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13,117 results for “Maps”
Map 4 in Genus Monacha FITZINGER 1833 in Bulgaria (Gastropoda, Pulmonata, Hygromiidae)
Map 4. Distribution of Monacha (Monacha) ocellata (ROTH 1839) (UTM-grid, 10 km-squares).
Map 3 in Description de quelques insectes nouveaux ou peu connus.
Map 3: Distribution of Lobrathium farsicum in Iran.
Map 1 in Description de quelques insectes nouveaux ou peu connus.
Map 1: Distribution of Lobrathium anale, based on examined records.
Map 1 in On some Acanthoglossa and Hypomedon species II. Two new species, a new synonymy, and additional records (Coleoptera: Staphylinidae: Paederinae)
Map 1: Distribution of Hypomedon galilaeus based on examined records.
Map 1 in On Oxypoda besucheti FOCARILE (Coleoptera: Staphylinidae: Aleocharinae: Oxypodini)
Map 1: Geographic position of the study region.
Map 2 in On Oxypoda besucheti FOCARILE (Coleoptera: Staphylinidae: Aleocharinae: Oxypodini)
Map 2: Localities where material of the Tectusa besucheti was collected.
Map 2 in New species and records of Staphylinidae from Greece, with two new synonymies (Insecta: Coleoptera)
Map 2: Distribution of Xantholinus pantokratoris BORDONI in Greece, based on examined records.
Map 1 in New species and records of Staphylinidae from Greece, with two new synonymies (Insecta: Coleoptera)
Map 1: Distribution of Xantholinus moreanus sp.n. in southern Greece.
Map 9 in On some species of Oxypoda MANNERHEIM from Turkey and adjacent regions (Insecta: Coleoptera: Staphylinidae Aleocharinae)
Map 9: Distribution of Oxypoda collaris in the eastern Mediterranean, based on examined records.
Map 10 in On some species of Oxypoda MANNERHEIM from Turkey and adjacent regions (Insecta: Coleoptera: Staphylinidae Aleocharinae)
Map 10: Distribution of Oxypoda disiuncta in the eastern Mediterranean.
Map 3 in On some species of Oxypoda MANNERHEIM from Turkey and adjacent regions (Insecta: Coleoptera: Staphylinidae Aleocharinae)
Map 3: Distribution of Oxypoda libanotica in the Eastern Mediterranean, based on examined records.
Map 2 in On some species of Oxypoda MANNERHEIM from Turkey and adjacent regions (Insecta: Coleoptera: Staphylinidae Aleocharinae)
Map 2: Distribution of Oxypoda cristata in Greece and Turkey.
Map 3 in Nine new species and additional records of Staphylinidae from southern Spain, with new synonymies (Insecta: Coleoptera)
Map 3: Distribution of Oxypoda flavissima nov.sp.
Modelling a Medieval Metropolis: A Virtual Map of Angkor, circa 1300
<p>Paper presented on Friday 11 June 2021 at the Digital Medievalist Global Symposium <em>The past, present, and future of Digital Medieval Studies</em> for the Asia & Oceania Panel, in the session Virtual Reconstructions.</p> <p>This presentation overviews the development of an extensive virtual map of the medieval capital of Angkor, Cambodia, and the diverse sources that inform the 3D models from which the virtual world is made.</p> <p> </p>
Dataset : Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps
<ul> <li><strong>The three files in the dataset are:</strong></li> </ul> <p>1) Healthy Sheep Atria Fibre Orientation Dataset 300µm</p> <p>2) Heart Failure Sheep Atria Fibre Orientation Dataset 300µm</p> <p>3) Human Atria Fibre Orientation Dataset 330µm</p> <ul> <li><strong>Data is stored as numpy binary files. Given below is an example .py script to open the flat datasets:</strong></li> </ul> <p> import numpy as np<br> data = np.load("Human_330um.npy")</p> <ul> <li><strong>Volume and fibre orientation dataset stored in flat format as given below:</strong></li> </ul> <p> i, j, k, v1, v2, v3, ... repeated for each voxel </p> <p>where (i, j, k) are voxel coordinates and (v1, v2, v3) are vector components corresponding to fibre orientation within that voxel.</p>
Galactic maps of H2, reconstructed from the CfA CO survey
<p>Maps of galactic H<sub>2</sub>, reconstructed from the CfA CO survey (Dame et al., ApJ 547 (2001) 792) data, <a href="https://www.cfa.harvard.edu/rtdc/">downloaded from the SAO Radio Telescope Data Center</a>, using a Bayesian variational inference approach.