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5,004 results for “Signature”
Transferring energy signatures across space and time to assess their viability for rapid urban energy demand estimation
<p>This data archive provides simulated hourly heating and cooling building energy demand for current and future RCP85 climate for 8 representative cities for a single-family and small office building archetype.</p> <p>The data forms part of the following publication:</p> <p><em>Eggimann S.; Fiorentini M. (2024): Transferring energy signatures across space and time to assess their viability for rapid urban energy demand estimation. Energy and Buildings. https://doi.org/10.1016/j.enbuild.2024.114348</em></p> <p><strong>Attributes</strong></p> <ul> <li>ID_origin: City ID of source city</li> <li>ID_destination: City ID of target city</li> <li>Signature_Cooling: Cooling demand determined by the signature approach</li> <li>Model_Cooling: Cooling demand determined by EnergyPlus</li> <li>Absolute_Diff: Absolute difference</li> <li>Percentage_Diff: Relative difference</li> <li>Daily_Tout: Average daily dry-bulb ambient temperature</li> </ul> <p><strong>Instruction</strong></p> <p>To obtain the simulation and energy signature-based results, it is required to filter the dataset and set the source ID to the destination ID. The city IDs are provided in the file city_table_ID.</p> <p><strong>Source</strong></p> <p>The archetypes are provided by the Office of Energy Efficiency & Renewable Energy: https://www.energycodes.gov/prototype-building-models</p>
Signalgun Signature measured in Water and Air (Tank Experiment)
<ul> <li>the experiments are performed in and above a water tank</li> <li>signatures of a Stalker R1 2.5'' gun fired at different elevations above the water surface are measured</li> <li>the Stalker R1 2.5'' gun has a caliber of 0.38 in (9 mm) and is fired with blank bullets</li> <li>signatures are measured in water and air with B&K 8105 hydrophones</li> <li>the signal recording is triggered with a hydrophone that is directly attached to the Stalker R1 2.5'' gun (it indicates when the gun is fired) - the measured signals are aligned to the main peak of the trigger signal</li> <li>recordings are averaged/stacked measurements of 4 shots with the Stalker R1 2.5'' gun at each source elevation "zs"</li> <li>the filename indicates the source type ("signalgun_"), where the signal is measured ("water_" or "air_") and the source elevation above the water surface ("zs_cm.txt")</li> <li>more information can be found in the referenced publication and the sketch of the experimental set up</li> </ul>
S15 Watergun Signature measured in Water and Air (Tank Experiment)
<ul> <li>the experiments are performed in a water tank (see photo)</li> <li>signatures of an S15 watergun fired at different water depths are measured</li> <li>S15 watergun has one cylindrical gun port and is fired at 130 bar</li> <li>signatures are measured in water and air with B&K 8105 hydrophones</li> <li>signatures in air are measured at normal incidence, directly above the source (yr = 0 cm, no "yr" in filename) and at different horizontal offsets from the source (varying "yr" as indicated in the filename)</li> <li>channel 3 is the trigger channel and indicates when the S15 watergun is fired</li> <li>recordings are averaged/stacked measurements of 3 shots with the S15 watergun at each source depth "zs"</li> <li>the filename indicates the source type ("watergun_S15_"), where the signal is measured ("water_" or "air_") and the source depth in water ("zs_cm.txt"), and the horizontal offset ("yr") for the specific experiments</li> <li>more information can be found in the referenced publication and the sketch of the experimental set up</li> </ul>
Data for Weighted Manifold Alignment using Wave Kernel Signatures for Aligning Medical image Datasets
<p>Data used in MRI experiments in paper 'Weighted Manifold Alignment using Wave Kernel Signatures for Aligning Medical image Datasets'. For each volunteer, breath-hold data (folder bhs) and dynamic free-breathing (folder dyn) data is provided in NIFTI format.</p>
Multi-study reanalysis of 2213 acute myeloid leukemia patients reveals age- and sex-dependent gene expression signatures
<p>Supplemental Information, Supplementary Tables, and Supplementary Files, as well as accompanying data for the manuscript "Stratified computational meta-analysis of 2213 acute myeloid leukemia patients reveals age- and sex-dependent gene expression signatures" by Raeuf Roushangar and George I. Mias. </p>
The topographic signature of ecosystem climate sensitivities in the western U.S.
