IEEE Sensors Journal最新文献_第8页

Sagnac Loop Twisted Pair Microfiber Sensors Enables Simultaneous Measurement of Temperature and Pressure

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3526651

Hongwei Liang;Jiaqi Fan;Jiali Du;Yu Sun;Lingling Kan;Penghui Dai;Shaoqing Wang

{"title":"Sagnac Loop Twisted Pair Microfiber Sensors Enables Simultaneous Measurement of Temperature and Pressure","authors":"Hongwei Liang;Jiaqi Fan;Jiali Du;Yu Sun;Lingling Kan;Penghui Dai;Shaoqing Wang","doi":"10.1109/JSEN.2025.3526651","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526651","url":null,"abstract":"This study presents a Sagnac loop-based twisted pair microfiber sensor for simultaneous temperature and pressure monitoring. The meticulously engineered microfiber is encapsulated within a polydimethylsiloxane (PDMS) film, enhancing the sensor’s sensitivity and structural stability. This improvement leverages the PDMS high thermo-optic coefficient and low Young’s modulus, along with the strong evanescent field transmission characteristics in the twisted microfiber coupling region and the interference period change in response to external environmental variations. Numerical simulation computations and theoretical modeling further analyze the response performance of the sensor. The experimental results demonstrate that the sensor has a temperature sensitivity of <inline-formula> <tex-math>$2.90~ text {nm/}^{circ }text {C}$ </tex-math></inline-formula> and a pressure sensitivity of 54.43 pm/Pa. The maximum temperature resolution is <inline-formula> <tex-math>$0.0013~^{circ }text {C}$ </tex-math></inline-formula> and the maximum pressure resolution is 0.0730 Pa. In addition, the temperature and pressure sensing can be simultaneously demodulated by operating on the cross-sensitivity matrix. The sensor boasts high sensitivity, excellent linearity, a compact structure, and straightforward manufacturing, offering broad application prospects in biochemistry and industrial production.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6218-6225"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430500","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

Terahertz Hybrid Detection of Chiral Enantiomers With Intrinsic Low Absorption Enabled by Metasurface

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3526274

Xueer Chen;Longfang Ye;Daquan Yu

{"title":"Terahertz Hybrid Detection of Chiral Enantiomers With Intrinsic Low Absorption Enabled by Metasurface","authors":"Xueer Chen;Longfang Ye;Daquan Yu","doi":"10.1109/JSEN.2025.3526274","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526274","url":null,"abstract":"The recognition of chiral enantiomers has great significance in biomedical fields such as drug detection, as they exhibit distinctive absorption characteristics in the terahertz (THz) region. However, there are certain biomolecules without prominent spectral features within specific frequency bands, making direct identification through THz time-domain spectroscopy challenging. Therefore, metasurface is employed to stimulate local field enhancement and increase the interaction between analyte and waves. Current studies on meta-sensors typically focus on detecting various types of biomolecules or different concentrations of the same biomolecules. To realize the identification of enantiomers, size-multiplexed broadband sensing technology with various scaling factors of unit cells is employed to achieve a broadband-enhanced sensor for analyzing spectral distinctions of enantiomers. It amplifies subtle absorption differences in the longitudinal direction, enabling the identification of chiral enantiomers even within weak absorption bands. In addition, we converted it from an achiral metasurface to an extrinsic chiral metasurface by incident angle manipulation with a maximum modulation rate of 52.5%, to excite extrinsic chiroptical responses. Here, besides the transmission rate of linearly polarized waves, circular dichroism (CD) spectra of circularly polarized waves are further extracted as sensing indicators additional with refractive index sensitivity of 39.4 GHz/RIU and <inline-formula> <tex-math>$Delta $ </tex-math></inline-formula>Amp of 29.0%, for enriching the evaluation standards. It also provides opportunities for dynamic modulation of the circularly polarized wave. This work is based on a traditional refractive index sensing mechanism, employing size-multiplexed broadband fingerprinting sensing technology and sensitive extrinsic chiral excitation, to realize multitechnical hybrid detection for enantiomers with intrinsic low absorption.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6301-6308"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430586","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

Effect of Test Mass Position on the UV Discharge Rate of Space Inertial Sensor

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3525799

Bingxue Chen;Qingqing Li;Wei Hong;Honggang Li;Liangyu Chu;Fangchao Yang;Yanzheng Bai;Zebing Zhou

