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1,079 results for “source data”
Source Data and Code - Calcaterra et al., 2024 (https://doi.org/10.1038/s41560-024-01606-7)
<p>Model results, code for processing it, and figure generation for Calcaterra et al., 2024, Nature Energy, "Reducing cost of capital to finance the energy transition in developing countries" (doi: <span>https://doi.org/10.1038/s41560-024-01606-7)</span></p> <div> <div> </div> </div>
Water level of Qinghai Lake based on multi-source satellite altimetry data
Open the record for dataset details and reuse information.
Data for "The Source of Hydrogen in Earth's Building Blocks"
<p>Sulfur X-ray absorption near edge structure spectroscopy data from LAR 12252, collected at beamline I18 at Diamond Light Source. </p>
A 40-year moisture source data for Tibetan Plateau precipitation using a 3D Lagrangian approach
<p>This repository contains the dataset that reproduces the work by Cheng et al. (2024). The zip files contain data in netCDF format. They consist of</p> <ol> <li>Data of Figures 1-5 in the article (Cheng et al. 2024)</li> <li>Moisture sources of precipitation in the Tibetan Plateau (TP) <ul> <li><code>TP_moisture_source_1971-2010.nc</code>: Global map (lon,lat,time) of 40 years of moisture source (mm/day) contributing to the TP precipitation based on the FLEXPART-WaterSip approach</li> <li><code>SR_1971-2010_TP_grids_1x1_XXX.nc</code>: Fractional contributions of different circulation regimes to each of 302 1˚x1˚ grids on the TP</li> </ul> </li> <li>Multi-product ensemble mean precipitation and evapotranspiration</li> <li>Boundary data of TP river basins used in the study</li> </ol> <p>For any enquiries, feel free to contact Dr. Tat Fan (Franklin) Cheng at <a href="mailto:franklin.cheng@ust.hk">franklin.cheng@ust.hk</a>. Please cite our two recent articles if you found the dataset useful. Thank you!</p> <p><strong>References</strong></p> <blockquote> <p>Cheng, T. F., Chen, D., Wang, B., Ou, T. & Lu, M. (2024). Human-induced warming accelerates local evapotranspiration and precipitation recycling over the Tibetan Plateau. <em>Commun Earth Environ </em>5, 388. <a href="https://doi.org/10.1038/s43247-024-01563-9">https://doi.org/10.1038/s43247-024-01563-9</a> </p> <p>Cheng, T. F., & Lu, M. (2023). Global Lagrangian Tracking of Continental Precipitation Recycling, Footprints, and Cascades. <em>Journal of Climate</em>, 36, 1923–1941. <a href="https://doi.org/10.1175/JCLI-D-22-0185.1">https://doi.org/10.1175/JCLI-D-22-0185.1 </a></p> </blockquote>
Source Data for Baldelli et al., Performance of single nanopore and multi-pore membranes for blue energy
<p>HOW TO read and utilized all the files used to create Figure 2 of the manuscript.<br><br>The files are divided in two folders:<br> - Charge: in the "Charge" folder, two files can be found: rt_2nm.log and rt_5nm.log.<br> In these files, 4 tables are reported. Each table represents the ionic currents<br> (I- and I+) versus the surface charge density, for a zero applied external voltage<br> and for different nanopore geometries.<br> In particular, in the rt_2nm.log file, the charge-current curves for the conical<br> and bullet-shaped nanopores with a tip radius (rt) of 2 nm are reported.<br> In rt_5nm.log, charge-current curve for all the geometries and for rt = 5 nm are reported.<br> In principle, these files can be used to evaluate the transference number t-, Eq.(1) and<br> then Eq.(3) and Eq.(4) of the manuscript it is possible to draw all the<br> panels in Fig.2 maintaining the error low. <br> To compute the total current, that is the osmotic current since no external voltage is<br> applied, sum the second and the third column with their sign.<br> In both the files: use the first table per conical nanopore performance; the second table<br> for BS2 nanopore performance; use the third table for BS4 nanopore performance;<br> use the fourth table for BS6 nanopore performance<br> <br> - Voltage: the "Voltage" folder is divided in other two sub-folders rt_2nm and rt_5nm.<br> In this folder the complete I-V curvers for all the surface charge considered in the<br> manuscrip are reported.<br> In rt_2nm (rt_5nm) subfolder the I-V curves for the nanopores characterized<br> by a tip radius (rt) of 2 nm (5 nm) are reported.<br> In each sub-folder the I-V, one file for each surface charge considered can be found.<br> For instance, the file rt2nm_160mCm2.log contains the I-V curves for all the geometries<br> with a surface charge of 160 mC/m^2.<br> In the following, we explained how to obtain each panels of Fig.2 of the main manuscript.<br> Note that the second row of Fig.2 (panels b,d,f and h)<br> can be drawn in the same way of the first row (panels a,c,e and g), hence<br> in the following we explain only how to draw the first rows and the same approach<br> remains valid for the second one.