<p>It has been suggested that hillslope topography can promote the persistence of hydrologic refugia, sites where ecosystem net primary productivity (NPP) is relatively insensitive to climate variation. However, the mechanisms that promote the persistence of these locations and their spatial distributions are poorly resolved. We quantified the response of ecosystem NPP to variability in the annual climatic water balance for 30 years across the western U.S. The slope of this pixel-specific linear regression represents ecosystem-climate sensitivity and provides a means to identify ecosystems that are buffered from droughts. Environmental conditions produced by hillslope convergence reduced ecosystem sensitivity to climate fluctuations across the entirety of the western U.S. We observed the greatest topographic effect in semi-arid climates, while vulnerability to drought was maximized in flat, arid landscapes. In aggregate, spatial patterns of ecosystem sensitivity can be implemented for regional planning to maximize conservation in landscapes that are more resistant to perturbations.</p>
Data for the publication "Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer"
<p>This dataset encompasses all data needed to reproduce the analyses presented in <a href="https://www.nature.com/articles/s41591-019-0406-6">Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer</a></p> <p>You can also check the <a href="https://github.com/zellerlab/crc_meta">GitHub repository</a></p>
Simulated submerged aquatic vegetation spectral signatures under different water quality conditions using Hydrolight
<p>Reflectance spectra were simulated using the Hydrolight radiative transfer model (Sequoia Scientific, Bellevue, WA) for four different submerged macrophyte species under a range of water quality conditions at two different depths. We used the four-component case-2 model with spectral reflectance of four submerged species, Egeria densa, Ceratophyllum demersum, Cabomba caroliniana, and Stukenia pectinata. These four reflectance spectra were calculated from the median of 10 measurements of the canopies of the representative species placed in clear tap-water made with a handheld ASD FieldSpec Pro spectrometer. Total suspended solids concentration was varied from 1 to 40 g·m<sup>−3</sup>, chlorophyll-a concentration was varied from 0.5 to 50 mg·m<sup>−3</sup>, and colored dissolved organic matter (CDOM) was varied from 0.25 to 3.5 m<sup>−1</sup>. A total of 4,742 spectra were simulated for all four species and a mud substrate at two different depths, 1 m and 5 m, and for optically deep water.</p>
Dynamic load model for passenger trains based on dynamic train signature
<p>20 conventional load model trains based on dynamic signature envelope of 3,140 operating passenger trains in Europe</p> <ul> <li>axle distances in m and axle loads in kN for all model trains as txt-files</li> </ul>
Data from: External validation of prognostic and predictive gene signatures in 1097 European head and neck squamous cell carcinoma patients
<p><span>Anonymized data containing survival endpoints and gene signature scores for head and neck cancer patients.</span></p> <p><span>File <strong>data_os_gs.csv</strong> : data linking overall survival and gene signature scores</span></p> <p><span>File <strong>data_dfs_gs.csv</strong> : data linking disease-free survival and gene signature scores</span></p> <p><span><strong>Variables</strong>:</span></p> <ul> <li><span><em>supertreat_id</em>: patient ID</span></li> <li><span><em>GS_score_172GS</em>: gene signature score for the <em>172-GS</em> signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span><em>GS_score_3clustersHPV</em>: gene signature score for the <em>3 clusters HPV</em> signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span><em>GS_score_RSI</em>: gene signature score for the <em>radiosenstivity index (RSI) </em>signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span><em>GS_score_pancancerCisplatin</em>: gene signature score for the <em>pancancer-cisplatin</em> signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span><em>GS_score_cl3Hypoxia</em>: gene signature score for the <em>Cl3-hypoxia</em> signature. The score is Z-score normalized with a mean of 0 and SD of 1. </span></li> <li><span>Variables only available in <strong>data_os_gs.csv: </strong></span> <ul> <li><span><em>overall_survival_days_2years</em>: Overall survival censored at 2 years since diagnosis. Number of days from diagnosis to death or censoring.