Dataset

This dataset was created by Prateek

Contents

The X-ray sources from observations made with the Einstein Observatory (HEAO-2) Imaging Proportional Counter (IPC) that have intensities of 2-sigma or more above the background are compiled in this catalog. This catalog covers more sky at fainter flux levels than the Einstein Medium Sensitivity Survey. Fields with diffuse emission sources such as bright Abell clusters of galaxies and supernova remnants were excluded. Thus, data within 10 degrees of the galactic plane as well as fields within the boundaries of the Magellanic Clouds were excluded. Regions crowded with galactic sources such as the Orion and Pleiades fiels were also excluded. Excluding redundant fields, this catalog covers 1850 sq. degrees of the sky. The generation of the Einstein Two-Sigma Catalog was described in detail by Moran et al. (1996). Please read this article carefully to ensure responsible use of the Catalog. Detailed scientific and technical questions on the contents and methodology of this catalog should be addressed to the first author, Ed Moran (edhed@igpp.llnl.gov). In particular, it should be noted that, by design, this catalog contains a significant number of spurious sources: only 28%, or about 13,000 sources, out of the 46,000 source in the 2-sigma catalog are real astrophysical sources, with the remainder of the sources being spurious ones. Moran et al. show in their paper that performing cross-correlations of 2-sigma sources with other catalogs is an effective way of selecting sources in this catalog that are probably real. This is a service provided by NASA HEASARC .

The X-ray sources from the observations with the Einstein Observatory (HEAO-2) with intensities of 2-sigma above the background are compiled in this catalog. This catalog covers more sky at fainter flux levels than the Einstein Medium Sensitivity Survey. Fields with diffuse emission sources were excluded. Thus data within 10 degrees of the galactic plane as well as fields within the boundaries of the Magellanic Clouds were excluded. The catalog covers 1850 sq. degrees of the sky. The generation of the Einstein Two-Sigma Catalog was described in detail by Moran et al. (1996). Read this article carefully to ensure responsible use of the Catalog. Address any questions to Ed Moran (edhed@igpp.llnl.gov). In particular it should be noted that only 28%, or about 13,000 sources in the 2-sigma catalog are real sources. The authors show that cross-correlations with other catalogs is an effective way to select sources in this catalog that are probably real. Cone search capability for table J/ApJ/461/127/twosigma (The 2-sigma catalog)

This data is from the two sigma news competition. The data contains the Category/Industry of each active equity in the train data. Of the 1515 active equities, 40 or so could not be categorized. Classes are labeled: [Factor_0]...[Factor_14] into 15 categories.

Gaussian Sigma 2

## Overview

Gaussian Sigma 2 is a dataset for object detection tasks - it contains GLIOMA annotations for 587 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This European Remote Sensing (ERS) Sigma-0 dataset is generated by the Scatterometer Climate Record Pathfinder (SCP) project at Brigham Young University (BYU) and is generated using a Scatterometer Image Reconstruction (SIR) technique developed by Dr. David Long at BYU. The dataset provides SIR processed Sigma-0 data from the ERS-2 C-band scatterometer, which is also known as the Active Microwave Instrument (AMI). AMI is a multimode radar operating at a frequency of 5.3 GHz (C-band), using vertically polarized antennas for both transmission and reception. The SIR technique results in an enhanced resolution image reconstruction and gridded on an equal-area grid (for non-polar regions) at 8.9 km pixel resolution stored in SIR files; polar regions are gridded at the same resolution using a polar-stereographic technique. A non-enhanced version is provided at 44.5 km pixel resolution in a format known as GRD (i.e., gridded) files. All files are produced in IEEE formatted binary. All data files are separated and organized by region, parameter, and sampling technique (i.e., SIR vs. GRD). The regions of China and Japan are combined into a single region. In addition to Sigma-0, various statistical parameters are provided for added guidance, including but not limited to: standard deviation, measurement counts, pixel time, Sigma-0 error, and average incidence angle. This dataset was once distributed on tape, but has been made available on FTP thanks to the BYU SCP. For more information, please visit: http://www.scp.byu.edu/docs/ERS_user_notes.html

All final posreal counts files for Paramotopy runs with \sigma = 100.

