Vehicular Communications最新文献

{"title":"Joint smooth trajectory design and wireless communication control for mobile internet of vehicles assisted by a UAV and ground RISs","authors":"Mohsen Eskandari ,&nbsp;Andrey V. Savkin ,&nbsp;Mohammad Deghat","doi":"10.1016/j.vehcom.2025.100968","DOIUrl":"10.1016/j.vehcom.2025.100968","url":null,"abstract":"<div><div>Low latency, reliable, and stable communication are essential for autonomous driving and mission accomplishment of Internet-of-Vehicles (IoVs) in smart cities. Therefore, future wireless networks will work based on quasi-optic millimeter wave (mmWave) signals for high-rate data transfer. However, given the mobility of vehicles, the mmWave links are prone to outages as they intrinsically rely on directional beamforming to line-of-sight (LoS) paths. Notably, fragile wireless links in dense urban canyons expose autonomous vehicles to safety risks. An unmanned aerial vehicle (UAV) equipped with a reconfigurable holographic surface (RHS) is navigated for establishing aerial LoS links for IoVs. RHS performs beamforming by adjusting the radiation patterns through the holographic surface, so it is energy efficient. The UAV-RHS is supported by terrestrial reconfigurable intelligent surfaces (RISs) installed on building facades, which are utilized to improve coverage and link reliability. The UAV’s navigation objectives are maintaining valid LoS links for IoVs, ensuring quality of service, and minimizing energy consumption. However, an obstacle-free kinematics-aware smooth trajectory, subject to motion constraints, is required for UAV navigation in dense urban environments. Satisfying these navigation objectives and constraints makes the trajectory design with valid LoS links a non-convex NP-hard optimization problem. To address this, we propose, for the first time, training generative adversarial networks (GANs) to generate valid paths in real time. State feedback control with quadratic optimization is proposed to smooth the trajectory. Simulation results are provided to evaluate the proposed method.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100968"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resource allocation and model split for energy-efficient federated split learning in Internet of Vehicles with imperfect CSI","authors":"Youqiang Hu","doi":"10.1016/j.vehcom.2025.100979","DOIUrl":"10.1016/j.vehcom.2025.100979","url":null,"abstract":"<div><div>Vehicular federated learning is able to deal with the data shortage dilemma in practical Artificial Intelligence (AI) projects in Internet of Vehicles (IoV) scenarios, but there is a bottleneck in this training paradigm, that is, the energy consumption issue. Since the training process is carried out on vehicles and the training tasks are generally computation-intensive, the battery lives of vehicles will be greatly affected if they participate in training. To improve the sustainability of the participants, split learning is introduced to the procedure of vehicular federated learning in this paper. Split learning divides the trained AI model into two parts. One is retained on terminals, and the other is sent to the cloud servers for remote training. Since the computation workload is reduced, the energy consumptions of participants are lowered. This training paradigm is called Vehicular Federated Split Learning (VFSL). Then, we model the computation and communication processes of VFSL and derive the energy consumption minimization problem. The estimated Channel State Information (CSI) between high-moving vehicles and Road Side Units (RSUs) is generally inaccurate. The imperfect CSI makes the formulated problem a stochastic mixed integer nonlinear programming problem, which is hard to solve. Therefore, we propose a resource allocation and model split strategy based on the Constrained Stochastic Successive Convex Approximation (CSSCA) and greedy algorithms. Simulation results demonstrate that the proposed strategy is able to achieve higher energy efficiency compared to the existing strategies in the case of imperfect CSI.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100979"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TP-IoV: A task prediction-oriented cloud-edge collaborative offloading framework for Internet of vehicles","authors":"Peiying Zhang ,&nbsp;Renzhuang Yuan ,&nbsp;Lizhuang Tan ,&nbsp;Konstantin Igorevich Kostromitin ,&nbsp;Athanasios V. Vasilakos ,&nbsp;Jian Wang","doi":"10.1016/j.vehcom.2025.100981","DOIUrl":"10.1016/j.vehcom.2025.100981","url":null,"abstract":"<div><div>With the rapid development of Intelligent Vehicles and Mobile Edge Computing, the Internet of Vehicles (IoV) faces numerous challenges when handling computationally intensive tasks, primarily including limited computing resources and dynamic requirement distributions in the IoV system. To address these challenges, this paper proposes a novel edge–cloud collaborative offloading framework for the Internet of Vehicles, named TP-IoV. This framework achieves proactive optimization of computation task offloading by combining time series task prediction with an adaptive decision mechanism. Specifically, TP-IoV utilizes the Informer model to predict future task characteristics and employs the Twin Delayed Deep Deterministic Policy Gradient algorithm to determine the optimal allocation strategy for tasks among local vehicles, edge nodes, and cloud servers. Simulation results demonstrate that under high load and strict latency conditions, TP-IoV significantly outperforms existing baseline methods in reducing task latency and improving the task completion success rate. This work provides a scalable and proactive solution for latency-sensitive applications in dynamic Internet of Vehicles environments.