</p> <p>Here, we provide the mean and standard deviation of the gas density (in cm<sup>-3</sup>) on a three-dimensional 512x512x16 grid, spanning -16 kpc < x < 16 kpc, 16 kpc < y < 16 kpc and -0.5 kpc < z < 0.5 kpc, both for the BEG03 and the SBM15 gas flow models:</p> <ul> <li> <p>H2_dens_mean_BEG03.fits</p> </li> <li> <p>H2_dens_stddev_BEG03.fits</p> </li> <li> <p>H2_dens_mean_SBM15.fits</p> </li> <li> <p>H2_dens_stddev_SBM15.fits</p> </li> </ul> <p>In addition, we also publish the mean and standard deviation of the mass surface density (in M<sub>sun</sub> pc<sup>-2</sup>) on a two-dimensional 512x512 grid, spanning -16 kpc < x < 16 kpc and 16 kpc < y < 16 kpc, again for both gas flow models:</p> <ul> <li> <p>H2_surf_mass_dens_mean_BEG03.fits</p> </li> <li> <p>H2_surf_mass_dens_stddev_BEG03.fits</p> </li> <li> <p>H2_surf_mass_dens_mean_SBM15.fits</p> </li> <li> <p>H2_surf_mass_dens_stddev_SBM15.fits</p> </li> </ul> <p>Throughout, we have assumed an CO-to-H<sub>2</sub> conversion factor X<sub>CO</sub>=2 10<sup>20</sup> molecules cm<sup>-2</sup> (K km s<sup>-1</sup>)<sup>-1</sup>. Refer to the FITS headers for more detailed information and see <a href="https://arxiv.org/abs/2012.15770">arXiv:2012.15770</a> for a detailed description of the reconstruction as well as a comparison with earlier studies.</p> <p>When using the deprojected gas maps in your research work, please refer to this Zenodo dataset and the following publication<br> P. Mertsch and A. Vittino, "Bayesian inference of three-dimensional gas maps: I. Galactic CO", <a href="https://arxiv.org/abs/2012.15770">arXiv:2012.15770</a>.</p>
Mapping the irrecoverable carbon in Earth's ecosystems
<p>These datasets provide global maps of carbon density (aboveground, belowground biomass carbon and soil organic carbon stocks) for the year 2010 and 2018 at ~300-m spatial resolution in Mg ha-1 (Coordinate System: WGS 1984, float format). Input maps were collected from published literature, and where necessary, updated to cover the focal time period. These updates were applied to the manageable carbon, vulnerable carbon and irrecoverable carbon maps. Manageable carbon is carbon in terrestrial and coastal ecosystems that could experience an anthropogenic land-use conversion event . Vulnerable carbon is the carbon that would be that would be released in a typical land-use conversion. Irrecoverable carbon is the carbon that, if lost, would not recover by mid-century. Datasets are disaggregated for carbon density in biomass or soils. To view these datasets, go to: <a href="https://irrecoverable.resilienceatlas.org/map">https://irrecoverable.resilienceatlas.org/map</a>.</p>
Dataset for "A graph-theoretic approach for spatial filtering and its impact on mixed-type spatial pattern recognition in wafer bin maps"
<p>This is the dataset used in the paper, Ezzat, Liu, Hochbaum, and Ding, 2021, “A graph-theoretic approach for spatial filtering and its impact on mixed-type spatial pattern recognition in wafer bin maps,” <em>IEEE Transactions on Semiconductor Manufacturing</em>, Vol. 34, pp. 194-206.</p>
COVID19 Flow-Maps Daily-Mobility for Spain
<p>This data-set contains daily aggregations of the hourly data provided by MITMA, aggregated at different levels of spatial resolution.</p> <p><strong>Maestra 1: Origin-Destination matrix for the mobility layer, with hourly resolution</strong> Each entry has a date and time period (the range between two consecutive hours), the origin and destination zones and the number of trips from origin to destination. Origin and destination zones correspond to geometries from the MITMA mobility layer and internal trips (same layer of origin and destination) are also reported.</p> <p><strong>Maestra 2: Trips per person matrix on each mobility area on a daily basis.</strong> This indicator reports population-based daily mobility behavior. For each date and zone from the MITMA mobility layer, the indicator reports how many persons have performed 0, 1, 2 or more than 2 trips. While the indicator does not provide the destination of the trips, it accounts for the fractions of people performing at least one trip or none, as well as the estimated total population in that zone for the given date (considering as population those persons who stay overnight in the zone on that date).</p> <p>Original data records come from a study conducted by the MITMA, which analyses the mobility and distribution of the population in Spain from February 14th 2020 to May 9th 2021. The study is based on a sample of more than 13 million anonymised mobile phone lines provided by a single mobile operator whose subscribers are evenly distributed.</p> <p>For more information visit: <a href="https://flowmaps.life.bsc.es/flowboard/data">https://flowmaps.life.bsc.es/flowboard/data</a> and <a href="https://www.mitma.gob.es/ministerio/covid-19/evolucion-movilidad-big-data">https://www.mitma.gob.es/ministerio/covid-19/evolucion-movilidad-big-data</a>.</p>
Fig. 6. Map showing all the 50 in Atlas of European millipedes 3: Order Chordeumatida (Class Diplopoda)
Fig. 6. Map showing all the 50 km squares which provided records in this volume.
ScienceDex guides
Understand access before you commit
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.