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7,370 results for “supplementation”
Supplemental IPWM Run for "Ion heating in the polar cap under northwards IMF Bz": AMPOP_May2014
<p>Full output from the Ionosphere/Polar Wind Model (IPWM) for results published in "Ion heating in the polar cap under northwards IMF Bz", by L. J. Lamarche, R. H. Varney, and A. S. Reimer. This is a simulation of the May 2014 event, with IPWM driven by AMPERE convection maps and Ovation Prime precipitation (AMPOP_May2014). Scripts to visualize these model output and produce the figures in the article are available in a separate repository <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>.</p> <p>If you are configuring the Resen bucket available in <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>, mount this repository to /home/jovyan/mount/AMPOP_May2014_output.</p>
PARE-Seq Spring 2021 Supplemental Data
<p>This repository hosts the soil, water, and wastewater fasta files for the PARE-Seq bioinformatics short course data.</p>
Data Supplement: Inputs and Outputs for Rahman et al. 2021
<p><strong>Contents:</strong></p> <p><strong>prototype_elec:</strong> Input Data Files (IDFs) generated by tempset for a small office with electric resistance heating. Only heating setpoints are modified.</p> <p><strong>output_elec:</strong> Output csvs corresponding to the IDFs generated in prototype_elec</p> <p><strong>prototype_gas:</strong> IDFs generated by tempset for a small office with gas furnace heating. Only heating setpoints are modified.</p> <p><strong>output_gas:</strong> Output CSVs generated corresponding to the IDFs generated in prototype_gas</p> <p><strong>prototype_cool:</strong> IDFs generated by tempset for a small office with vapor compression cooling. Only cooling setpoints are modified.</p> <p><strong>output_cool:</strong> Output CSVs generated corresponding to the IDFs generated in prototype_cool</p> <p><strong>Summary</strong>:</p> <p>Input and Output data for tradeoffs resulting from specific changes to those schedules in terms of three quantities: total electricity consumption per day; maximum hourly electricity consumption per day; and predicted percentage dissatisfied (occupant thermal comfort). The method for generating schedules requires a single base schedule as the starting point and, using a few clearly defined parameters, transforms it into a set of schedules that can be used for modeling an existing building stock or for performing parametric studies. Temperature setpoint schedules are generated and simulated for a small office building in a cool-dry climate in three different case studies pertaining to changing temperature setpoint schedules. </p> <p><strong>Accompanying software and workflow described here:</strong></p> <p>https://github.com/IMMM-SFA/rahman-etal_2021_tbd</p> <p> </p>
Berends_etal_2020_CP_Supplement
<p>Supplement to Berends, C. J., de Boer, B., and van de Wal, R. S. W.: Reconstructing the Evolution of Ice Sheets, Sea Level and Atmospheric CO2 During the Past 3.6 Million Years, Clim. Past Discuss., https://doi.org/10.5194/cp-2020-52, in review, 2020.</p> <p>Results from three separate simulations of the last 3.6 Myr with the hybrid ice-sheet - climate model.</p>
Supplement to "Estimation of the total magnetization direction of approximately spherical bodies"
<p>Supplementary data and source code to "Estimation of the total magnetization direction of approximately spherical bodies".</p> <p>Article submitted for publication to Nonlinear Processes in Geophysics.</p> <p>The original submission and open peer-review can be viewed at http://dx.doi.org/10.5194/npgd-1-1465-2014</p> <p>This is an archive of the git version controlled repository containing: the manuscript LaTeX source files; IPython notebooks (www.ipython.org) containing source code to perform the applications to synthetic and real data; the total field magnetic anomaly data used in the real data application.</p> <p>See the original repository at https://github.com/pinga-lab/Total-magnetization-of-spherical-bodies</p> <p>The source code that implements the proposed methodology is included in version 0.3 of the open-source software Fatiando a Terra (www.fatiando.org). See module fatiando.gravmag.magdir.</p>