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100981"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145363500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel distributed architecture incorporating deep learning and biased selection for vehicular communication mmWaves beamforming","authors":"Abishek Subramanian,&nbsp;Aurenice Oliveira","doi":"10.1016/j.vehcom.2025.100966","DOIUrl":"10.1016/j.vehcom.2025.100966","url":null,"abstract":"<div><div>Vehicle to Infrastructure (V2I) connectivity has historically relied on Dedicated Short Range Communication (DSRC) and more recently Cellular Vehicle to Everything (C-V2X). However, DSRC adoption has slowed due to high deployment costs, whereas C-V2X, limited to the 5.9 GHz sub 6 GHz band, provides modest data rates mainly suitable for safety critical messages. Emerging V2I services, such as high resolution sensor sharing and cooperative perception, demand multi gigabit throughput to transfer large volumes of data (4–10 GB) between vehicles and Mobile Edge Computing (MEC) servers, requirements exceeding the capacity of sub-6 GHz technologies. This study explores a novel distributed architecture utilizing a federated learning paradigm for optimizing mmWave beamforming processes in V2I communication systems. By leveraging multiple non-RF modality sensors (GPS and LiDAR) and deep learning models, this approach aims to enhance the global model's adaptability and reduce the sub-6 GHz channel usage. The proposed system uses client-biased selection strategies, including MaxLoss and Heuristic Multi-Arm Bandit, to train and update the global model, demonstrating significant improvements in convergence rates and overall performance. Simulation results using the Infocom FLASH dataset validate the framework's efficiency, highlighting its potential for real-world deployment in dynamic environments.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100966"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145009039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SHAP-based feature selection and MASV-weighted SMOTE for enhanced attack detection in VANETs","authors":"Zawiyah Saharuna ,&nbsp;Tohari Ahmad ,&nbsp;Royyana Muslim Ijtihadie","doi":"10.1016/j.vehcom.2025.100970","DOIUrl":"10.1016/j.vehcom.2025.100970","url":null,"abstract":"<div><div>Vehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS) but remain highly vulnerable to cyberattacks, such as malicious attacks and position falsification. Detection is hindered by high-dimensional traffic data and severe class imbalance. Existing intrusion detection methods often overlook feature importance, limiting adaptability to different attack types. This study proposes an adaptive Intrusion Detection System (IDS) integrating SHAP-based feature selection with a MASV-weighted SMOTE technique. To the best of our knowledge, this is the first framework to leverage SHAP values not only for feature selection but also to guide class rebalancing during synthetic sample generation. Unlike conventional approaches, which treat all features equally, our method prioritizes features based on their Mean Absolute SHAP Values (MASV) in both selection and oversampling. Evaluated on CICIDS-2017 and validated on VeReMi, the framework demonstrates strong generalizability between datasets. It reduces feature dimensionality by up to 80% (78 to 15 features) while maintaining 99.91% accuracy, achieving up to 50.79% faster training and real-time inference below 0.1 ms per instance. MASV-weighted SMOTE transforms minority class detection performance, elevating the Infiltration attack F1-score from 0 to 88.89% and PR-AUC from 4.43% to 100%. These results outperform baseline models, enabling accurate, efficient, and interpretable IDS for VANETs security applications.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100970"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145121225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FANET-enabled cluster-based emergency communication with 3D mobility in 5G and beyond","authors":"Md. Thouhidur Rahman ,&nbsp;A.F.M. Shahen Shah ,&nbsp;Muhammet Ali Karabulut ,&nbsp;Haci Ilhan","doi":"10.1016/j.vehcom.2025.100971","DOIUrl":"10.1016/j.vehcom.2025.100971","url":null,"abstract":"<div><div>In 5G and beyond, unmanned aerial vehicles (UAVs) are highly valued for their communication capabilities, affordability, and deployment flexibility. Multi-UAV systems, which operate in ad-hoc networks known as UAV ad-hoc networks or flying ad-hoc networks (FANETs), represent some of the most promising technologies both currently and in the future. In disaster situations, it will be crucial to set up temporary UAV-based emergency flying base stations (BSs), provide wireless