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2,113 results for “High resolution”
A 30-year high resolution simulation of the future climate over the Interior Western United States
<p>A high-resolution (4 km) convection-permitting regional climate simulation is conducted in the Interior Western United States (IWUS) using the Weather Research and Forecasting (WRF) model. The model integration is conducted over a 30-year period from October 1981 through September 2011, and over a 30-year future period centered at 2050 using the Pseudo–Global Warming (PGW) technique. The IWUS model output for the retrospective climate is available from https://doi.org/10.5281/zenodo.1157112.</p> <p>This repository contains a 30-year gridded dataset of precipitation, surface (2 m) temperature, surface pressure, water vapor mixing ratio at 2 m, and 10 m wind speed at a daily frequency from the IWUS simulation of future climate centered at 2050. Anyone interested in the full dataset of the IWUS simulation is encouraged to contact the lead author at yongganga.wang@gmail.com.</p>
Data From: TERRA-REF, An open reference data set from high resolution genomics, phenomics, and imaging sensors
<p>The ARPA-E funded TERRA-REF project is generating open-access reference datasets for the study of plant sensing, genomics, and phenomics. Sensor data were generated by a field scanner sensing platform that captures color, thermal, hyperspectral, and active flourescence imagery as well as three dimensional structure and associated environmental measurements. This dataset is provided alongside data collected using traditional field methods in order to support calibration and validation of algorithms used to extract plot level phenotypes from these datasets.</p> <p>Data were collected at the University of Arizona Maricopa Agricultural Center in Maricopa, Arizona. <br> This site hosts a large field scanner with fifteen sensors, many of which are capable of capturing mm-scale images and point clouds at daily to weekly intervals.</p> <p>These data are intended to be re-used, and are accessible as a combination of files and databases linked by spatial, temporal, and genomic information. In addition to providing open access data, the entire computational pipeline is open source, and we enable users to access high-performance computing environments.</p> <p>The study has evaluated a sorghum diversity panel, biparental cross populations, and elite lines and hybrids from structured sorghum breeding populations. <br> In addition, a durum wheat diversity panel was grown and evaluated over three winter seasons.<br> The initial release includes derived data from from two seasons in which the sorghum diversity panel was evaluated.<br> Future releases will include data from additional seasons and locations.</p> <p>The TERRA-REF reference dataset can be used to characterize phenotype-to-genotype associations, on a genomic scale, that will enable knowledge-driven breeding and the development of higher-yielding cultivars of sorghum and wheat. <br> The data is also being used to develop new algorithms for machine learning, image analysis, genomics, and optical sensor engineering.</p>
Dataset of "Gravity Wave Activity in the Atmosphere of Mars During the 2018 Global Dust Storm: Simulations With a High-Resolution Model" (1/2)
<p>This dataset contains the GrADS data of high-resolution Mars GCM results used for figures in the paper "Gravity Wave Activity in the Atmosphere of Mars During the 2018 Global Dust Storm: Simulations With a High-Resolution Model" by T. Kuroda, A.S. Medvedev and E. Yiğit.</p> <p>Each file with the name starting 'data' contains two-dimensional (X: longitude, Y: latitude) data of surface pressure (Ps) (unit: hPa) and dust opacity in infrared wavelength (tau), and three-dimensional (X: longitude, Y: latitude, Z:sigma-level) data of temperature (T) (unit: K), zonal wind velocity (u) (unit: m/s), meridional wind velocity (v) (unit: m/s) and vertical wind velocity (w) (unit: m/s), in snapshots of every 1/6 Sol for the periods of 30 degrees in Ls per a file as described below. The dust scenario implemented for producing this dataset is taken from Montabone et al. (2020), which is based on the observed dust opacity in Mars Year 24 (MY34).