuang Yao, Lixia Xiao, Kangyan Zhou, Jiaxi Zhou, Pei Xiao, Tao Jiang

{"title":"Joint design of beam pattern and multi-domain resource allocation for multi-satellite beam hopping systems","authors":"Zhuang Yao, Lixia Xiao, Kangyan Zhou, Jiaxi Zhou, Pei Xiao, Tao Jiang","doi":"10.1016/j.dcan.2026.06.006","DOIUrl":"10.1016/j.dcan.2026.06.006","url":null,"abstract":"<div><div>In this paper, a joint beam pattern scheduling and resource allocation design is proposed for multi-satellite Beam Hopping (BH) systems, which optimizes inter-satellite load balancing, beam pattern scheduling and multi-domain resource allocation under non-uniform traffic distribution. The optimization problem is formulated as a multi-dimensional max-min fairness problem, and is decomposed into three subproblems to obtain efficient solutions. Specifically, a two-stage cell-satellite assignment strategy is designed, exploiting both satellite visibility and channel quality to achieve effective inter-satellite load balancing. Next, a traffic- and distance-aware BH pattern scheduling algorithm is introduced, where cells are illuminated based on the real-time residual Traffic Satisfaction Ratio (TSR). To mitigate co-frequency interference, a distance-aware subband assignment algorithm is proposed, where each satellite independently updates its subband-cell mapping using the game-theoretic approach. Finally, to further mitigate the inter-beam interference, a Double-Loop Iterative Optimization (DLIO) algorithm based on alternating optimization is proposed to jointly allocate bandwidth and power for the illuminated beams. Simulation results demonstrate that the proposed method significantly outperforms benchmark schemes in terms of transmission fairness.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 8","pages":"Pages 1278-1289"},"PeriodicalIF":6.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148960980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Approximate dynamic precision computation in large-scale MIMO systems: analysis and applications 大规模MIMO系统的近似动态精度计算：分析与应用

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-08-01 Epub Date: 2026-05-27 DOI: 10.1016/j.dcan.2026.05.007

Shihan Wang, Yiran Chen, Chunping Yang, Zheqi Gu, Luping Xiang, Kun Yang, Jienan Chen

{"title":"Approximate dynamic precision computation in large-scale MIMO systems: analysis and applications","authors":"Shihan Wang, Yiran Chen, Chunping Yang, Zheqi Gu, Luping Xiang, Kun Yang, Jienan Chen","doi":"10.1016/j.dcan.2026.05.007","DOIUrl":"10.1016/j.dcan.2026.05.007","url":null,"abstract":"<div><div>As 6G technology advances, it promises to deliver ultra-high transmission speeds and enhanced network capabilities, supported by developments in Massive MIMO and Extremely Large MIMO technologies. However, the expansion of transmission antenna arrays significantly increases signal processing complexity. In this paper, we analyze approximate dynamic precision computation in large-scale MIMO systems and explore dynamic precision-aware approximate computation as a means to counteract the rising complexity. We develop a theoretical framework that clarifies the relationships between quantization bit width, spectral efficiency, and Bit Error Rate (BER). First, we determine a critical point (a <em>stationary point</em>) beyond which further increases in Signal-to-Noise Ratio (SNR) yield negligible gains in spectral efficiency. We show that this SNR stationary point shifts by approximately 6 dB for each additional bit of quantization precision. Moreover, we establish a relationship between quantization bit width and BER, identifying a threshold bit width beyond which further increases no longer yield meaningful BER reductions for a given modulation order and SNR. Using these findings, we propose several dynamic bit-width adaptation strategies to optimize system performance. Specifically, we introduce techniques to adjust the quantization bit width based on real-time SNR, modulation scheme, and target BER. These strategies move away from traditional worst-case fixed-precision designs toward more resource-efficient and performance-tailored approaches. Our methods offer a new framework to manage quantization complexity, paving the way for innovative designs in future 6G communication systems.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 8","pages":"Pages 1266-1277"},"PeriodicalIF":6.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148960979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vehicular communications for autonomous and intelligent transportation systems: a comprehensive survey 自动和智能交通系统的车载通信：综合调查

