IEEE Transactions on Instrumentation and Measurement最新文献

{"title":"PSO-Based Optimal Coverage Path Planning for Surface Defect Inspection of 3C Components With a Robotic Line Scanner","authors":"Hongpeng Chen;Shengzeng Huo;Muhammad Muddassir;Hoi-Yin Lee;Yuli Liu;Junxi Li;Anqing Duan;Pai Zheng;David Navarro-Alarcon","doi":"10.1109/TIM.2025.3552466","DOIUrl":"https://doi.org/10.1109/TIM.2025.3552466","url":null,"abstract":"The automatic inspection of surface defects is an essential task for quality control in the computers, communications, and consumer (3C) electronics industry. Traditional inspection mechanisms (i.e., line-scan sensors) have a limited field of view (FOV), thus prompting the necessity for a multifaceted robotic inspection system capable of comprehensive scanning. Optimally selecting the robot’s viewpoints and planning a path is regarded as coverage path planning (CPP), a problem that enables inspecting the object’s complete surface while reducing the scanning time and avoiding misdetection of defects. In this article, we present a new approach for robotic line scanners to detect surface defects of 3C free-form objects automatically. A two-stage region segmentation method defines the local scanning based on the random sample consensus (RANSAC) and K-means clustering to improve the inspection coverage. The proposed method also consists of an adaptive region-of-interest (ROI) algorithm to define the local scanning paths. Besides, a particle swarm optimization (PSO)-based method is used for global inspection path generation to minimize the inspection time. The developed method is validated by simulation-based and experimental studies on various free-form workpieces, and its performance is compared with that of two state-of-the-art solutions. The reported results demonstrate the feasibility and effectiveness of our proposed method.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Flexible Electrical Capacitance Tomography Sensor for Proximity Object Recognition","authors":"Xiaoli Xu;Xudong Guo;Wendong Zheng;Huaping Liu","doi":"10.1109/TIM.2025.3551985","DOIUrl":"https://doi.org/10.1109/TIM.2025.3551985","url":null,"abstract":"The ability to recognize objects plays a crucial role in the application of robots. Electrical capacitance tomography (ECT) effectively addresses the limitations of other types of proximity sensors in object recognition. This study introduces a flexible ECT sensor, examines the characteristics of coplanar ECT sensors in measurement strategies, and utilizes Tikhonov regularization for position and target contour reconstruction. A detailed analysis of the sensor’s response and performance metrics is conducted. Under proximity conditions, the support vector machine (SVM) achieves a recognition accuracy of up to 93.1% for 15 different object items. To validate the practicality and effectiveness of the sensor, we design a simple physical experiment that combines close-range identification based on the ECT sensor with obstacle avoidance using a robotic arm. The experimental results indicate that the robotic arm can select appropriate avoidance strategies based on the potential impact of the object on itself, thereby enhancing obstacle avoidance efficiency. This indicates that through ECT sensors, effective proximity recognition of objects in the environment is achievable, offering a new solution to enhance the perceptual abilities and autonomy of robots in complex environments.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multiscale Cross-Channel Attention Network for Remaining Useful Life Prediction With Variable Sensors","authors":"Tianao Zhang;Li Jiang;Ruyi Huang;Xin Zhang","doi":"10.1109/TIM.2025.3551011","DOIUrl":"https://doi.org/10.1109/TIM.2025.3551011","url":null,"abstract":"The remaining useful life (RUL) prediction of machinery based on deep learning (DL) represents a crucial component in the field of prognostics and health management (PHM). However, these DL-based methods for RUL prediction tend to become unreliable during online inference when only partial signals are available. To address this issue, we introduce the variable sensors scenario and propose a multiscale cross-channel attention network (MSCCAN) specifically designed for RUL prediction with variable sensors. For each input sample with variable sensors, the embedding layer is utilized to transform the dimensions of the input tensor. The multiscale cross-channel attention (MSCCA) layer is employed to extract and fuse multichannel degradation information, where the multiscale convolutional attention (MSCA) blocks extract the multiscale degradation features, and the anti-missing cross-channel attention (AMCCA) block effectively integrates feature information while mitigating interference from missing sensors. A mask global average (MGA) layer is used to compress high-dimensional features without being affected by the channels from missing sensors. Moreover, a new data augmentation method is used to improve the robustness of the model to the inputs with variable sensors. Finally, the experiments on the commercial modular aero-propulsion system simulation (CMAPSS) dataset and the New CMAPSS (N-CMAPSS) dataset validate the effectiveness of MSCCAN under both normal and variable sensor scenarios. Experimental results demonstrate that the proposed method can reduce the prediction error by more than 40% compared with the comparison methods under the worst scenario with variable-sensor inputs.