Sensors最新文献

{"title":"A 60 GHz Class-C Wide Tuning-Range Two-Core VCO Utilizing a Gain-Boosting Frequency Doubling Technique and an Adaptive Bias Scheme for Robust Startup.","authors":"Ioannis Dimitrios Psycharis, Vasileios Tsourtis, Grigorios Kalivas","doi":"10.3390/s25030981","DOIUrl":"10.3390/s25030981","url":null,"abstract":"<p><p>This paper presents the design and the performance of a wide tuning-range millimeter-wave (mm-wave) two-core class-C 60 GHz VCO in 40 nm CMOS process, which can be integrated into wireless communication transceivers and radar sensors. The proposed architecture consists of a two-core 30 GHz fundamental VCO, a gain-boosted frequency doubler and an adaptive bias configuration. The two-core fundamental VCO structure achieves frequency generation in the vicinity of 30 GHz, where each VCO core targets a different frequency band. The two bands have sufficient overlap to accommodate for corner variations providing a large continuous tuning range. The desired frequency band is selected by activating or deactivating the appropriate VCO core, resulting in a robust switchless structure. This approach enables a considerably broad tuning range without compromising phase noise performance. Furthermore, the proposed topology utilizes an adaptive bias mechanism for robust start-up. Initially, the selected VCO core begins oscillating in class-B mode, and subsequently it transitions into class-C operation to offer improved performance. From post-layout simulations, after frequency doubling, the low-band VCO covers frequencies from 50.25 to 60.40 GHz, while the high-band VCO core spans frequencies from 58.8 to 73 GHz, yielding an overall tuning range of 36.92%. Owing to the gain-boosting topology, output power exceeds -14.2 dBm across the whole bandwidth. Simulated phase noise remains better than -92.1 dBc/Hz at a 1 MHz offset for all bands. Additionally, the two VCO cores never operate simultaneously, aiding in power efficiency.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11820980/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Characteristics of Force Development and Muscle Excitation in Resisted and Assisted Jumps in Comparison with the Isometric Mid-Shin Pull.","authors":"Giuseppe Rosaci, Davide Latini, Federico Nigro, Sandro Bartolomei","doi":"10.3390/s25030975","DOIUrl":"10.3390/s25030975","url":null,"abstract":"<p><strong>Background: </strong>The purpose of this study was to examine the relationships between the characteristics of force development and electromyographic activity of the quadriceps muscles in the isometric mid-shin pull (MSP) and the countermovement jump (CMJ) performed under different conditions.</p><p><strong>Methods: </strong>Fifteen resistance-trained individuals (age = 25.9 ± 4.0 y; body mass = 73.2 ± 11.7 Kg; stature = 172.3 ± 9.5 cm) were tested for MSP and for the following CMJs: regular CMJ (CMJ); elastic band-assisted CMJ (CMJ_AB); elastic band-resisted CMJ (CMJ_RB); weighted vest CMJ (CMJ_V) in random order, using a force plate. Peak force (PF) and peak rate of force development (PRFD) were calculated in all the assessments, while peak velocity and power were calculated only in the CMJs. In addition, during all the tests, electromyographic activity of the vastus lateralis (EMG_VL) and of vastus medialis (EMG_VM) was detected.</p><p><strong>Results: </strong>Higher PF was registered in MSP compared to the CMJs (<i>p</i> < 0.001). PRFD and EMG_VL were significantly more elevated in the CMJs compared to the MSP (<i>p</i> < 0.05). No significant correlations were noted between the PRFD measured in MSP and in CMJs, while the PRFD in MSP was largely correlated with PP in CMJs (r = 0.68/0.83).</p><p><strong>Conclusions: </strong>Results of the present study showed that CMJs promote PRFD and the excitation of the vastus lateralis, to a greater extent compared to MSP. Regular CMJ performed at body mass may represent the best option for power development, and small variations in loads allowed by weighted vests or elastic bands do not seem to alter the characteristics of force development.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11820855/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Long-Term Prediction of Mesoscale Sea Surface Temperature and Latent Heat Flux Coupling Using the iTransformer Model.","authors":"Xuwei Hu, Yuan Feng, Jiahao Liu, Yuanxiang Xu, Shengyu Song","doi":"10.3390/s25030985","DOIUrl":"10.3390/s25030985","url":null,"abstract":"<p><p>Mesoscale air-sea interaction, which is active in Western Boundary Currents (WBCs), has a non-negligible effect on mid-latitude climate variability. The analysis and prediction of the mesoscale air-sea interaction rely on high-resolution observation datasets and mesoscale-resolving climate models, which often require long processing times to estimate future changes and have several limitations. Therefore, in this study, we used a newly developed iTransformer model, which integrates mesoscale sea surface temperature anomaly (SSTa) and latent heat flux anomaly (LHFa) coupling coefficient data to predict future changes