Astronomy and Computing最新文献

{"title":"Bridging gaps with computer vision: AI in (bio)medical imaging and astronomy","authors":"S. Rezaei ,&nbsp;A. Chegeni ,&nbsp;A. Javadpour ,&nbsp;A. VafaeiSadr ,&nbsp;L. Cao ,&nbsp;H. Röttgering ,&nbsp;M. Staring","doi":"10.1016/j.ascom.2024.100921","DOIUrl":"10.1016/j.ascom.2024.100921","url":null,"abstract":"<div><div>This paper explores how artificial intelligence (AI) techniques can address common challenges in astronomy and (bio)medical imaging. It focuses on applying convolutional neural networks (CNNs) and other AI methods to tasks such as image reconstruction, object detection, anomaly detection, and generative modeling. Drawing parallels between domains like MRI and radio astronomy, the paper highlights the critical role of AI in producing high-quality image reconstructions and reducing artifacts. Generative models are examined as versatile tools for tackling challenges such as data scarcity and privacy concerns in medicine, as well as managing the vast and complex datasets found in astrophysics. Anomaly detection is also discussed, with an emphasis on unsupervised learning approaches that address the difficulties of working with large, unlabeled datasets. Furthermore, the paper explores the use of reinforcement learning to enhance CNN performance through automated hyperparameter optimization and adaptive decision-making in dynamic environments. The focus of this paper remains strictly on AI applications, without addressing the synergies between measurement techniques or the core algorithms specific to each field.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100921"},"PeriodicalIF":1.9,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BIPP: An efficient HPC implementation of the Bluebild algorithm for radio astronomy","authors":"E. Tolley ,&nbsp;S. Frasch ,&nbsp;E. Orliac ,&nbsp;S. Krishna ,&nbsp;M. Bianco ,&nbsp;S. Kashani ,&nbsp;P. Hurley ,&nbsp;M. Simeoni ,&nbsp;J.-P. Kneib","doi":"10.1016/j.ascom.2024.100920","DOIUrl":"10.1016/j.ascom.2024.100920","url":null,"abstract":"<div><div>The Bluebild algorithm is a new technique for image synthesis in radio astronomy which decomposes the sky into distinct energy levels using functional principal component analysis. These levels can be linearly combined to construct a least-squares estimate of the radio sky, i.e. minimizing the residuals between measured and predicted visibilities. This approach is particularly useful for deconvolution-free imaging or for scientific applications that need to filter specific energy levels. We present an HPC implementation of the Bluebild algorithm for radio-interferometric imaging: Bluebild Imaging++ (<span>BIPP</span>). The library features interfaces to C++, C and Python and is designed with seamless GPU acceleration in mind. We evaluate the accuracy and performance of <span>BIPP</span> on simulated observations of the upcoming Square Kilometer Array Observatory and real data from the Low-Frequency Array (LOFAR) telescope. We find that <span>BIPP</span> offers accurate wide-field imaging and has competitive execution time with respect to the interferometric imaging libraries <span>CASA</span> and <span>WSClean</span> for images with <span><math><mrow><mo>≤</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>6</mn></mrow></msup></mrow></math></span> pixels. Furthermore, due to the energy level decomposition, images produced with <span>BIPP</span> can reveal information about faint and diffuse structures before any cleaning iterations. <span>BIPP</span> does not perform any regularization, but we suggest methods to integrate the output of <span>BIPP</span> with CLEAN. The source code of <span>BIPP</span> is publicly released.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100920"},"PeriodicalIF":1.9,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-bogus scores for active anomaly detection","authors":"T.A. Semenikhin ,&nbsp;M.V. Kornilov ,&nbsp;M.V. Pruzhinskaya ,&nbsp;A.D. Lavrukhina ,&nbsp;E. Russeil ,&nbsp;E. Gangler ,&nbsp;E.E.O. Ishida ,&nbsp;V.S. Korolev ,&nbsp;K.L. Malanchev ,&nbsp;A.A. Volnova ,&nbsp;S. Sreejith ,&nbsp;SNAD team","doi":"10.1016/j.ascom.2024.100919","DOIUrl":"10.1016/j.ascom.2024.100919","url":null,"abstract":"<div><div>In the task of anomaly detection in modern time-domain photometric surveys, the primary goal is to identify astrophysically interesting, rare, and unusual objects among a large volume of data. Unfortunately, artifacts — such as plane or satellite tracks, bad columns on CCDs, and ghosts — often constitute significant contaminants in results from anomaly detection analysis. In such contexts, the Active Anomaly Discovery (AAD) algorithm allows tailoring the output of anomaly detection pipelines according to what the expert judges to be scientifically interesting. We demonstrate how the introduction real-bogus scores, obtained from a machine learning classifier, improves the results from AAD. Using labeled data from the SNAD ZTF knowledge database, we train four real-bogus classifiers: XGBoost, CatBoost, Random Forest, and Extremely Randomized Trees. All the models perform real-bogus classification with similar effectiveness, achieving