coverage in cellular networks, and establish communication relays for long-distance data transmission. To establish this network, efficient communication between the UAVs is the most vital point. Additionally, due to mobility, the topology changes frequently, leading to potential collisions and packet losses. Therefore, in this paper, a minimum distance clustering scheme (MDCS)-based FANET is proposed, where the topology is controlled by a back-off mechanism and network connectivity is maintained even when the UAVs are moving at different altitudes by calculating the relative velocity on a 3D platform while considering the randomized path-based 3D mobility model. An efficient cluster build-up process and a method for determining the position of the cluster head (CH) are introduced to control the cluster proficiently. An analytical study is performed considering Rayleigh, Nakagami-m, and Rician fading channels. Moreover, the obtained Monte Carlo simulation results justify the analytical findings. Finally, the simulations show better results than existing work in terms of throughput with changes in distance, velocity, and the number of UAVs, as well as outage probability, packet dropping rate, and delay. In the case of the Rician fading channel, for 40 UAVs, a cluster size of 7 or fewer is more favorable, showing a maximum connection distance of 165 m, a maximum throughput of 10.2 Mbps, and a maximum delay of 55.57 ms.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100971"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"UAV-assisted wireless communications in the 6G-and-beyond era: An extensive survey on characteristics, standardization and regulations, enabling technologies, challenges, and future directions","authors":"Mobasshir Mahbub ,&nbsp;Mir Md. Saym ,&nbsp;Sarwar Jahan ,&nbsp;Anup Kumar Paul ,&nbsp;Alireza Vahid ,&nbsp;Seyyedali Hosseinalipour ,&nbsp;Bobby Barua ,&nbsp;Hen-Geul Yeh ,&nbsp;Raed M. Shubair ,&nbsp;Tarik Taleb ,&nbsp;Aryan Kaushik ,&nbsp;Mohammed H. Alsharif ,&nbsp;M. Shariful Islam ,&nbsp;Russel Reza Mahmud ,&nbsp;Dusit Niyato","doi":"10.1016/j.vehcom.2025.100977","DOIUrl":"10.1016/j.vehcom.2025.100977","url":null,"abstract":"<div><div>Unmanned Aerial Vehicles (UAVs) have emerged as transformative tools in wireless communication systems, revolutionizing the landscape of next-generation networks, including 6G and beyond. This survey comprehensively examines the technical advancements, challenges, and future directions of UAV-assisted wireless communications. It begins with analyzing UAV characteristics, such as flight dynamics, payload capacity, and power systems, and explores their pivotal role in enabling efficient connectivity across terrestrial, aerial, and maritime domains. The survey then delves into enabling technologies like advanced antenna designs, beamforming techniques, channel modeling, energy consumption models, and mobility optimization, emphasizing their necessity for achieving seamless UAV-to-ground, UAV-to-UAV, and UAV-to-satellite interactions. It further discusses regulatory frameworks and standardization efforts by global entities to address safety, spectrum allocation, and privacy concerns. Innovative routing protocols, including AI-driven and software-defined networking approaches, are analyzed, highlighting their potential to enhance scalability, reduce latency, and optimize resource management in dynamic UAV networks. This work identifies significant challenges such as energy efficiency, secure communication in hostile environments, and trajectory optimization while navigating complex three-dimensional (3D) spaces. The survey finally proposes directions for future research, including the exploration of sub-THz and THz communication, cross-layer routing, and the integration of UAVs with emerging networking paradigms. By synthesizing lessons learned and outlining unresolved questions, this paper serves as a resource for advancing UAV-enabled connectivity and unlocking new capabilities for ubiquitous and resilient wireless networks.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100977"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of multichannel operation mechanisms for vehicular networks","authors":"Felipe García Vidal,&nbsp;Esteban Egea López,&nbsp;José Santa Lozano","doi":"10.1016/j.vehcom.2025.100978","DOIUrl":"10.1016/j.vehcom.2025.100978","url":null,"abstract":"<div><div>Upon the massive deployment of Cooperative Intelligent Transportation Systems (C-ITS), services developed for connected vehicles need an efficient, reliable and predictable network access to assure proper operation. European Telecommunications Standards Institute (ETSI) Release 2 services cannot be deployed using a single control channel, and require the management of multiple channels used simultaneously by applications. Because of this, ETSI defined a mechanism called Multi-Channel Operation (MCO). Two simple MCO load allocation mechanisms have been recommended, load balancing and sequential filling, but they have not been evaluated in detail until now. In this paper, these two mechanisms, as well as their congestion control variants, are evaluated. An open-source simulation framework has been implemented for such a work, which is open to future extensions. Then, through multiple evaluations following the ETSI simulation setup, we discuss the behavior of these mechanisms under scenarios with a highly congested medium, employing different traffic loads and vehicular densities. Our results show that MCO improvement is limited under high-load conditions, by saturation of channels before switching to a new one (sequential filling) and synchronization of channel assignment among vehicles (load balancing), and the introduction of a simple reactive congestion control does not improve their performance. The main limitations are examined, and recommendations are provided to guide the evolution of these mechanisms.