Mendeley Data Showcase

System for Rapid Analysis of Ionospheric Dynamics based on GNSS TEC Signals (S-RAID) performs downloading, parsing, and processing of Global Navigation Satellite System (GNSS) signal measurements and their geometry of observations, calculation of slant and vertical total electron contents (sTEC and vTEC) and subsequent visualization for selected band-passes of fluctuations with periods shorter than two hours. In a routine operation, the System processes 15/30 sec GNSS signal measurements over Continental United States (CONUS) from ~2700 stations. Raw GNSS signal measurements are collected from public archives, including The Crustal Dynamics Data Information System (CDDIS), EarthScope/UNAVCO, National Oceanic and Atmospheric Administration (NOAA), and Scripps Institution of Oceanography's Orbit and Permanent Array Center (SOPAC). The System is oriented towards rapid access to GNSS sTEC/vTEC data for the investigation of traveling ionospheric disturbances (TIDs) of various nature, from large scale TIDs to irregularities of ~10s of km and minutes of periods, in particular those driven by atmospheric acoustic and gravity wave dynamics. The details of data processing methodology are provided in the manuscript (1). Currently, this archive provides an access to high-resolution visualization of processed vTEC mapped over CONUS for years 01/2017-12/2025 (Version 3 to the left - includes full archive). The structure of the archive: /YYYY/MM/DD/animation.mp4, where YYYY - year, MM - month, DD - day of month, animation.mp4 - temporally evolving visualization of processed vTEC (see Steps to Reproduce for the details of data processing methodology). To reference the archive or the methodology for data processing, we suggest to: (1) Cite the manuscript: Inchin, P. A., Deshpande, K. B., Egan, S., Lay, E. H., Obenberger, K. S., Zettergren, M. D., & Snively, J. B. (2025). Ionospheric disturbances in GNSS TEC data: SpaceX Falcon 9 deorbit maneuvers over CONUS in April–May 2024. Geophysical Research Letters, 52, e2024GL112364. https://doi.org/10.1029/2024GL112364 (2) Cite this archive by its DOI: 10.17632/jbx98yscmd.1, and/or Being processed in an automated regime, the visualizations may contain errors and bugs and thus should be used with caution as is. If you encounter any issues or wish to obtain data for animation replication, contact P.A. Inchin pinchin@cpi.com, J.B. Snively snivelyj@erau.edu or M.D. Zettergren zettergm@erau.edu. Research is supported by DARPA Cooperative Agreement HR00112120003. This work is approved for public release; distribution is unlimited. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.

Date (local and GMT), Time (local and GMT), Latitude (decimal degrees N), Longitude (decimal degrees W), Station, Depth of images (m), Volume filtered (m^3), Marine snow particle size (area mm2), Abundance (count/m^3). Files names are CruiseDate (Month/Year)_Station: WB0810_DSH08. SIPPER used a high speed Dalsa Piranha-2 line-scan camera and a pseudo-collimated LED generated light sheet to image the shadows and outlines of resolvable particles that passed through a 100 cm2 field of view. The operational optical resolution of the system is ~65 um. SIPPER was towed at speeds between 2-3 knots in an oblique profile through the water column, spending approximately equal amounts of time at each meter of depth between the surface and 300 m. At stations with a bottom depth shallower than 300 m, SIPPER was towed within approximately 5 m from the seafloor. Imaging and environmental data were stored internally on a Firewire hard drive and processed upon retrieval of the SIPPER instrument from a deployment using a customized software package called the Plankton Image Classification and Extraction Software (PICES). PICES was used to extract images of interest, classify them using user-specified training libraries and to manage the SIPPER images and environmental data collected. The particle size spectra show the size dependence of particles and follows the methods described in Jackson & Burd (1998) and Jackson & Checkley (2011). A normalized particle volume spectrum (nVd) was calculated, where n is particle abundance, V is particle volume, and d is the median particle diameter within each size bin. Pixel width of images was fixed, while pixel length took into account the flow rate and scan rate. The pixel area of each image was determined, and the equivalent spherical diameter (ESD) and volume (V) were calculated based on the optical cross-section. The ESD is defined as the diameter of a circle having the same area as the projected image of the particle (Billiones et al., 1999). Particle diameter (d) size bins ranged from 0.100 to 105.12 mm, where each bin size increased in a geometric progression by about 6% (bin size scale, k = 21/12) over the previous one, since the number of large particles is rare compared to the abundance of smaller sized particles. Normalizing the abundance data (n) to volume (V) gives more weight to larger sized particles. SIPPER Environmental Sensors. Environmental data were collected simultaneously with the SIPPER imaging system during each deployment. Sensors included a Seabird 19Plus CTD, Seabird SBE43 oxygen sensor, and WET Labs FLNTURTD chlorophyll fluorescence and turbidity, and a transmissometer. AWET Labs CDOM sensor also was used on a few cruises. Sensors were calibrated at Seabird and WET Labs and then integrated into the SIPPER towed platform.

