IEEE Open Journal of Vehicular Technology最新文献

{"title":"MMTraP: Multi-Sensor Multi-Agent Trajectory Prediction in BEV","authors":"Sushil Sharma;Arindam Das;Ganesh Sistu;Mark Halton;Ciarán Eising","doi":"10.1109/OJVT.2025.3574385","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3574385","url":null,"abstract":"Accurate detection and trajectory prediction of moving vehicles are essential for motion planning in autonomous driving systems. While traffic regulations provide clear boundaries, real-world scenarios remain unpredictable due to the complex interactions between vehicles. This challenge has driven significant interest in learning-based approaches for trajectory prediction. We present <bold>MMTraP:</b> <bold>M</b>ulti-Sensor and <bold>M</b>ulti-Agent <bold>Tra</b>jectory <bold>P</b>rediction in BEV. This method integrates camera, LiDAR, and radar data to create detailed Bird's-Eye-View representations of driving scenes. Our approach employs a hierarchical vector transformer architecture that first detects and classifies vehicle motion patterns before predicting future trajectories through spatiotemporal relationship modeling. This work specifically focuses on vehicle interactions and environmental constraints. Despite its significance, multi-agent trajectory prediction and moving object segmentation are still underexplored in the literature, especially in real-time applications. Our method leverages multisensor fusion to obtain precise BEV representations and predict vehicle trajectories. Our multi-sensor fusion approach achieves the highest vehicle Intersection over Union (IoU) of 63.23% and an overall mean IoU (mIoU) of 64.63%, demonstrating its effectiveness in utilizing all available sensor modalities. Additionally, we demonstrate vehicle segmentation and trajectory prediction capabilities across various lighting and weather conditions. The proposed approach has been rigorously evaluated using the nuScenes dataset. Results show that our method improves the accuracy of trajectory predictions and outperforms state-of-the-art techniques, particularly in challenging environments such as congested urban areas. For instance, in complex traffic scenarios, our approach achieves a relative improvement of 5% in trajectory prediction accuracy compared to baseline methods. This work advances vehicle-focused prediction systems by integrating multi-sensor BEV representation and interaction-aware transformers. Our approach shows promise in enhancing the reliability and accuracy of trajectory predictions for autonomous driving applications, potentially improving overall safety and efficiency in diverse driving environments.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1551-1567"},"PeriodicalIF":5.3,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11016806","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Roads Infrastructure Digital Twin: Advancing Situational Awareness Through Bandwidth-Aware 360° Video Streaming and Multi-View Clustering","authors":"Oussama El Marai;Sotirios Messinis;Nikolaos Doulamis;Tarik Taleb;Jukka Manner","doi":"10.1109/OJVT.2025.3572405","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3572405","url":null,"abstract":"Future-facing cities increasingly integrate smart and autonomous objects for their smooth functioning and operations, which ultimately benefit city dwellers and the ecosystem at large. In such highly complex and digital environments, the increased situational awareness is very important for the safety of road participants. In this paper, we propose a new bandwidth-aware framework that maximizes the situational awareness of a given region, using mobile digital boxes and <inline-formula><tex-math>$360^{circ }$</tex-math></inline-formula> cameras, mounted on connected vehicles, taking into account the constrained uplink capacity. The proposed framework leverages the multi-view spectral clustering approach and the K-Means++ algorithms to ensure efficient clustering of vehicles based on their GPS coordinates. The clustering step is crucial for larger spatial coverage and, thus, higher situational awareness. Vehicle selection and video quality attribution, under limited uplink constraints, are then performed per cluster to fairly cover the region. Extensive simulations and comparisons against state-of-the-art solutions have been conducted to evaluate the performance of the proposed framework, in terms of region coverage rate and normalized mutual information score, at both small- and large-scale deployments. The results obtained demonstrate the superiority of the proposed approach.