<br> Let's start using files in the rt_2nm sub-folders.<br> - Panel (a): The osmotic current I_o, is the current for a zero applied<br> external voltage.<br> Therefore, this panel can be drawn using the first row of each column for all the files<br> in the sub-folder. Note that in the first row of a table the current for a zero voltage<br> is reported.<br> The second way to draw this panel is using the Charge/rt_2nm.log file.<br> In fact in this file the current for zero voltage and for all the charges is reported.</p> <p> - Panel (c): The membrane potential E_m is the voltage measured across the membrane<br> at zero current condition. Therefore can be obtained through the I-V curve<br> observing at which voltage value the current curve intersects the voltage axis itself.<br> For those files that contain separate ionic and cationic currents, these should be<br> summed to obtain the total current I_tot. If the file only contains tables with a <br> voltage column and I_tot, then the second column can be used directly.</p> <p> - Panel (e): The transference number t_- can be calculated using the Eq.(1).<br> For those files that contain separate ionic and cationic currents, t_- can be<br> calculated using the second (anionic current I-)<br> and third column (cationic current I+) (and Eq.(1)). <br> For those file that contain only I_tot, t- can be calculated by inverting Eq.(3)<br> (considering the activity coefficients equal to 1), having previously calculated<br> the membrane potential E_m (see the previous point).</p> <p> - Panel (g): From the I-V curve, draw the P-V curve and then estimate the maximum power.<br> If the file contains the anionic and cationic current separately, sum these currents<br> to obtain I_tot and then using it to draw the P-V curve.<br> If only I_tot is reported, use it directly to plot the P-V curve.<br> <br> For the panels (b, d, f and h) use the same approach but working with the data reported<br> in the rt_5nm sub-folder.</p>
Data from: Source-sink relationships during grain filling in wheat in response to various temperature, water deficit and nitrogen deficit regimes
<p>Grain filling is a critical process for improving crop production under adverse conditions caused by climate change. Here, using a quantitative method, we quantified post-anthesis source-sink relationships of a large data set to assess the contribution of remobilized pre-anthesis assimilates to grain growth for both biomass and nitrogen. The data set came from 13 years' semi-controlled field experimentation, in which six bread wheat genotypes were grown at plot scale under contrasting temperature, water, and nitrogen regimes. On average, grain biomass was ~10% higher than post-anthesis aboveground biomass accumulation across regimes and genotypes. Overall, the estimated relative contribution (%) of remobilized assimilates to grain biomass became increasingly significant with increasing stress intensity, ranging from virtually nil to 100%. This percentage was altered more by water and nitrogen regimes than by temperature, indicating the greater impact of water or nitrogen regimes relative to high temperatures under our experimental conditions. Relationships between grain nitrogen demand and post-anthesis nitrogen uptake were generally insensitive to environmental conditions, as there was always significant remobilization of nitrogen from vegetative organs, which helped to stabilize the amount of grain nitrogen. Moreover, variations in the relative contribution of remobilized assimilates with environmental variables were genotype-dependent. Our analysis provides an overall picture of post-anthesis source-sink relationships and pre-anthesis assimilate contributions to grain filling across (non-)environmental factors, and highlights that designing wheat adaption to climate change should account for complex multi-factor interactions.</p>
Data from Figures in "Ultralow-loss integrated photonics enables bright, narrow-band, photon-pair sources"
<p><span>The MATLAB code and data used </span><span>to produce the plots within "Ultralow-loss integrated photonics enables bright, narrow-band, photon-pair sources". </span></p>
Source data for figures in the main text of the publication: "Iron-catalyzed cooperative red-ox mechanism for the simultaneous conversion of nitrous oxide and nitric oxide"
<p>Source data for figures 2, 4, 5 and 6 present in the main text of the manuscript titled: "Iron-catalyzed cooperative red-ox mechanism for the simultaneous conversion of nitrous oxide and nitric oxide"</p>
Source data of Mirtronstructdb - A comprehensive database of mirtrons with predicted secondary structure
Open the record for dataset details and reuse information.