</p> <p>data180rdc-my34.tar.xz: for Ls=180-210 (49 Sols)</p> <p>data210rdc-my34.tar.xz: for Ls=210-240 (47 Sols)</p> <p>data240rdc-my34.tar.xz: for Ls=240-270 (46 Sols)</p> <p>The .tar.xz files can be extracted in Linux with 'tar Jxvf' command, and .grd and .ctl files with the same stem are generated.</p> <p>The file 'flux61ls5-my34.tar.xz' contains the three-dimensional fluxes and physical parameters calculated from the model output with the MY34 dust scenario. The contents are (T')^2, (u')^2, (v')^2, u'v', u'w', v'w' T(bar), u(bar), v(bar), squared Brunt-Vaisala frequency, and geopotential height. (bar) denotes the sum of the total wavenumber s=0-60 components, and the dash denotes the deviation from (bar), i.e. sum of the total wavenumber s=61-106 components. There are 36 time grids between Ls=182.5 and Ls=357.5 with the step of Ls=5 degrees. Kinetic and potential energies can be derived from these values using the formulae in the paper.</p> <p>The file 'flux61ls5-lowdust.tar.xz' is the same as 'flux61ls5-my34.tar.xz', except the model output with the 'low-dust' scenario (Kuroda et al., 2019; Kuroda, 2019a, 2019b).</p> <p>The file 'scripts.zip' contains the FORTRAN scripts to derive the fluxes and physical parameters equivalent to the file 'flux61ls5-my34.tar.xz' from the model outputs in this dataset and Kuroda (2020), i.e. data180rdc-my34.tar.xz, data210rdc-my34.tar.xz, data240rdc-my34.tar.xz, data270rdc-my34.tar.xz, data300rdc-my34.tar.xz and data330rdc-my34.tar.xz. Also, the fluxes and physical parameters equivalent to the file 'flux61ls5-lowdust.tar.xz' can be derived with those scripts from the model outputs data180rdc.tar.xz, data210rdc.tar.xz, data240rdc.tar.xz, data270rdc.tar.xz, data300rdc.tar.xz and data330rdc.tar.xz which are available in Kuroda (2019a, 2019b).</p>
Global High Resolution Dust Emission Inventory for Chemical Transport Models
<p><strong>Overview:</strong><br> ==================================================================================</p> <p>Offline dust emissions in 2016 are now available at 0.25° x 0.3125° resolution. This dataset is calculated using the native resolution <a href="http://wiki.seas.harvard.edu/geos-chem/index.php/GEOS-FP">GMAO meteorology (GEOS-FP) fields</a>. </p> <p>Codes and Instructions (README file in the GitHub repository) to generate these offline emissions can be found on <a href="https://github.com/Jun-Meng/geos-chem/tree/v11-01-Patches-UniCF-vegetation">GitHub</a>.</p> <p>The offline emissions in this database have no scale factor applied, so users should apply the required scale factor in their application. Suggested scale factor to make the global total annual dust emission to 2000 Tg is 5.7141e-4. </p> <p><br> <strong>Zip File Details:</strong><br> ===============================================================================</p> <p>2016.zip contains daily (366 in total) netCDF files (stored in monthly folders) of global gridded hourly mineral dust emission flux rate. </p> <p> </p> <p>Individual file: </p> <p>/YYYY/MM/dust_emissions_025x0.3125.YYYYMMDD.nc</p> <p> Resolution : 0.25 x 0.3125 grid (721 x 1152 boxes)<br> Units : kg m-2 s-1<br> Timestamps : Hourly, 2016<br> Compression : Level 1 (nccopy -d1)<br> Chunking : nccopy -c lon/1152,lat/721,time/24</p> <p> </p> <p>Variables in each file: </p> <p>EMIS_DST1, EMIS_DST2, EMIS_DST3 and EMIS_DST4 represent dust emission flux rate in four size bins (0.1-1.0, 1.0-1.8, 1.8-3.0, and 3.0-6.0 micro in radius). </p> <p> </p> <p>*<em>Version 2020_v1.0 of this dataset was produced to accompany the following manuscript:<br> Meng, Jun, R. V. Martin, P. Ginoux, M. Hammer, M. P. Sulprizio, D. A. Ridley, and A. van Donkelaar, Grid-independent high resolution dust emissions (v1.0) for chemical transport models: application to GEOS-Chem (version 12.5.0), Geoscientific Model Development, Submitted</em></p>
Monitoring recent changes in the Beaufort Sea coast using very high resolution remote sensing