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1348-1362"},"PeriodicalIF":5.3,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11016160","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Impact of Bistatic Target Reflectivity in ISAC-Enabled V2V Setup Across Diverse Geometrical Road Layouts","authors":"Aamir Ullah Khan;Saw James Mint;Syed Najaf Haider Shah;Christian Schneider;Joerg Robert","doi":"10.1109/OJVT.2025.3554365","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3554365","url":null,"abstract":"Integrated Sensing and Communication (ISAC) is an intriguing emerging research area that combines radar sensing and communication functionalities in a unified platform, capitalizing on shared aspects of signal processing, spectrum utilization, and system design. For sensing applications, the reflectivity of objects between Transmitter (TX) and Receiver (RX) is crucial. It is normally modeled as a uniform scatterer or a group of uniform scatterers in wireless channels. These models do not take into account the dependence of reflectivity on the aspect angles of incident and scattering waves, the composed material, and the geometry of the objects. Therefore, we model the reflectivity of target vehicles using their bistatic Radar Cross Section (RCS), as in radar sensing, within a Vehicle to Vehicle (V2V) setup under the Integrated Sensing and Communication (ISAC) framework. Moreover, we consider constant and variable bistatic Target Reflectivity (TR) integrated setups with two diverse traffic scenarios. These traffic scenarios are modeled to be realistic, with diverse geometrical road layouts, variable vehicle velocities, distinct vehicle positions, and the presence of Diffuse (DI) scattering components. Then, we inspect the impact of the bistatic TR on the behavior of the wireless channel and target detection capability. The variable TR integrated setup leads to a more accurate realization of the scenario, leading to outcomes that closely resemble real-world conditions. The results show the substantial impact of the geometrical setup on the distribution of TR, which emphasizes the need to integrate TR into ISAC-enabled V2V channel models.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"948-968"},"PeriodicalIF":5.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10938128","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model-Based Analysis of Transient Currents to Dimension a Vehicular Power System With Electronic Fuses Regarding Short Circuit Selectivity","authors":"Christoph Mayer;Martin Baumann;Luis Finkl;Leo T. Peters;Hans-Georg Herzog","doi":"10.1109/OJVT.2025.3573836","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3573836","url":null,"abstract":"A fail-operational vehicular power system requires the selective tripping of electronic fuses (eFuses) in case of a fault event, e.g. short circuit, impermissible wire temperature. As a result of a short circuit and the associated interruption of the fault current by an eFuse, transient currents within the vehicular power system commutate into neighboring paths and potentially cause an unintended tripping of other eFuses. In this paper, modeling of the vehicular power system and an analytical methodology using state-space systems are proposed to calculate the transient currents during a short circuit and switch-off process. Comparing the results of the new approach with data obtained from simulation and measurement revealed a sufficient accuracy to represent the current trajectories. Furthermore, the analytical methodology enables a significant runtime reduction compared to simulations. Using the methodology, a parameter study is done to examine the influencing parameters on the transient currents in a <inline-formula><tex-math>$12 ,mathrm{V}$</tex-math></inline-formula> or <inline-formula><tex-math>$48 ,mathrm{V}$</tex-math></inline-formula> vehicular power system, and to derive guidelines for accomplishing selectivity. Based on this knowledge, an exemplary dimensioning process of a vehicular power system with regard to selectivity is shown and the effect of the different parameters on the critical currents regarding selectivity is discussed. The fault isolation time and the current threshold of the tripping eFuse have shown to be crucial parameters to reduce the transient currents efficiently.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1399-1425"},"PeriodicalIF":5.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11015788","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved SOH Prediction of Lithium-Ion Batteries Based on Multi-Dimensional Feature Analysis and Transformer Framework","authors":"Tianfeng Long;Pengcheng Zhang;Xiaoqi Liu;Huaqing Shang;Meiling Yue;Xuesong Shen;Jianwen Meng","doi":"10.1109/OJVT.2025.3573705","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3573705","url":null,"abstract":"Data-driven state-of-health (SOH) prediction is increasingly critical for the effective management of lithium-ion batteries; however, challenges remain in practical applications. Traditional methods that rely on a single health indicator often fail to capture the complexity and multi-dimensional nature of battery performance changes. To address these limitations, this paper presents a novel Transformer-based approach for accurate SOH prediction. The correlation between various measured and computed features extracted from battery charge/discharge curves and their impact on battery performance degradation are investigated using Pearson correlation coefficients. Three strongly correlated features are identified as multiple input variables for the Transformer framework. The effectiveness of this Transformer-based SOH prediction method is demonstrated using public datasets, revealing that predictions for internal resistance and capacity closely align with actual values, with most RMSE values falling below 0.01. Furthermore, validation with an additional laboratory dataset confirms the accuracy and adaptability of our proposed approach, highlighting its potential to enhance SOH prediction in real-world applications.