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MIMO Microwave Sensor for Selective and Simultaneous Detection of Methanol and Ethanol Gases at Room Temperature","authors":"Mohammad Mahmudul Hasan;Todd Cowen;Onur Alev;Michael Cheffena","doi":"10.1109/TIM.2025.3551791","DOIUrl":"https://doi.org/10.1109/TIM.2025.3551791","url":null,"abstract":"This article presents a machine learning (ML)-assisted novel microwave sensor for the simultaneous and selective detection of multiple volatile organic compounds (VOCs) at room temperature (RT) using molecularly imprinted polymer (MIP)/carbon nanotube (CNT)-based sensing layers. The synthesized materials were characterized using Fourier-transform infrared (FT-IR) spectroscopy and subsequently used to develop two chemiresistive sensors, two single-port antenna sensors, and a two-port multiple-input-multiple-output (MIMO) antenna sensor, all systematically developed step by step. First, high-precision interdigitated electrode (IDE)-based sensors were functionalized with MIP/CNT sensing materials for individual target VOCs. These sensors were then evaluated for their electrical and gas-sensing properties and optimized to achieve the desired sensitivity. Next, antenna sensors were developed using these optimized structures, demonstrating selectivity for methanol and ethanol with a sensitivity of ~1.0 MHz/1000 ppm. The detection limits (DLs) were 77 ppm for ethanol and 90 ppm for methanol, both well below their safety thresholds, ensuring the sensors’ suitability for practical applications. ML-based signal processing techniques were used to isolate cross-reactivity between chemical interferents and mutual coupling effects from closely spaced array elements. This enabled the simultaneous and selective detection of multiple VOCs in complex mixtures. The ML models trained on experimental data achieved an impressive F1 score of 0.9917, demonstrating accurate discrimination of VOC types. In addition, the models produced an R-squared value of 0.994 for gas concentration estimation, confirming their predictive accuracy. The developed sensors exhibited high selectivity and specificity when tested against methanol, ethanol, acetone, and isopropanol. Moreover, the antenna sensors operated within their bandwidth during gas sensing, eliminating the need for complex tuning circuits. In addition, perturbation analysis confirmed the ML model’s robustness, as it maintained high accuracy despite input noise, ensuring reliable real-world performance.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-13"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Minimally Invasive Temperature Mapping for Laser Ablation: A Preliminary Study on Ex Vivo Livers","authors":"Aurora Bellone;Massimo Olivero;Gianni Coppa;Alberto Vallan;Guido Perrone","doi":"10.1109/TIM.2025.3551467","DOIUrl":"https://doi.org/10.1109/TIM.2025.3551467","url":null,"abstract":"The optimization of laser ablation (LA) surgical procedures—specifically for the treatment of tumors—requires evaluating the temperature distribution across the entire area under treatment (e.g., the tumor volume). However, minimally invasive temperature sensors can only provide information in a limited number of points. Therefore, an effective prediction algorithm is required to reconstruct the temperature map for the entire heat affected tissue from as few temperature measurements as possible. This work presents an approach for predicting the temperature around the laser delivery fiber, based on the thermal Green’s function, where patient-specific tissue thermal parameters are obtained through a fitting procedure using measurement of the temperature evolution at known locations. The proposed method is independent of the specific temperature sensor used; in the experiments reported, the temperature was measured both at the prediction points and at validation points using a quasi-distributed sensor composed of dense fiber Bragg grating (FBG) arrays, written with a femtosecond laser. A preliminary validation under ideal conditions, represented by ex vivo cases, has been performed through a series of experiments on bovine liver samples. The obtained results demonstrate that it is possible to predict the temperature distribution across the entire ablated area, with errors well below the commonly accepted uncertainty for treatments of this type.