Biomedical Physics & Engineering Express最新文献

{"title":"Optimized VCG signal compression using sparse PSO.","authors":"Aditya Tiwari, Ronak Vimal, Anil Kumar","doi":"10.1088/2057-1976/ae607c","DOIUrl":"10.1088/2057-1976/ae607c","url":null,"abstract":"<p><p>Vectorcardiogram (VCG) signal compression is very much in demand in the present-day scenario due to the increasing number of cardiac patients. Hence, in this paper, a new technique is proposed that compresses VCG signal by optimizing the tunable quality wavelet transform (TQWT) parameters. The noise in VCG signal is firstly removed by applying a Savitzky-Golay filter, and then passing noise-free signal to an optimization algorithm that optimizes the TQWT parameters, and obtains the frequency domain signal. This signal is then quantized through dead-zone quantization and processed by a lossless compression mechanism: run-length encoding (RLE) to improve the compression ratio & encode the signal. This compressed signal is reconstructed by Inverse RLE to obtain the decoded signal. Inverse of TQWT is applied to get the reconstructed signal back from the transformed frequency domain to time domain. The parameters of TQWT, especially the<i>Q</i>and<i>R</i>, are optimized to get the highest<i>CR</i>at lowest percent root-mean-square-difference<i>(PRD)</i>with best reconstruction quality and least distortions, along with acceptable values of signal-to-noise-ratio<i>(SNR)</i>, quality score<i>(QS)</i>, and<i>Similarity</i>with lowest mean-square-error<i>(MSE)</i>. The comparative analysis of different optimization methods indicates that the sparse-particle swarm optimization is best among all the approaches for the tuning of parameters in TQWT for VCG signal compression and reconstruction achieving a<i>CR</i>of 48.18 at a<i>PRD</i>of 3.68,<i>SNR</i>of 29.39,<i>QS</i>of 15.71, similarity of 0.99845,<i>MSE</i>of 0.00016, with<i>Q</i>value of 2.04307 and<i>R</i>value of 1.20568 with<i>computational time</i>of 4.48508 s.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147697449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel machine learning approach for prediction of postoperative delirium using multi-domain features of high-density EEG.","authors":"Bowen Yu, Mengmeng Tang, Juan Wang, Xinxin Cui, Fan Wu, Yuanyuan Zou, Jianhui Liu, Jun Zhang, Zhenhu Liang","doi":"10.1088/2057-1976/ae5f98","DOIUrl":"10.1088/2057-1976/ae5f98","url":null,"abstract":"<p><p><i>Background.</i>Postoperative delirium (POD) poses a significant risk to patients, and accurate prediction of POD can provide guidance for positive interventions. Although many studies have applied machine learning (ML) to electronic health records to predict POD, there has been a lack of studies utilizing electroencephalogram (EEG) data to accurately predict POD.<i>Methods.</i>This retrospective study included 142 patients from two hospitals, among whom 33 developed POD. We extracted multi-domain features from high-density EEG (HD-EEG), screened 39 key features using recursive feature elimination, and analyzed the feature space structure using linear discriminant analysis (LDA). Four ML models, namely support vector machine (SVM), logistic regression (LR), random forest (RF), and gradient boosting machine, were compared. The dataset was divided using 5-fold cross-validation for model training and testing.<i>Results.</i>Compared to the other three models, SVM (linear kernel) performed best in predicting POD, achieving a classification accuracy of 95.71%. Alpha (8-12 Hz) and theta (4-8 Hz) powers, combined with nonlinear dynamics, critically contributed to the model. Furthermore, the performance of the linear models (SVM and LR) was significantly (<i>p</i>< 0.001) better than that of the nonlinear models, with LDA confirming strong feature space separability (Jensen-Shannon divergence = 0.69).<i>Conclusions.</i>HD-EEG data can be used to establish high-quality ML models for POD predictions. Multidomain features enable more comprehensive integration of EEG information related to delirium. The feature space structure significantly affects the performance of the prediction model, with the linear model offering distinct advantages in predicting POD.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147688023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergistic effects of plaque geometry and composition on coronary hemodynamics and mechanical stability: a multiscale computational study.","authors":"Yinghong Zhao, Aoxue Chen, Han Liu, Hang Cao, Jiayi Chen, Hui Tang, Huihui Wang, Gang Hua","doi":"10.1088/2057-1976/ae5fa0","DOIUrl":"10.1088/2057-1976/ae5fa0","url":null,"abstract":"<p><p>Cardiovascular disease remains the leading cause of global mortality, with the rupture of vulnerable atherosclerotic plaques accounting for the majority of acute myocardial infarctions. While plaque morphology and composition are well recognized as critical determinants of vulnerability, their combined effects across clinically relevant stenosis severities (50%-80%) remain incompletely understood. To address this gap, this study aimed to systematically investigate the collective influence of plaque geometry (eccentric vs. concentric) and material composition (lipid, fibrous, calcified) on coronary hemodynamics and mechanical plaque stability under identical stenosis