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3,696 results for “Reference”
Golden-reference and data-under-attack from TRNG on FPGA
<p>This dataset consists of the raw output from an elementary TRNG on a Xilinx Spartan-6 FPGA. The first group of data is called golden-reference. And the second group is called data-under-attack and was collected with an oversampled clock rate.</p>
Supplementary file pwt: Female length of Tylorida striata per taxonomic reference, examined syntypes and specimens from India from Bridging the distributional gap of Tylorida striata (Thorell, 1877) and new synonymy (Araneae: Tetragnathidae) - Biodiversity Data Journal 3: e4878 (26 March 2015) https://doi.org/10.3897/BDJ.3.e4878
Female length of Tylorida striata per taxonomic reference, examined syntypes and specimens from India
Collaborative Reference Database as of 2017-02-17
<p><strong>Abstract</strong> (our paper)</p> <p><strong>Code</strong></p> <p>crd-reference-v2.pl:<br> mew.</p> <p><strong>Data</strong></p> <p>crd-reference-v2.txt.gz:<br> mew.</p> <p>crd-reference-v2-urls.txt.gz:<br> mew.</p> <p><strong>Publication</strong></p> <p>This data set was created for our study. If you make use of this data set, please cite:<br> Sho Sato, Mitsuo Yoshida. Current Status of Reference Services in Japanese Libraries Analyzed with the Collaborative Reference Database. <em>Current Awareness (in Japanese)</em>. no.332, pp.xx-xx, 2017.<br> http://current.ndl.go.jp/ca_list</p> <p><strong>Note</strong></p> <p>The raw data is available in the following page.<br> http://crd.ndl.go.jp/jp/help/general/api.html</p>
Gathered datasets of cardiorespiratory activity by using the inductive coupling with single coil together with reference waveforms of ECG and spirometer
<p>Hereby the datasets, that were gathered during the experiments of monitoring the cardiorespiratory activity by using the inductive coupling together with the reference waveforms of ECG and spirometer, are published.:<br> Waveforms of inductive monitoring.zip<br> Reference waveforms of ECG and spirometer.zip</p> <p>A single volunteer participated in the experiments: healthy male, 33 years old, height of 183 cm and weight of 70 kg.</p> <p>The results are gathered from 12 positions lying around the thorax in imaginary horizontal level, approximately 10 mm below xiphisternal joint. The central position on front side of thorax is designated according to xiphisternum. The central position on front side of thorax is designated according to backbone.</p> <p>The datasets are available in .txt format, and are in separate .zip packages for inductive monitoring and reference waveforms. The correcponding dataset for every position can de identified by position number in both datasets. The signals are raw signals, not processed in any way.</p> <p>In the case of inductive monitoring the change variation of equivalent parallel resonance impedance (Rp) is shown. Concerning the reference waveforms, in the case of ECG, the result is shown in voltages (V). The reference data of respiration (gathered by using spirometer) is available in the form of two sets of digital pulses (0-s and 1-s). These pulses are representing the inhalation and exhalation i.e. either the rotor of the spirometer turns in one way or another. According to the frequency of the pulses, depending on the air flowing speed, the respiratory waveform can be constructed.</p>
Additional reference file for descriptive components of the survey questionnaires
<p>Additional references for descriptive components of the survey questionnaires for manuscript entitled "A systematic review of the literature on survey questionnaires to assess self-medication practices"</p>
AVATAR-Soils Database: A Database of 137Cs and 239+240Pu in Equatorial and Southern Hemisphere Reference Soils