</span></li> <li><span><em>overall_survival_days_5years</em>: Overall survival censored at 5 years since diagnosis. Number of days from diagnosis to death or censoring.</span></li> <li><span><em>overall_survival_status_2years</em>: Overall survival status when censored at 2 years since diagnosis. Coded as 0 if censored, and 1 if dead. </span></li> <li><span><em>overall_survival_status_5years</em>: Overall survival status when censored at 5 years since diagnosis. Coded as 0 if censored, and 1 if dead. </span></li> </ul> </li> </ul> <ul> <li><span>Variables only available in <strong>data_dfs_gs.csv:</strong></span> <ul> <li><span><em>disease_free_survival_days_2years</em>: Disease-free survival censored at 2 years since diagnosis. Number of days from diagnosis to an event (death or cancer recurrence) or censoring.</span></li> <li><span><em>disease_free_survival_days_5years</em>: Disease-free survival censored at 5 years since diagnosis. Number of days from diagnosis to an event (death or cancer recurrence) or censoring.</span></li> <li><span><em>disease_free_survival_status_2years</em>: Disease-free survival status when censored at 2 years since diagnosis. Coded as 0 if censored, and 1 if an event (death or recurrence). </span></li> <li><span><em>disease_free_survival_status_5years</em>: Disease-free survival status when censored at 5 years since diagnosis. Coded as 0 if censored, and 1 if an event (death or recurrence). </span></li> </ul> </li> </ul>
Insights into non-axisymmetric instabilities in three-dimensional rotating supernova models with neutrino and gravitational-wave signatures
<p>Those are movies of numerical supernova models, which appear in Takiwaki, Kotake, and Foglizzo, (2021), Monthly Notices of the Royal Astronomical Society, Volume 508, Issue 1, pp.966-985</p>
Transcriptomic analyses of normal-appearing CNS white matter from multiple sclerosis donors reveal subtype-specific molecular signatures of disease (REVISED)
<p>Datasets of bulk RNA-sequencing of NAWM from MS donors + supplementary images of RNA deconvolution of cell trajectories</p>
Data for: Patterns of shared signatures of recent positive selection across human populations
<p>Genome-wide summary stats for modified iHS scan in 1KG as reported in:</p> <p><a href="https://pubmed.ncbi.nlm.nih.gov/29459708/">Patterns of shared signatures of recent positive selection across human populations.</a></p> <p>Johnson KE, Voight BF.Nat Ecol Evol. 2018 Apr;2(4):713-720. doi: 10.1038/s41559-018-0478-6. Epub 2018 Feb 19.</p> <p>PMID: 29459708</p> <p>Code available at: https://github.com/bvoightlab/iHS_calc</p>
Light and confocal micrographs on the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, the accumulation of lipid droplets, and the heterologous expression and localisation of signature LD protein homologs to tobacco pollen tubes
<p>These micrographs accompany the work "Environmental gradients reveal stress hubs predating plant terrestrialization", posted as a pre-print on bioRxiv https://doi.org/10.1101/2022.10.17.512551 </p> <p>The light and confocal micrographs show the response of Mesotaenium endlicherianum SAG 12.97 to a bifactorial environmental gradient, especially their accumulation of lipid droplets (LDs); in confocal micrographs, LDs appeared as distinct structures upon staining with BODIPY.</p> <p>Further confocal micrographs show the heterologous expression and localisation of signature LD protein homologs detected in Mesotaenium endlicherianum SAG 12.97; heterologous expression was carried out in tobacco pollen tubes were also stained with BODIPY and proteins were tagged with mCherry.</p>
Molecular adaptations in response to exercise training are associated with tissue-specific transcriptomic and epigenomic signatures