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-08-01 Epub Date: 2026-06-17 DOI: 10.1016/j.dcan.2026.06.003

Inam Ullah, Zeeshan Ali Haider, Xin Su, Chang Choi, Ali Arishi, Hazrat Bilal

{"title":"Vehicular communications for autonomous and intelligent transportation systems: a comprehensive survey","authors":"Inam Ullah, Zeeshan Ali Haider, Xin Su, Chang Choi, Ali Arishi, Hazrat Bilal","doi":"10.1016/j.dcan.2026.06.003","DOIUrl":"10.1016/j.dcan.2026.06.003","url":null,"abstract":"<div><div>The rapid advancement of Autonomous and Intelligent Transportation Systems (A-ITS) has driven the widespread adoption of vehicular communication technologies to enhance the safety, efficiency, and sustainability of modern transportation networks. Key communication technologies, including Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Everything (V2X), are fundamental for the operation of A-ITS, enabling seamless interaction among vehicles, infrastructure, and other road users. This survey provides a comprehensive analysis of these critical communication technologies and explores the integration of edge computing and Artificial Intelligence (AI) to optimize A-ITS performance. Furthermore, we identify and discuss the major challenges facing A-ITS, including network reliability, data privacy, security, and interoperability, which must be addressed for successful deployment. We also examine the role of emerging 5G/6G networks in smart cities and the Internet of Things (IoT), focusing on their potential to advance autonomous transportation systems. This work serves as a valuable resource for understanding the current state and future prospects of vehicular communications in A-ITS.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 8","pages":"Pages 1177-1196"},"PeriodicalIF":6.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148870551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Joint secure beamforming and sensing strategy for ISAC-enabled LEO satellite system 基于isac的LEO卫星系统联合安全波束形成和传感策略

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-08-01 Epub Date: 2026-04-28 DOI: 10.1016/j.dcan.2026.04.007

Songsong Qu, Yubin Zhao

{"title":"Joint secure beamforming and sensing strategy for ISAC-enabled LEO satellite system","authors":"Songsong Qu, Yubin Zhao","doi":"10.1016/j.dcan.2026.04.007","DOIUrl":"10.1016/j.dcan.2026.04.007","url":null,"abstract":"<div><div>In the aspect of enhancing the spectrum and hardware efficiency in satellite communications, Integrated Sensing and Communication (ISAC) plays a vital role. However, the open nature of the wireless channel makes satellite communication networks extremely vulnerable to eavesdropping. In this paper, we propose a Physical Layer Security (PLS) strategy in the ISAC Low Earth Orbit (LEO) satellite system, which guarantees the communication safety and position privacy simultaneously. In the ISAC LEO satellite system, the targets are regarded as potential Eavesdroppers (Eves), and these Eves may eavesdrop on the information transmitted by the communication transmitter to the legitimate users. To guarantee the secrecy of the transmission, Artificial Noise (AN) is introduced at the transmitter. Then, we respectively formulate the communication and sensing channel models of the ISAC LEO satellite system and thereby deduce the expressions of the secrecy rate. Meanwhile, considering the extreme difficulty in obtaining information at Eves, the Cram<span><math><mrow><mover><mi>e</mi><mo>´</mo></mover></mrow></math></span>r-Rao Bound (CRB) is adopted to characterize the evaluation of the estimation accuracy of Eves. To explore the optimal trade-off between the sensing performance and the secrecy rate of the system, we propose a normalized weighted optimization strategy to maximize the secrecy rate and minimizing the CRB of Eves’ estimation simultaneously. The numerical results validate the performance improvement of the proposed scheme with respect to the security of ISAC-enabled LEO satellite system.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 8","pages":"Pages 1302-1312"},"PeriodicalIF":6.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148997753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards text semantic communication: two-phase variable bitrate control 迈向文本语义交流：两相可变比特率控制