<p>A total of 1122 reference soil profiles with <sup>137</sup>Cs and <sup>239+240</sup>Pu data from 135 publications were included to build a database under the AVATAR Project (“A reVised dATing framework for quantifying geomorphological processes during the AnthRopocene”), with a focus on compiling available data from the Equatorial and Southern Hemisphere regions. The AVATAR-Soils Database covers parts of the continents of Asia and the Sub-Saharan Africa, and the whole of Oceania and South America. The <sup>137</sup>Cs (decay-corrected to 2024) and <sup>239+240</sup>Pu data extracted from the literature include the inventory (in Bq/m<sup>2</sup>) and average activities (in Bq/kg) of the soil profile collected, and the <sup>137</sup>Cs/<sup>239+240</sup>Pu activity and <sup>239</sup>Pu/<sup>240</sup>Pu atomic ratios. In addition to the <sup>137</sup>Cs and <sup>239+240</sup>Pu data, the associated spatial, climatic, and topographic parameters and sampling details were also added in the database. The database contains the metadata describing the column names, separate tabs for <sup>137</sup>Cs and <sup>239+240</sup>Pu, and the list of publications.</p> <p> To cite the AVATAR-Soils Database, please use:</p> <p>Dicen, G., Guillevic, F., Gupta, S., Chaboche, P.-A., Meusburger, K., Sabatier, P., Evrard, O., and Alewell, C.: <strong>Distribution and sources of fallout <sup>137</sup>Cs and <sup>239+240</sup>Pu in equatorial and Southern Hemisphere reference soils</strong>, Earth Syst. Sci. Data, 17, 1529–1549, https://doi.org/10.5194/essd-17-1529-2025, 2025.</p> <p>***NOTES TO RESEARCHERS***</p> <p>Researchers who wish to add data to the AVATAR-Soils Database may do so through the following link: https://docs.google.com/spreadsheets/d/15R-rDMH6zW65B3ok3YRb0cdtyY67X_mdlC0H1t1atoY/edit?usp=drive_link</p>
eDNAExplorer.org reference libraries
Open the record for dataset details and reuse information.
TANGO reference spectra and gain vectors MRD V1.2
<p>TANGO_reference_spectra.xlsx contains TANGO reference spectra for the visible and shortwave infrared (cloudy scene added). TANGO_reference_gain_vector.xlsx includes gain vectors for XCO2, XCH4, and the tropospheric NO2 column for the Lref reference scene (not changed). </p>
WRF-Chem output- concentrations for the 4 simulations: reference, urbanization, extension of agricultural areas and more urban parks
<p>We use the WRF-Chem air-quality model with an urban canopy scheme to investigate how land use (urban, agriculture, parks) affects the urban climate and chemical processes (dry deposition, biogenic emissions), resulting in changes in air quality for scenarios proposed by the Urban Master Plan of the Metropolitan Area of Barcelona. We selected a heatwave period, 4th-7th July 2015, with maximum temperatures reaching 40 °C in the interior of the AMB and 35 °C on the coast. Here we provide averaged model output for the heatwave period for the different pollutants, surface temperature, wind speed, PBLH, deposition, and biogenic emissions under different urban scenarios: reference (REF), urbanization (URB), extension of agriculture (AGR), and increase in urban parks (PARK).<br><br>The results for a period before the heatwave (1-3 July 2015), with temperatures 3-4 degrees lower than during the heatwave, are also provided. <br><br>Land-use and irrigation is also provided for each scenaio. </p>
Mash Sketch of RefSeq Bacterial Reference Genomes