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1363-1379"},"PeriodicalIF":5.3,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11015565","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the Impact of Rain on Perception in Automated Vehicle Applications","authors":"Tim Brophy;Darragh Mullins;Ashkan Parsi;Jonathan Horgan;Enda Ward;Patrick Denny;Ciarán Eising;Brian Deegan;Martin Glavin;Edward Jones","doi":"10.1109/OJVT.2025.3553718","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3553718","url":null,"abstract":"The reliable performance of object detection perception algorithms in automated vehicles under adverse conditions such as rain is critical for maintaining vulnerable road user safety. Visible-spectrum cameras provide a rich source of information and are cost-effective compared with other sensors; however, their performance can degrade under adverse environmental conditions. Despite the general consensus that the object detection performance in computer vision is adversely affected by rain, there is a relative lack of research investigating this relationship in detail. This study investigates the performance of object detection under rain conditions, focusing on algorithm performance and low-level object characteristics. Using the publicly available BDD100 k dataset, this study examines object detection performance across multiple deep-learning object detection architectures, analyzing error types and image characteristics under rain and no rain conditions. In addition, statistical methods were used to compare image-level metrics to determine statistical significance. The results reveal that rain is not detrimental to object detection performance, and in some cases, better performance is observed. For some models, medium-sized objects experience improved detection and classification under rain conditions, while large objects experience a slight decline in performance. The error analysis shows an increase in localization errors and a decrease in classification errors. The object-level analysis revealed statistically significant changes in the contrast-to-noise ratio, entropy, mean pixel value, pixel variance, hue, saturation, and value, with hue and saturation experiencing the most significant changes. This study highlights the need for more detailed weather labeling in datasets to fully understand the nuances of the relationship between rain and object detection.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1018-1032"},"PeriodicalIF":5.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10937197","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143856345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensor Switching-Based Automatic Misalignment Detection and Correction System for Wireless Power Transfer","authors":"Ali Younis Al Dahhan;Shayok Mukhopadhyay;Mohamed S. Hassan;Ahmed H. Osman","doi":"10.1109/OJVT.2025.3572413","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3572413","url":null,"abstract":"Misalignment between the transmitting and receiving coils is an inevitable problem for electric vehicle (EV) wireless power transfer (WPT) systems. Regardless of the WPT system being static or dynamic, coil misalignment reduces the efficiency of the charging system. This paper, focuses on using a combination of computer vision and one of two different misalignment sensors to detect, and further correct lateral misalignment between the EV receiving (Rx) coil and the segmented transmitting (Tx) coils in a charging lane. The vision-based component uses a camera for lane detection and is primarily responsible for detecting larger deviations and making coarse compensations by estimating the lateral shift of the EV, relative to the center of the charging lane. The sensor-based approach relies on Hall effect sensors or detection coils to detect the misalignment in a smaller range, and perform finer corrections. A one-dimensional (1D) actuator moves the receiving coil to correct the coil misalignment, independent of vehicle movements. The vision-based approach showed a wide detection range for misalignment spanning [<inline-formula><tex-math>$-$</tex-math></inline-formula>15,15] cm, with a correction accuracy of <inline-formula><tex-math>$approx pm$</tex-math></inline-formula>2 cm. This is juxtaposed with the sensor-based approach which operates on a misalignment range of [<inline-formula><tex-math>$-$</tex-math></inline-formula>3,3] cm, but outperforms the vision-based approach with a correction accuracy of less than <inline-formula><tex-math>$pm$</tex-math></inline-formula>1 mm. The proposed sensor switching-based approach combines the advantages of the above individual techniques. An experimental setup is developed and tests are performed to evaluate the proposed approach while transferring 108 W of power wirelessly.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1380-1398"},"PeriodicalIF":5.