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-08-01 Epub Date: 2026-05-15 DOI: 10.1016/j.dcan.2026.05.001

Dapeng Wu, Jialun Li, Tong Tang, Zhiyuan Zhu, Ruyan Wang

{"title":"Towards text semantic communication: two-phase variable bitrate control","authors":"Dapeng Wu, Jialun Li, Tong Tang, Zhiyuan Zhu, Ruyan Wang","doi":"10.1016/j.dcan.2026.05.001","DOIUrl":"10.1016/j.dcan.2026.05.001","url":null,"abstract":"<div><div>Bitrate plays a crucial role in the transmission of semantic symbols, necessitating a trade-off between semantic information preservation and transmission efficiency. However, most existing Semantic Communication (SEMCOM) designs employ pre-fixed bitrate schemes that lack the flexibility to adapt to dynamic communication environments. To address this limitation, we propose a novel two-phase varibale bitrate control algorithm designed to dynamically adjust the bitrate, thereby achieving an optimal balance between semantic performance and communication resource consumption. In Phase I, we introduce a Deep Learning (DL) based Imitation Network to model the relationship between semantic performance and bitrate across varying channel conditions, enabling the calculation of environment-specific rewards. Subsequently, Phase II employs a Deep Reinforcement Learning (DRL) agent to predict the optimal bitrate for each communication round through environmental exploration. Experimental results demonstrate that our approach yields at least 10% and 2.3% performance improvements over fixed-length bitrate systems under diverse user requirements and bit budgets.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 8","pages":"Pages 1290-1301"},"PeriodicalIF":6.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148997752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Semantic-aware visual information transmission with key information extraction over wireless networks 基于无线网络的语义感知视觉信息传输与关键信息提取

IF 6.3 2区计算机科学

Digital Communications and Networks Pub Date : 2026-08-01 Epub Date: 2026-03-28 DOI: 10.1016/j.dcan.2026.03.014

Chen Zhu, Kang Liang, Jianrong Bao, Zhouxiang Zhao, Zhaohui Yang, Zhaoyang Zhang, Mohammad Shikh-Bahaei

{"title":"Semantic-aware visual information transmission with key information extraction over wireless networks","authors":"Chen Zhu, Kang Liang, Jianrong Bao, Zhouxiang Zhao, Zhaohui Yang, Zhaoyang Zhang, Mohammad Shikh-Bahaei","doi":"10.1016/j.dcan.2026.03.014","DOIUrl":"10.1016/j.dcan.2026.03.014","url":null,"abstract":"<div><div>The advent of 6G networks demands unprecedented levels of intelligence, adaptability, and efficiency to address challenges such as ultra-high-speed data transmission, ultra-low latency, and massive connectivity in dynamic environments. Traditional wireless image transmission frameworks, reliant on static configurations and isolated source-channel coding, struggle to balance computational efficiency, robustness, and quality under fluctuating channel conditions. To bridge this gap, this paper proposes an Artificial Intelligent (AI)-native deep Joint Source-Channel Coding (JSCC) framework tailored for resource-constrained 6G networks. Our approach integrates key information extraction and adaptive background synthesis to enable intelligent, semantic-aware transmission. Leveraging AI-driven tools, Mediapipe for human pose detection and Rembg for background removal, the model dynamically isolates foreground features and matches backgrounds from a pre-trained library, reducing data payloads while preserving visual fidelity. Experimental results demonstrate significant improvements in Peak Signal-to-Noise Ratio (PSNR) compared with traditional JSCC method, especially under low-SNR conditions. This approach offers a practical solution for multimedia services in resource-constrained mobile communications.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"12 8","pages":"Pages 1223-1232"},"PeriodicalIF":6.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148960975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0