<p>Arctic permafrost coasts are major carbon (Schuur et al., 2015) and mercury pools (Schuster et al., 2018). They represent about 34% of the Earth’s coastline, with long sections affected by high erosion rates (Fritz et al, 2017), increasingly threatening coastal communities. Year-round reduction in Arctic sea ice is forecasted and by the end of the 21st century, models indicate a decrease in sea ice area from 43 to 94% in September and from 8 to 34% in February (IPCC, 2014). An increase of the sea-ice free season leads to a longer exposure of coasts to wave action. Further, climate warming is also expected to modify the contribution of terrestrial erosion (Fritz et al., 2015, Ramage et al., 2018, Irrgang et al., 2018). Within the project EU Horizon2020 project NUNATARYUK, we are updating the mapping of the Arctic coast, with the Canadian Beaufort coast as a case-study. The surveying methodology includes: i. a high resolution update of the coastline mapping and change rates using Pleiades (CNES) satellite acquisitions from 2018, ii. a survey using RTK-UAV aerial imagery of long-term monitoring sites from the Canada-US border to King Point, and iii. the experimental use of TerraSAR-X staring spotlight scenes and PAZ at key sites to monitor intraseasonal dynamics of cliff edge retreat. This research is funded by the EC H2020 Project NUNATARYUK. Support on remote sensing imagery access by the WMO Polar Space Task Group.</p>
High Resolution Fundus Image Database for Monomodal Single-Channel Image Registration of Thin Features
<p>A high resolution image database of 42 image pairs (related by elastic deformations) created from original images from the High Resolution Fundus Image Database.<br> <br> Consists of thin linear structures that lack sufficient overlap to pose a challenge for classic similarity measures based on overlapping pixels commonly used in image registration.</p> <p>The dataset contains the intensity grayscale images, as well as binary masks of the retinal area, and labels of the vessels, segmented by expert annotators.<br> </p>
An automatically generated high-resolution earthquake catalogue for the 2016-2017 Central Italy seismic sequence, including P and S phase arrival times
<p>Catalog of 440,697 earthquakes of the 2016-2017 Central Italy seismic sequence semi-automatically generated by Spallarossa et al. (2020). The catalogue covers one year of aftershocks following the first mainshock of the sequence (from 08242016 to 08312017).</p> <p>The catalog has been generated using the Complete Automatic Seismic Processor (CASP) procedure (Scafidi et al., 2019) to detect the events and an advanced picker engine (RSNI-Picker<sub>2</sub>; Scafidi et al., 2018; Spallarossa et al., 2014) to determine their phase arrival times. The final set of about 7 million P- and 10 million S-wave arrival times have been used to locate the events using a non-linear location algorithm (NonLinLoc; Lomax et al. 2000), with a 1D velocity model calibrated for the area (De Luca et al., 2009) and station corrections. For each event, also local magnitudes (M<sub>L</sub>) has been calculated as well as a locations quality.</p> <p>Earthquake locations quality has been classified by means of the procedure proposed by Michele et al., (2019) consisting of the combination of diverse uncertainty parameters provided by the NonLinLoc location code. Locations quality is provided in terms of a unique numeric normalized value, named quality factor, varying between qf=0 (best quality location) and qf=1 (worst quality location). Then locations have been assigned to a quality class depending on the qf parameter value according to the following scheme: A-class (0 < qf ≤ 0.25), B-class (0.25 < qf ≤ 0.50), C-class (0.50 < qf ≤ 0.75), and D-class (0.75 < qf < 1.00). The earthquake locations are distributed between the quality classes as A-30.6%, B-31.4%, C-18.6%, and D-19.4% (details in Spallarossa et al., 2020).</p> <p>We accompanied the catalogue with the 30 events with M>3.5 missed by our procedure (bring the total number of events to 440,727), including the first Amatrice mainshock (M<sub>W</sub>6.0; see Spallarossa et al., 2020). These 30 missing events recognisable by the ID starting with ISI), have been taken from INGV bulletin (<a href="http://terremoti.ingv.it">http://terremoti.ingv.it</a>; ISIDe Working Group., 2007), manually generated. These additional events report INGV locations and magnitude parameters while are missing related quality factors and quality class, being generated by a different procedure.</p> <p>We added to the larger events, the available moment magnitudes (M<sub>W</sub>) from Time Domain Moment Tensor catalogue (<a href="http://terremoti.ingv.it/tdmt">http://terremoti.ingv.it/tdmt</a>; Scognamiglio et al., 2006).