{"title":"Influences of Human Presence on the Indoor Air Quality of Educational Institutions: Concurrent Multipollutant Sensing Approach","authors":"Rajib Das;Aritra Acharyya;Shubhankar Majumdar","doi":"10.1109/OJIM.2025.3583294","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3583294","url":null,"abstract":"This study evaluates how human presence influences classroom air quality using an edge-intelligent, low-cost monitoring system [air quality monitoring system (AQMS)] that senses multiple pollutants and quantifies occupancy with an on-board camera and custom object-detection model. Over seven days in a laboratory, we varied air-conditioning and ventilation settings while the AQMS logged pollutant levels every minute. Spearman rank-order analysis showed strong positive correlations between occupancy and CO2, total volatile organic compounds (VOCs), and gas-sensor resistance, but no significant link with CO, NH3, or NO2. Particulate matter (PM2.5 and PM10) briefly fell as occupancy rose, yet this trend vanished when air-conditioning was active, indicating its filtration effect. Rooms without air-conditioning but with adequate ventilation maintained lower CO2 and VOC levels. PM findings were inconclusive because of concurrent inhalation effects. All occupancy data were privacy-preserving—images were processed on the device and never stored. Although demonstrated in a single room, the architecture is inherently scalable, and a multiroom urban–rural deployment is underway.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11052753","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Integrating Confidence Maps and Visual Servoing for Needle Tracking in Robotic US-Guided Percutaneous Nephrolithotomy","authors":"Hoorieh Mazdarani;James Watterson;Rebecca Hibbert;Carlos Rossa","doi":"10.1109/OJIM.2025.3581634","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3581634","url":null,"abstract":"Ultrasound (US)-guided percutaneous nephrolithotomy (PCNL) is a minimally invasive procedure to remove large kidney stones through an incision in the patient’s back. PCNL requires a high level of dexterity to steer a surgical tool while visualizing it using US images. A robotic system that controls the US probe to automatically image the tool would alleviate the surgeon’s cognitive workload and potentially lead to more accurate kidney access. We propose a novel algorithm that combines visual servoing and confidence maps to track the position of a manually steered needle using a robotically actuated US probe. The algorithm automatically adjusts the position of the US probe so that the same longitudinal portion of the needle shaft is visible in the image, while simultaneously ensuring acoustic contact between the US probe and the tissue over uneven surfaces. Unlike previous methods, where confidence maps were used for probe positioning with static targets, this article introduces the first unified algorithm that optimizes image quality while tracking a moving tool. It ensures continuous probe–tissue contact on uneven surfaces and does not require prior knowledge of the needle’s trajectory or additional sensors. The algorithm, evaluated in phantom tissue and in a realistic kidney mannequin, shows an average tool tracking accuracy of 1.65 and 1.17 mm, respectively, confirming its ability to reliably track a manually inserted tool during PCNL.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11045695","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Millimeter-Wave Reflectometry for Detecting Graphite Contamination in Titanium (Ti64) Powder Used in Additive Manufacturing (AM)","authors":"Jayaram Kizhekke Pakkathillam;Jessica Haack;Reza Zoughi","doi":"10.1109/OJIM.2025.3580117","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3580117","url":null,"abstract":"Titanium (Ti64) alloys are extensively used for additive manufacturing (AM) of complex and critical parts in the aerospace industry. Titanium powder particle size, shape, and presence of satellites (in case of recycled powder) are important Ti64 feedstock powder quality indicators. In this investigation, millimeter-wave characterization of Ti64 alloy and graphite powders was performed by studying the reflection coefficient response of the powder samples using a circular waveguide probe (an open cavity) operating in axially symmetric mode (TE0m) at Ka-band (32–40 GHz) and Q-band (42–50 GHz) frequency ranges. In addition to Ti64 and graphite powders, graphite-contaminated Ti64 samples, containing different amounts of graphite powder, were prepared and measured. The primary objective of this work has been to evaluate the efficacy of millimeter-wave reflectometry, and the capability of this measurement technique, for distinguishing among different contaminated Ti64 powder samples with low levels of contamination (by weight). The contamination levels ranged from 0.0015% to 5% (graphite percentage of Ti64 weight). Measurements were carried out at different powder (cavity) depths to determine the optimum sample holder depth for the increased measurement sensitivity. It is reported that a 0.05% (by weight) level of carbon contamination in powder feedstock can lead to defects in the final printed part. Crucially, the results of this investigation showed that graphite contamination levels as low as 0.0045% (percentage by weight) can be robustly detected by this method.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11038835","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Bodo;L. Ciccarelli;V. Bello;S. Morganti;S. Merlo