Using laboratory hollow cathode spectra we have identified lines of the less common magnesium isotopologues of MgH, ^25^MgH and ^26^MgH, in the A^2^{Pi}-X^2^{Sigma}^+^ system. Based on the previous analysis of ^24^MgH, molecular lines have been measured and molecular constants derived for ^25^MgH and ^26^MgH. Term values and linelists, in both wavenumber and wavelength units, are presented. The A^2^{Pi}-X^2^{Sigma}^+^ system of MgH is important for measuring the magnesium isotope ratios in stars.

This page contains some well-known datasets (and some original ones) for sorted unsigned 32/64 bit integers. Most of them come from the SOSD learned index benchmark (https://github.com/learnedsystems/SOSD), but a few were generated by "flattening" adjacency lists of graphs.

All binary datasets have a 64-bit preamble containing the dataset size. The filename always ends with uint32 or uint64, specifying the number of bits used for storing the integers.

Specifics about the single datasets will follow:

• books_200M_uint32: "amzn" dataset from SOSD
• books_800M_uint64: larger slice (and 64-bit version) of the "amzn" dataset in SOSD
• companynet_uint32: flattened adjacency list of a proprietary (companies) network. Its size is 1 million items.
• exponential_uint32: 50 million integer dataset following an exponential distribution (z=2, all items then multiplied by uint32_max/5).
• fb_200M_uint64: "fb" dataset from SOSD.
• friendster_50M_uint32: flattened adjacency list of the "friendster" network from https://snap.stanford.edu/data/com-Friendster.html.
• lognormal_uint32: 50 million integer dataset following a lognormal distribution (mu = 0, sigma = 0.5, all items then multiplied by uint32_max/5).
• normal_800M_uint32: 800 million integer dataset following a normal distribution (mu = uint32_max/2, sigma = uint32_max/4).
• normal_uint32: 50 million integer dataset following a normal distribution (mu = uint32_max/2, sigma = uint32_max/4).
• osm_cellids_800M_uint64: "osm" dataset from SOSD.
• wiki_ts_200M_uint32: "wiki" dataset from SOSD, but integers are all cast to 32 bits.
• wiki_ts_200M_uint64: "wiki" dataset from SOSD.
• zipf_uint32: 50 million integer dataset following a Zipf distribution (q = 0.7, max_val = uint32_max/2).
• books_50M_uint64: 50M slice of the 64-bit "amzn" dataset from SOSD

This dataset contains the ISS-RapidScat Version 2.0 Level 1B geo-located Sigma-0 measurements and antenna pulse "egg" and "slice" geometries as derived from ephemeris and the Level 1A dataset. The pulse "egg" represents the complete footprint of the pulse, which has a spatial geometry of approximately 25 km by 35 km. There are 8 slices that constitute the range-binned components of a pulse each of which has a spatial geometry of approximately 25 km by 7 km. The orientation of the long dimension of the slices varies with the rotation of the antenna and thus does not align with the along/across track orientation of the wind vector grid in the L2B/L2A products. Version 2.0 represents a complete historical re-processing of the L1B data record (see the technical note for Version 2.0 under Documentation). Data are provided in single-orbit files in HDF-4 format. This dataset is intended for expert use only. If you must use RapidScat Sigma-0 data but you are unsure about how to use the L1B data record, please consider using either of the following L2A datasets: 1) https://podaac.jpl.nasa.gov/dataset/RSCAT_L2A_25KM_V2.0 or 2) https://podaac.jpl.nasa.gov/dataset/RSCAT_L2A_12KM_V2.0. If you have any questions or concerns, please visit our Forum at https://podaac.jpl.nasa.gov/forum/. RapidScat is a Ku-band dual beam circular rotating scatterometer retaining much of the same hardware and functionality of QuikSCAT, with exception of the antenna sub-system and digital interface to the ISS Columbus module, which is where RapidScat is mounted. The NASA mission is officially referred to as ISS-RapidScat. Unlike QuikSCAT, ISS-RapidScat is not in sun-synchronous orbit, and flies at roughly half the altitude with a low inclination angle that restricts data coverage to the tropics and mid-latitude regions; the extent of latitudinal coverage stretches from approximately 61 degrees North to 61 degrees South. Furthermore, there is no consistent local time of day retrieval.