in SSTa-LHFa coupling. First, we individually trained the model using data corresponding to 1-15 past winters from ERA5 dataset. Thereafter, we used the trained model to predict SSTa-LHFa coupling coefficient for the next 10 winters. Compared with the predictions using only the coupling coefficient, the prediction yields 3.0% relative improvements when SST data were incorporated. The iTransformer model also showed the ability to reproduce the linear trend and mean value of mesoscale SSTa-LHFa coupling coefficients. Furthermore, we chose the optimal input length for each WBC and used the model to predict changes in mesoscale SSTa-LHFa coupling in the future. The results thus obtained were comparable to those obtained using mesoscale-resolving climate models, indicating that the iTransformer model showed satisfactory prediction performance. Therefore, it provides a novel pathway for exploring mesoscale air-sea interaction variations and predicting future climate change.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11821020/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Effects of Gait Rehabilitation Robot Combined with Electrical Stimulation on Spinal Cord Injury Patients' Blood Pressure.","authors":"Takahiro Sato, Ryota Kimura, Yuji Kasukawa, Daisuke Kudo, Kazutoshi Hatakeyama, Motoyuki Watanabe, Yusuke Takahashi, Kazuki Okura, Tomohiro Suda, Daido Miyamoto, Takehiro Iwami, Naohisa Miyakoshi","doi":"10.3390/s25030984","DOIUrl":"10.3390/s25030984","url":null,"abstract":"<p><strong>Background: </strong>Orthostatic hypotension can occur during acute spinal cord injury (SCI) and subsequently persist. We investigated whether a gait rehabilitation robot combined with functional electrical stimulation (FES) stabilizes hemodynamics during orthostatic stress in SCI.</p><p><strong>Methods: </strong>Six intermediate-phase SCI patients (five males and one female; mean age: 49.5 years; four with quadriplegia and two with paraplegia) participated. The participants underwent robotic training (RT), with a gait rehabilitation robot combined with FES, and tilt table training (TT). Hemodynamics were monitored using a laser Doppler flowmeter for the earlobe blood flow (EBF) and non-invasive blood pressure measurements. The EBF over time and the resting and exercise blood pressures were compared between each session. Adverse events were also evaluated.</p><p><strong>Results: </strong>The EBF change decreased in TT but increased in RT at the 0.5-min slope (<i>p</i> = 0.03). Similarly, the pulse rate change increased in TT but decreased in RT at the 1-min slope (<i>p</i> = 0.03). Systolic and mean blood pressures were slightly higher in RT than in TT but not significantly (<i>p</i> = 0.35; 0.40). No adverse events occurred in RT, but two TT sessions were incomplete due to dizziness.</p><p><strong>Conclusions: </strong>RT with FES can reduce symptoms during orthostatic stress in intermediate-phase SCI. Future studies require a larger number of cases to generalize this study.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11819915/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Towards Explainable Artificial Intelligence for GNSS Multipath LSTM Training Models.","authors":"He-Sheng Wang, Dah-Jing Jwo, Zhi-Hang Gao","doi":"10.3390/s25030978","DOIUrl":"10.3390/s25030978","url":null,"abstract":"<p><p>This paper addresses the critical challenge of understanding and interpreting deep learning models in Global Navigation Satellite System (GNSS) applications, specifically focusing on multipath effect detection and analysis. As GNSS systems become increasingly reliant on deep learning for signal processing, the lack of model interpretability poses significant risks for safety-critical applications. We propose a novel approach combining Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) cells with Layer-wise Relevance Propagation (LRP) to create an explainable framework for multipath detection. Our key contributions include: (1) the development of an interpretable LSTM architecture for processing GNSS observables, including multipath variables, carrier-to-noise ratios, and satellite elevation angles; (2) the adaptation of the LRP technique for GNSS signal analysis, enabling attribution of model decisions to specific input features; and (3) the discovery of a correlation between LRP relevance scores and signal anomalies, leading to a new method for anomaly detection. Through systematic experimental validation, we demonstrate that our LSTM model achieves high prediction accuracy across all GNSS parameters while maintaining interpretability. A significant finding emerges from our controlled experiments: LRP relevance scores consistently increase during anomalous signal conditions, with growth rates varying from 7.34% to 32.48% depending on the feature type. In our validation experiments, we systematically introduced signal anomalies in specific time segments of the data sequence and observed corresponding increases in LRP scores: multipath parameters showed increases of 7.34-8.81%, carrier-to-noise ratios exhibited changes of 12.50-32.48%, and elevation angle parameters increased by 16.10%. These results demonstrate the potential of LRP-based analysis for enhancing GNSS signal quality monitoring and integrity assessment. Our approach not only improves the interpretability of deep learning models in GNSS applications but also provides a practical framework for detecting and analyzing signal anomalies, contributing to the development of more reliable and trustworthy navigation systems.