</p> <p>The catalog is in csv format, semicolon separator, ordered by origin time and the header content is the following:</p> <ul> <li>Id-event – ID</li> <li>Latitude (°) expressed in decimal degrees - LAT</li> <li>Longitude (°) expressed in decimal degrees - LON</li> <li>Depth(km) hypocentral depth expressed in kilometres - DEP</li> <li>Year of origin time in the format yyyy - YR</li> <li>Month of origin time in the format mo - MON</li> <li>Day of origin time in the format dd - DY</li> <li>Hour of origin time in the format hh - HR</li> <li>Minute of origin time in the format mi - MIN</li> <li>Second of origin time in the format XX.XXX s - SEC</li> <li>Local Magnitude - ML</li> <li>Standard deviation of the Local Magnitude – STD</li> <li>Moment Magnitude – Mw (from TDMT)</li> <li>Horizontal Error (from NLL output) (km) expressed in kilometres - ERH</li> <li>Vertical Error (from NLL output) (km) expressed in kilometres - ERZ</li> <li>RMS (from NLL output) (s) expressed in seconds - RMS</li> <li>Number of Phases – NPHS</li> <li>Stations Azimuthal GAP (°) expressed in decimal degrees - GAP</li> <li>Quality factor - Qf</li> <li>Quality class - Qc</li> </ul> <p> </p> <p>De Luca G., M. Cattaneo, G. Monachesi and A, Amato (2009). Seismicity in the Umbria-Marche region from the integration of national and regional seismic networks. Tectonophysics, 476(1), 219-231. doi: 10.1016/j.tecto.2008.11.032.</p> <p>ISIDe Working Group. (2007). Italian Seismological Instrumental and Parametric Database (ISIDe). Istituto Nazionale di Geofisica e Vulcanologia (INGV); https://doi.org/10.13127/ISIDE.</p> <p>Lomax, A., J. Virieux, P. Volant, and C. Berge-Thierry (2000). Probabilistic earthquake location in 3D and layered models: introduction of a Metropolis–Gibbs method and comparison with linear locations. In: Advances in seismic event location, ed. C. H. Thurber and N. Rabinowitz, 101–134. Dordrecht and Boston: Kluwer Academic Publishers.</p> <p>Michele, M., Latorre, D., Emolo, A. (2019). An Empirical Formula to Classify the Quality of Earthquake Locations. Bulletin of the Seismological Society of America. Vol. 109, No. 6, pp. 2755–2761, December 2019, doi: 10.1785/0120190144.</p> <p>Scafidi, D., Viganò A., Ferretti G., and Spallarossa D. (2018). Robust picking and accurate location with RSNI-Picker2: real-time automatic monitoring of earthquakes and non-tectonic events, Seismol. Res. Lett, Vol. 89 (4), pp. 1478-1487, doi: 10.1785/0220170206.</p> <p>Scafidi D, Spallarossa D, Ferretti G, Barani S, Castello B, Margheriti L (2019). A complete automatic procedure to compile reliable seismic catalogs and travel-time and strong-motion parameters datasets. Seismol Res Lett 90(3):1308–1317.</p> <p>Scognamiglio, L., Tinti, E., Quintiliani, M. (2006). Time Domain Moment Tensor [Data set]. Istituto Nazionale di Geofisica e Vulcanologia (INGV). https://doi.org/10.13127/TDMT.</p> <p>Spallarossa, D., G. Ferretti, D. Scafidi, C. Turino, and M. Pasta (2014). Performance of the RSNI-Picker, Seismol. Res. Lett. 85, 1243–1254.</p> <p>Spallarossa D., Cattaneo M., Scafidi D., Michele M., Chiaraluce L., Segou M. and I. G. Main (2020). An automatically generated high-resolution earthquake catalogue for the 2016-2017 Central Italy seismic sequence, including P and S phase arrival times. Geophys. J. Int. doi: 10.1093/gji/ggaa604.</p>
Data from: Multi-modal ultra-high resolution structural 7-Tesla MRI data repository
Structural brain data is key for the understanding of brain function and networks, i.e., connectomics. Here we present data sets available from the 'atlasing of the basal ganglia (ATAG)' project, which provides ultra-high resolution 7Tesla (T) magnetic resonance imaging (MRI) scans from young, middle-aged, and elderly participants. The ATAG data set includes whole-brain and reduced field-of-view MP2RAGE and T2*-weighted scans of the subcortex and brainstem with ultra-high resolution at a sub-millimeter scale. The data can be used to develop new algorithms that help building high-resolution atlases both relevant for the basic and clinical neurosciences. Importantly, the present data repository may also be used to inform the exact positioning of electrodes used for deep-brain-stimulation in patients with Parkinson's disease and neuropsychiatric diseases.