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and Development of Self-Sustained RF Energy Harvested Rectenna for Sensor Node Application","authors":"Khushbu Singh Raghav;Richa Paliwal;Navin Singhal;M. Santosh Kumar;Deepak Bansal","doi":"10.1109/TIM.2025.3550955","DOIUrl":"https://doi.org/10.1109/TIM.2025.3550955","url":null,"abstract":"Today, radio frequency energy harvesting (RFEH) is seen as an emerging method for powering wireless ubiquitous Internet-of-Things (IoT) devices. However, the major roadblock is the availability of adequate power density, antenna, and the receiver’s sensitivity. This article experimentally demonstrates the challenges owing to the low power density of ambient sources and the antenna configuration in retrieving RF power to run and sustain an actual RFEH system. To tackle this, antenna design tradeoffs among size, frequency, and gain have been reported and design rules have been proposed. among, a proof-of-concept of successful demonstration of powering IoT-capable Texas Instrument CC1350 SOC sensor node from a dedicated source backed by experimental measurements of temperature, power generation, and dissipation has been reported. The experimental results show that the proposed RFEH system is capable of running and sustaining more than one sensor node load. The power generated by RFEH after charging the supercapacitor to 3.3 V is approximately 2 mW and is capable of maintaining and running the IoT-enabled sensor node when temperature data is recorded in an interval of 1 min to help replenish the voltage on the supercapacitor. Thus, the experimental measurement results show that energy harvested from the dedicated RF source along with a high-gain antenna can achieve self-sustained IoT operations, eradicating the need for batteries. Finally, the thermal analysis of the harvesting circuitry has also been demonstrated compared with the state-of-the-art RFEH systems.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Ameliorated Positioning Scheme for Optical Fiber Interferometer-Based Vibration Sensors in Perimeter Security Monitoring Application","authors":"Zhenshi Sun;Haokun Yang;Jinqi Zhang;Peizhou Fang;Chengwei Zhao","doi":"10.1109/TIM.2025.3552384","DOIUrl":"https://doi.org/10.1109/TIM.2025.3552384","url":null,"abstract":"Optical fiber interferometer vibration sensors demonstrate a distinctive capability to monitor mechanical vibrations across numerous independent points using a multicore fiber cable, making them highly promising for applications in perimeter security monitoring. However, precisely locating vibrations along a long-haul fiber cable remains a significant challenge in these applications. To address this challenge, this article presents and validates an enhanced positioning strategy based on multivariate variational mode decomposition. In contrast to previously reported positioning approaches for long-range interferometer-based vibration sensors, which predominantly rely on demodulating the phase information of the applied vibration to determine the specific locations, the proposed positioning scheme offers notable advantages, including reduced computational complexity, lower hardware costs, and improved positioning accuracy. To validate the effectiveness of the proposed positioning scheme, experiments were conducted to localize vibration events along a 101-km sensing fiber cable using an annular asymmetric dual Mach-Zehnder interferometer-based long-range distributed optical fiber vibration sensing system. The experimental results show an accuracy of 0.026%, corresponding to a mean positioning error of 26.2 m. In addition, the proposed scheme achieves a mean positioning processing time of just 0.379 s. Consequently, we believe that the proposed positioning scheme offers significant potential for long-distance perimeter security monitoring and other related fields that rely on interferometer-based distributed optical fiber vibration sensors.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time EMG Decomposition Across Neural Excitation Levels Using Dual Self-Attention Residual Network","authors":"Yixin Li;Guanghua Xu;Kai Zhang;Gang Wang;Yang Zheng","doi":"10.1109/TIM.2025.3551898","DOIUrl":"https://doi.org/10.1109/TIM.2025.3551898","url":null,"abstract":"Motor unit (MU) discharge information extracted via real-time electromyogram (EMG) decomposition shows superiority in dexterous finger motion decoding. The variation of excitation levels can, however, lead to MU recruitment/de-recruitment, resulting in nonstationary EMG activities and then degraded decomposition and decoding performance; therefore, a novel online decomposition approach based on the multiple separation vector strategy was developed in this study. First, the separation vectors corresponding to different excitation levels were extracted offline via the fast independent component analysis (FastICA) algorithm and then merged to construct the separation vector pool for each MU via a previous MU action potential classification network. Under the online condition, a dual self-attention residual network was proposed to identify the excitation level, and the separation vectors were alternated correspondingly [termed alternating strategy (AS) method]. The conventional method that always used a fixed separation (FS) vector was compared. The 30-min synthetic EMG and the 15-min experiment EMG with the neural drive and the contraction strength, respectively, varying between 0% and 45% maximum voluntary contraction (MVC) were used. The experiment involved dexterous multifinger extension