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11008810","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aerial-Terrestrial Heterogeneous Networks for Urban Air Mobility: A Performance Analysis","authors":"Abdullah Abu Zaid;Baha Eddine Youcef Belmekki;Mohamed-Slim Alouini","doi":"10.1109/OJVT.2025.3551209","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3551209","url":null,"abstract":"Urban air mobility (UAM) is increasingly capturing the attention of researchers and industry experts, as it holds the promise of providing faster and more economical solutions for urban commuting. Ensuring reliable communication for UAM aircraft is of paramount importance in maintaining operational safety. To that end, we use stochastic geometry tools to analyze the joint uplink-downlink coverage probability of an integrated aerial-terrestrial heterogeneous network (HetNet) for UAM aircraft, specifically electric vertical takeoff and landing (eVTOL) vehicles. We assume eVTOLs travel on predefined air corridors which are modeled as a Poisson line process (PLP). Furthermore, we model the spatial distribution of eVTOLs as a Matern hardcore process (MHCP) with a designated safety distance. We model the aerial base stations (ABSs) as a two-dimensional (2D) binomial point process (BPP), and the terrestrial base stations (TBSs) as a 2D Poisson point process (PPP). We use a suitable air-to-ground channel model to include line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions. In the paper, we derive distance distributions to the closest ABS, LOS TBS, and NLOS TBS to a typical eVTOL, then we provide the association probability of each BS. Furthermore, we characterize the uplink interference and derive Laplace transforms for the PLP-MHCP distributed eVTOLs. Finally, we derive the coverage probability of the overall HetNet and carry out Monte Carlo simulations to validate our expressions.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"912-926"},"PeriodicalIF":5.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10925893","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Open-Source-Based Evaluation Platform for Highly Spectral-Efficient 5G With Simplified UTW-OFDM","authors":"Kazuki Takeda;Keiichi Mizutani;Hiroshi Harada","doi":"10.1109/OJVT.2025.3569518","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3569518","url":null,"abstract":"Fifth-generation mobile communication (5G) systems are increasingly being deployed in both commercial and private wireless networks to meet the growing demand for high-speed, reliable connectivity. While 5G systems adopt orthogonal frequency-division multiplexing (OFDM) for its high data rates and spectral efficiency, OFDM is known to generate large out-of-band emissions (OOBE), which must be suppressed to maximize spectrum usage. In this study, to tackle this issue, we propose and develop an experimental 5G full-stack evaluation platform that implements a waveform-shaping function for OFDM signals. The platform utilizes software-defined radio and open-source 5G software compliant with third-generation Partnership Project standards. We implement a simplified universal time-domain windowed OFDM as an application of the waveform shaping. This is a waveform shaping technique that can strongly suppress OOBE by applying a long time-domain window to the conventional cyclic prefix OFDM symbol. The transmission performance of the proposed platform was evaluated using a complete 5G system, which includes a 5G base station, user equipment, and a 5G core network. The effectiveness of the proposed platform is verified through link-level computer simulations. The results demonstrate that the block error rate characteristics exhibited a signal-to-noise power ratio difference of less than 1 dB between the platform and simulations and achieved an OOBE suppression of up to 24 dB at a bandwidth of 40 MHz. Furthermore, connectivity with a commercial 5G device demonstrated the feasibility of achieving OOBE suppression of 22 dB at a bandwidth of 100 MHz with a tolerable decrease of 18% in user throughput.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1426-1437"},"PeriodicalIF":5.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11002599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"URLLC Over Slow Fading Channels: K-Repetition Versus Multi-Connectivity","authors":"Qingjiao Song;Fu-Chun Zheng;Jingjing Luo","doi":"10.1109/OJVT.2025.3569187","DOIUrl":"https://doi.org/10.1109/OJVT.2025.3569187","url":null,"abstract":"In this work, we analyze the performance of the uplink ultra-reliable and low-latency communications (URLLC) for the low-mobility users (UEs) in a factory environment. The <inline-formula><tex-math>$K$</tex-math></inline-formula>-repetition scheme is a promising approach for improving URLLC reliability, but most studies so far have been carried out assuming fast fading. A UE with low mobility typically experiences a time-correlated slow fading channel. We therefore consider the effects of time correlation in analyzing the performance of a <inline-formula><tex-math>$K$</tex-math></inline-formula>-repetition scheme. On the other hand, multi-connectivity (MC) schemes can overcome such effects and improve reliability through space diversity. We then apply differential modulation to both schemes to support URLLC services, and compare their performance. The simulation results show that such slow fading channels severely decreases the time diversity of a <inline-formula><tex-math>$K$</tex-math></inline-formula>-repetition scheme, and the MC scheme outperforms the <inline-formula><tex-math>$K$</tex-math></inline-formula>-repetition scheme in terms of reliability and transmission latency.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"6 ","pages":"1280-1286"},"PeriodicalIF":5.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10999067","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}