Source data behavioural results in figures - "Beliefs matter - Enhanced instructed fear learning in delusion-proneness"
<p>Dataset compiling the source data of the behavioural results presented in figures of the manuscript "Beliefs matter - Enhanced instructed fear learning in delusion-proneness" (main text and supplementary material). The file contains different spreadsheets that are associated with individual figures (specified in spreadsheet names).</p>
Synchrotron source FTIR data (high-pressure, high-temperature) on chrysene, C18H12.
<p>This dataset contains experimental data collected on chrysene, C18H12, in a diamond anvil cell at pressures up to 10 GPa and a temperature range of 30-300 C</p> <p>Experimental data: synchrotron source FTIR data collected at Beamline X01DC in 2009, using the instrumentation documented in "<a href="http://dx.doi.org/10.1021/jp105020f">Stability of Coronene at High Temperature and Pressure</a>," <em>JOURNAL OF PHYSICAL CHEMISTRY B</em>, Vol: 114, Pages: 15753-15758, ISSN: 1520-6106, doi: 10.1021/jp105020f. FTIR-microspectrometry in transmission was performed using synchrotron light at the Swiss Light Source operated in top-up mode. Thus the infrared intensity remains constant with time. The IR focus available at the end of the beamline was coupled to the side port of a Bruker Vertex 70 FTIR spectrometer with an <em>f</em>1 = 34 mm/<em>f</em>2 = 213 mm ellipsoidal mirror. The spectrometer, equipped with a KBr beamsplitter, was coupled to the input of a Bruker Hyperion IR microscope without any additional optics. The microscope was equipped with two ×15 gold-coated Cassegrain objectives. The illuminated region of the sample was determined by an aperture of some 20−45 μm × 20−45 μm. In order to reduce the effect of scattered light and to enhance contrast fidelity, an identical conjugate aperture was placed between the collecting optics and the nitrogen-cooled mercury−cadmium−telluride (MCT) detector. Resolution and number of coadded scans were 4 cm<sup>−1</sup> and 256, respectively. Crystals were observed in parallel by use of white light and a charge-coupled device (CCD) camera.</p> <p>Each zip file contains data files in raw (OPUS) and plain text (.dpt) formats, and a pdf scane of the labbook, which provides a key to relate the file names to the pressure/temeprature of the sample. Raw files are provided for both the background and the sample; plain text files were created from processed files. </p>
Crossref as a source of scientometric data for social & human sciences [dataset]
<p>This is a dataset used in and produced by research described in the paper titled "Crossref as a source of scientometric data for social & human sciences".</p>
Supporting data and source codes for Hnilica et al. (submitted to HESS)
<p>Data and source codes to reproduce the results and plots presented in Technical note: Changes of cross- and auto-dependence structures in climate projections of daily precipitation and their sensitivity to outliers (submitted to Hydrology and Earth System Sciences)</p>
Characteristics of summer season raindrop size distribution in western Pacific (Data source)
<p>Datailed information on the data sets used in our manuscript are provided, along with the main code in data process.</p>
Single-molecule source data files