引用次数: 0

Cooperative PPG/ECG Wearable System for Atrial Fibrillation Diagnosis

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3526245

Yongbin Lee;Soyoung Lee;Sang Kyu Kim;Dong Keon Yon;Yunyoung Nam;Jinseok Lee

{"title":"Cooperative PPG/ECG Wearable System for Atrial Fibrillation Diagnosis","authors":"Yongbin Lee;Soyoung Lee;Sang Kyu Kim;Dong Keon Yon;Yunyoung Nam;Jinseok Lee","doi":"10.1109/JSEN.2025.3526245","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526245","url":null,"abstract":"Recent advancements in wearable technology, particularly wrist-type electrocardiography (ECG) devices, offer a promising alternative for atrial fibrillation (AF). These devices allow for continuous monitoring but typically require the user to touch an electrode to capture accurate readings. This study introduces a novel photoplethysmography (PPG)/ECG cooperative wearable device that leverages PPG for continuous heart rate (HR) monitoring and ECG for precise AF detection. Beyond sensor development, this study emphasizes the processing of sensor data, with the system utilizing a robust motion artifact (MA) cancellation algorithm and an AF-finite-state machine (AF-FSM) framework to enhance the accuracy of PPG signal analysis. The system employs PPG for preliminary AF screening, and, upon detecting irregularities, it prompts ECG measurements with data transmitted to medical professionals for confirmation. In this study, to enhance the accuracy of AF confirmation while reducing false alarms and increasing true positives, we mainly propose a robust MA cancellation algorithm combined with an AF-FSM framework. Evaluation using the BAMI-II and ISPC datasets shows that our method achieves a mean absolute error (MAE) of 1.31 and 1.16 beats per minute (bpm), respectively, for HR estimation and an AF detection sensitivity of 0.9927, specificity of 0.9768, and accuracy of 0.9847 on a clinical dataset. On the MIMIC PERform AF dataset, our method achieved an AF detection sensitivity of 0.9536, specificity of 0.9500, and accuracy of 0.9517. A pilot study further validates the system’s practical application in a clinical setting, demonstrating its potential for long-term, user-friendly cardiac monitoring.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7331-7344"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446288","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 Deep Learning Hybrid Model for Identifying Gait Patterns and Transition States of Lower Limb Exoskeleton Wearer

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3526646

Lifei Chen;Qiyin Lin;Haiyan Cheng;Bin Fang;Jinhua Zhang;Jun Hong

{"title":"A Deep Learning Hybrid Model for Identifying Gait Patterns and Transition States of Lower Limb Exoskeleton Wearer","authors":"Lifei Chen;Qiyin Lin;Haiyan Cheng;Bin Fang;Jinhua Zhang;Jun Hong","doi":"10.1109/JSEN.2025.3526646","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526646","url":null,"abstract":"Addressing the synchronization issue between lower limb exoskeletons and the limbs of wearer, this article proposes a deep learning hybrid model for identifying gait patterns and transition states using only lower limb angle data. The proposed hybrid model integrates 1-D convolutional networks with BiGRU. The model accurately predicts subsequent gait patterns by identifying transition states, thus achieving smoother transitions during movement and enhancing wearer comfort. Compared to other models, this article introduces a novel evaluation index named HIAM, which demonstrates the comprehensive performance advantage of the proposed model. The model classifies five gait patterns and eight transition states using only the angle data from the thighs and shanks of wearer. The classification accuracy and <inline-formula> <tex-math>${F}1$ </tex-math></inline-formula>-score are 99.05% on the validation set, achieving 99.11% accuracy and <inline-formula> <tex-math>${F}1$ </tex-math></inline-formula>-score on the test set. The HIAM reaches 99.29 on the validation set and 99.36 on the test set.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7698-7707"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438513","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

Time-Series Forecasting in Industrial Environments: A Performance Study and a Novel Late Fusion Framework