The MMCO-EOT conundrum: same benthic δ18O, different CO2; data supplement
<p>Data supplement to "The MMCO-EOT conundrum: same benthic δ18O, different CO2" by Stap et al. (2016) in Paleoceanography</p>
Supplement of manuscript DSRI2707 ( http://dx.doi.org/10.1016/j.dsr.2016.11.002 )
<p>This folder contains analysis data from the study published as article:</p> <p>TITLE: Molecular diversity patterns among various phytoplankton size-fractions in West Greenland in late summer</p> <p>AUTHORS:</p> <ul> <li>Stephanie Elferink</li> <li>Stefan Neuhaus</li> <li>Sylke Wohlrab</li> <li>Kerstin Toebe</li> <li>Daniela Voß</li> <li>Marc Gottschling</li> <li>Nina Lundholm</li> <li>Bernd Krock</li> <li>Boris P. Koch</li> <li>Oliver Zielinski</li> <li>Allan Cembella</li> <li>Uwe John</li> </ul> <p>JOURNAL: Deep Sea Research Part I: Oceanographic Research Papers</p> <p>MS-ID: DSRI2707</p> <p> </p> <p>List of Files:</p> <p> </p> <p>Description: Filename</p> <p>-------------------------------------------------------------------------------------------------------------------------</p> <p>QIIME-ZIP archive from the QZIP-pipeline: Greenland_Iceland_Euk_28S_M_N_P_combined_R454_20150618_173010.zip</p> <p>(the QZIP addionally contains OTU table as biom, OTU sequences, pipeline log files, result statistics, configure files; to navigate in the QZIP use index.htm)</p> <p>OTU table from QZIP: Greenland_Iceland_Euk_28S_M_N_P_combined_OTU.tab</p> <p>(OTU representatives taxonomically annotated by QIIME internal UCLUST consensus classifier)</p> <p>Phyloassigner OTU annotations: Greenland_Iceland_28S_M_N_P_combined_Strameno_pa.annotation and Greenland_Iceland_28S_M_N_P_combined_Dino_pa.annotation</p> <p>(Additional annotation of Stramenopile and Dinoflagellate OTUs based on phylogenetic placement and LCA determination)</p> <p>Phyloassigner databases:</p> <p>Stramenopiles_LSU_SSU_concat_1777.phyloassignerdb/ and Dinoflagellates_LSU_SSU_concat_640.phyloassignerdb/</p> <p>This README-file: README-DSRI2707.txt</p> <p>-------------------------------------------------------------------------------------------------------------------------</p> <p>For further information on supplement data and related publications see Bioinformatics Group at AWI: http://www.awi.de/en/go/bioinformatics and links therein.</p> <p>Bremerhaven, 04/Jan/2017</p>
Supplemental Movie for "The basis of sharp spike onset in standard biophysical models"
<p>Simulation of extracellular field during action potential.</p>
Data supplementing the article: Schultz, N.M., Lawrence P.J, Lee X., Global satellite data highlights the diurnal asymmetry of the surface temperature response to deforestation. Journal of Geophysical Research - Biogeosciences
<p>These data supplement the article: Schultz, N.M., Lawrence P.J, Lee X. Global satellite data highlights the diurnal asymmetry of the surface temperature response to deforestation, under review at the Journal of Geophysical Research - Biogeosciences.</p> <p>contact: Natalie M. Schultz, natalie.schultz@yale.edu</p> <p>Below are descriptions of the data files included here:</p> <p><br> (1) Global LST data: globalLST_Forest_Open.YYYY.nc [2003-2013]</p> <p>- DayLST1/NightLST1 and DayLST2/NightLST2 are the final (after the DEM correction) LST values for forest, and open land cover classes, respectively.<br> - Count variables show the number of pixels of each land cover class in each 0.5 degree grid<br> - The average elevation of each class is given by the DEM1 and DEM2 vars<br> - The DEM correction is the dLSTdDEM vars</p> <p>(2) Global fluxes data: globalFluxes_Forest_Open.YYYY.nc [2003-2013]<br> - Again, forest class = var1, open class = var2<br> - SWRABS is absorbed solar radiation<br> - LE is the latent heat flux<br> - HP is the heating potential term, as defined in the manuscript<br> - As described for the LST data, class pixel counts and DEM data are included</p> <p>(3) climzones3.nc<br> - The delineation of the three climate zones defined in this paper</p> <p>(4) MERRA inversion data: MERRA_11yr_TS_T10M.mat [2003-2013]<br> - 11 years of daily 1am local data averaged over 8-day intervals for 2003-2013<br> - TS = surface temperature<br> - T10M = 10M air temperature (above d)</p> <p> </p> <p> </p>
