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9,677
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9,677 results for “one”
Interior Alaska managed sites: soil organic layer and mineral soil nutrient concentrations and additional characteristics measured one time in either summer 2012 or 2013
This dataset contains soil organic layer and mineral soil depth, C and N concentrations, and other soil characteristics collected at all managed and adjacent unmanaged study sites.
Interior Alaska managed sites: soil organic layer depth and thaw depth measured one time in either summer 2012 or 2013
This dataset contains estimates of soil organic layer depth and thaw depth along transects measured at a suite of managed and unmanaged areas in interior Alaska in summers 2012 and 2013.
Interior Alaska managed sites: tree inventory measured one time in either summer 2012 or 2013
This dataset contains the diameter of all trees (diameter at breast height) and shrubs (basal diameter) measured in managed areas and adjacent unmanaged black spruce forest, in Summers 2012 and 2013.
Interior Alaska managed sites:vegetation community composition and ground cover measured one time in either summer 2012 or 2013
This dataset contains number of hits by different vegetation types and ground cover measured using a pin flag using the point intercept method.
Interior Alaska managed sites: downed woody debris measured one time in either summer 2012 or 2013
This dataset contains counts of fine woody debris collected along transects measured at a suite of managed and unmanaged areas in interior Alaska in summers 2012 and 2013. Dataset also includes diameters of large (>=7cm diameter) downed woody debris pieces.
Measurements of 10 year old Alaskan paper birch saplings before and one-year after exposed to varying intensities of leaf stripping
This dataset contains woody, leaf, and resin gland measurements of Alaskan paper birch saplings before and one-year after a leaf stripping experiment. Saplings were all growing in the Boundary fire (within CPCRW and the rocket range) and thus 10 years old.
Tree regeneration after fire: Delta 1994 burn surveys, Data from one soil sample/transect to obtain bulk density.
Data for this study were collected in 2001 and 2002 by Jill Johnstone (University of Alaska Fairbanks) and Eric Kasischke (University of Maryland). Sites were located within the perimeter of the 1994 burn southeast of Delta Junction Alaska, USA, bordering the Alaska Highway to the North and the Gerstle River to the West. Sites were selected from satellite classifications prepared by Eric Kasischke to represent different levels of burn severity and post-fire vegetation canopy greenness (NDVI). Site selection was constrained by road access, and only areas where all trees had been killed by the fire were selected. At each site, a central point was located in an area of visually homogeneous vegetation. Five parallel transects, each 50 m long, were laid out as follows: 1) the first transect started at the central point and followed a randomly-selected compass direction, 2) two additional transects were established parallel to the first, but at a random distance from the central transect up to 25 m distant. Vegetation was sampled in a 2-m wide belt centered on each transect, and soil samples were made at intervals along the transect line. Vegetation measurements included: a) basal diameters of all pre-fire trees greater than 1.3 m in height, b) counts of all post-fire tree seedlings, and c) basal diameters of tree seedlings and willows, measured in a randomly chosen 5x2 m portion of each transect. General notes were made on visual percent cover of different vegetation growth forms at the site. Destructive measurements of tree seedlings and willows made in 2001 were used to develop allometric equations to predict dry biomass from basal diameter. Measurements of soil organic layer depth were made at 5 m intervals with the use of a spade to excavate small chunks of sod. At one randomly-selected sample point per transect, a 10x10 cm sample of the organic layer was collected for bulk density measurements. Bulk density samples were dried in a 60degC oven for 48 hours and then w
Assembled file of one minute averages for high resolution surface meteorological (Met) and sea water intake (SWI) data from continuous underway measurements from CCE LTER process cruises in the CCE region, 2006 - 2019.
As the research vessel is underway for the duration of a CCE Process Cruise (since 2006, ongoing), 30 parameters are continuously measured regarding the oceanographic surface and atmospheric and navigational environment of the vessel, along the ship's trackline in the CCE region.
Summary of lysimeter ion concentrations at Coweeta Watershed One at the Coweeta Hydrologic Laboratory from 1985 to 1988
None provided by researcher.
Bulk throughfall at Coweeta White Pine, Watershed One at the Coweeta Hydrologic Laboratory from 1985 to 1988
None provided by researcher.
Bulk stemflow at Coweeta White Pines, Watershed One (Coweeta Hydrologic Laboratory) from 1985 to 1988
Data was collected from six collectors. Statistical means were volume weighted.
