IEEE Sensors Journal最新文献_第5页

Performance Evaluation of Embroidered Honeycomb Resistive Textile Strain Sensors 绣花蜂窝电阻式纺织品应变传感器的性能评价

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3573636

J. Guillermo Colli Alfaro;Ana Luisa Trejos

{"title":"Performance Evaluation of Embroidered Honeycomb Resistive Textile Strain Sensors","authors":"J. Guillermo Colli Alfaro;Ana Luisa Trejos","doi":"10.1109/JSEN.2025.3573636","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3573636","url":null,"abstract":"The rise of soft wearable sensors has opened the door for less obtrusive sensing during upper limb rehabilitation. Many studies have proposed different methods of fabrication for these sensors, but the simplest ones include those made using knitting, stitching, or embroidering to create resistive strain sensors. However, the reliability of these sensors is influenced by the amount of contact points of the conductive thread used at any given time. These contact points can suffer from deformations due to forces applied during each stretching cycle, which can affect the sensor response and produce erroneous measurements. These issues can be avoided by creating embroidered sensors with patterns that do not affect the contact points of the stitches. Still, forces applied directly to the conductive thread can cause irreparable damage to the sensor. Therefore, in this study, a novel embroidered strain sensor is created using a honeycomb pattern. This pattern has two main purposes: a distribution of the axial forces across the walls of the pattern to protect the conductive thread and the addition of stretchiness to the embroidered sensor. Sensors created using this pattern were embroidered onto an elastic band and then attached to a strain divider system to increase the stretchability of the sensor further. After 50 stretching cycles, sensors showed good linearity, an average gauge factor (GF) of 0.24, an average hysteresis of 36.85%, and a 55.56% working range. These results show that the proposed sensor is robust to thread damages, thus making it a viable alternative for strain sensing applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"24396-24406"},"PeriodicalIF":4.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural Network-Based Prediction of Response Signal of Metal Oxide Semiconductor Gas Sensors 基于神经网络的金属氧化物半导体气体传感器响应信号预测

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3573330

Yixuan Hou;Jialiang He;Hengfu Huang;Guangheng He;Yingbang Yao

{"title":"Neural Network-Based Prediction of Response Signal of Metal Oxide Semiconductor Gas Sensors","authors":"Yixuan Hou;Jialiang He;Hengfu Huang;Guangheng He;Yingbang Yao","doi":"10.1109/JSEN.2025.3573330","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3573330","url":null,"abstract":"This study presents a novel method for predicting the response signal and recovery time of metal oxide semiconductor (MOS) gas sensors at different gas concentrations just based upon their initial power-on behaviors in air. First, we measured the resistance changing behavior of the MOS gas sensors during the power-on period in pure air (power-on data). Second, their response behaviors, including response signal as well as recovery time, in the target hydrogen gas of varying concentrations (from 20 to 1000 ppm) were collected (signal data). The initial power-on data and the signal data were found to be closely related based on a neural network model, therefore one can use just the power-on data to predict the gas sensor’s signal in the target gas at different concentrations. Thus, the tedious calibration work for these MOS gas sensors in real target gas can be dispensable. Two types of neural networks were used for the model: Artificial Neural Network (ANN) and Convolutional Neural Network (CNN). Experimental results indicate that the CNN outperforms the ANN in both response signal and recovery time predictions, with an average voltage prediction error of 0.166 V and an average recovery time prediction error of 4.746 s. Instead of using measurements in actual gases, this study offers a practical way to obtain the signal data (i.e., response signal and recovery time) of MOS gas sensors.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 13","pages":"25872-25878"},"PeriodicalIF":4.3,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Sensors Council IEEE传感器委员会

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-06-02 DOI: 10.1109/JSEN.2025.3571375

引用次数: 0

Pressure Sensor Based on Melamine Frame Graphene Aerogel for Pulse Recording and Identification in Traditional Chinese Medicine 基于三聚氰胺框架石墨烯气凝胶的中医脉搏记录与识别压力传感器

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-04-30 DOI: 10.1109/JSEN.2025.3561953

Bo Li;Keshuai Yang;Yizhao Zhou;Chengbing Fang;Chengqi Zhang;Xian Song;Yaoran Sun;Pengyu Wang;Tong Li;Yuxin Peng;Fang Han

