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1,838 results for “location”
The 2009 Mw6.1 L'Aquila normal fault system imaged by 64,051 high-precision foreshock and aftershock locations.
<p>The earthquake catalogue is composed by 64,051 high-precision foreshock and aftershock recorded during the Mw6.1 2009 L'Aquila (Central Italy) normal faulting seismic sequence. The catalog includes events occurred between 1<sup>st</sup> of January and 31<sup>st</sup> December 2009. The completeness magnitude is 0.7. Earthquake locations were obtained by combining an automatic picking procedure for P and S waves, together with cross-correlation and double-difference location methods. </p> <p>Seismic data were recorded at a very dense local network composed of 67 three-component seismic stations (20 permanent stations of the Italian National Network located within 80 km from the epicentral area and 47 temporary stations installed soon after the occurrence of the main shock [Margheriti et al., 2011]). </p> <p>Earthquakes were extracted by the continuous recordings by applying a detection algorithm to all stations, based on the classical STA/LTA coincidence-sum algorithm applied to the trace of the 3C covariance matrix. To these events, we applied an automatic picking algorithm (Manneken Pix) [Di Stefano et al., 2006] able to provide about 1.9 million P-wave and 503,000 S-wave accurate readings, with an estimation of the measurement errors. </p> <p>We applied a time domain cross-correlation method (Schaff and Waldhauser, 2005) to all event pairs with separation distances ≤ 5 km at all stations that recorded the pair. Seismograms were filtered in the 1-15 Hz frequency range using a 4 pole, zero phase band‐pass Butterworth filter. We selected measurements with correlation coefficients greater than 0.85, resulting in a total of ~190 million P and ~85 million S-wave delay times. </p> <p>Earthquakes were located following a two steps procedure. Initial locations for 133,236 events were computed with the Hypoellipse code [Lahr , 1989] using a 1D P-wave gradient velocity model optimized for the area [Chiaraluce et al., 2011]. In the second step, we computed relative locations by applying the large scale double-difference method described in Waldhauser and Schaff, (2008) to the catalog picks and phase delay times measured from waveform cross correlation. The entire dataset was sub-divided in 84 rectangular overlapping boxes, containing a maximum of 3000 earthquakes, orthogonal to the mean strike of the seismic sequence. Resulting relative locations from all boxes were combined into a single catalog, computing the weighted mean of double hypocenters in the overlapping regions (Waldhauser and Schaff, 2008). </p> <p>The final double-difference catalog includes 64,051 events. A subset made of 51,271 earthquakes (i.e., 80% of the whole dataset) indicates highly correlated earthquakes, having at least 10 P-waves and 5 S-waves correlated phases with at least one other event. Highly correlated events (flag=1 in the attached file) mostly occur on the major fault segments, while poorly correlated earthquakes (flag=0 in the attached file) mostly occur in the volume around the major faults.</p> <p>The attached file is a plain text with ";" separator and .csv extension.</p> <p>Here below the header is explained.</p> <p><strong>id_dd: </strong>the hypoDD unique event identifier</p> <p><strong>origin_time: </strong>date of the origin time in the format YYYY-MM-DD[T]hh:mm:ss.msec</p> <p><strong>lat</strong>: hypocenter latitude expressed in degrees </p> <p><strong>lon</strong>: hypocenter longitude east of Greenwich, expressed in degrees</p> <p><strong>dep</strong>: hypocenter depth expressed in km </p> <p><strong>mag</strong>: magnitude (pure number)</p> <p><strong>flag</strong>:<strong> </strong>1 for highly correlated earthquakes; 0 for poorly correlated earthquakes. </p> <p> </p> <p> </p> <p> </p>
IMDB Shows data with scenes and locations ontology
<p>We proudly present you the IMDB show ontology. This is an ontology based on IMDB data and geocoded locations data for many scenes for shows which previously was not available in a single dataset. The present ontology is extensively documented in our GitHub repository: https://github.com/AlexHoorn/group51-kdd Relations are aligned with foaf and schema ontologies and every show is explicitly aligned with wikidata via a Owl:sameAs predicate.</p> <p>For the contents and structure of this ontology we would kindly refer you here: https://github.com/AlexHoorn/MovieLocationsOntology</p> <p>For the creation and data in this ontology we would kindly refer you here: https://github.com/AlexHoorn/MovieLocationsOntology/tree/main/data</p> <p>We highly recommended you to visit our movie location app to explore this data. </p>
Existing well locations in Cebu and Mactan islands, Philippines (CSV format)
<p>This dataset consist of comma-separated values files containing the coordinate location of wells in Cebu and Mactan islands, Philippines expressed as points x (longitude) and y (latitude) in decimal degrees. The dataset is partitioned between a training and test subset at a proportion of 70% and 30%, respectively. The sources of the data were two government agencies tasked to manage the water resources in the Philippines. Shapefiles can be generated directly from the dataset using appropriate GIS software. </p>