ROC-AUC scores ranging from 0.93 to 0.95. Consequently, we select the Random Forest model as the main model due to its simplicity and interpretability. The Random Forest classifier is applied to 67 million light curves from ZTF DR17. The output real-bogus score is used as an additional feature for two anomaly detection algorithms: static Isolation Forest and AAD. The number of artifacts detected by both algorithms decreases significantly with the inclusion of the real-bogus score in cases where the feature space regions are densely populated with artifacts. However, it remains almost unchanged in scenarios where the overall number of artifacts in the outputs is already small. We conclude that incorporating the real-bogus classifier result as an additional feature in the active anomaly detection pipeline reduces the number of artifacts in the outputs, thereby increasing the incidence of astrophysically interesting objects presented to human experts.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100919"},"PeriodicalIF":1.9,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermodynamic topology of Hot NUT-Kerr-Newman-Kasuya-Anti-de Sitter black hole","authors":"M.U. Shahzad ,&nbsp;Nazek Alessa ,&nbsp;A. Mehmood ,&nbsp;R. Javed","doi":"10.1016/j.ascom.2024.100900","DOIUrl":"10.1016/j.ascom.2024.100900","url":null,"abstract":"<div><div>This work is devoted to studying the thermodynamic topology of Hot Nut-Kerr-Newman-Kasuya-AdS black holes (BHs). To accomplish this, we identify the critical points that play a crucial role in understanding the intricate structure of these BHs. We determine these critical points’ associated topological charges, providing important information about the underlying topology. Furthermore, we explore the concept of zero points and their corresponding winding numbers. These calculations allow us to evaluate the topological number associated with BHs and provide important information about their overall topological characteristics. One of the most important characteristics is the triple critical point. These points support the conjecture that the behavior of BHs undergoes significant transformations, presenting us with unique opportunities to observe and comprehend novel physical phenomena. A winding number of zero corresponds to a simple, connected horizon, while non-zero winding numbers indicate more complex topologies, such as multi-sheeted horizons. For comprehensive analysis, we fixed various parameters, such as the electric and magnetic charges and the electric and magnetic potentials. This approach allows us to isolate and examine specific aspects of BH topology.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100900"},"PeriodicalIF":1.9,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RatanSunPy: A robust preprocessing pipeline for RATAN-600 solar radio observations data","authors":"I. Knyazeva ,&nbsp;I. Lysov ,&nbsp;E. Kurochkin ,&nbsp;A. Shendrik ,&nbsp;D. Derkach ,&nbsp;N. Makarenko","doi":"10.1016/j.ascom.2024.100918","DOIUrl":"10.1016/j.ascom.2024.100918","url":null,"abstract":"<div><div>The advancement of observational technologies and software for processing and visualizing spectro-polarimetric microwave data obtained with the RATAN-600 radio telescope opens new opportunities for studying the physical characteristics of solar plasma at the levels of the chromosphere and corona. These levels remain some difficult to detect in the ultraviolet and X-ray ranges. The development of such methods allows for more precise investigation of the fine structure and dynamics of the solar atmosphere, thereby deepening our understanding of the processes occurring in these layers. The obtained data also can be utilized for diagnosing solar plasma and forecasting solar activity. However, using RATAN-600 data requires extensive data processing and familiarity with the RATAN-600. This paper introduces <span>RatanSunPy</span>, an open-source Python package developed for accessing, visualizing, and analyzing multi-band radio observations of the Sun from the RATAN-600 solar complex. The package offers comprehensive data processing functionalities, including direct access to raw data, essential processing steps such as calibration and quiet Sun normalization, and tools for analyzing solar activity. This includes automatic detection of local sources, identifying them with NOAA (National Oceanic and Atmospheric Administration) active regions, and further determining parameters for local sources and active regions. By streamlining data processing workflows, <span>RatanSunPy</span> enables researchers to investigate the fine structure and dynamics of the solar atmosphere more efficiently, contributing to advancements in solar physics and space weather forecasting.