{"title":"Assessment of Vibration Frequencies of Piezo-Actuated Panel by Model-Assisted Self-Mixing Interferometry","authors":"E. Bodo;L. Ciccarelli;V. Bello;S. Morganti;S. Merlo","doi":"10.1109/OJIM.2025.3580120","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3580120","url":null,"abstract":"Flat surfaces driven by attached piezoelectric actuators are promising devices for the development of future generations of speakers. Although audio devices characterization requires sound pressure level measurements, preliminary testing of electromechanical frequency response and actuation efficiency may provide meaningful insights into the operation capability of these innovative systems. In this work, we have investigated a Plexiglas panel attached to a piezo-ceramic actuator as test structure. In particular, we successfully combined finite element analysis and out-of-plane displacement measurements performed with a semiconductor laser feedback (or self-mixing) interferometer in a few selected spots of the optically diffusing panel. To rapidly detect the spectral response, the actuator was driven by electrical white noise to obtain a photodetected interferometric signal in the frequency domain directly proportional to the vibration amplitude. Sinusoidal driving of the actuator at selected frequencies and interferometric signal analyses in the time domain allowed quantifying the actuation efficiency, as a function of the frequency and of the position on the panel, of the three mechanical modes exhibiting out-of-plane displacement in the range up to approximately 1 kHz. The values of natural frequencies numerically obtained match the experimentally detected values, with a difference up to 3%, 6%, and 9% for Mode 1, Mode 4, and Mode 8, respectively, that are the three lowest modes with effective modal mass along the z-direction.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11037483","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Massimiliano Gaffurini;Dennis Brandão;Stefano Rinaldi;Alessandra Flammini;Emiliano Sisinni;Paolo Ferrari
{"title":"Characterizing the Real-Time Communication Performance of Virtual PLC in Industrial Edge Platform","authors":"Massimiliano Gaffurini;Dennis Brandão;Stefano Rinaldi;Alessandra Flammini;Emiliano Sisinni;Paolo Ferrari","doi":"10.1109/OJIM.2025.3559573","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3559573","url":null,"abstract":"The integration of virtual programmable logic controllers (vPLCs) into industrial automation systems introduces the potential for enhanced maintainability and scalability through container-based automation. Unlike traditional hardware-based PLCs, vPLCs operate within edge computing environments, leveraging lightweight virtualization to provide flexibility and support modern microservices architectures. However, the open question is: can vPLCs meet the stringent real-time performance requirements of industrial control applications, particularly in communication with sensors and actuators? This article objective is to fill this gap. Differently from other works in the literature, the performance of the real-time data exchange between vPLCs and sensors/actuators is evaluated. In particular, this article presents and describes a methodology designed for comparing real PLC and vPLC in real-time industrial automation scenarios. The methodology includes the definition of specific performance metrics, the design of a standardized experimental setup to characterize both device real-time performance and uncertainty sources, and the development of analytical models to support simulations and digital twin applications. The proposed method of comparison is demonstrated in a reference use case, including real-time Ethernet connectivity; results lead to: 1) important conclusions about methodology effectiveness and 2) the analytical model of the considered use case. In detail, the analysis indicates that vPLCs exhibit approximately 50% higher jitter, suggesting a minimum recommended PROFINET cycle time of 2 ms for optimal performance. The findings contribute to the broader understanding of vPLC capabilities in industrial automation, offering practical insights for industries aiming to transition to modern, containerized control systems without compromising real-time communication performance.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10963754","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sayed Mohammad Kameli;Abdelaziz Abuelrub;Mohammad AlShaikh Saleh;Shady S. Refaat;Ali Ghrayeb;Haitham Abu-Rub;Marek Olesz