<p>The mash reference that can be downloaded from <a href="https://mash.readthedocs.io/en/latest/data.html">the mash documentaion</a> is for RefSeq version 70.</p> <p>I do not inherently have a problem with RefSeq version 70, but RefSeq is well past version 200 now. </p> <p>RefSeq updates four times year, and I needed an easy way to create and distribute a mash sketch file of the representative bacterial/prokaryotic genomes.<br><br>This is intended to be a place to hold the mash sketches from <a href="https://github.com/erinyoung/update_mash_dist">https://github.com/erinyoung/update_mash_dist</a>.<br><br>The mash sketch file from erinyoung/update_mash_dist requires git lfs to be installed when cloning the repository, which is cumbersome for some users.<br><br>The update requency is intended to mirror that of RefSeq (i.e. 4 time a year), but... is likely to be less frequent than that.<br><br>Don't hesitate to <a href="https://github.com/erinyoung/update_mash_dist/issues">submit an issue</a> if this needs to get updated.<br><br>I do have some prior zenodo repositories (https://zenodo.org/records/10519852 , https://zenodo.org/records/7887021 , and https://zenodo.org/records/7348463 ) which hold the same mash sketch reference, but the refseq version is in the title. I'd rather have one repository that gets updated rather than create new repositories each time.<br><br>This is how the mash reference file was created:<br><br></p> <pre><code># Step 1. Download Datasets and Dataformat </code></pre> <pre><code>wget https://ftp.ncbi.nlm.nih.gov/pub/datasets/command-line/v2/linux-amd64/datasets wget https://ftp.ncbi.nlm.nih.gov/pub/datasets/command-line/v2/linux-amd64/dataformat chmod +x datasets dataformat</code></pre> <pre><code> # Step 2. Download Mash <br></code></pre> <pre><code> wget https://github.com/marbl/Mash/releases/download/v2.3/mash-Linux64-v2.3.tar tar -xvf mash-Linux64-v2.3.tar </code></pre> <pre><code><br> # Step 3. Get a list of all the genomes # Note: this also changes how some of the names are represented datasets summary genome taxon bacteria --reference --as-json-lines | \ dataformat tsv genome --fields accession,organism-name --elide-header | \ sed 's/\[//g' | \ sed 's/\]//g' | \ sed 's/["'\'']//g' | \ sed 's/endosymbiont of /endosymbiont_of_/g' > \ ids.txt # Step 4. Download the reference files and sketch them # Note: Since this is done in Github Actions (GA), I need to keep everything below 30G. # The best way to do this is to download the process each reference file individually, and then combine it to the whole. # This obviously does not need to be followed if not under those same limitations. while read line do id=$(echo $line | awk '{print $1}') ge=$(echo $line | awk '{print $2}') if [ ! -n "$ge" ] ; then ge="unknown" ; fi sp=$(echo $line | awk '{print $3}') if [ ! -n "$sp" ] ; then sp="unknown" ; fi datasets download genome accession $id unzip ncbi_dataset.zip cp ncbi_dataset/data/*/*_genomic.fna ${ge}_${sp}_${id}.fasta if [ ! -f RefSeqSketches_${version}.msh ] then mash sketch ${ge}_${sp}_${id}.fasta -o RefSeqSketches_${version} else mash sketch ${ge}_${sp}_${id}.fasta -o ${ge}_${sp}_${id} mv RefSeqSketches_${version}.msh tmp.msh mash paste RefSeqSketches_${version} tmp.msh ${ge}_${sp}_${id}.msh rm tmp.msh ${ge}_${sp}_${id}.msh fi rm ${ge}_${sp}_${id}.fasta rm -rf ncbi_dataset/ rm ncbi_dataset.zip rm README.md rm md5sum.txt done < ids.txt</code></pre> <pre><br><br>To use</pre> <pre><code># download file wget <insert url for file> mask sketch sample.fasta RefSeqSketches_<version>.msh > mash_results.txt # These results are unsorted, so many find it useful to sort them. sort -gk3 mash_results.txt > sorted_mash_results.txt</code></pre> <p> <br>The should look like the following:</p> <pre><code>2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_pyogenes_GCF_900475035.1.fasta 0.0116661 0 643/1000 2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_dysgalactiae_GCF_016128095.1.fasta 0.0782587 0 107/1000 2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_canis_GCF_900636575.1.fasta 0.132399 2.34894e-153 32/1000 2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_agalactiae_GCF_001552035.1.fasta 0.164662 1.32611e-72 