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100918"},"PeriodicalIF":1.9,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermodynamic topology of Phantom AdS black holes in massive gravity via non-extensive entropies","authors":"Abdelhay Salah Mohamed ,&nbsp;M.U. Shahzad ,&nbsp;A. Mehmood ,&nbsp;E.E. Zotos","doi":"10.1016/j.ascom.2024.100909","DOIUrl":"10.1016/j.ascom.2024.100909","url":null,"abstract":"<div><div>In this study, we explore the topological numbers associated with Phantom AdS black holes (BHs) in massive gravity using non-extensive entropies. We analyze their characteristics using various entropy measures, including the Bekenstein–Hawking entropy, Rényi entropy, Barrows entropy, Sharma-Mittal entropy, and the logarithmic-corrected entropy. We observe that the calculated topological number (<span><math><mi>T</mi></math></span>) varies across different entropy measures. Nevertheless, what is particularly intriguing is the persistent coherence in the topological classification of BH, regardless of whether we consider the Rényi entropy, the logarithmic-corrected entropy or the Bekenstein–Hawking entropy.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100909"},"PeriodicalIF":1.9,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New crescent moon detection using Circular Hough Transform (CHT)","authors":"A.L.A.M. Nasir ,&nbsp;R. Umar ,&nbsp;W.N.J.W. Yussof ,&nbsp;N. Ahmad ,&nbsp;A.N. Zulkeflee ,&nbsp;N.H. Sabri ,&nbsp;W.M.Y.W. Chik ,&nbsp;N.A. Mahiddin ,&nbsp;A.H. Bely ,&nbsp;A.I.S. Izdihar","doi":"10.1016/j.ascom.2024.100902","DOIUrl":"10.1016/j.ascom.2024.100902","url":null,"abstract":"<div><div>Over 1.5 billion Muslims worldwide rely on a calendar based on the observation of the new crescent moon, particularly during the Hijri calendar months of Ramadhan, Shawal, and Zulhijjah. Accurately detecting the new crescent moon immediately after its conjunction is essential for ensuring the precision of the calendar, but it poses a technical challenge due to the low contrast between the new crescent moon and its background. This study aimed to solve the challenge of reliably identifying the new crescent moon at this critical phase, which is vital for accurately determining important dates that signify religious events. It intended to create and verify a computer vision model that would greatly improves the precision and efficiency of identifying a new crescent moon based on images. This will assist in precisely identifying important dates relevant to Muslim religious practices. The methodology employs image preprocessing techniques such as Gaussian Blur for image smoothing and Adaptive Thresholding for contrast enhancement to optimize the visibility of the crescent moon in a single image. The Circular Hough Transform (CHT) technique was used to accurately detect the new crescent moon, while the OpenCV software package helped to implement all of these methods, thus, providing a strong foundation for precisely identifying the new crescent moon. Findings of this study, which involved observations at Kolej Ugama Sultan Zainal Abidin (KUSZA) Observatory, Teluk Kemang Observatory, and Miri Observatory, indicate that the utilization of image processing techniques results in significant improvements in both the efficiency and precision of identifying and detecting the new crescent moon. These enhancements exceed the performance of conventional digital imaging methods employed during regular observations. The model’s processing rate surpasses the usual observation efficiency and showcases exceptional accuracy in distinguishing images that feature the new crescent moon from those that do not. In conclusion, the proposed model demonstrates an effective and efficient methodology for improving the precision of lunar calendar management and the quick planning of important Islamic religious events in accordance with the lunar cycle. This technological advancement offers a reliable method for accurately seeing the crescent moon, which has important implications for enhancing the precision of lunar-based calendars and coordinating important Islamic religious occasions.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100902"},"PeriodicalIF":1.9,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Processing of GASKAP-Hi pilot survey data using a commercial supercomputer","authors":"I.P. Kemp ,&nbsp;N.M. Pingel ,&nbsp;R. Worth ,&nbsp;J. Wake ,&nbsp;D.A. Mitchell ,&nbsp;S.D. Midgely ,&nbsp;S.J. Tingay ,&nbsp;J. Dempsey ,&nbsp;H. Dénes ,&nbsp;J.M. Dickey ,&nbsp;S.J. Gibson ,&nbsp;K.E. Jameson ,&nbsp;C. Lynn ,&nbsp;Y.K. Ma ,&nbsp;A. Marchal ,&nbsp;N.M. McClure-Griffiths ,&nbsp;S. Stanimirović ,&nbsp;J. Th. van Loon","doi":"10.1016/j.ascom.2024.100901","DOIUrl":"10.1016/j.ascom.2024.100901","url":null,"abstract":"<div><div>Modern radio telescopes generate large amounts of data, with the next generation Very Large Array (ngVLA) and the Square Kilometre Array (SKA) expected to feed up to 292 GB of visibilities per second to the science data processor (SDP). However, the continued exponential growth in the power of the world’s largest supercomputers suggests that for the foreseeable future there will be sufficient capacity available to provide for astronomers’ needs in processing ‘science ready’ products from the new generation of telescopes, with commercial platforms becoming an option for overflow capacity. The purpose of the current work is to trial the use of commercial high performance computing (HPC) for a large scale processing task in astronomy, in this case processing data from the GASKAP-H<span>i</span> pilot