Anatomy of the neural endocranium and stapes of Diadectes absitus (Diadectomorpha) from the early Permian of Germany based on the high‐resolution X‐ray microcomputed tomography
<p>A detailed anatomy of the braincase and stapes of the subadult specimen of <i>Diadectes absitus</i> from early Permian sediments of Germany based on the high-resolution X-ray microcomputed tomography are described for the first time. In contrast to previous studies of <i>Diadectes</i>, the bones of the braincase (opisthotic, prootic, supraoccipital, basioccipital, exoccipital, basisphenoid, sphenethmoid), and parasphenoid of <i>D. absitus</i> are not co-ossified, but suturally defined. This has allowed for a reconstruction of a complete braincase with all sutures between the individual bones. The opisthotic, prootic, and supraocciptal contain a well-preserved endosseous labyrinth. The 3D-reconstruction of its cavities shows a well-preserved vestibule, three semicircular canals, and well-developed cochlear recess. In addition, a shallow subarcuate fossa is present on the ventral surface of the supraoccipital, which lies medial to the anterior semicircular canal. A typical feature of the diadectid braincase is the presence of the otic tube leading from the fenestra vestibuli to the vestibule. A revision of the topology of this structure is presented here. Here we describe new structures of the stapes, especially in its proximal portion, as well as its position to the fenestra vestibuli. These structures are described for the first time not only in <i>D. absitus</i>, but for the genus.</p>
Montreal high-resolution climate data
<p>This proof-of-concept study couples machine learning and physical modelling paradigms to develop a computationally efficient simulator-emulator framework for generating super-resolution (< 250 m) urban climate information, that is required by many sectors. The temperature and dew point fields for 2019 and 2020 and the geophysical fields (geophys.rar) for the study domain, at 2.5 km (LR) and 250 m (HR) resolutions, which are used to train and validate the proposed super-resolution deep learning (DL) model/emulator are provided. </p>
Figure 6. High-resolution x in Two new catfish species of typically Amazonian lineages in the Upper Rio Paraguay (Aspredinidae: Hoplomyzontinae and Trichomycteridae: Vandelliinae), with a biogeographic discussion
Figure 6. High-resolution x-ray computerized microtomography (HRXCT) of Ernstichthys taquari, MZUSP 125825, holotype, 22.8 mm SL. (a) Dorsal view, (b) lateral view of left side, (c) ventral view. acf: anterior cranial fontanel; ach: anterior ceratohyal; ang: anguloarticular; bp: basipterygium; br: branchiostegal rays; cl: cleithrum; co: coracoid; cv: complex vertebra; den: dentary; ds: dorsal shield element; eap: expanded first anal-fin pterygiophore (= second ventral shield); ehs: expanded hemal spine (= first ventral shield); fr: frontal; hyo: hyomandibula; io1: first infraorbital; iop: interopercle; let: lateral ethmoid; lp: lateral plate element (= expanded lateral-line ossicle); mes: mesethmoid; mnp: middle nuchal plate; mx: maxilla; op: opercle; pa: parasphenoid; pal: palatine; pch: posterior ceratohyal; pfr: pelvic-fin rays; pfs: pectoral-fin spine; pmx: premaxilla; pnp: posterior nuchal plate (= first dorsal shield); pso: parietosupraoccipital; pto: pterotic; pv5: parapophysis of fifth vertebra; qu: quadrate; sc: posttemporosupracleithrum; spo: sphenotic; vh: ventral hypohyal; vs: ventral shield element.