{"title":"Pressure Sensor Based on Melamine Frame Graphene Aerogel for Pulse Recording and Identification in Traditional Chinese Medicine","authors":"Bo Li;Keshuai Yang;Yizhao Zhou;Chengbing Fang;Chengqi Zhang;Xian Song;Yaoran Sun;Pengyu Wang;Tong Li;Yuxin Peng;Fang Han","doi":"10.1109/JSEN.2025.3561953","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3561953","url":null,"abstract":"In this article, we developed a graphene-melamine graphene aerogel sensor to integrate the traditional Chinese medicine (TCM) pulse diagnosis with modern information technologies. Owing to the reduced graphene oxide (GO) network embedded in the melamine frame, the sensor demonstrates a high gauge factor (GF) of 596.2 with high repeatability, enhancing the accuracy of pulse signal detection. Moreover, the porous structure of the sensing material augments its piezoresistive properties, exhibiting a “fast-then-slow” pattern in resistance changes. The reasonable pulse signal is collected by experienced TCM practitioners accurately locating specific pulse points—Cun, Guan, and Chi—and applying the optimal pressure with the proposed sensor adhered on their fingertip. By employing continuous wavelet transform (CWT) and ResNet-50 for advanced signal processing and classification, the study attains a classification accuracy of 90.1% in differentiating pulse patterns between pregnant and nonpregnant women. This high level of accuracy demonstrates the potential of integrating this technology to standardize and validate TCM diagnostic techniques, potentially broadening the acceptance of TCM in global health systems.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"21185-21193"},"PeriodicalIF":4.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of By-Products From Metal Welding on the Temperature Measurement of MEMS-Based Thermoelectric Infrared Sensors 金属焊接副产物对mems热电红外传感器测温的影响

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-04-30 DOI: 10.1109/JSEN.2025.3564062

Changwen Shi;Yu Gao;Haozhu Chen;Jiagen Cheng;Weihuang Yang;Chaoran Liu;Linxi Dong

{"title":"Impact of By-Products From Metal Welding on the Temperature Measurement of MEMS-Based Thermoelectric Infrared Sensors","authors":"Changwen Shi;Yu Gao;Haozhu Chen;Jiagen Cheng;Weihuang Yang;Chaoran Liu;Linxi Dong","doi":"10.1109/JSEN.2025.3564062","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3564062","url":null,"abstract":"In metal welding processes, micro-electromechanical system (MEMS)-based thermoelectric infrared sensors are widely employed for real-time temperature monitoring to ensure weld quality. However, welding by-products, particularly fumes and molten metal spatter particles, introduce significant measurement errors in these sensors. This study investigates the mechanistic interaction between welding by-products and MEMS sensor performance, followed by systematic experimental analysis under varying operating conditions (object temperatures: <inline-formula> <tex-math>$30~^{circ }$ </tex-math></inline-formula>C–<inline-formula> <tex-math>$110~^{circ }$ </tex-math></inline-formula>C; measurement distances: 10–40 cm). A novel characterization method is proposed using binary classification of spatter-induced filter screen damage to quantify particle impact severity. Furthermore, a mathematical model is developed to correlate measurement error with temperature and distance variables, enabling real-time error compensation for by-product interference. Experimental validation demonstrates that the proposed compensation compensation algorithm reduces temperature measurement errors by up to 80.9% in high-spatter welding scenarios, demonstrating its practical utility in enhancing sensor reliability for industrial applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"22756-22764"},"PeriodicalIF":4.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Lightweight and Explainable Hybrid Deep Learning Model for Wearable Sensor-Based Human Activity Recognition 基于可穿戴传感器的人体活动识别的轻量级可解释混合深度学习模型

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-04-30 DOI: 10.1109/JSEN.2025.3564045

