Summary The Veterans Affairs Precision Oncology Data Repository (VA-PODR) is a large, nationwide repository of de-identified data on patients diagnosed with cancer at the Department of Veterans Affairs (VA). Data include longitudinal clinical data from the VA's nationwide electronic health record system and the VA Central Cancer Registry, targeted tumor sequencing data, and medical imaging data including computed tomography (CT) scans and pathology slides. A subset of the repository is available at the Genomic Data Commons (GDC) and The Cancer Imaging Archive (TCIA), and the full repository is available through the Veterans Precision Oncology Data Commons (VPODC). By releasing this de-identified dataset, we aim to advance Veterans' health care through enabling translational research on the Veteran population by a wide variety of researchers.
We use the magnetic field measurements from four spacecraft of the Cluster-II mission (three events from 2005 to 2015) for the analysis of turbulent processes in the Earth's magnetotail. For this study we conduct the spectral, wavelet and statistical analysis. In the framework of statistical examination, we determine the kurtosis for selected events and conduct extended self-similarity evaluation (analysis of distribution function moments of magnetic field fluctuations on different scales). We compare the highorder structure function of magnetic fluctuations during dipolarization with the isotropic Kolmogorov model and threedimensional log-Poisson model with She-Leveque parameters. We obtain power-law scaling of the generalized diffusion coefficient (the power index that varies within the range of 0.2-0.7). The obtained results show the presence of superdiffusion processes. We find the significant difference of the spectral indices for the intervals before and during the dipolarization. Before dipolarization the spectral index lies in the range from − 1.68 ± 0.05 to −2.08 ± 0.05 (∼ 5/3 according to the Kolmogorov model). During dipolarization the type of turbulent motion changes: on large timescales the turbulent flow is close to the homogeneous models of Kolmogorov and Iroshnikov-Kraichnan (the spectral index lies in the range from −2.20 to −1.53), and at smaller timescales the spectral index is in the range from −2.89 to −2.35 (the Hall-MHD model). The kink frequency is less than or close to the average value of the proton gyrofrequency.The wavelet analysis shows the presence of both direct and inverse cascade processes, which indicates the possibility of self-organization processes, as well as the presence of Pc pulsations.
Abstract. We use the ferroprobe measurements from four spacecraft of Cluster-2 mission (3 events from 2005 to 2015) for the analysis of turbulent processes in the Earth's magnetotail. For this study we conduct the spectral, wavelet and statistical analysis. In the framework of statistical examination, we determine the kurtosis for selected events and conduct extended selfsimilarity evaluation (analysis of distribution function moments of magnetic field fluctuations on different scales). We compare high order structure function of magnetic fluctuations during dipolarization with isotropic Kolmogorov and three-dimensional The wavelet analysis shows the presence of both direct and inverse cascade processes, which indicates the possibility of self-organization processes, as well as the presence of Pc pulsations. 15Copyright statement.
e18094 Background: Gen3 is an open source software platform for developing and operating data commons. Gen3 systems are now used by a variety of institutions and agencies to share and analyze large biomedical datasets including clinical and genomic data. One of the challenges of working with these datasets is disparate clinical data standards used by researchers across different studies and fields. We have worked to address these hurdles in a variety of ways. Methods: Gen3 is an open source software platform for developing and operating data commons. Detailed specification and features can be found at https://gen3.org/ with code located on GitHub ( https://github.com/UC-cdis ). Results: The Gen3 data model is a graphical representation of the different nodes or classes of data that have been collected. Examples include diagnosis, demographic, exposure, and family history. The properties and values on each node are controlled by the data dictionary specified by the data commons creator. While each commons may have a unique data model and dictionary, specifying external standards allows for easier submission of new data and assists data consumers with interpretation of results. A variety of external references can be supported, but here we demonstrate the use of the National Cancer Institute Thesaurus (NCIt). NCIt provides reference terminologies and biomedical standards that contain a rich set of terms, codes, definitions, and concepts. Using the same reference standards across commons allows for the export of clinical data between commons. The Portable Format for Biomedical Data (PFB) was created to facilitate data export and to allow the data dictionary schema as well as the raw data to be compressed and exported. This new file format, which utilizes an Avro serialization, is small, fast, easy to modify, and enables simple data export and import. PFB also has the ability to house entire external reference ontologies and it is easy to update the PFB references as changes are introduced. Conclusions: We have shown here how the Gen3 data model, use of external reference standards for clinical data, and the export/import format of PFB enable the harmonization of clinical data across different data commons.
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