<p>This data archive contains single-molecule source data for "Delayed inhibition mechanism for secondary channel factor regulation of ribosomal RNA transcription" by Sarah K. Stumper, Harini Ravi, Larry J. Friedman, Rachel Anne Mooney, Ivan R. Corrêa, Jr., Anne Gershenson, Robert Landick, and Jeff Gelles.</p> <p>The data archive (doi: 10.5281/zenodo.2530159) provides files for each figure and figure supplement. The files are ‘intervals’ files readable by the imscroll program (<a href="https://github.com/gelles-brandeis/CoSMoS_Analysis">https://github.com/gelles-brandeis/CoSMoS_Analysis</a>).</p>
Single-molecule source data files
<p>This data archive contains single-molecule source data for "A Conserved Mcm4 Motif is Required for Mcm2-7 Double-hexamer Formation and Origin DNA Unwinding" by Kanokwan Champasa, Caitlin Blank, Larry J. Friedman, Jeff Gelles, and Stephen P. Bell.</p> <p>The data archive (doi: 10.5281/zenodo.2556799) provides files for figure 5 and 6. The ‘intervals’ files are readable by the imscroll program (<a href="https://github.com/gelles-brandeis/CoSMoS_Analysis">https://github.com/gelles-brandeis/CoSMoS_Analysis</a>).</p>
Volcanic ash source inversion data for paper "A near-real-time method for estimating volcanic ash emissions using satellite retrievals"
<p>This dataset consists of volcanic ash source inversion data for the paper "A near-real-time method for estimating volcanic ash emissions using satellite retrievals" by Rachel E. Pelley, David J. Thomson, Helen N. Webster, Michael C. Cooke, Alistair J. Manning, Claire S. Witham and Matthew C. Hort, Atmosphere, 2021, 12, 1573, https://doi.org/10.3390/atmos12121573. Satellite retrievals, dispersion model simulations and inversion calculations are included for the eruptions of Eyjafjallajokull in 2010 and Grimsvotn in 2011.</p>
Supplemental Data_Examination of Nutrient Sources and Transport in a Catchment with an Audubon Certified Golf Course
<p>In the attached .zip there are two documents that serve as supplemental information to our paper entitled "Examination of Nutrient Sources and Transport in a Catchment with an Audubon Certified Golf Course". The first document, entitled "Supplemental Data 1," contains the scatter plot for the linear regression model used to model chloride from electrical conductivity. The other document, entitled "Supplemental Data 2," contains a set of figures that explains a second storm hydrograph in which three-end-member mixing were observed, similar to the one discussed in the original manuscript.</p>
Data for the study: Comparison of beamformer implementations for MEG source localization
<p>This data set is a part of the study 'Comparison of beamformers implementations for MEG source localization'. The dataset includes 64 phantom datasets, 2 human datasets, and 50 simulated datasets. The data also include segmented MRI files from FreeSurfer for MEG phantom (Megin Oy, Helsinki, Finland) and a human subject MRI. It also includes the used versions of the four beamforming packages (MNE-Python, FieldTrip, SPM12(DAiSS), and Brainstorm) and codes used for the analysis.</p>
Fig. 4 Species distribution models for Vaejovis carolinianus. Results were projected onto LGM conditions from MIROC a and CCSM4 b data sources invoking the model generated using current climates data c in Pliocene origins, Pleistocene refugia, and postglacial range expansions in southern devil scorpions (Vaejovidae: Vaejovis carolinianus)
Fig. 4 Species distribution models for Vaejovis carolinianus. Results were projected onto LGM conditions from MIROC a and CCSM4 b data sources invoking the model generated using current climates data c. Localities used to test and train the model are indicated by
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.