conditions. The left anterior descending artery were reconstructed using clinical computed tomography angiography data, and key hemodynamic (wall shear stress [WSS], oscillatory shear index [OSI], relative residence time [RRT]) and structural metrics (plaque von Mises stress and deformation) were quantified via coupled computational fluid dynamics and fluid-structure interaction simulations. The results demonstrated that eccentric plaques induced significantly more pronounced asymmetric flow disturbances, steeper WSS gradients, and higher RRT values compared to concentric geometries, particularly at higher stenosis severities; notably, at 70% stenosis, the mean RRT of eccentric plaques (0.108 65) was nearly double that of concentric plaques (0.056 86), and eccentric plaques exhibited a unique low-oscillatory shear environment with upstream mean OSI reduced to 0.141 01, whereas concentric plaques showed upstream mean OSI elevated to 0.256 07. Compositionally, lipid-rich regions experienced the greatest deformation, highlighting their role as mechanical 'weak spots,' whereas calcified areas showed minimal deformation but generated interfacial stress concentrations. These findings elucidate the synergistic interaction between plaque geometry and composition in modulating coronary hemodynamics and mechanical integrity, with eccentric morphology exacerbating adverse biomechanical conditions as stenosis progresses. This study provides a novel, multiscale biomechanical framework for assessing plaque vulnerability and informs the development of personalized intervention strategies tailored to specific plaque characteristics.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147687943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Taguchi-optimized agar phantom for temperature-based validation in electro-hyperthermia.","authors":"Chih-Wu Cheng, Wen-Tyng Li, Yuk-Wah Tsang","doi":"10.1088/2057-1976/ae5ca7","DOIUrl":"10.1088/2057-1976/ae5ca7","url":null,"abstract":"<p><p><i>Objective</i>. This study aimed to develop and optimize an agar-based phantom using the Taguchi method for temperature-based validation of electro-hyperthermia systems in a quality assurance (QA) framework.<i>Materials and methods</i>. This study utilized the Taguchi method with an orthogonal array to design nine agar phantom formulations with varying concentrations of three factors: agar, sodium chloride (NaCl), and sodium azide (NaN₃). Heating was performed using the Oncotherm EHY-2000 RF hyperthermia device under six different power levels (25-100 W), with each stage lasting 5 min for a total duration of 30 min. Temperature changes were measured at a depth of 5 cm within the phantom using a type T thermocouple thermometer. A pork tissue model was used as the reference standard for comparison.<i>Results.</i>All phantom formulations exhibited a linear increase in temperature during the heating process. Analysis using Minitab software identified the optimal formulation, consisting of 5.0% agar, 0.1% NaCl, and 0.44% NaN₃, as producing a temperature profile most closely resembling that of the pork tissue model. Taguchi analysis indicated that agar concentration was the most significant factor influencing temperature variation. The interactions among the three formulation variables were weak, suggesting that each factor could be optimized independently.<i>Significance.</i>The agar phantom developed in this study features simple fabrication, reusability, and long-term storability, making it a practical tool for detecting abnormal heating in hyperthermia devices and enhancing treatment safety and accuracy. It is suited for routine QA of the Oncotherm electro-hyperthermia system.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147637941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kali MC: an open-source toolkit for intraoperative electron radiation therapy treatment planning.","authors":"Rafael Ayala, Rocío García, Gema Ruiz, Susana Gómez, Marina Santos, Ana Álvarez, María Jesús García, Álvaro Soza, José Manuel Udías, Paula Ibáñez","doi":"10.1088/2057-1976/ae5f9d","DOIUrl":"10.1088/2057-1976/ae5f9d","url":null,"abstract":"<p><p>Intraoperative electron radiation therapy (IOERT) is commonly delivered without intraoperative imaging, limiting patient-specific planning and requiring fast, reliable treatment calculations in the operating room. As a result, monitor unit (MU) calculations are often performed using spreadsheets and static look-up tables derived from measurements in water. We present Kali MC, an open source, Python-based software developed to streamline IOERT absorbed dose visualization, MU calculation and report generation for treatments delivered with the Liac HWL mobile accelerator. The software provides a graphical interface to visualize precomputed Monte Carlo absorbed dose distributions in water and performs MU calculations using experimentally determined output factors. Optional atmospheric pressure correction and predefined rescaling factors are supported to improve consistency of dose delivery and target coverage with the prescription isodose. Kali MC also generates customizable PDF treatment reports and exports DICOM RT Plan objects to facilitate integration with record-and-verify systems. By integrating validated dosimetric data, correction methods, and 3D dose visualization into a transparent platform, Kali MC supports efficient intraoperative decision-making; however, its use should be locally commissioned and evaluated according to institution-specific procedures and equipment characteristics.