Melt Focusing Along Permeability Barriers at Subduction Zones and the Location of Volcanic Arcs: Numerical models
<p>The dataset includes 2-D subduction zone models calculated by Comsol Mutiphysics®, slab geometry, subduction parameters, and the prediction results.</p> <p>Each numerical model solves the thermal structure of 31 subduction zones. The 2-D slab geometry of each subduction zone is obtained from the compilations of global subduction geometries based on earthquake catalogs Slab 1.0 and Slab2 (Hayes et al., 2012; 2018). Each slab geometry is imported in the corresponding Comsol model as a text file format. Below the point where the slab depth data is unavailable, the slab interface is simply defined as a straight line with the same dip to the bottom of the computation domain. The subduction parameters used in the models are available in Table 1.</p> <p>Using the calculated thermal structure at 30 Ma, we approximate the locations of the arc as the apices of 5 isotherms at 100°C interval within 800°C – 1200°C. The predicted arc locations from each isotherm are reported in Table 2 as the horizontal distance from the trench. The actual arc location in each model is defined as the point on the surface where the slab interface reaches the subarc slab depth <em>H</em> in Table 1 and reported as the horizontal distance from the trench in Table 2. The slab water loss depth and rate obtained from van Keken et al. (2011) are presented in Table 2. In case of the maximum temperature above the water loss depth is higher than the experimentally-derived melting condition, 800°C, we report the horizontal distance from the trench. The width of the horizontal distance of slab water loss depth is assumed as the expected melting region. </p>
Lost at Night located images (Data release 1)
<p>Correspondences between ISS images and locations. </p>
Oceanographic habitat location data to support range shift analyses for the manuscript: "Climate-driven range shifts are rapid yet variable among recreationally important coastal-pelagic fishes"
<p>This data file contains the latitudinal location of suitable oceanographic habitat for a suite of coastal-pelagic fishes off eastern Australia at monthly time-steps between 1998 and 2018. Please refer to the manuscript "Climate-driven range shifts are rapid yet variable among recreationally important coastal-pelagic fishes" for a full description of the methodologies applied to derive these data.</p>
Variation in mouse pelvic morphology maps to locations enriched in Sox9 Class II and Pitx1 regulatory features
<p><span><span><span><span><span><span><span><span><span><span><span>Variation in pelvic morphology has a complex genetic basis and its patterning and specification is governed by conserved developmental pathways. Whether the mechanisms underlying the differentiation and specification of the pelvis also produce the morphological covariation on which natural selection may act is still an open question in evolutionary developmental biology. We use high-resolution Quantitative Trait Locus (QTL) mapping in the F<sub>34</sub> generation of an advanced intercross experiment (LG,SM-G<sub>34</sub>) to characterize the genetic architecture of the mouse pelvis. We test the prediction that genomic features linked to developmental patterning and differentiation of the hind limb and pelvis and the regulation of chondrogenesis are overrepresented in QTL. We find 31 single QTL-trait associations at the genome- or chromosome-wise significance level coalescing to 27 pleiotropic loci. We recover further QTL at a more relaxed significance threshold replicating locations found in a previous experiment in an earlier generation of the same population. QTL were more likely than chance to harbor Pitx1 and Sox9 Class II ChIP-seq features active during development of skeletal features. There was weak or no support for the enrichment of seven more categories of developmental features drawn from the literature. Our results suggest genotypic variation is channeled through a subset of developmental processes involved in the generation of phenotypic variation in the pelvis. This finding indicates the evolvability of complex traits may be subject to biases not evident from patterns of covariance among morphological features or developmental patterning when either is considered in isolation.</span></span></span></span></span></span></span></span></span></span></span></p>
Figure 3 in Ilha Grande, one of the locations with the most records of bat species (Mammalia, Chiroptera) in Rio de Janeiro state: results of a long-term ecological study
Figure 3. Relationship between number of species in the Phyllostomidae family (A) and number of captures in the Phyllostomidae family, (B) and capture effort (h.m²) in bat inventories in Rio de Janeiro state. Numbers correspond to locations listed in Table IV. Dots: cross = study 1 on Ilha Grande; square = study 2 on Ilha Grande; star = study 3 on Ilha Grande; triangle = study 4 on Ilha Grande; black circle = study 5 on Ilha Grande; grey circle = other studies in Rio de Janeiro state.