Data supplementing the article "Assessing ecological status with diatoms DNA metabarcoding : scaling-up on a WFD monitoring network (Mayotte island, France)" V. Vasselon, F. Rimet, K. Tapolczai, A. Bouchez submitted to Ecological Indicators journal
<p>These data supplement the article"Assessing ecological status with DNA metabarcoding or microscopy? Comparison using benthic diatoms in tropical rivers" V. Vasselon, F. Rimet, K. Tapolczai, A. Bouchez submitted to Ecological Indicators journal.</p> <p>The directory contains the following files:</p> <p><strong>80 PGM sequencing libraries (raw data, fastq files).rar </strong>- contains the 80 fastq files provided by the sequencing platform with demultiplexed DNA reads (raw data prior any bioinformatics treatments).</p> <p><strong>80 fastq files information.xlsx</strong> - contains the information relative to the 80 samples including: the ID used in Mothur analyses (corresponding to the name of the fastq files), the sample name, the sampling site code, the name of the river, the monitoring network to which rivers belong, the year of sampling and the GPS coordinates of sampling sites.</p> <p><strong>OTU (95 percent of similarity) list of 80 Mayotte samples.xlsx</strong> - contains the final OTU list obtained after applying all the bioinformatics treatments (trimming, clustering,...): OTUs created at 95% of similarity, the number of DNA reads per sample was normalized at 5710 reads (the smallest values obtained in one sample). A DNA representative sequence and the taxonomic assignment determined using Mothur (using classify.otu command) are also provided for each OTU.</p>
Data supplementing the conference paper "Who you gonna call? Analyzing web requests in Android applications", 14th International Conference on Mining Software Repositories 2017.
<p>This repository contains the data supplementing the paper:</p> <p>M. Rapoport, P. Suter, E. Wittern, O. Lhótak, J. Dolby, "Who you gonna call? Analyzing web requests in Android applications", MSR 2017.</p> <p>A detailed description of the data is included in the archive in README.md.</p>
Supplemental 3D Model Data - New insights into the evolutionary history of Fungi from a 407 million year old blastocladiomycota-like fossil showing multiple sporangia and an extensive hyphal network (SPIERSView and VAXML format)
<p>Three-dimensional reconstruction models of Fungi from a 407 million year old blastocladiomycota-like fossil showing multiple sporangia and an extensive hyphal network in SPIERSView and VAXML format. 2D and 3D (Red/Cyan) images also provided as a PDF.</p> <p>Notes:</p> <ol> <li>SPIERSView file (.SPV) models can conveniently be viewed using the SPIERSView software, freely available in both Windows and Mac versions from http://www.spiers‐software.org. However, note that low-performance computers may not possess a sufficiently powerful graphics card to render and rotate the model.</li> <li>VAXML file format models are saved as a ZIP-compressed VAXML datasets. VAXML uses one or more .STL files to define the geometry of objects that comprise the dataset, together with one .VAXML file that provides metadata on the dataset as a whole, and specifies how the .STL files should be put together. We recommend using the free SPIERS software to view this model format (http://spiers-software.org/). However, .STL files can be opened independently in several freely available software programs (e.g. MeshLab, Blender). Additional information on the VAXML format can be found here: http://spiers-software.org/VAXML.htm.</li> </ol>