This table contains (some of) the results from an X-ray imaging survey of the young cluster NGC 2264, carried out with the European Photon Imaging Cameras (EPIC) on board the XMM-Newton spacecraft. XMM-Newton EPIC observations were made separately of the northern and southern portions of NGC 2264 on 2001 March 20 and 2002 March 17 - 18, respectively. Details concerning the two pointings are summarized in Table 1 of the reference paper. The nominal integration time was 42 ks for both observations. The three EPIC cameras were operated in full window mode. To prevent contamination of the X-ray images by the XUV and EUV emission of the optically and UV-bright sources in the field of view, the thick filter was used, which imposes a strong cut-off in the response at the lower energies. The X-ray data are merged with extant optical and near-infrared photometry, spectral classifications, H-alpha emission strengths, and rotation periods to examine the interrelationships between coronal and chromospheric activity, rotation, stellar mass, and internal structure for a statistically significant sample of pre-main-sequence stars. Out of the 316 distinct point-like sources that were detected at >= 3-sigma levels in one or more of six EPIC images, a total of 300 distinct X-ray sources can be identified with optical or near-infrared counterparts. The sources are concentrated within three regions of the cluster: in the vicinity of S Mon, within the large emission/reflection nebulosity southwest of S Mon, and along the broad ridge of molecular gas that extends from the Cone Nebula to the NGC 2264 IRS 2 field. From the extinction-corrected color-magnitude diagram of the cluster, ages and masses for the optically identified X-ray sources are derived. A median age of ~ 2.5 Myr and an apparent age dispersion of ~ 5 Myr are suggested by pre-main-sequence evolutionary models. The X-ray luminosity of the detected sources appears well-correlated with bolometric luminosity, although there is considerable scatter in the relationship. Stellar mass contributes significantly to this dispersion, while isochronal age and rotation do not. X-ray luminosity and mass are well correlated such that L_X ~ (M/M_solar)^1.5, which is similar to the relationship found within the younger Orion Nebula Cluster. No strong evidence is found for a correlation between E(H-K), the near-infrared color excess, and the fractional X-ray luminosity, which suggests that optically thick dust disks have little direct influence on the observed X-ray activity levels. Among the X-ray-detected weak-line T Tauri stars, the fractional X-ray luminosity, L_X/L_bol, is moderately well correlated with the fractional H-alpha luminosity, L_H(alpha)/L_bol, but only at the 2-sigma level of significance. The cumulative distribution functions for the X-ray luminosities of the X-ray-detected classical and weak-line T Tauri stars within the cluster are comparable, assuming the demarcation between the two classes is at an H-alpha equivalent width of 10 Angstroms. However, if the non-detections in X-rays for the entire sample of H-alpha emitters known within the cluster are taken into account, then the cumulative distribution functions of these two groups are clearly different, such that classical T Tauri stars are underdetected by at least a factor of 2 relative to the weak-line T Tauri stars. Examining a small subsample of X-ray-detected stars that are probable accretors based on the presence of strong H-alpha emission and near-infrared excess, the authors conclude that definitive non-accretors are ~ 1.6 times more X-ray luminous than their accreting counterparts. In agreement with earlier published findings for the Orion Nebula Cluster, the authors find a slight positive correlation (valid at the 2-sigma confidence level) between L_X/L_bol and the rotation period in NGC 2264 stars. The lack of a strong anti-correlation between X-ray activity and rotation period in the stellar population of NGC 2264 suggests that either the deeply convective T Tauri stars are rotationally saturated or that the physical mechanism responsible for generating magnetic fields in pre-main-sequence stars is distinct from the one that operates in evolved main-sequence stars. This table was created by the HEASARC in September 2007 based on the electronic version of Table 2 from the reference paper which was obtained from the electronic AJ site. This is a service provided by NASA HEASARC .