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100978"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Secure quantum aggregate signature scheme for vehicular ad-hoc networks","authors":"Sunil Prajapat ,&nbsp;Dheeraj Kumar ,&nbsp;M. Shamim Hossain","doi":"10.1016/j.vehcom.2025.100974","DOIUrl":"10.1016/j.vehcom.2025.100974","url":null,"abstract":"<div><div>The rapid evolution of smart cities and intelligent transportation systems has led to the widespread deployment of Vehicular Ad Hoc Networks (VANETs), enabling real-time inter-vehicular communication and data sharing related to traffic congestion, vehicle location, and road safety. However, the open and dynamic nature of VANETs makes them vulnerable to various security threats, including identity tracing and message forgery. To address these concerns, this paper proposes a quantum aggregate signature scheme that leverages quantum teleportation and untraceable identity mechanisms for secure and privacy-preserving communication in VANETs. The proposed scheme enables the aggregation of multiple signatures into a single, compact signature while preserving the anonymity of vehicular nodes through pseudo-identities and quantum-enhanced privacy techniques. By incorporating quantum teleportation, our scheme ensures quantum-level security for message transmission without directly transferring the secret state. Furthermore, it supports efficient batch verification to authenticate messages from multiple vehicles with minimal computational and communication overhead. The protocol's correctness and security are validated using both Scyther tool-based formal verification and informal analysis, demonstrating strong resistance against existential forgery, impersonation, and traceability attacks. Compared to existing schemes, our approach reduces computational time by 0.053 ms and communication overhead by 778 bytes, making it scalable, efficient, and highly applicable for real-world VANET deployments.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100974"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scalable AI-driven intent-based vehicle-to-everything communications for secure, low-latency, and energy-efficient smart cities","authors":"Wasim Ahmad ,&nbsp;Farman Ali ,&nbsp;Aitizaz Ali","doi":"10.1016/j.vehcom.2025.100973","DOIUrl":"10.1016/j.vehcom.2025.100973","url":null,"abstract":"<div><div>The Internet of Things (IoT) and vehicle-to-vehicle (V2V) communication technologies are rapidly growing, and a smart, efficient, and scalable communication framework could accomplish the optimum resource allocation and network performance objective. In view of this, although significant progress has been made in terms of V2V communication through IoT, current urban deployments through dense traffic (&gt; 1,500 vehicles / hour experience average packet latencies ≥120 ms and per-packet energy consumptions ≥100 J, precluding life critical safety applications. To address these constraints, we introduce a novel four-layer V2X framework, AI-integrated Intent-Based Networking (AI-IBN), that:<ul><li><span>1.</span><span><div>Abstracts high-level safety and flow intents into the active per-link policies by way of a Deep Reinforcement-Learning controller.</div></span></li><li><span>2.</span><span><div>Integrates vehicle-to-vehicle(V2V)/vehicle-to-infrastructure (V2I)/vehicle-to-pedestrian (V2P)/vehicle-to-network (V2N) communication in a single intention manager.</div></span></li><li><span>3.</span><span><div>Formulates new subproblems that optimize intersection timing and allocate bus-lanes based, online, and with stochastic gradient updates; and</div></span></li><li><span>4.</span><span><div>Encrypts all intents in an end-to-end manner with a lightweight and symmetric-key authentication protocol.</div></span></li></ul> In the urban traffic data set (2 km2 grid, 1500 veh / h) generated by Google Colab in Python, AI-IBN decreases the average packet latency from 150 to 50 ms (67%), reduces the energy per message from 150 to 50 J (67%) and increases the packet success rate from 0.65 to 0.93. In a specific intensity Jamming attack (we have disrupted 10% percent of the channel), our security module maintains a success rate of &gt; 0.90, while a baseline is lower than 0.70. These results enable sub-50-ms and sub-50 J collision-avoidance alerts and set the stage for scalable, life-critical V2X safety services in integrated intelligent transport systems.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"56 ","pages":"Article 100973"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}