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147687962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Derivation of elemental concentrations maps in a thin lamb bone sample from a two-dimensional synchrotron-based x-ray fluorescence scanning experiment.","authors":"Mihai R Gherase, Nikhil N Hematillake, Gavin E R Hopper, David E B Fleming, Renfei Feng","doi":"10.1088/2057-1976/ae5dd4","DOIUrl":"10.1088/2057-1976/ae5dd4","url":null,"abstract":"<p><p><i>Objective.</i>Microscopic two-dimensional (2D) elemental distributions of tissues can be probed by synchrotron-based 2D x-ray fluorescence (XRF) scanning. Converting 2D XRF data into elemental concentration maps (ECMs) enhances the scientific value of such studies by facilitating comparisons within the increasingly larger pool of published data. This study developed and tested a computationally fast method able to perform such conversions.<i>Approach.</i>A semicircular cortical bone slice, 0.38-mm-thick and ∼150 mm²in area, transversally sectioned from a lamb tibia was analyzed at the VESPERS beamline of the Canadian Light Source synchrotron. The 2D XRF scan consisted of short sequential microbeam irradiations in 10<i>µ</i>m steps. The scan was repeated at four incident photon energies and probed two rectangular areas (0.24 mm²) at the sample's opposite edges. K-shell XRF peaks of seven elements (P, Ca, Fe, Ni, Cu, Zn, and Sr) were identified in the acquired x-ray spectra. Using physical and geometrical assumptions of the fundamental parameter method (FPM), the developed computer code generated ECMs of the investigated microscopic areas.<i>Main Results.</i>Generated ECMs indicated relatively uniform distributions of the seven chemical elements, with localized peaks near the sample edges. The average elemental concentrations at the four photon energies agreed with each other and compared well with literature data.<i>Significance.</i>A fast FPM-based computer code for converting 2D XRF data into ECMs was developed and tested. The code can be applied to investigations of other biological tissues extending the applicability of existing quantitative XRF methods.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147653674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural identifiability of single-beat estimation of the ventricular end-systolic pressure-volume relationship.","authors":"Fabijan Lulić, Severino Krizmanić, Igor Vodopija, Zdravko Virag","doi":"10.1088/2057-1976/ae5f9b","DOIUrl":"10.1088/2057-1976/ae5f9b","url":null,"abstract":"<p><p>Single-beat (SB) approaches for estimating the end-systolic pressure-volume relationship (ESPVR) from a single pressure-volume (<i>P</i>-<i>V</i>) loop are widely used in experimental and clinical research, yet their structural foundations remain insufficiently formalized. ESPVR is a phenomenological construct defined from multi-beat (MB) measurements across varying loading conditions, and its SB estimation therefore constitutes an inverse problem. We show that SB estimation of the ESPVR slope (<i>E</i>_es) is intrinsically underdetermined, as a single<i>P</i>-<i>V</i>loop provides fewer independent constraints than unknown parameters. Consequently, any SB method requires auxiliary information to achieve mathematical closure. Using nine high-fidelity<i>P</i>-<i>V</i>loops obtained during vena cava occlusion in a porcine model as a demonstrator dataset, we quantify (i) the sensitivity of the MB-derived<i>E</i>_es,MBto the selection of the<i>P</i>-<i>V</i>loop subset, and (ii) the sensitivity of<i>E</i>_esto representative classes of auxiliary information. The analysis reveals that auxiliary information based solely on population-averaged normalized elastance curves is structurally inconsistent with the MB reference definition. Among the examined candidates, the normalized elastance at the onset of ejection (<i>E</i>_N,dia) exhibits the most favorable structural properties, combining low sensitivity of<i>E</i>_esto estimation errors with a strong empirical association captured by regression modeling. By reframing SB estimation of ESPVR as a structural identifiability problem rather than a purely numerical task, this study establishes criteria for physiologically consistent auxiliary relations and highlights the necessity of large, standardized MB databases for future data-driven SB methodologies.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147687984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of alternative scintillation crystals to improve performance and cost-effectiveness in total-body PET scanner.","authors":"Maryam Ghanbari Khanqah, Alireza Sadremomtaz, Mohammad Babaei Ghane","doi":"10.1088/2057-1976/ae5f99","DOIUrl":"10.1088/2057-1976/ae5f99","url":null,"abstract":"<p><p><i>Introduction.