Sensor data from three different fishing ships for a period of one month
<p>The purpose of the data is to analyse data produced by fishing ships in order to reduce fuel consumption. The data has been used in WP3 of DataBio project. Data were processed and supplied by the VTT and UPV/EHU DataBio project team.</p>
Tables and figures complementing the European Union One Health 2018 Zoonoses Report
<p>All summary tables and figures produced for the European Union One Health 2018 Zoonoses Report are provided as archives containing Excel files for tables, and as PDF or PNG files for figures.</p> <p><strong>All country data connected to this Report are published SEPARATELY on Knowledge Junction - see related identifiers. This is because DATA OWNERSHIP for country data stays with the organisation(s) of the country submitting the data - for further reference see doi:10.2903/sp.efsa.2019.EN-1544.</strong></p>
Prevalence data complementing the European Union One Health 2018 Zoonoses Report
<p>This dataset contains monitoring data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agentsin foodstuffs. Relevant EU legislation is:Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014.</p>
Food and waterborne outbreaks data complementing the European Union One Health 2018 Zoonoses Report
<p>Food and waterborne outbreaks data reported under the framework of Directive 2003/99/EC and in accordance with the update of the technical specifications for harmonised reporting of FBOs through the EU reporting system in accordance with Directive 2003/99/EC. This dataset includes the number of outbreaks, as well as the number of human cases, hospitalisations and deaths, per causative agent. In addition, other information can include data on causative agents, food vehicles, and the factors in food preparation and handling that contributed to the food-borne outbreaks. Reporting countries can also provide information on the nature of the evidence supporting the suspicion of the food vehicle. This evidence can be epidemiological, microbiological, descriptive environmental, or based on product tracing investigations. </p>
Dataset for Mininig Off-by-One Errors
<p>The dataset that was made by downloading top 500 starred Java projects from GitHub and then eliminating common projects found with java-large-training and java-large-testing raw datasets*. The resulting dataset consists of 155 GitHub projects.</p> <p>The repositories were downloaded and the code analyzed using code found in the following repository: <a href="https://github.com/serg-ml4se-2019/group5-deep-bugs/tree/master">https://github.com/serg-ml4se-2019/group5-deep-bugs/tree/master</a> (more specifically, the code found in bug_mining folder)</p> <p>* java-large raw dataset can be found at <a href="https://github.com/tech-srl/code2seq/blob/master/README.md#datasets">https://github.com/tech-srl/code2seq/blob/master/README.md#datasets</a></p>
Sample based prevalence data complementing the European Union One Health 2018 Zoonoses Report
<p>This dataset contains monitoring sample based data on zoonoses and zoonotic agents under the Directive 2003/99/EC. This Directive requires Member Sates (MSs) to collect, evaluate and report data on zoonoses and zoonotic agents. MSs can also report monitoring data and information on some other pathogenic microbiological agentsin foodstuffs. Relevant EU legislation is:Commission Regulation (EC) No 2073/2005,Commission Regulation (EC) No 1441/2007, Commission Regulation (EU) No 1086/2011, Commission Regulation (EU) No 209/2013, Commission Regulation(EU) No 217/2014. </p>
A dataset for evaluating one-shot categorization of novel object classes
<p>From just a single example, we can derive quite precise intuitions about what other class members look like. This stands in stark contrast to machine learning algorithms, which typically require tens or even hundreds of thousands of examples to learn a new category. One of the most important open questions in our field is: How do humans achieve this? The stimuli and data provided here (in MATLAB format) are from thousands of crowd-sourced human responses to novel objects. The data can be used to test machine learning generalization as compared to human and also can be used as a test bed for various kinds of category learning models. </p>
Dataset: The TCR repertoire reconstitution in multiple sclerosis: comparing one-shot and continuous immunosuppressive therapies
<p>This dataset, containing TCRbeta-chain data, is the basis for the following publication in Frontiers in Immunology: The TCR repertoire reconstitution in multiple sclerosis: comparing one-shot and continuous immunosuppressive therapies. The file key can be found in the file: file_key.xlsx. Relevant methodological details maybe found in the corresponding publication.</p>
Figure 1.19. Rex C in One Hundred Years of Tyrannosaurus rex: The Skeletons
Figure 1.19. Rex C, maxilla and premaxilla (A), pes phalanges (B).
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.