SMAP Level 1B Sigma Naught Low Res Product Version 2

This table contains some of the results of an analysis of the full EPIC field in an XMM-Newton observation of the young (~2 - 4 Myr) cluster around the hot star sigma Orionis. The authors have detected 175 X-ray sources, 88 of which have been identified with cluster members, including very low-mass stars down to the substellar limit. They detected eleven new possible candidate members from the 2MASS (CDS Cat. ) catalog. The authors find that late-type stars have a median log L_X/L_bol ~ -3.3, i.e. very close to the saturation limit. They detected significant variability in ~ 40% of late-type members or candidates, including 10 flaring sources; rotational modulation was detected in one K-type star and possibly in another 3 or 4 stars. Spectral analysis of the brightest sources shows typical quiescent temperatures in the range T₁ ~ 0.3 - 0.8 keV and T₂ ~ 1 - 3 keV, with subsolar abundances Z ~ 0.1 - 0.3 solar, similar to what is found in other star-forming regions and associations. The authors find no significant difference in the spectral properties of classical and weak-lined T Tauri stars, although classical T Tauri stars tend to be less X-ray luminous than weak-lined T Tauri stars. XMM-Newton observations of the sigma Ori cluster, centered on the hot star sigma Ori AB, were carried out as part of the Guaranteed Time of Roberto Pallavicini using both the EPIC MOS and PN cameras and the RGS instrument. The observation (ID 0101440301) started at 21:47 UT on March 23, 2002 and ended at 9:58 UT on March 24, 2002, for a total duration of 43 ks. The EPIC cameras were operated in Full Frame mode using the thick filter. This table contains the combined list of 88 X-ray sources positionally (<= 5") associated with confirmed or candidate cluster members, and 66 X-ray sources with no such positional associations, detected above a significance threshold of 5 sigma. The two X-ray sources (source numbers 67 and 167) with 2 possible positional associations are listed twice, once for each positional association, with the X-ray information repeated. Thus, there are 156 entries in this HEASARC table. This table was created by the HEASARC in May 2007 based on CDS catalog J/A+A/446/501 files tablea1.dat and tableb.dat. This is a service provided by NASA HEASARC .

This dataset contains operational near-real-time Level 2 coastal ocean surface wind vector retrievals from the Advanced Scatterometer (ASCAT) on MetOp-B at 12.5 km sampling resolution (note: the effective resolution is 25 km). It is a product of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) provided through the Royal Netherlands Meteorological Institute (KNMI). This coastal dataset differs from the standard 12.5 and 25 km datasets in that it utilizes a spatial box filter (rather than the Hamming filter) to generate a spatial average of the Sigma-0 retrievals from the Level 1B dataset; all full resolution Sigma-0 retrievals within a 15 km radius of the wind vector cell centroid are used in the averaging. Since the full resolution L1B Sigma-0 retrievals are used, all non-sea retrievals are discarded prior to the Sigma-0 averaging. Each box average Sigma-0 is then used to compute the wind vector cell using the same CMOD5.n geophysical model function as in the standard OSI SAF ASCAT wind vector datasets. With this enhanced coastal retrieval, winds can be computed as close to ~15 km from the coast, as compared to the static ~35 km land mask in the standard 12.5 km dataset. Each file is provided in netCDF version 3 format, and contains one full orbit derived from 3-minute orbit granules. Latency is approximately 2 hours from the latest measurement. The beginning of the orbit is defined by the first wind vector cell measurement within the first 3-minute orbit granule that starts north of the Equator in the ascending node. ASCAT is a C-band dual swath fan beam radar scatterometer providing two independent swaths of backscatter retrievals in sun-synchronous polar orbit aboard the MetOp-B platform. For more information on the MetOp-B mission, please visit: https://www.eumetsat.int/our-satellites/metop-series . For more timely announcements, users are encouraged to register with the KNMI scatterometer email list: scat@knmi.nl. Users are also highly advised to check the dataset user guide periodically for updates and new information on known problems and issues. All intellectual property rights of the OSI SAF products belong to EUMETSAT. The use of these products is granted to every interested user, free of charge. If you wish to use these products, EUMETSAT's copyright credit must be shown by displaying the words "copyright (year) EUMETSAT" on each of the products used.

