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1,221 results for “Aggregators”
ERA5-Land selected indicators daily aggregates for the Latin America region, 2012
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2012.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2007
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2007.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2004
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2004.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2008
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2008.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2015
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2015.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2010
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2010.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2022
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2022.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2021
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2021.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2020
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2020.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2018
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2018.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2019
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2019.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
Geochemical characterization of mineral particulate aggregates and associated biomass collected in boreholes at the Soudan Underground Mine State Park, Soudan, MN, USA.
Mineral and biological samples were collected from boreholes on the 27th level of the Soudan Underground Mine State Park, Soudan, MN, USA. These samples were characterized in order to describe the biogeochemical cycling of iron and sulfur in the crustal regions accessed by the mine's boreholes as well as the microbial communities supported by and responsible for that biogeochemical cycling. The mineral samples were characterized through X-ray diffraction and Fe XANES, the microbial biomass associated with the mineral aggregates was characterized through C XANES, and the microbial community was characterized through the assembly of metagenomes.
Soil aggregate size distribution and particulate organic matter content from Arctic LTER moist acidic tundra nutrient addition plots, Toolik Field Station, Alaska, sampled July 2011.
Soil aggregate size distribution, aggregate carbon and nitrogen, and light fraction carbon were determined for mineral soils in moist acidic tundra. Soil was sampled in control, and N+P plots of the Arctic LTER Moist Acidic Tundra plots established in 1989 and 2006.
MCR LTER: Coral Reef: Conspecific aggregation mitigation of OA on calcification of the coral Pocillopora verrucosa, JEXBIO 2017
The study was conducted in April 2015 in Moorea, French Polynesia, using colonies of Pocillopora verrucosa (~ 4 cm in planar diameter) collected from the outer reef of the north shore at 10–12 m depth. Corals were collected from multiple sites separated by 100-200 m on the outer reef to maximize the likelihood that the selected coral colonies were genetically unique, and transferred directly to an acclimation tank. The experiment used a sequential design, in which corals first were incubated under 130 ambient or elevated pCO2 in flow-through tanks, and then were incubated in a recirculating flume under the same pCO2 crossed with a contrast of two colony densities (Fig. S1). Two response variables were measured in the light (calcification and net photosynthesis at a single irradiance), two response variables were measured in the dark (aerobic respiration and calcification), and two response variables were calculated from these values (gross 135 photosynthesis, and calcification integrated over 24 h). Aerobic respiration was measured as oxygen uptake, and net photosynthesis was measured as the flux of oxygen at a constant irradiance, and in both cases, oxygen uptake was given a negative notation and oxygen evolution a positive notation; gross photosynthesis was obtained by subtracting respiration from net photosynthesis. Daily calcification was calculated by integrating calcification in the 140 light over 12 h, calcification in the dark over 12 h, and summing the two values assuming each day consisted of 12 h of light at a constant intensity. The six response variables were measured for aggregates of a fixed number (n = 12) of similar-sized colonies placed in the flume in either high or low density arrays. With this design, it was not possible to measure the physiology of individual colonies in each aggregate, and therefore our results describe the 145 performance corals averaged across each aggregate. These data support the publication Evensen & Edmunds, 'Conspecific
Parramore Island of the Virginia Coast Reserve Permanent Plot Resurvey: Landcover Class Aggregation data 1996
First 3-5 year resurvey of permanent monitoring plots using essentially the same protocol as the intial survey of 1992-1993 except that: 1.) standing biomass of the herbaceous groundcover was added (including for new lower salt marsh plots) using clip plots at the subplot locations; and 2.) an estimate of landcover/habitat class aggregation was conducted surrounding each plot center out to 60m in the four cardinal directions. Extends baseline data useful for estimating landscape-scale vegetative productivity, mortality, and turnover; for establishing pre-disturbance conditions in the case of later stand- or island-wide disturbance; and for assisting in the ground-truthing of landcover and habitat classification using aerial or satellite remote-sensing imagry.
Aggregated Eco Province data
<p>Aggregated Eco Province (AEP) data for each AEP between complexity 1 to 115.</p> <p>To accompany Sonnewald et al. "Elucidating Ecological Complexity: Unsupervised Learning determines global marine eco-provinces".</p> <p>NOTE: A complexity >12 is recommended.</p>
Matsim Simulation Aggregated Results Hasselt
<p>This dataset contains aggregated results for the following scenarios based on Matsim simulations.</p> <p>1. Base scenario</p> <p>2. Car access restriction scenario (Policy 1)</p> <p>3. Increased in bus frequency scenario (Policy 2)</p>
Matsim Simulation Aggregated Results Bologna
<p>This dataset contains aggregated results for the following scenarios based on Matsim simulations.</p> <p>1. Base scenario</p> <p>2. Car access restriction scenario (Policy 1)</p> <p>3. Increased in bus frequency scenario (Policy 2)</p>
Parent aggregates
<p>Rubble pile models of parent aggregates. The models are obtained through numerical N-body simulations, using the GRAINS software. Simulations are performed using non-spherical particles, mutually interacting under contact/collisions and self-gravity. See Ferrari & Tanga 2020 (doi: 10.1016/j.icarus.2020.113871), Ferrari et al 2020 (doi: 10.1093/mnras/stz3458), Ferrari et al 2016 (doi: 10.1007/s11044-016-9547-2) for further details on the numerical model.</p>
PARADE: Passage Representation Aggregation for Document Reranking
<p>This submission includes all pretrained models on MSMARCO, and run files on the Robust04/GOV2 dataset for the paper "PARADE: Passage Representation Aggregation for Document Reranking". Please follow the instructions in the <a href="https://github.com/canjiali/PARADE">PARADE repo</a> to reproduce the results.</p> <p> </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.