{"title":"Analysis of Partial Discharges in Oil-Impregnated Transformer Paper Insulation and PET-G Insulation","authors":"Sayed Mohammad Kameli;Abdelaziz Abuelrub;Mohammad AlShaikh Saleh;Shady S. Refaat;Ali Ghrayeb;Haitham Abu-Rub;Marek Olesz","doi":"10.1109/OJIM.2025.3555323","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3555323","url":null,"abstract":"Partial discharge (PD) is a widespread phenomenon instigated in power transformer (PT) insulation systems. PDs are triggered by voids that vary in size and position within the PT insulation. The electrical characteristics of those damaging, PD-causing cavities must be well understood, to accelerate the development of advanced PD detection techniques. Thus, the impact of varying the radius and position of spherical air voids on the characteristics of PDs in PTs is examined using a 3-D finite element analysis (FEA) model designed in COMSOL Multiphysics. The spherical voids are positioned between two windings of a 512 kV, three-phase (3<inline-formula> <tex-math>$varphi $ </tex-math></inline-formula>) PT. The peak electric field (EF) and aggregate energy in the FEA model are used in conjunction with laboratory measurements of the apparent discharge magnitude, for detailed analysis of Polyethylene Terephthalate Glycol (PET-G)-based cylindrical voids with different heights. Simulations demonstrate that the inception of PD activity in the PT model occurs for spherical voids with a radius exceeding 1 mm. Furthermore, the most severe PDs occur within the press-board insulation, adjacent to the uppermost part of the innermost windings. Experiments demonstrate that a significant increase in PD activity was observed for PET-G-based cylindrical voids with heights exceeding 1 mm.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10943204","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143913403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Real-Time Player Engagement Measurement Using Nonintrusive Game Telemetry","authors":"Ammar Rashed;Shervin Shirmohammadi;Mohamed Hefeeda","doi":"10.1109/OJIM.2025.3555326","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3555326","url":null,"abstract":"Player engagement is crucial for the success of modern video games, yet its real-time measurement remains challenging due to the intrusive nature of traditional measurement methods. In this article, we present a novel framework for nonintrusive, real-time, and indirect measurement of engagement in multiplayer online games based on flow theory. Our approach combines graph convolutional networks for modeling player interactions with Transformer networks for temporal processing, enabling indirect measurement of both player skill and game challenge, which in turn are used to classify player engagement. Using playerunknown’s battlegrounds (PUBGs) as a case study, we demonstrate that our framework can effectively measure phase-specific engagement using one minute of gameplay telemetry data. Our framework achieves 73% accuracy and 0.83 ROC-AUC in engagement classification, matching the performance of traditional survey-based methods while operating nonintrusively and in real time. Further cross-domain validation of the framework, as is and without transfer learning, with the games FIFA’23 and Street Fighter V, leads to 66% accuracy, demonstrating the model’s stable performance despite the significant differences in the test domains. Interestingly, our results suggest that objective gameplay metrics may better reflect engagement than subjective player assessments, with skill estimates showing significant correlation with self-reports.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10943161","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143875213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arthur P. LeBlanc;Samir Trabelsi;Khaled Rasheed;John A. Miller
{"title":"Machine Learning Algorithms for Nondestructive Sensing of Moisture Content in Grain and Seed","authors":"Arthur P. LeBlanc;Samir Trabelsi;Khaled Rasheed;John A. Miller","doi":"10.1109/OJIM.2025.3568080","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3568080","url":null,"abstract":"Machine learning (ML) models were used to determine the moisture content (MC) for multiple grains and seeds after training on a large dataset obtained through several decades of research. The dataset consisted of attenuation, phase shift, dielectric properties, frequency, bulk density, and sample thickness collected for corn, barley, sorghum, soybeans, and wheat. In this article, a new ML-based approach for calibrating microwave sensors for rapid and nondestructive determination of MC in multiple grains and seeds is proposed. For this purpose, a single model trained on multiple grains and seeds was developed and allowed moisture determination in individual grain or seed samples. Performance of this model is investigated and compared with models trained on an individual grain or seed by using different algorithms, including artificial neural network (NN), support vector regression (SVR), ElasticNet, among other algorithms. In addition, these models were tested on new data collected for corn, wheat, and soybeans at <inline-formula> <tex-math>$24~^{circ }$ </tex-math></inline-formula>C with MC ranging from 7.89% to 20.19% and frequencies between 5 and 15 GHz. The lowest mean absolute error (MAE) of MC was obtained with frequencies between 8 and 12 GHz for most models. Training when using the dielectric properties, frequency, and grain type with a single SVR-based model had the lowest error at 9 GHz for soybeans and corn. The SVR-based model showed no drawbacks and a slight improvement predicting MC using a single model when training over all grains and seeds compared with training several models over each grain individually.