<p>Processed data associated with the manuscript DOI: <a href="https://doi.org/10.1016/j.xgen.2023.100421" target="_blank" rel="noopener">10.1016/j.xgen.2023.100421 </a></p> <p>Analysis code on GitHub: <a href="../doi/10.5281/zenodo.8253917" target="_blank" rel="noopener">10.5281/zenodo.8253917</a></p> <p> </p>
Hanle rotation signatures in Sr I 4607 Å
<p>This data set contains spectropolarimetric measurements of the solar limb in the Sr I 4607 A line, obtained with the Gregory Coudé Telescope at IRSOL in Locarno, Switzerland, with the ZIMPOL polarimeter. These observations are described and discussed in the article:<br> <br> Zeuner, F.; Belluzzi, L.; Guerreiro, N.; Ramelli, R.; Bianda, M.:<br> 2022, "Hanle rotation signatures in Sr I 4607 Å", Astronomy and Astrophysics, 662, A46, <a href="https://ui.adsabs.harvard.edu/link_gateway/2022A&A...662A..46Z/doi:10.1051/0004-6361/202243350">doi: 10.1051/0004-6361/202243350</a></p> <p>Remark: due to the slit rotation, the published data of Stokes U has to be multiplied by -1 to get a correct Stokes reference system. This error was not taken into account in the paper.</p>
Genome-Wide Mutational Signatures of Aristolochic Acid and Its Application as a Screening Tool
<p>The .zip files contain the fastq files for the cell line data published in DOI: 10.1126/scitranslmed.3006086 plus results of analyzing these data. HK2_AA and HK2b-8d2 were exposed to AA (aristolochic acid I), and HK2_ctrl was an unexposed control. The .tsv files are VCF-like files with the mutations found in the exposed cells. spectrum_counts.txt are what are now called "SBS96" spectra -- counts of single base substitutions in the contexts of preceding and following bases. The PDF file has plots of these. (The HUC1 cells that were exposed did not show AA-related mutations.)</p> <p> </p>
Output tomographic models for "The attenuation and scattering signature of fluids and tectonic interactions in Central-Southern Apennine."
<p>Output ASCII file for the seismic attenuation tomography in Central-Southern Apennines. The output format is the one from MuRAT software (De Siena et al., 2014). Q and Peak-Delay models in 1.5 Hz, 3 Hz and 6 Hz frequencies are reported as specificated by the files name. The output points of a grid with coordinates available in WGS84 degrees ("Degrees" suffix) or already projected in kilometric UTM coordinates ("UTM" suffix).</p> <p>All other information can be found in the main and supplementary text.</p>
SignEEG v1.0 : Multimodal Electroencephalography and Signature Database for Biometric Systems
<p>Noninvasive electroencephalography (EEG) is a method for measuring electrical brain activity from the surface of the scalp. Recent developments in artificial intelligence accelerate the automatic recognition of brain patterns, allowing more reliable and increasingly faster Brain-Computer interfaces, including biometric applications. Biometric research is also focusing on multimodal systems using EEG along with other modalities. This paper presents a new multimodal SignEEG v1.0 dataset based on EEG and hand-drawn signatures from 70 subjects. EEG signals and hand-drawn signatures have been collected with Emotiv Insight and Wacom One sensors, respectively. The multimodal data consists of three paradigms with increasing brain functioning: (i) visualizing a signature image, (ii) doing a signature in mind, and (iii) physically drawing a signature. Extensive experiments have been done in order to provide a solid baseline with machine learning classifiers. We release the raw, pre-processed data and easy-to-follow implementation details.</p>
Biomass %N, %C, natural abundance 15N and 13C isotopic signatures for common and rare under- and overstory plants in long unburned and burned (1999) boreal forest stands, Caribou-Poker Creek and Delta Junction
This dataset contains leaf, aboveground stem, and fruit carbon and N concentration and natural abundance isotope data for new and old tissue fractions of common and rare plant species in burned and unburned black spruce forest stands. Stands were located in either Caribou-Poker Creek or Delta Junction, in either unburned areas, or in areas burned in 1999 fires. Biomass was collected between 2000 and 2001 in mid-July at peak biomass.
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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.