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11820723/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Ultra-Thin Plastic Scintillator-Based Proton Detector for Timing Applications.","authors":"Mauricio Rodríguez Ramos, Javier García López, Michael Seimetz, Jessica Juan Morales, Carmen Torres Muñoz, María Del Carmen Jiménez Ramos","doi":"10.3390/s25030971","DOIUrl":"10.3390/s25030971","url":null,"abstract":"<p><p>The development of advanced detection systems for charged particles in laser-based accelerators and the need for precise time of flight measurements have led to the creation of detectors using ultra-thin plastic scintillators, indicating their use as transmission detectors with low energy loss and minimal dispersion for protons around a few MeV. This study introduces a new detection system designed by the Institute for Instrumentation in Molecular Imaging for time of flight and timing applications at the National Accelerator Center in Seville. The system includes an ultra-thin EJ-214 plastic scintillator coupled with a photomultiplier tube and shielded by aluminized mylar sheets. The prototype installation as an external trigger system at the ion beam nuclear microprobe of the aforementioned facility, along with its temporal performance and ion transmission, was thoroughly characterized. Additionally, the scintillator thickness and uniformity were analyzed using Rutherford backscattering spectrometry. Results showed that the experimental thickness of the EJ-214 sheet differs by approximately 46% from the supplier specifications. The detector response to MeV protons demonstrates a strong dependence on the impact position but remains mostly linear with the applied working bias. Finally, single ion detection was successfully achieved, demonstrating the applicability of this new system as a diagnostic tool.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11820069/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Repeatable Imaging of Soil Processes Through a Stabilized Port: Examples of (i) Soil Contaminants and (ii) Plant Root Growth.","authors":"Julio A Zimbron, Christian C Rayo","doi":"10.3390/s25030968","DOIUrl":"10.3390/s25030968","url":null,"abstract":"<p><p>This work presents an imaging testing system (software and hardware) that can generate repeatable images through a stabilized port in the soil for processes known to change with time. The system includes (i) a stabilized port in the ground made of standard PVC pipe, with sections lined with a borosilicate glass tube, and (ii) a digital imaging instrument to survey the optically transparent portion of the stabilized port. The instrument uses a probe containing a digital camera and two light sources, one using white lights and one using ultraviolet (UV) lights (365 nm). The main instrument controls the probe using a cable within the stabilized port to take overlapping pictures of the soil under the different light sources. Two examples are provided, one to document the distribution of soil and groundwater contaminants known as non-aqueous phase liquids (NAPL, which include petroleum) at variable water saturation levels and a second one to monitor the growth of a plant over a 2-week interval. In both examples, the system successfully identified critical changes in soil processes and showed a resolution of approximately 15 µm (in the order of the thickness of a human hair), demonstrating the potential for repeated imaging of soil processes known to experience temporal changes. Both examples are illustrative, as additional applications might be possible. The novelty of this system lies in its ability to generate repeated measurements at larger depths than the current shallow systems installed by hand.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11820744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Noise Resilience of Successor and Predecessor Feature Algorithms in One- and Two-Dimensional Environments.","authors":"Hyunsu Lee","doi":"10.3390/s25030979","DOIUrl":"10.3390/s25030979","url":null,"abstract":"<p><p>Noisy inputs pose significant challenges for reinforcement learning (RL) agents navigating real-world environments. While animals demonstrate robust spatial learning under dynamic conditions, the mechanisms underlying this resilience remain understudied in RL frameworks. This paper introduces a novel comparative analysis of predecessor feature (PF) and successor feature (SF) algorithms under controlled noise conditions, revealing several insights. Our key innovation lies in demonstrating that SF algorithms achieve superior noise resilience compared to traditional approaches, with cumulative