</i>Total-body PET scanners are advanced technologies in medical imaging, enabling whole-body imaging with high precision and sensitivity. They reduce radioactive dose and shorten imaging time. One of the most advanced systems is the Biograph Vision Quadra by Siemens Healthineers, representing the new generation of this technology. With LSO crystals and an axial field of view of 106 cm, it provides complete body imaging in a single scan, improving efficiency and safety. However, their high cost remains a challenge; prices typically range from 3 to 5 million dollars. To reduce costs and improve performance, alternative scintillation crystals such as LYSO, BGO, and NaI (Tl) have been investigated due to their properties of light sensitivity, decay time, and production cost.<i>Materials and methods.</i>The performance of the Biograph Vision Quadra was evaluated using the GATE Monte Carlo simulation tool. Simulations followed NEMA NU 2-2018 standards to assess parameters including image resolution, sensitivity, count rate, and scatter fraction. Data were reconstructed and analyzed using CASToR and AMIDE software.<i>Results.</i>The simulations closely matched experimental data, showing an error rate of about 8% with clinical data, confirming their accuracy. Among the crystals, BGO proved the most cost-effective, offering 19% higher sensitivity than LSO, LYSO, and NaI (Tl), while maintaining adequate spatial resolution and NECR. Although its light output is lower than LSO, BGO's cost-effectiveness and good performance in sensitivity and count rate make it a suitable choice for reducing scanner costs.<i>Conclusion.</i>Replacing LSO with BGO can significantly improve the cost-effectiveness of the Biograph Vision Quadra without compromising image quality. This study highlights the potential for optimizing PET scanners through alternative scintillation materials, improving accessibility and supporting early disease detection in clinical practice.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147687949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-invasive dynamic blood oxygen monitoring system based on multispectral imaging technology.","authors":"JiaXuan Yan, Yi Xie, XiaoJing Chen, YuShi Yang, LiBin Zhu, TianCi Weng, DanFei Huang","doi":"10.1088/2057-1976/ae5f9c","DOIUrl":"10.1088/2057-1976/ae5f9c","url":null,"abstract":"<p><p>Multispectral imaging (MSI) systems leverage the differing optical absorption properties of oxygenated and deoxygenated haemoglobin across various wavelengths to enable non-invasive dynamic monitoring of relative blood oxygen saturation. Existing systems struggle to meet demands for portable, efficient monitoring due to high costs and slow response times. This study developed a compact MSI system utilising a multi-band light-emitting diode array as its light source. Combined with a triple-isosbestic point calibration algorithm, it rapidly generates pseudo-colour maps of blood oxygen distribution. The system was validated in human finger and rabbit small intestine ischemia-reperfusion models. Following occlusion, relative blood oxygen saturation in the ischaemic regions decreased to 66.3% (finger) and 29.5% (small intestine), both significantly distinct from normal areas. Post-reperfusion, the ischaemic regions exhibited marked recovery with characteristic reperfusion response patterns. These findings demonstrate the system's capability to accurately identify hypoxemic zones, indicating its potential for dynamic<i>in vivo</i>blood oxygen monitoring applications.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147687997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A graph deep learning method for diagnosis of Parkinson's disease using brain functional connectivity features.","authors":"Meili Lu, Xiangyu Zhao","doi":"10.1088/2057-1976/ae5dd3","DOIUrl":"10.1088/2057-1976/ae5dd3","url":null,"abstract":"<p><p>Early and precise identification of Parkinson's disease (PD) is crucial for clinical intervention. Resting-state functional magnetic resonance imaging (rs-fMRI) provides a valuable approach for revealing PD-related differences in brain functional connectivity (FC). However, existing methods often focus solely on characterizing the spatial topology of FC while neglecting its time-varying dynamic fluctuations. Furthermore, they frequently exhibit limited generalization capability when dealing with small sample sizes, and their decision-making mechanisms lack interpretability. To address these limitations, this study proposes an interpretable graph convolutional network framework. This framework integrates both static and dynamic FC information to capture both the stable topological structure and the dynamic temporal characteristics of brain networks. Simultaneously, it models population relationships by constructing an inter-subject similarity graph to enhance the model's representational capacity. Additionally, this study incorporates interpretability analysis techniques to deeply dissect the model's decision-making mechanism and identify key brain regions critical for classification. Results demonstrate that the proposed model achieves superior performance in PD classification tasks and exhibits good generalization ability. More importantly, by interpreting the model's decisions, key brain regions associated with PD discrimination were successfully identified. This study provides an effective computational framework for PD identification and offers new insights into understanding its pathological mechanisms.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147653630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}