surveys. We delineate a four-step process which can be followed by other researchers wishing to port an existing workflow from a public facility to a commercial provider. We used the process to provide reference images for an ongoing upgrade to ASKAPSoft (the ASKAP SDP software), and to provide science images for the GASKAP collaboration, using the joint deconvolution capability of WSClean. We document the approach to optimising the pipeline to minimise cost and elapsed time at the commercial provider, and give a resource estimate for processing future full survey data. Finally we document advantages, disadvantages, and lessons learned from the project, which will aid other researchers aiming to use commercial supercomputing for radio astronomy imaging. We found the key advantage to be immediate access and high availability, and the main disadvantage to be the need for improved HPC knowledge to take best advantage of the facility.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100901"},"PeriodicalIF":1.9,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143144109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AstroMLab 1: Who wins astronomy jeopardy!?","authors":"Y.-S. Ting (丁源森) ,&nbsp;T.D. Nguyen ,&nbsp;T. Ghosal ,&nbsp;R. Pan (潘瑞) ,&nbsp;H. Arora ,&nbsp;Z. Sun (孙泽昌) ,&nbsp;T. de Haan ,&nbsp;N. Ramachandra ,&nbsp;A. Wells ,&nbsp;S. Madireddy ,&nbsp;A. Accomazzi","doi":"10.1016/j.ascom.2024.100893","DOIUrl":"10.1016/j.ascom.2024.100893","url":null,"abstract":"<div><div>We present a comprehensive evaluation of proprietary and open-weights large language models using the first astronomy-specific benchmarking dataset. This dataset comprises 4,425 multiple-choice questions curated from the Annual Review of Astronomy and Astrophysics, covering a broad range of astrophysical topics.<span><span>¹</span></span> Our analysis examines model performance across various astronomical subfields and assesses response calibration, crucial for potential deployment in research environments. Claude-3.5-Sonnet outperforms competitors by up to 4.6 percentage points, achieving 85.0% accuracy. For proprietary models, we observed a universal reduction in cost every 3-to-12 months to achieve similar score in this particular astronomy benchmark. open-weights models have rapidly improved, with LLaMA-3-70b (80.6%) and Qwen-2-72b (77.7%) now competing with some of the best proprietary models. We identify performance variations across topics, with non-English-focused models generally struggling more in exoplanet-related fields, stellar astrophysics, and instrumentation related questions. These challenges likely stem from less abundant training data, limited historical context, and rapid recent developments in these areas. This pattern is observed across both open-weights and proprietary models, with regional dependencies evident, highlighting the impact of training data diversity on model performance in specialized scientific domains. Top-performing models demonstrate well-calibrated confidence, with correlations above 0.9 between confidence and correctness, though they tend to be slightly underconfident. The development for fast, low-cost inference of open-weights models presents new opportunities for affordable deployment in astronomy. The rapid progress observed suggests that LLM-driven research in astronomy may become feasible in the near future.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"51 ","pages":"Article 100893"},"PeriodicalIF":1.9,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142745130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extended black hole solutions in Rastall theory of gravity","authors":"M. Sharif ,&nbsp;M. Sallah","doi":"10.1016/j.ascom.2024.100897","DOIUrl":"10.1016/j.ascom.2024.100897","url":null,"abstract":"<div><div>We utilize the gravitational decoupling via the extended geometric deformation to extend the Schwarzschild vacuum solution to new black holes in Rastall theory. By employing linear transformations that deform both the temporal and radial coefficients of the metric, the field equations with a dual matter source are successfully decoupled into two sets. The first of these sets is described by the metric for the vacuum Schwarzschild spacetime, while the second set corresponds to the added extra source. Three extended solutions are obtained using two restrictions on the metric potentials and extra source, respectively. For selected values of the Rastall and decoupling parameters, we study the impact of the fluctuation of these parameters on the obtained models. We also investigate the asymptotic flatness of the resulting spacetimes by analysis of the metric coefficients. Finally, the nature of the additional source is explored for each model, via analysis of the energy conditions. It is found among other results that none of the obtained models satisfy the energy conditions, while only the model corresponding to the barotropic equation of state mimics an asymptotically flat spacetime.</div></div>","PeriodicalId":48757,"journal":{"name":"Astronomy and Computing","volume":"50 ","pages":"Article 100897"},"PeriodicalIF":1.9,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}