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3526362

Dimitrios Oikonomou;Lampros Leontaris;Nikolaos Dimitriou;Dimitrios Tzovaras

{"title":"Time-Series Forecasting in Industrial Environments: A Performance Study and a Novel Late Fusion Framework","authors":"Dimitrios Oikonomou;Lampros Leontaris;Nikolaos Dimitriou;Dimitrios Tzovaras","doi":"10.1109/JSEN.2025.3526362","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526362","url":null,"abstract":"In manufacturing environments, monitoring of the overall equipment effectiveness (OEE) via soft sensors plays a pivotal role in enhancing productivity and efficiently planning maintenance schedules. However, the accurate forecasting of the OEE presents considerable challenges due to the complexity of manufacturing data and equipment interdependence across stages. To this end, advanced time-series forecasting methods based on deep learning (DL) pose a promising avenue in tackling these challenges. In this study, we present a taxonomy of DL forecasting architectures, consisting of multilayer perceptrons (MLPs), recurrent models, Transformer-based models, and temporal convolutional networks (TCNs), and we perform a comparative study of the state-of-the-art approaches. Additionally, a lightweight late fusion linear architecture is proposed, incorporating patching, moving average (MA) decomposition, and Fourier Transform decomposition (PDFLinear), and an exponentially weighted averaging (EWA) module responsible for late fusion. Representative state-of-the-art models of each taxonomy class are benchmarked using a real-world antenna assembly line use case and compared against our proposed method. The experimental results show that our proposed model consistently matches or outperforms the state-of-the-art models in terms of forecasting efficacy for all forecast horizons, while requiring a fraction of the computational resources.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7681-7697"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10839285","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SDCBM: A Secure Data Collection Model With Blockchain and Machine Learning Integration for Wireless Sensor Networks

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3526807

P. V. Pravija Raj;Ahmed M. Khedr

{"title":"SDCBM: A Secure Data Collection Model With Blockchain and Machine Learning Integration for Wireless Sensor Networks","authors":"P. V. Pravija Raj;Ahmed M. Khedr","doi":"10.1109/JSEN.2025.3526807","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526807","url":null,"abstract":"Wireless sensor networks (WSNs) often struggle with managing extensive data volumes, given their resource-constrained nature. Deployed in unattended areas, they face significant security risks and attacks. This study introduces the secure data collection model with blockchain and machine learning integration for WSNs (SDCBM), designed to identify intrusions and ensure secure data collection and storage for WSN applications. SDCBM employs an extreme learning machine (ELM) model, a fast single-layer feedforward neural network (NN), and integrates techniques for balancing the data distribution and selecting relevant features to enhance real-time detection of malicious attacks. Data is preprocessed and balanced utilizing the synthetic minority oversampling technique (SMOTE) and Tomek-Links combination method. To enhance the feature selection process, the Harris Hawk optimization (HHO)-based method is proposed. The blockchain module manages network node registration, authentication, node revocation, and secure storage of data hashes and node credentials. Simulation results demonstrate the efficacy of the proposed SDCBM method in detecting malicious nodes and enhancing secure data collection, thereby strengthening the security of WSNs.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"7457-7466"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446284","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

CVD-Grown MoS₂ Monolayer-Based Ultrasensitive Hg²+ Ion Sensing in Water

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3526719

Sumit Chaudhary;Chandrabhan Patel;Brahmadutta Mahapatra;Mayank Dubey;Vikash Kumar Verma;Pawan Kumar;Rajour Tanyi Ako;Sharath Sriram;Shaibal Mukherjee

{"title":"CVD-Grown MoS₂ Monolayer-Based Ultrasensitive Hg²+ Ion Sensing in Water","authors":"Sumit Chaudhary;Chandrabhan Patel;Brahmadutta Mahapatra;Mayank Dubey;Vikash Kumar Verma;Pawan Kumar;Rajour Tanyi Ako;Sharath Sriram;Shaibal Mukherjee","doi":"10.1109/JSEN.2025.3526719","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526719","url":null,"abstract":"Mercury (Hg) is widely acknowledged as one of the most hazardous heavy metals, even in trace amounts. Its presence poses the risks of both chronic and acute poisoning, leading to serious health issues, including cancer, nerve damage, acrodynia, and movement disorders, which can ultimately result in fatalities. Current mercury sensing devices have several disadvantages, including sluggish response times, high cost, and limited portability. In this study, we present an interdigitated electrode-based sensor with molybdenum disulfide (MoS2) as the sensing layer to detect trace amounts of toxic Hg<inline-formula> <tex-math>$^{{2}+}$ </tex-math></inline-formula> ions. The MoS2 layer has been synthesized using a chemical vapor deposition (CVD) system and transferred to the interdigitated device through an energy-assisted wet transfer method. Comprehensive characterizations have confirmed the successful synthesis and transfer onto the IDE device. The fabricated sensor exhibits remarkable performance with excellent selectivity toward Hg<inline-formula> <tex-math>$^{{2}+}$ </tex-math></inline-formula> ions, an impressive limit of detection of 27.9 part per trillion (ppt), a remarkable sensitivity of <inline-formula> <tex-math>$957~mu $ </tex-math></inline-formula> A/ppb, and a quick response time of less than 4 s.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"8000-8007"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553420","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