Ormond Castle, Avoch (High resolution model)
**(High resolution model, which may take some time to load and may not be suitable for portable devices)** Following a site survey in March 2016 carried out by members of Avoch Community Archaeology (ACA) and the North of Scotland Archaeological Society (NOSAS), this 3d model of Ormond Hill has been produced. Many hitherto unknown features were recorded, adding to our knowledge of the site, which is far more complex than Beaton's plan of 1885 might suggest. Further investigation/excavation is planned. https://canmore.org.uk/site/13572/ormond-castle (Special thanks to Alan Thompson of NOSAS for permitting the use of his photographs in creating the model.) Source: Objaverse 1.0 / Sketchfab
Greyside 2022 dig high resolution
3D model made from 40 photos to record final state of main excavation trench in 2nd season archaeology dig in March 2022 at Greyside near Warden, Northumberland. In 2022 a 2m (N-S) x 10m (E-W) trench was excavated along the axis of the farmstead eastwards (with a small overlap) from the 2020 trench which focussed on the western part of the central compartment shown to be a byre. It crossed the wall between the central compartment, entering the eastern compartment. Later it was extended southwards each side of this wall, reaching the south wall of the farmstead. A second small trench 0.8m (N-S) x 3.5m (E-W) was dug across the east wall of the farmstead, to examine the floor in the east end of the eastern compartment. Source: Objaverse 1.0 / Sketchfab
Trilobite - Printable (high resolution)
Trilobite fossil found in Mount Holyoke College's Skinner Museum! Photogrammetry by Laura Shea, model constructed using Agisoft Photoscan and help from Laura Shea. Created as part of a final project for Mark McMenamin's Geosciences in the Makerspace course. Highest resolution possible. Source: Objaverse 1.0 / Sketchfab
High-resolution air temperature observations near the surface using fiber-optic distributed temperature sensing
<p>Time-lapse animation of air temperature observations near the surface, highlighting wave-like motion in opposite direction of the mean wind. </p> <p> </p>
Data for "The effect of pattern overlap on the accuracy of high resolution electron backscatter diffraction measurements"
<p>Data for "The effect of pattern overlap on the accuracy of high resolution electron backscatter diffraction measurements"</p> <p>Vivian Tong1, Jun Jiang1, Angus J Wilkinson2, and T Ben Britton1<br /> 1. Department of Materials, Imperial College London, Prince Consort Road, London, SW7 2AZ, UK<br /> 2. Department of Materials, University of Oxford, Parks Road, Oxford, OX1 3PH, UK</p> <p>For more information please contact: b.britton@imperial.ac.uk (Ben Britton)</p> <p>--<br /> The zip contains three subfolders:<br /> Fig4 Interaction volume measurement<br /> Fig14 Error approaching gb<br /> Fig16 GrainBoundaryProbability</p> <p>--<br /> Further details:</p> <p>Fig4 Interaction volume measurement -</p> <p>Measurement and simulation data of EBSD inteaction volume</p> <p>Includes calculated model & EBSD patterns for measurement<br /> EBSD patterns are from Zircaloy-4 and scanned on a Bruker eFlashHR camera in high resolution mode (1600 x 1200) attached to a Zeiss Auriga-40 SEM. The sample was tilted to 70 degrees and the SEM image shows the tilt corrected scanned region.</p> <p><br /> Fig14 Error approaching gb -<br /> 15 patterns are included that were used to create many simulated grain boundary pairs. These were captured from the same sample as used in Fig4.<br /> The spreadsheet details results shown in Fig 4.</p> <p><br /> Fig 16 GrainBoundary Pobability -<br /> This describes results from the simple Voronoi tessalation model (virtual grain structure) and sampling with a fixed step size, similar to a real EBSD scan. Probabilities were calcualted for different interaction volume sizes and critical distances.</p> <p> </p>
Globular Cluster Abundances from High-Resolution, Integrated-Light Spectroscopy. II. Expanding the Metallicity Range for Old Clusters and Updated Analysis Techniques