In this paper, we present the results of searching the Kepler Q2 public data set for the secondary eclipses of 76 hot Jupiter planet candidates from the list of 1235 candidates published by Borucki et al., 2011, Cat. J/ApJ/736/19. This search has been performed by modeling both the Kepler pre-search data conditioned light curves and new light curves produced via our own photometric pipeline. We derive new stellar and planetary parameters for each system, while calculating robust errors for both. We find 16 systems with 1{sigma}-2{sigma}, 14 systems with 2{sigma}-3{sigma}, and 6 systems with >3{sigma} confidence level secondary eclipse detections in at least one light curve produced via the Kepler pre-search data conditioned light curve or our own pipeline; however, results can vary depending on the light curve modeled and whether eccentricity is allowed to vary or not. We estimate false alarm probabilities of 31%, 10%, and 6% for the 1{sigma}-2{sigma}, 2{sigma}-3{sigma}, and >3{sigma} confidence intervals, respectively.

This dataset contains the ISS-RapidScat Version 2.0 Level 1B geo-located Sigma-0 measurements and antenna pulse "egg" and "slice" geometries as derived from ephemeris and the Level 1A dataset. The pulse "egg" represents the complete footprint of the pulse, which has a spatial geometry of approximately 25 km by 35 km. There are 8 slices that constitute the range-binned components of a pulse each of which has a spatial geometry of approximately 25 km by 7 km. The orientation of the long dimension of the slices varies with the rotation of the antenna and thus does not align with the along/across track orientation of the wind vector grid in the L2B/L2A products. Version 2.0 represents a complete historical re-processing of the L1B data record and provides a calibration which is consistent across the several signal to noise ratio states experienced by RapidScat throughout its operation period (see the technical note for Version 2.0 under Documentation). The Version 2.0 is also the dataset used to derive the Version 2.0 wind products (L2B). Data are provided in single-orbit files in HDF-4 format. This dataset is intended for expert use only. If you must use RapidScat Sigma-0 data but you are unsure about how to use the L1B data record, please consider using either of the following L2A datasets: 1) https://podaac.jpl.nasa.gov/dataset/RSCAT_L2A_25KM_V2.0 or 2) https://podaac.jpl.nasa.gov/dataset/RSCAT_L2A_12KM_V2.0. RapidScat is a Ku-band dual beam circular rotating scatterometer retaining much of the same hardware and functionality of QuikSCAT, with exception of the antenna sub-system and digital interface to the ISS Columbus module, which is where RapidScat is mounted. The NASA mission is officially referred to as ISS-RapidScat. Unlike QuikSCAT, ISS-RapidScat is not in sun-synchronous orbit, and flies at roughly half the altitude with a low inclination angle that restricts data coverage to the tropics and mid-latitude regions; the extent of latitudinal coverage stretches from approximately 61 degrees North to 61 degrees South. Furthermore, there is no consistent local time of day retrieval.