16/1000 2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_castoreus_GCF_000425025.1.fasta 0.174408 2.34302e-58 13/1000 2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_didelphis_GCF_000380005.1.fasta 0.182269 8.30736e-49 11/1000 2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_uberis_GCF_900475595.1.fasta 0.186761 5.62934e-44 10/1000 2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_iniae_GCF_000831485.1.fasta 0.191731 3.33152e-39 9/1000 2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_ictaluri_GCF_000188015.2.fasta 0.197292 1.75608e-34 8/1000 2024CK-00429-UT-M03999-240412_contigs.fa Streptococcus_phocae_GCF_001302265.1.fasta 0.203604 2.46548e-30 7/1000</code></pre> <pre> </pre>
Experimental dataset referring to: Non-intrusive temperature measurements for transient freezing in laminar internal flow using laser induced fluorescence
<p>This data set corresponds to the paper 'Non-intrusive temperature measurements for transient freezing in laminar internal flow using laser induced fluorescence. Please cite this paper when using this data. </p><p>The following conditions are included (for both the inlet and the centre of the channel):</p><p>Re = 474, T_in,set = 0.5</p><p>Re = 474, T_in,set = 5.0</p><p>Re = 474, T_in,set = 10.0</p><p>Re = 474, T_in,set = 15.0</p><p>Each folder includes the original two-color LIF ratio-metric data and the temperature recordings of the cold-plate as well as the inlet, outlet temperatures and the flow rate (TData). The header for the recordings is included in the main dataset which may be used to navigate the columns and select the relevant data.</p><p> </p>
Extended reference scenarios (ERS) file (including only the temperature and trace species climatology)
<p>Extended reference scenarios are store in a single NetCDF file providing the atmospheric state (pressure, temperature and composition) expected to be seen by CAIRT for different conditions (altitude, latitude, season, time, solar activity and volcanic activity). </p>
Fig. 8 in Revision of the Small Tropical Whipsnakes Previously Referred to Demansia olivacea (Gray, 1842) and Demansia torquata (Günther, 1862) (Squamata: Elapidae)
Fig. 8. Head shields and colour pattern of the head
Fig. 21 in Revision of the Small Tropical Whipsnakes Previously Referred to Demansia olivacea (Gray, 1842) and Demansia torquata (Günther, 1862) (Squamata: Elapidae)
Fig. 21. Holotype of Demansia torquata (BMNH 1946.1.17.41).
Fig. 10 in Revision of the Small Tropical Whipsnakes Previously Referred to Demansia olivacea (Gray, 1842) and Demansia torquata (Günther, 1862) (Squamata: Elapidae)
Fig. 10. Distribution of Demansia olivacea
Fig. 11 in Revision of the Small Tropical Whipsnakes Previously Referred to Demansia olivacea (Gray, 1842) and Demansia torquata (Günther, 1862) (Squamata: Elapidae)
Fig. 11. Holotype of Demansia quaesitor (NTM R16836).
Fig. 6 in Revision of the Small Tropical Whipsnakes Previously Referred to Demansia olivacea (Gray, 1842) and Demansia torquata (Günther, 1862) (Squamata: Elapidae)
Fig. 6. Head shields and colour pattern of the head and
Fig. 16 in Revision of the Small Tropical Whipsnakes Previously Referred to Demansia olivacea (Gray, 1842) and Demansia torquata (Günther, 1862) (Squamata: Elapidae)
Fig. 16. Holotype of Demansia rufescens (WAM R52747).
Fig. 4 in Revision of the Small Tropical Whipsnakes Previously Referred to Demansia olivacea (Gray, 1842) and Demansia torquata (Günther, 1862) (Squamata: Elapidae)
Fig. 4. Holotype of Demansia calodera (WAM R54992).
Fig. 9 in Revision of the Small Tropical Whipsnakes Previously Referred to Demansia olivacea (Gray, 1842) and Demansia torquata (Günther, 1862) (Squamata: Elapidae)
Fig. 9. Holotype of Elapocephalus ornaticeps (AM R31918).
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.