Data set corresponding to "NAPS: Integrating pose estimation and tag-based tracking." This dataset contains the corresponding videos, tracking scripts, and SLEAP models along with SLEAP, NAPS, and ArUco tracking results.
Zweben SJ, Myra JR, Diallo A, Russell DA, Scotti F, Stotler DP
Transient small-scale structures were identified in the wake of blobs movingpoloidally through the SOL of high-powered H-mode plasmas in NSTX, using the gaspuff imaging (GPI) diagnostic. These blob wakes had a poloidal wavelength in therange 3.5 cm, which is significantly smaller than the average blob scale of~12 cm, and the wakes had a poloidal velocity of 1.5 km/sec in theelectron diamagnetic direction, which is opposite to the blob poloidal velocity inthese shots. These wakes were radially localized 0-4 cm outside the separatrix andoccurred within ~50 microsec after the passage of a blob through the GPI field of view.The clearest wakes were seen when the GPI viewing angle was well aligned with thelocal B field line, as expected for such small-scale structures given the diagnosticgeometry. A plausible theoretical interpretation of the wakes is discussed: theobserved wakes share some features of drift waves and/or drift-Alfven waves whichcould be excited
The Magnetospheric Multiscale (MMS) mission has given us unprecedented access to high cadence particle and field data of magnetic reconnection at Earth's magnetopause. MMS first passed very near an X-line on 16 October 2015, the Burch event, and has since observed multiple X-line crossings. Subsequent 3D particle-in-cell (PIC) modeling efforts of and comparison with the Burch event have revealed a host of novel physical insights concerning magnetic reconnection, turbulence induced particle mixing, and secondary instabilities. In this study, we employ the Gkeyll simulation framework to study the Burch event with different classes of extended, multi-fluid magnetohydrodynamics (MHD), including models that incorporate important kinetic effects, such as the electron pressure tensor, with physics-based closure relations designed to capture linear Landau damping. Such fluid modeling approaches are able to capture different levels of kinetic physics in global simulations and are generally less costly than fully kinetic PIC. We focus on the additional physics one can capture with increasing levels of fluid closure refinement via comparison with MMS data and existing PIC simulations. In particular, we find that the ten-moment model well captures the agyrotropic structure of the pressure tensor in the vicinity of the X-line and the magnitude of anisotropic electron heating observed in MMS and PIC simulations. However, the ten-moment model has difficulty resolving the lower hybrid drift instability, which has been observed to plays a fundamental role in heating and mixing electrons in the current layer.
Complete dataset of pore water chemical parameters measured at the Marsh Resource Meadowlands Mitigation Bank, a tidal marsh within the New Jersey Meadowlands, from March 2011 to April 2012. Analytes measured include dissolved methane, sulfate, dissolved organic carbon, temperature, salinity, and pH. Measurements were conducted using porewater dialysis samplers, and water was sampled from the surface to a depth of 60 cm.
This dataset contains all the data, model and MATLAB codes used to generate the figures and data reported in the article (DOI: 10.1002/2014JD022278). The data was generated during September 2013 and February 2014 using the Ocean-Land-Atmosphere Model also provided with this package. The data was generated using the computational resources supported by the PICSciE OIT High Performance Computing Center and Visualization Laboratory at Princeton University. The dataset contains a pdf Readme file which explains in detail how the data can be used. Users are recommended to go through this file before using the data.
A subset of the Fermi-LAT public data for use with NPTFit:
The data here is for use with the Jupyter example notebooks provided with the
main code. Details of the files provided are given below. All files are provided
as numpy arrays binned as nside=128 HEALPix maps.
For the full public data, see: