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1,646 results for “plot”
Figure 4 Network plots for CD013122
<p>This is the high-resolution image of network plots for the Cochrane review: "Secondary prevention of variceal bleeding in adults with previous oesophageal variceal bleeding due to decompensated liver cirrhosis: a network meta-analysis (DOI: 10.1002/14651858.CD013122)"</p>
Coordinates and description of sample plots described in the manuscript
<p>Coordinates and description of sample plots described in the manuscript "High canopy cover of invasive Acer negundo L. affects ground vegetation diversity" (Veselkin D.V., Dubrovin D.I., Pustovalova L.A.).</p>
A 249-year chronosequence of forest plots from eight successive fires in the eastern Canada boreal mixedwoods
<p>A combination of wildfires and defoliating insect outbreaks play an important role in the natural successional dynamics of North American boreal forests, which, in the long term, change the post-disturbance composition and structure of forest stands. After stand-replacing disturbances (mainly wildfires), early successional hardwoods typically dominate the affected areas in boreal forests. Provided sufficient time following disturbances, the increasing recruitment of mid- to late-successional softwoods as well as the mortality of hardwoods gradually change forest composition from hardwoods to admixtures of hardwood-conifer species and conifer-dominated stands in mid and late successional stages, respectively. Such mixed woods are abundant across the southern Canadian boreal forest. In boreal Canada, mixed woods are the most structurally heterogeneous forest ecosystems, are highly productive, and form an important source of timber supply. Here we present the EASTERN BOREAL MIXEDWOODS CANADA dataset, which documents the changes in composition and structure of stands originating from eight successive wildfires representing a chronosequence of 249 years in eastern Canada. This dataset has been used in several different projects to study and model the influence of natural (e.g., insect outbreaks) and anthropogenic disturbances (e.g., harvesting) on the dynamics of post-fire stands. The data covers a high range of variability in stand composition and structure, explained by species establishment, dominance and mixture. It thus constitutes a useful source of information to trace the dynamics of the main boreal tree species of eastern north America, from their establishment to their replacement at different spatial scales (e.g., from stand to landscape level).</p>
Figure 4 Network plots for CD013121
<p>High resolution image of network plots for the Cochrane review: "Primary prevention of variceal bleeding in people with oesophageal varices due to liver cirrhosis: a network meta-analysis" (DOI: 10.1002/14651858.CD013121)</p>
Katharine Tynan Memorial Plot
a model of Katharine Tynan Memorial Plot, Tallaght, Dublin, Ireland Source: Objaverse 1.0 / Sketchfab
Testing global isotropy with WMAP data - MC chains and plots
<p>Testing isotropy with WMAP data: Monte Carlo chains, marginalized posteriors and triangle plots.</p> <p>File content:</p> <p>all_coupled_chains.zip: MC chains for all the coupled models and pure <span class="math-tex">\(\Lambda\text{CDM}\)</span>;</p> <p>all_coupled_plots.zip: plots of marginalised posteriors and triangle plots for all the coupled models and pure <span class="math-tex">\(\Lambda\text{CDM}\)</span>;</p> <p>all_decoupled_chains.zip: MC chains for all the decoupled models;</p> <p>all_decoupled_plots.zip: plots of marginalised posteriors and triangle plots for all the decoupled models.</p> <p> </p> <p>All plots were made with GetDist ( https://github.com/cmbant/getdist ).</p>
Data and plotting scripts used in "High level implementation of geometric multigrid solvers for finite element problems: applications in atmospheric modelling"
<p>Raw performance data and plotting scripts used to generate the figures in the paper "High level implementation of geometric multigrid solvers for finite element problems: applications in atmospheric modelling"</p>
Tree map plots of women's share across MSC 2010 classes
<p> Hierarchical maps visualising the share of women authors resp. women's publications in zbMATH across the MSC 2010 classes on level 1 and 2. Each rectangle represents a mathematical class and displays the corresponding name and code within the MSC 2010; its size is proportional to the number of authors resp. publications in that field, and the darker the color, the larger the share of women resp. their publications in that field.</p> <p>Detailed information can be obtained using the hover; a right-click allows to get back from MSC level 2 to level 1. Note that the interactive feature requires the activation of JavaScript.</p>
Data and plotting scripts used in "High level implementation of geometric multigrid solvers for finite element problems: applications in atmospheric modelling"
<p>Raw performance data and plotting scripts used to generate the figures in the paper "High level implementation of geometric multigrid solvers for finite element problems: applications in atmospheric modelling"</p> <p>A previous version of this dataset (corresponding to an earlier revision of the paper) is available as https://doi.org/10.5281/zenodo.50533.</p>
Metabolic impacts of climate change on marine fish communities and fisheries - Dataset and figure plot script
<p>Here we provide the MATLAB functions, model forcing data (net primary production and temperature), and model output required to generate the figures and perform calculations from the manuscript "Metabolic impacts of climate change on marine fish communities and fisheries", which is currently in submission as a research article. The figures plot script (plot_figures_climate_fish_deconstruction.m) is written in MATLAB version R2012a.</p>
Plots of De Rham's function and its fractional velocity
<p>Plots of De Rham's function and its fractional velocity. Examples can be run in Maxima. Dataset complements the paper "Characterization of strongly non-linear and singular functions by scale space analysis", Chaos, Solitons & Fractals, 2016, 93, 14-19.</p>
Scenario data, model source code and plotting routine for manuscript: Separating CO2 emission from removal targets comes with limited cost impacts
<p>This data archive contains REMIND model setup, results data and data analysis files for manuscript:<br><strong>Separating CO2 emission reduction from removal targets comes with limited cost impact.<br><br>plotting</strong>(directory) contains results data, manuscript specific data analysis and plotting routine scripts used to generate the figures of the manuscript.<br><strong>remind</strong>(directory) contains REMIND model source code and scenario set-up. Detailed scenario configurations are set in remind/config/scenario_config_SepMark.csv.<br><strong>remind2</strong>(directory) contains the slightly modified R-library package used for post-processing of REMIND output.<br><br>AMENDMENT<br><strong>Plots_SeparateMarkets_afterReviewProcess.Rmd</strong> After the review process, the new plotting script was added including the additional figures in the Supplementary Material. This file should replace the previous R-markdown file SepMark_essential/plotting/Plots_SeparateMarkets.Rmd.</p>
BFM17 Optimization Data and Plotting Scripts
<p>This is the data and plotting scripts for the optimization of a high-dimensional biophysical model by coupling it to DAKOTA. The biophysical model used is this work was the Biogeochemical Flux Model with 17 state variables coupled to a 1D implementation of the Princeton Ocean Model, referred to as BFM17+POM1D. </p> <p>Included is data from a one-at-a-time sensitivity analysis, random sampling of the model's parameter space, and optimization runs. The data is accompanied by plotting scripts. This material is published to accompany a forthcoming paper describing the parameter estimation methodology applied here. </p>
Data, code and supplementary plots for "A hierarchical spline model for correcting and hindcasting temperature data"
<p>Data, code and supplementary plots for the paper "A hierarchical spline model for correcting and hindcasting temperature data". Please see README.txt for detailed description of the files and relevant instructions.</p>
Figure 8. Bivariate plots for reputed T in A taxonomic revision of the Tragulus mouse-deer (Artiodactyla)
Figure 8. Bivariate plots for reputed T. napu specimens from the small Sundaland islands.
Dataset for plots and results in manuscript: "Reliance on fossil fuels increases during extreme temperature events in the continental United States"
<p>These are the dataset for plots and results in the manuscript titled "Reliance on fossil fuels increases during extreme temperature events in the continental United States".</p><p>Figure 1,2,3,4,5 are the dataset used for analysis and plotting the figures in the manuscript.</p><p>Other dataset are the 34 years' air temperature and population-weighted air temperature thresholds for detecting extreme temperature events in each U.S. states. For example, Ta_threshold(1990-2023)_99th_percentiles.csv is the 99th percentiles for each U.S. states.</p><p>Any questions and further assitance or collaborations are welcome to contact through: wz2481@columbia.edu, happystillwaterzhao@gmail.com</p><p> </p><p> </p>
Taxation of forest stands on 29 plots conducted of the Lyalsky test site in the Central-Eastern Forest Taxation District of the European part of Russia was carried out during August 2023
<p>The taxation characteristics of a forest stand include: forest type, tree species, diameter, height, age, state, and degree of decomposition for fallen trees and stumps. Forest taxation was carried out according to the methodology [Fieldwork methodology for forest inventory on a test site as part of the implementation of the important state-level innovative project 'Carbon in Ecosystems: Monitoring'. URL: https://ritm-c.ru/wp-content/uploads/2023/09/metodika-polevyh-rabot-po-taksaczii-na-ppp_27_06_2023-.pdf].</p><p>The research was carried out by employees of the Institute of Biology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences as part of the most important innovative project of national importance 'Development of a system for ground-based and remote monitoring of carbon pools and greenhouse gas fluxes in the territory of the Russian Federation, ensuring the creation of recording data systems on the fluxes of climate-active substances and the carbon budget in forests and other terrestrial ecological systems' (Registration number: 123030300031-6).</p>