LiDAR Denoising Methods in Adverse Environments: A Review

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3526175

Ji-Il Park;SeungHyeon Jo;Hyung-Tae Seo;Jihyuk Park

{"title":"LiDAR Denoising Methods in Adverse Environments: A Review","authors":"Ji-Il Park;SeungHyeon Jo;Hyung-Tae Seo;Jihyuk Park","doi":"10.1109/JSEN.2025.3526175","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526175","url":null,"abstract":"Although light detection and ranging (LiDAR) is a sensor type for autonomous vehicles, it is recognized as an essential tool in various fields, such as drones, unmanned surface vehicles (USVs), unmanned ground vehicles (UGVs), and surveillance facilities. This is because LiDAR has advantages including a high resolution, 360° sensing capabilities, and consistent performance during the day and at night. However, LiDAR has the fatal disadvantage of performing poorly in snow, rain, and fog. Therefore, studies are attempting to remove noise points caused by snow, rain, and fog to ensure that LiDAR performs well even under extreme weather conditions. These studies began in approximately 2020, coinciding with accelerated research on autonomous driving, and they are still being actively pursued today. In particular, with the development of artificial intelligence technology in addition to the existing conventional methods, various approaches are being developed, but papers that thoroughly analyze and organize this research have not yet been published. Accordingly, in this study, we aim to comprehensively review the studies that have attempted to remove LiDAR sensor noise under extreme weather conditions through various methods. This review discusses the latest LiDAR denoising algorithms, with a particular focus on techniques implemented under snowy conditions. These algorithms can be categorized into five types: distance-based, intensity-based, fusion-based, learning-based, and other methods. In addition, this article covers extreme weather datasets and related perception studies.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 5","pages":"7916-7932"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553442","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 Parallel Multistepped-Impedance Transmission Line (PMSITL)-Based Microwave Measurement System for Characterizing Binary Aqueous Mixtures

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2025-01-13 DOI: 10.1109/JSEN.2025.3526774

Wen-Jing Wu;Hao Xie;Wen-Sheng Zhao;Wensong Wang

{"title":"A Parallel Multistepped-Impedance Transmission Line (PMSITL)-Based Microwave Measurement System for Characterizing Binary Aqueous Mixtures","authors":"Wen-Jing Wu;Hao Xie;Wen-Sheng Zhao;Wensong Wang","doi":"10.1109/JSEN.2025.3526774","DOIUrl":"https://doi.org/10.1109/JSEN.2025.3526774","url":null,"abstract":"A parallel multistepped-impedance transmission line (PMSITL)-based microwave measurement system for retrieving complex permittivity of binary aqueous mixtures is proposed in this article. The proposed measurement system is composed of a standard characteristic impedance transmission line with multistepped-impedance resonators connected in parallel, a reflective radio frequency (RF) oscillator based on pseudomorphic high electron mobility transistor (PHEMT) ATF34143, and a frequency demodulation circuit. The transmission coefficient phase of standard characteristic impedance transmission line with parallel multistepped-impedance resonators (PMSIRs) loaded is utilized to detect the permittivity of liquid samples, the optimal parameter values of PMSITL are calculated by analyzing the mathematical model of PMSIR-based transmission line, and the optimal parameter values of PMSITL imply the highest change rate of transmission coefficient phase with regard to permittivity. Next, the reflective RF oscillator is constituted by a PMSIR-based transmission line and PHEMT ATF34143 is designed by negative impedance theory, which adopts the oscillation frequency to measure the permittivity of liquid samples. To improve the system integration level, the frequency demodulation circuit is added to the RF oscillator, which can transform the change of oscillation frequency into the variation of direct current (dc) voltage. In measurement, the proposed microwave measurement system exhibits an average sensitivity of approximately 0.2287% and 1.01% for the two channels, which are increased by dozens of times compared to state-of-the-art microwave sensors.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 4","pages":"6309-6319"},"PeriodicalIF":4.3,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430545","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