Pratibha Tokas;Vijay Bhaskar Semwal;Sweta Jain

{"title":"A Lightweight and Explainable Hybrid Deep Learning Model for Wearable Sensor-Based Human Activity Recognition","authors":"Pratibha Tokas;Vijay Bhaskar Semwal;Sweta Jain","doi":"10.1109/JSEN.2025.3564045","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3564045","url":null,"abstract":"Human activity recognition (HAR) is critical for rehabilitation and clinical monitoring, but robust recognition using wearable sensors (e.g., sEMG or IMU) remains challenging due to signal noise and variability. We propose X-LiteHAR, a lightweight, explainable hybrid deep learning framework for real-time HAR, combining adaptive EEMD for noise-robust signal enhancement and a multihead CNN-LSTM for spatio-temporal feature learning. The optimized framework demonstrates efficient edge deployment through structured pruning and quantization, achieving 70% model size reduction while maintaining competitive performance, with on-device validation on an Android OnePlus 6T smartphone showing 9 ms inference latency. The model was trained and evaluated independently on two distinct datasets: 1) the UCI sEMG dataset (muscle activity signals) and 2) the IMU-only MHealth dataset (motion signals), demonstrating the architecture’s adaptability to different sensor modalities. On the UCI dataset, X-LiteHAR achieved 99.0% accuracy (healthy subjects) and 98.7% (pathological), while on MHealth (IMU-only), it reached 99.2% accuracy. Leveraging explainable AI (XAI), we interpret muscle activation patterns for personalized rehabilitation insights. By unifying signal processing, efficient deep learning, and interpretability, X-LiteHAR advances real-time HAR for clinical and wearable applications.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"22618-22628"},"PeriodicalIF":4.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Laser Interferometer With Harmonic Contrast Demodulation for Nanometer Distance Measurement 用于纳米距离测量的谐波对比解调激光干涉仪

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-04-30 DOI: 10.1109/JSEN.2025.3564166

Jialin Jiang;Wentao Liu;Yang Xia;Zhaochun Deng;Xiaohua Lei;Zinan Wang;Weimin Chen

{"title":"Laser Interferometer With Harmonic Contrast Demodulation for Nanometer Distance Measurement","authors":"Jialin Jiang;Wentao Liu;Yang Xia;Zhaochun Deng;Xiaohua Lei;Zinan Wang;Weimin Chen","doi":"10.1109/JSEN.2025.3564166","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3564166","url":null,"abstract":"High-precision 3-D topography is essential for surface profile detection in chips, precision optical lenses, and other components. A nanometer-scale laser interferometric distance sensor serves as a key component in such applications. In this kind of sensor, displacement of the target or the measurement position change induces phase shifts in the laser interference signal. Piezoelectric ceramic transducers (PZTs) are commonly used as modulators, but their lifespan, linearity, and frequency response—key factors determining the sensor’s performance—are closely tied to the modulation depth. This article introduces a harmonic contrast (HC) method to demodulate phase changes with high speed, minimal modulation depth, and single-channel detection. For scenarios involving nonstandard phase modulation functions, such as those influenced by loaded PZTs, a novel calibration approach is proposed. This method enables precise calibration without relying on expensive nanometer-precision multistep mirrors, thereby reducing the dependence on stringent modulation depth and linearity requirements. As a result, the same modulator can achieve an extended lifespan and higher sensing frequencies, making it more suitable for industrial applications. Experimental results demonstrate a resolution of 0.7 nm for step displacement signals, showcasing the good performance of the proposed scheme.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"21617-21623"},"PeriodicalIF":4.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Age of Information in IoT Devices With Integrated Heterogeneous Sensors Under Slotted ALOHA 开槽ALOHA下集成异构传感器的物联网设备的信息时代

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-04-30 DOI: 10.1109/JSEN.2025.3563452

Show-Shiow Tzeng;Ying-Jen Lin;Sheng-Wei Wang

{"title":"Age of Information in IoT Devices With Integrated Heterogeneous Sensors Under Slotted ALOHA","authors":"Show-Shiow Tzeng;Ying-Jen Lin;Sheng-Wei Wang","doi":"10.1109/JSEN.2025.3563452","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3563452","url":null,"abstract":"Sensors deployed in environments transmit status update data using the slotted ALOHA for radio channel access. The age-of-information (AoI) metric, representing the time elapsed since the last data received by a destination (e.g., base station) was generated at a sender, quantifies data freshness, which is crucial in diverse Internet of Things (IoT). Recent advancements have integrated heterogeneous sensors into IoT devices, with each sensor potentially sensing and generating status updates with different probabilities, impacting both AoI and energy consumption levels. This creates a complex challenge in balancing tradeoffs among various sensors’ sensing probabilities, AoI constraints, and energy efficiency. Yet, the AoI impact of IoT devices equipped with heterogeneous sensors using slotted ALOHA remains largely unexplored. This study investigates the AoI performance of IoT devices equipped with heterogeneous sensors within a slotted ALOHA framework. We present three data generation and transmission schemes: multisensor device with independent sensing (MSDIS), multisensor device with simultaneous sensing (MSDSS), and multisensor device with probabilistic simultaneous sensing (MSDPSS). We analyze and prove that MSDSS and MSDPSS achieve a lower average AoI (AAoI) compared with other schemes. Furthermore, we show that AAoI solutions for systems with at least five sensors per type cannot be expressed in radical form. Hence, we further design a low-time-complexity procedure for MSDPSS to determine optimal data sensing and generation probabilities that meet diverse AAoI requirements of various sensors while minimizing energy consumption. Our analysis, validated by simulations, indicates that MSDPSS demonstrates superior energy efficiency while meeting the diverse AAoI requirements of various sensors.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"20842-20853"},"PeriodicalIF":4.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Microwave Sensor System for the Unattended Control of Corrosion in Urban Metallic Infrastructures 城市金属基础设施腐蚀无人值守控制的微波传感器系统