URL: https://geoscience.data.qld.gov.au/dataset/cr017947

PL 34, SSL SIGMA 2, WELL COMPLETION REPORT

SMAP Level 1C Sigma Naught High Res Product Version 2

VoroCrack3d is an annotated data set of 3d CT images of concrete with synthetic crack structures. Its main purpose is the training and testing of machine learning models for 3d crack segmentation. The data set comprises 1344 images together with their corresponding ground truths. The concrete backgrounds are cropped out sections of size 400x400x400 voxels of CT images of concrete. To this end, several different concrete samples were scanned (normal concrete (NC), high-performance concrete (HPC), ultra-high-performance concrete (UHPC), air pore concrete; without and with reinforcements (straight steel fibers, crimped steel fibers, hooked-end steel fibers, polypropylene fibers, fibers made of glass fiber-reinforced polymer). The original concrete images have a resolution between 2.8 and 106 micrometers.

The crack structures are modeled via minimum-weight surfaces in Voronoi diagrams according to the paper

[1] C. Jung, C. Redenbach, Crack Modeling via Minimum-Weight Surfaces in 3d Voronoi Diagrams, Journal of Mathematics in Industry, 13, 10 (2023). https://doi.org/10.1186/s13362-023-00138-1.

The surfaces are discretized, dilated and superimposed on the concrete backgrounds.

The data set offers a high variety regarding concrete types, noise levels and crack widths, shapes, regularity and branching. This makes it suitable for studying the generalizability and robustness of 3d crack segmentation methods.

The folder 'data' contains seven subfolders, each containing the data generated from a specific concrete type (NC, HPC, air pore concrete, polypropylene fiber-reinforced concrete, steel fiber-reinforced concrete (straight, crimped and hooked-end steel fibers)).

Each subfolder again contains four subfolders according to the point process model that was used for generating the 3d Voronoi diagrams. The point processes and Voronoi diagrams are restricted to windows of size 400x150x400.

• 'hc': Hard core point process with 60% volume density and intensity 0.000025 obtained from force-biased sphere packing.- 'matclust': Matérn cluster process with parent intensity 0.0002/50, offspring intensity 50 and cluster radius 20.- 'ppp': Poisson point process with intensity 0.0002.- 'ppp-scaled': Poisson point process with intensity 0.0002 (but inside 200x150x200 window). The resulting Voronoi diagram is stretched in x- and z- direction by a factor of 2.

Each of these contains five subfolders: one for the 3d input images, two for the corresponding labels (ground truths; one with and one without pores/fibers), one for the input and label previews (slice z=200 for each of the images) and a misc folder containing the concrete background without crack and, if applicable, the pore/fiber segmentation image.

The data itself then contains 48 images:1a-1d: crack with up to seven branches; fixed crack width (~1 voxel).2a-2d: crack with up to four branches; fixed crack width (~1 voxel).3a-3d: crack with up to one branch; fixed crack width (~1 voxel).4a-4d: crack with no branches; fixed crack width (~1 voxel).5a-5d: crack with no branches; fixed crack width (~3 voxels).6a-6d: crack with no branches; fixed crack width (~5 voxels).7a-7d: crack with no branches; fixed crack width (~7 voxels).8a-8d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.01);9a-9d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.02);10a-10d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.05);11a-11d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.1);12a-12d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.2);

The names 'a'-'d' indicate level of added noise added to the image:a: None.b: Uniformly on [-sigma,sigma] c: Uniformly on [-2*sigma,2*sigma] d: Uniformly on [-4*sigma,4*sigma] Negative values are mapped to 0. For inputs of type int, noise values are rounded to the nearest integer.(sigma = standard deviation of voxel greyvalues in image)

Note that the labels in the ground truths correspond to the local crack width.

For more details, we refer to [1].

URL: https://geoscience.data.qld.gov.au/dataset/bh001588