Marine snow images were collected using the towed SIPPER v.3 camera system, which was developed by the College of Marine Science, University of South Florida, to assess the abundance and distribution of particles, phytoplankton, zooplankton, and larval fish (Remsen et al., 2004). Particles were sampled through a square 9.6 cm sampling tube, having a 92.2 cm2 mouth area, which extended in front of the towed platform. As particles passed down the tube they were imaged by a Dalsa Piranha-2 line-scan camera, which imaged 36,000 lines per second and used a pseudo-collimated LED generated light sheet to image the shadows and outlines of resolvable particles. The Plankton Imaging Classification Extraction Software (PICES) was used to extract and classify SIPPER images using a Support Vector Machines (SVM) approach, and to manage the images and environmental data collected (Kramer, 2010). A total of 117,058,275 marine snow images were validated for this project. All particles > 0.053 mm2 (area of 100 pixels) were extracted. This dataset provides measures of marine snow particle shape (elongation) and surface roughness (fractal dimension) during and after the Deepwater Horizon oil spill between May 2010 and August 2014. Elongation ratios (ER) were determined as ER = 1 - aspect ratio, where the aspect ratio is the minor axis length of the particle over the major axis length. Fractal dimension were used to assess the surface roughness or boundary irregularity of particles and were computed using a variation of the box counting method in which the grid comprised rectangular boxes maintaining the same aspect ratio as the particle (Kilps et al. 1994, Brown 1995). File names are: NormalizedDataReport_Cruise name_Station name. Both elongation ratios and fractal dimensions are ratios and therefore do not have units. Depth is in meters; Volume sampled is in m^3; ESDbinstart is the Equivalent Spherical Diameter (ESD) of the particle at the beginning of a size range; ESDbinend is the end of the size range; Particle size is in millimeters; TotalNumberOfParticlesAtDepthESD is the total number of particles in the size range at the listed depth (no units); Elongation is the elongation ratio (no units) of particles in the size range an the listed depth; FractalDim is the fractal dimension of the particles (no units); Abundance is the number of particles in the ESD size range at the listed depth having the listed elongation ratio and fractal dimension.

Marine snow images were collected using the towed SIPPER v.3 camera system, which was developed by the College of Marine Science, University of South Florida, to assess the abundance and distribution of particles, phytoplankton, zooplankton, and larval fish (Remsen et al., 2004). Particles were sampled through a square 9.6 cm sampling tube, having a 92.2 cm2 mouth area, which extended in front of the towed platform. As particles passed down the tube they were imaged by a Dalsa Piranha-2 line-scan camera, which imaged 36,000 lines per second and used a pseudo-collimated LED generated light sheet to image the shadows and outlines of resolvable particles. The Plankton Imaging Classification Extraction Software (PICES) was used to extract and classify SIPPER images using a Support Vector Machines (SVM) approach, and to manage the images and environmental data collected (Kramer, 2010). A total of 117,058,275 marine snow images were validated for this project. All particles > 0.053 mm2 (area of 100 pixels) were extracted. This dataset provides measures of marine snow particle shape (elongation). Elongation ratios (ER) were determined as ER = 1 - aspect ratio, where the aspect ratio is the minor axis length of the particle over the major axis length. Elongation ratios do not have units. File names are: NormalizedDataReport_Cruise name_station name. Depth is in meters; Volume sampled is in m^3; ESDbinstart is Equivalent Spherical Diameter (ESD) beginning of a size range; ESDbinend is the end of the size range; Particle size is in millimeters; TotalNumberOfParticlesAtDepthESD is the total number of particles in the size range at the listed depth (no units); Elongation is the elongation ratio (no units); Abundance is the number of particles in the ESD size range at listed depth having the listed elongation ratio.

Supplemental Material

Studies on Pulmonary Fibrosis Western Blot Raw data

Collectively, our findings support a hierarchical assembly paradigm in the coffee rhizosphere, whereby soil physicochemical properties define the primary rules of community membership and function, and the root metabolome provides secondary, taxa-specific modulation. This conceptual framework offers a theoretical basis for steering rhizosphere microbiomes toward more sustainable and functional states through soil-focused management strategies.

Environmental Factor Data from 1,120 Sampling Sites in the Southern Subtropics

Freely available dataset compiled from publicly available sources, describing allogeneic CAR-T therapy outcomes in hematologic malignancies.

This repository contains supplementary material for the article "Strategy vs. Direct-Response Method: Evidence from a Large Online Experiment on Simple Social Dilemmas" by Marcus Roel and Zhuoqiong Chen; https://doi.org/10.1016/j.geb.2025.10.010