Figure 1 in Ilha Grande, one of the locations with the most records of bat species (Mammalia, Chiroptera) in Rio de Janeiro state: results of a long-term ecological study
Figure 1. Map of Ilha Grande with sampling points of the five studies described in this paper, conducted between 1998 and 2018 on Ilha Grande, Angra dos Reis, Rio de Janeiro state, Brazil. A map of South America is shown, detailing the location of the state of Rio de Janeiro, in southeastern Brazil, while in the enlargement is shown the state of Rio de Janeiro detailing the location of Ilha Grande.
Figure 2 in Ilha Grande, one of the locations with the most records of bat species (Mammalia, Chiroptera) in Rio de Janeiro state: results of a long-term ecological study
Figure 2. Locations in Rio de Janeiro state where bat inventories have been conducted. Numbers correspond to locations in Table 4. A map of South America is shown, detailing the location of the state of Rio de Janeiro in southeastern Brazil.
023488_2050_zoom_location_004_mars_hirise
023488_2050_zoom_location_004_mars_hirise depression -- another look into this area: https://skfb.ly/6MW87 more info may be available here: "Proposed Landing Site in Mawrth Vallis" https://www.uahirise.org/dtm/dtm.php?ID=ESP_023488_2050 This signal was analyzed by Organic. Tools used: gdal, qgis, houdini https://www.instagram.com/organiccomputer/ Source: Objaverse 1.0 / Sketchfab
The Font, located at Lichfield Cathedral, UK
The Font, in Lichfield Cathedral, England, made of Caen stone and alabaster, with richly coloured marble pillars, early French Gothic detail, and high relief scenes and figures. This elaborate font with its instructive Bible stories and appealing details was designed by William Slater (1819-1872) and executed by James Forsyth (1827-1910). It dates from about 1862. Model generated from about 100 images taken with an LG G6 smartphone. Source: Objaverse 1.0 / Sketchfab
Pythia Generated Jet Images for Location Aware Generative Adversarial Network Training
<p>Dataset containing 872666 jet images to train Location Aware Generative Adversarial Networks (LAGAN) for High Energy Physics. Results are published in [arXiv:1701.05927].</p> <p><strong>Format</strong>:<br> HDF5 file with the following fields:</p> <ul> <li>'image' : array of dim (872666, 25, 25), contains the pixel intensities of each 25x25 image</li> <li>'signal' : binary array to identify signal (1, i.e. W boson) vs background (0, i.e. QCD)</li> <li>'jet_eta': eta coordinate per jet</li> <li>'jet_phi': phi coordinate per jet</li> <li>'jet_mass': mass per jet</li> <li>'jet_pt': transverse momentum per jet</li> <li>'jet_delta_R': distance between leading and subleading subjets if 2 subjets present, else 0</li> <li>'tau_1', 'tau_2', 'tau_3': substructure variables per jet (a.k.a. n-subjettiness, where n=1, 2, 3)</li> <li>'tau_21': tau<sub>2</sub>/tau<sub>1</sub> per jet</li> <li>'tau_32': tau<sub>3</sub>/tau<sub>2</sub> per jet</li> </ul> <p><strong>Details</strong>:</p> <ul> <li>Simulated using Pythia 8.219 at √ s = 14 TeV</li> <li>Image pre-processing using method from in L. de Oliveira et al., Jet-Images -- Deep Learning Edition [arXiv:1511.05190]</li> <li>scikit-image==0.12.0 implementation of cubic spline rotation</li> <li>Finite calorimeter granularity simulated with 0.1×0.1 grid in η and φ, with η × φ ∈ [−1.25, 1.25] × [−1.25, 1.25]</li> <li>Jet clustering with anti-k<sub>t</sub> algorithm with a radius R = 1.0 using FastJet 3.2.1; constituent re-clustering into R = 0.3 k<sub>t</sub> subjets</li> <li>Intensity of pixel = p<sub>T</sub> of cell</li> <li>60 GeV < m<sup>jet</sup> < 100 GeV</li> <li>250 GeV < p<sub>T</sub><sup>jet</sup> < 300 GeV</li> <li>Sparse images (~10% NNZ)</li> </ul> <p>Full dataset description in [arXiv:1701.05927].</p>
Figure 1. - Nesting habitat of Xylocopanasalis; A nesting habitat of Xylocopanasalis on a makeshift roof of a restaurant in Suan Pheung district, Ratch Buri province, Thailand. The red arrows indicate locations where the bamboo culms were arranged ca. 2.50 m above the ground (1a and 1b). At the nest entrance, the female of Xylocopanasalis was dehydrating the nectar previously foraged (1c).