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010870","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144280016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dahlia Musa;Frank Guido-Sanz;Mindi Anderson;Desiree A. Díaz;Salam Daher
{"title":"Impact of Digital Guidance on Accuracy, Reliability, and Time Efficiency of Wound Measurements","authors":"Dahlia Musa;Frank Guido-Sanz;Mindi Anderson;Desiree A. Díaz;Salam Daher","doi":"10.1109/OJIM.2025.3571155","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3571155","url":null,"abstract":"Wound size measurement is essential for clinical assessment, as it can indicate the patient’s healing progress and influence clinical decisions. Healthcare providers traditionally use physical wound measurement methods, such as rulers and digital calipers; however, these methods have limitations. Our team developed software to compute wound measurements from 3-D scans. The software provides unguided and guided wound measurement modes in which the measurements are identified manually and semi-automatically, respectively. Healthcare providers (N=23) measured (i.e., length, width, and depth) six simulated wounds using physical, unguided software, and guided software methods. The accuracy, inter-rater reliability, and time efficiency of these methods were evaluated. The guided software method demonstrated more favorable overall accuracy (97.68%), inter-rater reliability (intraclass correlation coefficient (ICC): 0.957), and time efficiency (48.15 s) compared to the physical (93.29%; ICC: 0.833; 94.89 s) and unguided software (93.71% ICC: 0.935; 105.04 s) methods. These results indicate that digital tools with standardized measurement processes may improve the validity and efficiency of wound measurements, potentially enhancing clinical practice and training.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11006886","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Niels F. Cleymans;Mark Van De Casteele;Julie Vandewalle;Aster K. Desouter;Frans K. Gorus;Kurt Barbé
{"title":"Analyzing Random Forest’s Predictive Capability for Type 1 Diabetes Progression","authors":"Niels F. Cleymans;Mark Van De Casteele;Julie Vandewalle;Aster K. Desouter;Frans K. Gorus;Kurt Barbé","doi":"10.1109/OJIM.2025.3551837","DOIUrl":"https://doi.org/10.1109/OJIM.2025.3551837","url":null,"abstract":"Type 1 diabetes (T1Ds) is a chronic, for now, incurable multifactorial disease caused by the immune-mediated destruction of insulin-producing pancreatic <inline-formula> <tex-math>$beta $ </tex-math></inline-formula>-cells, causing devastating and costly acute and chronic complications, despite lifelong insulin treatment. Abrupt clinical onset is preceded by an asymptomatic disease phase of highly variable duration which is marked by the sequential appearance of various types of <inline-formula> <tex-math>$beta $ </tex-math></inline-formula>-cell autoantibodies (AAbs). Optimized predictions of time to clinical onset facilitate early diagnosis which is also key to reducing the incidence of inaugural life-threatening diabetic ketoacidosis and planning novel prevention trials in the asymptomatic stage. Research in first-degree relatives of known T1D patients has shown that disease progression can be predicted by genetic and immune biomarkers, but these predictions are limited by using the traditional statistical approaches such as Cox regression models. This explorative study aims to uncover the potential of random forest machine learning algorithms as survival models within the biomedical context of T1D. Two random forest survival models were constructed in R. The first constructed model predicts how long it will take for individuals to go from single to multiple AAb positivity (AAb+), a crucial step in T1D development. The second model predicts the transition from multiple AAb+ to the onset of T1D. This article demonstrates that our random forest survival models outperform traditional Cox regression methods; we conduct a detailed analysis of variable importance to uncover novel biomarker interactions; and we establish a refined framework for precise measurement and risk stratification of T1D, paving the way for earlier and more targeted intervention.","PeriodicalId":100630,"journal":{"name":"IEEE Open Journal of Instrumentation and Measurement","volume":"4 ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10929762","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}