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-04-30 DOI: 10.1109/JSEN.2025.3564003

Paris Vélez;Ferran Paredes;Pau Casacuberta;Xavier Canalias;Lijuan Su;Ferran Martín

{"title":"A Microwave Sensor System for the Unattended Control of Corrosion in Urban Metallic Infrastructures","authors":"Paris Vélez;Ferran Paredes;Pau Casacuberta;Xavier Canalias;Lijuan Su;Ferran Martín","doi":"10.1109/JSEN.2025.3564003","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3564003","url":null,"abstract":"This article presents a microwave sensor system (including the electromagnetic module and the associated electronics for signal generation and processing) useful for unattendedly monitoring the corrosion level in urban metallic infrastructures, particularly, streetlights and traffic lights. The electromagnetic module consists of a microstrip line loaded with a slot resonator, the sensitive element, transversely etched in the ground plane. To make the electromagnetic module conformal, a necessity for the intended application, the slot-loaded line has been implemented in a narrow (and hence flexible) low-loss microwave substrate. To adapt it to the circular shape of the metallic infrastructure, streetlights with different curvature shapes in the reported example cases, a conformal 3-D-printed piece of polylactic acid (PLA) has been fabricated. By sandwiching the electromagnetic module between such PLA piece and the surface of the streetlight subjected to corrosion control, perfect contact of it with the sensing element is achieved. The output variable of the sensor is the magnitude of the transmission coefficient of the slot-loaded line at a specific frequency (correlated with the level of corrosion of the surface) converted to a voltage by means of an envelope detector. The functionality of the proposed sensor is validated by means of a complete system, including the associated electronics.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 11","pages":"20455-20465"},"PeriodicalIF":4.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Low Power Digitizer Array With Adaptive Split Current Source for 3-D-Stacked 100 MP High Dynamic Range Imager 三维堆叠100mp高动态范围成像仪的低功耗自适应分流电流源数字化仪阵列

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-04-30 DOI: 10.1109/JSEN.2025.3563964

Youngwoo Lee;Seyeon Kim;Jinha Kim;Suhwan Kim;Jaehoon Jun

{"title":"A Low Power Digitizer Array With Adaptive Split Current Source for 3-D-Stacked 100 MP High Dynamic Range Imager","authors":"Youngwoo Lee;Seyeon Kim;Jinha Kim;Suhwan Kim;Jaehoon Jun","doi":"10.1109/JSEN.2025.3563964","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3563964","url":null,"abstract":"The increasing demand for high dynamic range (HDR), power efficiency, and high resolution has driven the adoption of single-exposure dual conversion gain (DCG) techniques. This article proposes an adaptive split current source to optimize power consumption in single-exposure DCG readouts. By splitting the comparator bias current, the power consumption of the digitizer array can be adaptively optimized based on the conversion gain (CG) of pixel in single-exposure DCG operation. Additional power-saving features including decision-feedback and auto-zeroing (AZ) power-down techniques are also implemented to further improve power efficiency. The proposed digitizer chip was fabricated in a 28 nm CMOS process, achieving a power consumption reduction of 44.5% in comparator. The integral nonlinearity (INL) was measured as +2.67/–2.34 LSB in high CG (HCG) and +2.95/–1.92 LSB in low CG (LCG). The input-referred random noise (RN) values of 2.17 LSB (HCG) and 2.41 LSB (LCG) were measured at an analog gain of 16, corresponding to <inline-formula> <tex-math>$93~mu ! {V}_{text {rms}}$ </tex-math></inline-formula> and <inline-formula> <tex-math>$103~mu ! {V}_{text {rms}}$ </tex-math></inline-formula>, respectively. The prototype chip shows a highly competitive figure of merit (FoM) of 2.41 mV<inline-formula> <tex-math>$cdot $ </tex-math></inline-formula>pJ/pixel/frame.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 12","pages":"22609-22617"},"PeriodicalIF":4.3,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144299233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0