Figure 1. - Nesting habitat of Xylocopanasalis; A nesting habitat of Xylocopanasalis on a makeshift roof of a restaurant in Suan Pheung district, Ratch Buri province, Thailand. The red arrows indicate locations where the bamboo culms were arranged ca. 2.50 m above the ground (1a and 1b). At the nest entrance, the female of Xylocopanasalis was dehydrating the nectar previously foraged (1c).
Figure 1. - World map representing all the locations mentioned in the dataset. Areas of particular interest are represented with the same colour (⬤ Madagascar, ⬤ Western Indian Ocean, ⬤ Papuasia, ⬤ New Caledonia, ⬤ South Pacific). Grey spots gather all the other locations.
Figure 1. - World map representing all the locations mentioned in the dataset. Areas of particular interest are represented with the same colour (⬤ Madagascar, ⬤ Western Indian Ocean, ⬤ Papuasia, ⬤ New Caledonia, ⬤ South Pacific). Grey spots gather all the other locations.
Figure 1. - Location of sites where records of caterpillars of Phengarisalcon (triangles) and Phengarisnausithous (circles) in ant nests are known in the Czech Republic.
Figure 1. - Location of sites where records of caterpillars of Phengarisalcon (triangles) and Phengarisnausithous (circles) in ant nests are known in the Czech Republic.
Figure 1. - Location of sites where records of caterpillars of Phengarisalcon (triangles) and Phengarisnausithous (circles) in ant nests are known in the Czech Republic.
Figure 1. - Location of sites where records of caterpillars of Phengarisalcon (triangles) and Phengarisnausithous (circles) in ant nests are known in the Czech Republic.
Universal microbial network decomposes mammals despite varied climate, location, and seasonal influence
<p>Microbial breakdown of organic material is one of the most important processes on earth, yet enormous knowledge gaps exist about its controls. We demonstrate that a universal, inter-kingdom microbial network assembles in response to nutrient-rich, terrestrial mammalian decomposition, despite selection effects of location, climate and season. We created the first metagenome-assembled genome library from mammalian decomposition-associated soils and combined it with metabolomics to identify a microbial decomposer network that interacts by cross-feeding to efficiently metabolize labile decomposition products. The key fungal and bacterial decomposers appear unique to the breakdown of terrestrial cadavers, and are rare in relative abundance across non-decomposition environments. Blow flies are suggested as an important decomposer vector and the observed lockstep of microbial interactions underlies a robust microbial forensic tool for predicting the time since death. </p>
Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma - Location Data
<p>This dataset is meant to be used with "Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma - Results and Data". It provides spatial output data for 4 different setups (spheroid, traditional, 3d gravity, and traditional floating) of an agent-based model of <i>in vitro </i>tuberculosis infection models. </p>
Figs 32–37. Head tubercles located and form. 32–34 in ON SPLITTING OF THE GENUS NOTOCUPES (COLEOPTERA: ARCHOSTEMATA): NEW DATA ON MORPHOLOGY AND TAXONOMY
Figs 32–37. Head tubercles located and form. 32–34 – linedrawings: 32 – Rhabdocupes
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.