<p>Data from:</p> <p> Globular Cluster Abundances from High-Resolution, Integrated-Light Spectroscopy.<br> II. Expanding the Metallicity Range for Old Clusters and Updated Analysis Techniques (Astrophysical Journal)</p> <p> J. E. Colucci, R. A. Bernstein, A. McWilliam, Observatories of the Carnegie Institution for Science</p> <p>This repository contains reduced globular cluster integrated light echelle spectra in IRAF readable format. <br> NOTE: Spectra are *not* flux calibrated or doppler corrected. Sky/Background emission and absorption lines <br> are present. See reference paper for data reduction details.</p> <p>For each globular cluster:<br> <br> 1. *Approximately* normalized spectra are found in files ending with "ils_normalized.fits." The echelle<br> blaze function normalization was performed with an order by order fit to spectra of a reference G-type star.</p> <p> 2. Unnormalized spectra are found in files ending with "ils.fits." These spectra are not flux calibrated so do not<br> use the count values in each order for science purposes. </p> <p><br> Spectra for the globular clusters NGC 104, NGC 362, NGC 2808, NGC 6093, NGC 6397, NGC 6752 were <br> taken with the DuPont telescope. A reference star spectrum associated with the DuPont data is included : hr914_std.fits</p> <p>Spectra for the globular clusters NGC 6388, NGC 6440, NGC 6441, NGC 6528, NGC 6553 were taken with the <br> MIKE spectrograph on Magellan Clay. A reference star spectrum associated with this data is included: ltt9239_std.fits</p> <p>Spectra for the globular cluster Fornax 3 was taken with the MIKE spectrograph on Magellan Clay on a different run. <br> A reference star spectrum associated with this data is included: hd033771_std.fits</p> <p>This research was supported by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under award AST-1302710.</p>
High-resolution tracking of microbial colonization in Fecal Microbiota Transplantation experiments via metagenome-assembled genomes
<p>This project contains anvi'o profiles and contigs databases that is used and/or referenced from the Lee STM and Khan SA, <em>et al.</em> study titled "<strong>High-resolution tracking of microbial colonization in Fecal Microbiota Transplantation experiments via metagenome-assembled genomes</strong>". The pre-print of this study is available via http://dx.doi.org/10.1101/090993.</p> <p>To be able to work with the data files you will need anvi'o <strong>v2.1.0</strong> to be installed on your system. For installation instructions, or to have access to a Docker image for anvi'o, please visit this URL: http://merenlab.org/software/anvio</p> <p>Public data:</p> <ul> <li><strong>ANVIO-FMT-D-R01-R02-QUICK-VISUALIZATION.tar.gz</strong>: Data files for a quick visualization of the 97 MAGs and their distribution across the two FMT recipients. A run script in the archive explains how to use this data.<br> </li> <li><strong>ANVIO-FMT-D-R01-R02-MERGED-PROFILE.tar.gz</strong>: The merged anvi'o profile for the entire data, which also contains a collection of 97 MAGs identified in the donor. The profile database contains no hierarchical clustering of contigs, however, individual MAGs can be displayed via the following notation since the collection 'MAGs' describe the organization of contigs in each MAG referenced from the dataset `ANVIO-FMT-D-R01-R02-QUICK-VISUALIZATION`, as well as from the paper: "anvi-refine -c CONTIGS.db -p PROFILE.db -C MAGs -b <em>FMT-Donor_MAG_00054</em>". All MAG names are in the supplementary tables in our paper.<br> </li> <li><strong>ANVIO-FMT-D-R01-R02-MAGs-SUMMARY.tar.gz</strong>: A static HTML website that contains FASTA files for each MAG, and TAB-delimited matrices for coverage and detection values, and others. After unpacking, you can double-click the index.html file. </li> </ul>
Raw data sets for: A simple calculation algorithm to seperate high-resolution CH4 flux measurements into ebullition- and diffusion derived components (AMT)
<p>Raw data sets for the research article "A simple calculation algorithm to seperate high-resolution CH4 flux measurements into ebullition- and diffusion derived components", published in "Atmospheric Measurment Techniques" (AMT). Data sets include raw data sets for the field and laboratory study, as well as calculated CH4 fluxes (field).</p>
High resolution X-ray diffraction images for yeast 5-aminolevulinic acid dehydratase complexed with levulinic acid.
<p>X-ray diffraction images collected at DESY Hamburg in June 1998 using beamline BW7B. </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.