rewards of 2216.88±3.83 (mean ± SEM), even under high noise conditions (σ=0.5) in one-dimensional environments, while Q learning achieves only 19.22±0.57. In two-dimensional environments, we discover an unprecedented nonlinear relationship between noise level and algorithm performance, with SF showing optimal performance at moderate noise levels (σ=0.25), achieving cumulative rewards of 2886.03±1.63 compared to 2798.16±3.54 for Q learning. The λ parameter in PF learning is a significant factor, with λ=0.7 consistently achieving higher λ values under most noise conditions. These findings bridge computational neuroscience and RL, offering practical insights for developing noise-resistant learning systems. Our results have direct applications in robotics, autonomous navigation, and sensor-based AI systems, particularly in environments with inherent observational uncertainty.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11820235/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging.","authors":"Zirak Khan, Seung-Chul Yoon, Suchendra M Bhandarkar","doi":"10.3390/s25030970","DOIUrl":"10.3390/s25030970","url":null,"abstract":"<p><p>Ensuring the safety and quality of poultry products requires efficient detection and removal of foreign materials during processing. Hyperspectral imaging (HSI) offers a non-invasive mechanism to capture detailed spatial and spectral information, enabling the discrimination of different types of contaminants from poultry muscle and non-muscle external tissues. When integrated with advanced deep learning (DL) models, HSI systems can achieve high accuracy in detecting foreign materials. However, the high dimensionality of HSI data, the computational complexity of DL models, and the high-paced nature of poultry processing environments pose challenges for real-time implementation in industrial settings, where the speed of imaging and decision-making is critical. In this study, we address these challenges by optimizing DL inference for HSI-based foreign material detection through a combination of post-training quantization and hardware acceleration techniques. We leveraged hardware acceleration utilizing the TensorRT module for NVIDIA GPU to enhance inference speed. Additionally, we applied half-precision (called FP16) post-training quantization to reduce the precision of model parameters, decreasing memory usage and computational requirements without any loss in model accuracy. We conducted simulations using two hypothetical hyperspectral line-scan cameras to evaluate the feasibility of real-time detection in industrial conditions. The simulation results demonstrated that our optimized models could achieve inference times compatible with the line speeds of poultry processing lines between 140 and 250 birds per minute, indicating the potential for real-time deployment. Specifically, the proposed inference method, optimized through hardware acceleration and model compression, achieved reductions in inference time of up to five times compared to unoptimized, traditional GPU-based inference. In addition, it resulted in a 50% decrease in model size while maintaining high detection accuracy that was also comparable to the original model. Our findings suggest that the integration of post-training quantization and hardware acceleration is an effective strategy for overcoming the computational bottlenecks associated with DL inference on HSI data.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11819658/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143409891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}

{"title":"Camera-LiDAR Wide Range Calibration in Traffic Surveillance Systems.","authors":"Byung-Jin Jang, Taek-Lim Kim, Tae-Hyoung Park","doi":"10.3390/s25030974","DOIUrl":"10.3390/s25030974","url":null,"abstract":"<p><p>In traffic surveillance systems, accurate camera-LiDAR calibration is critical for effective detection and robust environmental recognition. Due to the significant distances at which sensors are positioned to cover extensive areas and minimize blind spots, the calibration search space expands, increasing the complexity of the optimization process. This study proposes a novel target-less calibration method that leverages dynamic objects, specifically, moving vehicles, to constrain the calibration search range and enhance accuracy. To address the challenges of the expanded search space, we employ a genetic algorithm-based optimization technique, which reduces the risk of converging to local optima. Experimental results on both the TUM public dataset and our proprietary dataset indicate that the proposed method achieves high calibration accuracy, which is particularly suitable for traffic surveillance applications requiring wide-area calibration. This approach holds promise for enhancing sensor fusion accuracy in complex surveillance environments.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 3","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11820416/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143410570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}