INTERACT arctic research stations: Historic weather data fetched and plotted from Copernicus Climate Data Store
<p>Plots with historic weather data for arctic research stations covered by International Network for Terrestrial Research and Monitoring in the Arctic (INTERACT). Comparison with WMO climate normal periods 1961-1990 and 1991-2020, averages and stations deviations from the normal periods are calculated and plotted.</p><p>The data source for historic data of temperature and precipitation is: </p><p>Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 </p><p>See the linked github repository https://zenodo.org/doi/10.5281/zenodo.10214962 for how data was fetched from Copernicus Climate Data Store, prepared and plotted. The github repository also contains CSVs with source data for the plots.</p>
ChromatoShiny: an interactive R/Shiny App for plotting chromatography profiles
<p>Raw data for the manuscript.</p> <p>"011221_Run15_533.tif" - an uncropped gel scan (Fig. 1A)</p> <p>"CPC_SurvK62A_preps_CPC_SP_IE512.tif" - a scan of the marker used in the gel image in Fig. 1A (the gel on the right)</p> <p>"Fig. 1B.pdf" - a raw plot for Fig. 1B exported from the shiny app</p> <p>"Fig. 1C.pdf" - a raw plot for Fig. 1C exported from the shiny app</p> <p>"Fig. 2A.pdf" - a raw plot for Fig. 2A exported from the shiny app</p> <p>"Fig. 2B.png" - a raw screenshot from the shiny app for Fig. 2B </p> <p>"Fig. 3.pdf" - a raw plot for Fig. 3 exported from the shiny app</p> <p> </p>
Data Set: Radio Frequency Senser (RFS) example waveforms, altitudes, and density plot
<p>This data set contains data for the paper entitled "Radio Frequency Sensor: radio frequency lightning detection in geostationary orbit", submitted to <em>Radio Science </em>in December 2023.</p> <p>This data set contains three types of RFS data. 1) The first are time domain waveforms of three lightning events, in both the RFS high band (116 – 142 MHz) and the RFS low band (10-60 MHz), sampled at 155 MHz. The waveforms are right-hand circularly polarized waveforms. 2) The second type of data is altitudes and locations of trans-ionospheric pulse pairs (TIPPs) over time. The locations were determined by time coincidence with geolocated World Wide Lightning Location Network strokes. 3) The third type is RFS events per square kilometer per year in latitude and longitude. The RFS event were located by time correlation to Earth Networks Global Lightning Network lightning strokes.</p> <p><strong>Data set 1:</strong></p> <p>Consists of six ASCII files – 3 high band & 3 low band example RFS right-hand circularly polarized waveforms. Each ascii file contains a header with the RFS event time in UTC, the label of “RFS high band (77.5 – 155 MHz)” or “low band (0 – 77.5 MHz)”, and sample rate (155 MHz). Data following the header are time samples of electric field in uV/m sampled at 155 MHz.</p> <p>Filenames are:</p> <p>RFS_waveform_HighBand_20230607_010803.txt</p> <p>RFS_waveform_HighBand_20230607_015553.txt</p> <p>RFS_waveform_HighBand_20230607_034055.txt</p> <p>RFS_waveform_LowBand_20230607_010803.txt</p> <p>RFS_waveform_LowBand_20230607_015553.txt</p> <p>RFS_waveform_LowBand_20230607_034055.txt</p> <p> </p> <p><strong>Data set 2:</strong></p> <p>Filename = ‘RFS_TIPPs_20230607_0100-0500_UTC.txt’</p> <p>1 ASCII comma separated value (CSV) file. Columns are:</p> <p>1. UTC date yyyy/mm/dd</p> <p>2. UTC seconds of day</p> <p>3. WWLLN-determined latitude (degrees, wwlln_latitude in header)</p> <p>4. WWLLN-determined longitude (degrees, wwlln_longitude in header)</p> <p>5. TIPP-estimated height (km, height in header)</p> <p> </p> <p><strong>Data set 3:</strong></p> <p>Filename = ‘RFS_map.csv’</p> <p>1 CSV file of a 2-dimensional data set.</p> <p>1. Row 1, Longitude (degrees, in 0.25-degree steps)</p> <p>2. Column 1, Latitude (degrees, in 0.5-degree steps)</p> <p>3. 2-D grid in latitude and longitude: events per square kilometer per year</p> <p>Notes: Since the RFS coverage range goes across longitude = -180/180 degrees, longitudes go from 147.75 to 180, then start at -180 to -12.75. Latitude range goes from -58.5 to 68.5, as there were no detected RFS events outside these latitudes.</p> <p>The three examples given in data set 1 are those shown in LA-UR-23-32419, Figure 2. The TIPP data in data set 1 is shown in LA-UR-23-32419, Figure 4, and comprises data from 07 June 2023 between 01:00-05:00 UTC. Data set 3 contains RFS event rates per sq. km per year for data from 1 March 2022 – 1 March 2023, with the caveats described in LA-UR-23-32419.</p>
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.