Dataset S1: Oxfordiana motturii gen. et sp. nov. supplemental information (XMT data for BU 5265.1)
<p><strong>Dataset S1.</strong> XMT 8-bit BMP tomographic dataset of BU5265.1. The dataset consists of 754 8-bit bitmap images compressed as a ZIP archive. Image brightness/contrast optimized and despeckling applied. Note that images from the tomographic have been cropped to include only the specimen. [ZIP/BMP format 249 MB]</p>
Dataset S4: Oxfordiana motturii gen. et sp. nov. supplemental information (SRXMT data for BU 5265.2)
<p><strong>Dataset S4.</strong> SRXMT 8-bit BMP tomographic dataset of BU5265.2. The dataset consists of 1200 8-bit bitmap images compressed as a ZIP archive. Image brightness/contrast optimized and despeckling applied. Note that images from the tomographic stack beginning and end, without specimen data present, have not been included. [ZIP/BMP format 10.6 GB]</p>
Dataset S6: Oxfordiana motturii gen. et sp. nov. supplemental information (SRXMT data for slide BU 5266.3)
<p><strong>Dataset S6.</strong> SRXMT 8-bit BMP tomographic dataset of slide BU 5266.3. The dataset consists of 300 8-bit bitmap images compressed as a ZIP archive. Image brightness/contrast optimized and despeckling applied. Note that images from the tomographic stack beginning and end, without specimen data present, have not been included. [ZIP/BMP format 3.3 GB]</p>
Dataset S8: Oxfordiana motturii gen. et sp. nov. supplemental information (SRXMT data for slide BU 5266.37)
<p><strong>Dataset S8.</strong> SRXMT 8-bit BMP tomographic dataset of slide BU 5266.37. The dataset consists of 400 8-bit bitmap images compressed as a ZIP archive. Image brightness/contrast optimized and despeckling applied. Note that images from the tomographic stack beginning and end, without specimen data present, have not been included. [ZIP/BMP format 3.9 GB]</p>
Dataset S3: Oxfordiana motturii gen. et sp. nov. supplemental information (SRXMT data for BU 5265.1)
<p><strong>Dataset S3.</strong> SRXMT 8-bit BMP tomographic dataset of BU5265.1. The dataset consists of 2180 8-bit bitmap images compressed as a ZIP archive. Image brightness/contrast optimized and despeckling applied. Note that images from the tomographic stack beginning and end, without specimen data present, have not been included. [ZIP/BMP format 23.1 GB]</p>
Dataset S9: Oxfordiana motturii gen. et sp. nov. supplemental information (SRXMT data for slide BU 5266.38)
<p><strong>Dataset S9.</strong> SRXMT 8-bit BMP tomographic dataset of slide BU 5266.38. The dataset consists of 351 8-bit bitmap images compressed as a ZIP archive. Image brightness/contrast optimized and despeckling applied. Note that images from the tomographic stack beginning and end, without specimen data present, have not been included. [ZIP/BMP format 3.4 GB]</p>
Dataset S10: Oxfordiana motturii gen. et sp. nov. supplemental information (SRXMT data for slide BU 5266.39)
<p><strong>Dataset S10.</strong> SRXMT 8-bit BMP tomographic dataset of slide BU 5266.39. The dataset consists of 421 8-bit bitmap images compressed as a ZIP archive. Image brightness/contrast optimized and despeckling applied. Note that images from the tomographic stack beginning and end, without specimen data present, have not been included. [ZIP/BMP format 4 GB]</p>
Dataset S2: Oxfordiana motturii gen. et sp. nov. supplemental information (XMT data for BU 5265.2)
<p><strong>Dataset S2.</strong> XMT 8-bit BMP tomographic dataset of BU5265.2. The dataset consists of 724 8-bit bitmap images compressed as a ZIP archive. Image brightness/contrast optimized and despeckling applied. Note that images from the tomographic have been cropped to include only the specimen. [ZIP/BMP format 635 MB]</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.