with isometric contractions. The results showed that the AS method obtained a higher spike consistency (87.55% <inline-formula> <tex-math>$pm ~3.75$ </tex-math></inline-formula>% versus 84.05% <inline-formula> <tex-math>$pm ~4.11$ </tex-math></inline-formula>%) with the true spike trains using the synthetic EMG and improved force prediction performance using the experiment EMG, i.e., a higher correlation (<inline-formula> <tex-math>$R^{2}$ </tex-math></inline-formula>: <inline-formula> <tex-math>$0.82~pm ~0.06$ </tex-math></inline-formula> versus <inline-formula> <tex-math>$0.76~pm ~0.07$ </tex-math></inline-formula>) and a lower prediction error root-mean-square error (RMSE): 8.87% <inline-formula> <tex-math>$pm ~1.53$ </tex-math></inline-formula>% versus 13.61%MVC <inline-formula> <tex-math>$pm ~0.92$ </tex-math></inline-formula>%MVC) compared with the FS method. Further development of the proposed method could potentially provide a robust humanmachine interface for dexterous finger force prediction in realistic applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-12"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Low Walk Error Timing Discrimination ASIC With Rail-to-Rail Dynamic Range and ICMR for Pulsed ToF LiDAR Receiver","authors":"Kaiyou Li;Shengzhao Su;Zijun Huang;Yubin Zhao;Jianping Guo","doi":"10.1109/TIM.2025.3552469","DOIUrl":"https://doi.org/10.1109/TIM.2025.3552469","url":null,"abstract":"The adopted laser pulse widths in different pulsed time-of-flight (ToF) light detection and ranging (LiDAR) systems from short- to long-distance applications would vary from 1 to <inline-formula> <tex-math>$geq 100$ </tex-math></inline-formula> ns, which demands the timing discrimination (TD) circuit has good adaptability to the input pulsewidth. Meanwhile, the dynamic range (DR) and input common-mode range (ICMR) of the TD circuit are preferred to be as large as possible to reduce the complexity of the front-end circuits. In this article, a TD application-specific integrated circuit (ASIC) is proposed to address the above issues. Featuring rail-to-rail DR and ICMR, the proposed TD circuit consists of a high-speed arming comparator (A-COMP), a low walk error zero-crossing comparator (ZC-COMP), and a robust latch/reset circuit. The rail-to-rail A-COMP has been modified to have low propagation delay and low delay dispersion to improve the accuracy. A novel low walk error input stage with rail-to-rail DR and ICMR is proposed for the ZC-COMP, and resistive-feedback (RFB) inverters combined with a common-mode feedback (CMFB) loop are proposed for reducing the walk error induced by the differential-to-CMOS level conversion. Fabricated in a 0.18-<inline-formula> <tex-math>$mu $ </tex-math></inline-formula>m CMOS process and demonstrated as a constant-fraction discriminator (CFD), the ASIC achieves walk errors of ±310, ±130, ±105, and ±50 ps for the input pulses with full-width at half-maximum (FWHM) of 150, 25, 3, and 1 ns, respectively, across a wide DR of 20 mVpp to rail-to-rail amplitude. Comparisons with discrete counterparts and prior works highlight the ASIC’s superior performance in terms of ICMR, DR, walk error, and adaptability to different laser pulse widths.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-13"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FOS-YOLO: Multiscale Context Aggregation With Attention-Driven Modulation for Efficient Target Detection in Complex Environments","authors":"Shuilong He;Wei Yu;Tao Tang;Shanchao Wang;Chao Li;Enyong Xu","doi":"10.1109/TIM.2025.3552465","DOIUrl":"https://doi.org/10.1109/TIM.2025.3552465","url":null,"abstract":"Computer vision techniques have significantly advanced autonomous driving but still face specific challenges in complex environments, such as accurately detecting small, occluded, or low-contrast objects amidst dynamic backgrounds and varying lighting conditions. This article introduces FOS-you only look once (YOLO), a novel model designed to enhance detection performance in these scenarios. FOS-YOLO integrates the FocalNet mechanism to improve feature representation, effectively addressing target scale variations and low contrast through multiscale context aggregation and multilevel modulation. In addition, the zoomed spatial convolutional block attention module (ZS_CBAM) is introduced to improve the detection of small targets, occlusions, and illumination changes by effectively fusing channel and spatial attention with a focus on scaled spatial features. The model also includes two lightweight modules, the adaptive depthwise enhanced module (ADEM) and the lite enhanced reduction module (LERM), which reduce parameters and computational load, accelerating convergence and improving accuracy. Experimental results, compared with state-of-the-art (SOTA) methods, show that FOS-YOLO achieves a mAP of 90.4% on the KITTI dataset and 64.3% on the RTTS dataset, with a 20.07% reduction in parameters, significantly enhancing real-time detection accuracy and efficiency.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-13"},"PeriodicalIF":5.6,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}