Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
818
datasets available to search
ShareScore release 0.9.0
Dataset results
818 results for “Neutrality”
Supplementary information for: Macrophage- and CD4+ T cell-derived SIV differ in glycosylation, infectivity, and neutralization sensitivity
<p>The human immunodeficiency virus (HIV) envelope protein (Env) mediates viral entry into host cells and is the primary target for the humoral immune response. Env is extensively glycosylated, and these glycans shield underlying epitopes from neutralizing antibodies. The glycosylation of Env is influenced by the type of host cell in which the virus is produced. Thus, HIV is distinctly glycosylated by CD4<sup>+</sup> T cells, the major target cells, and macrophages. However, the specific differences in glycosylation between viruses produced in these cell types have not been explored at the molecular level. Moreover, it remains unclear whether the production of HIV in CD4<sup>+</sup> T cells or macrophages affects the efficiency of viral spread and resistance to neutralization. To address these questions, we employed the simian immunodeficiency virus (SIV) model. Glycan analysis implied higher relative levels of oligomannose-type <em>N</em>-glycans in SIV from CD4<sup>+</sup> T cells (T-SIV) compared to SIV from macrophages (M-SIV), and the complex-type <em>N</em>-glycans profiles seem to differ between the two viruses. Notably, M-SIV demonstrated greater infectivity than T-SIV, even when accounting for Env incorporation, suggesting that host cell-dependent factors influence infectivity. Further, M-SIV was more efficiently disseminated by HIV-binding cellular lectins. We also evaluated the influence of cell type-dependent differences on SIV's vulnerability to carbohydrate-binding agents (CBAs) and neutralizing antibodies. T-SIV demonstrated greater susceptibility to mannose-specific CBAs, possibly due to its elevated expression of oligomannose-type <em>N</em>-glycans. In contrast, M-SIV exhibited higher susceptibility to neutralizing sera in comparison to T-SIV. These findings underscore the importance of host cell-dependent attributes of SIV, such as glycosylation, in shaping both infectivity and the potential effectiveness of intervention strategies.</p>
VCF for neutral data set and potential connectivity matrices of Harpagifer antarcticus, along the Western Antarctic Peninsula
<p>Connectivity is a fundamental process of population dynamics in marine ecosystems. In the last decade, with the emergence of new methods, combining different approaches to understand the patterns of connectivity among populations and their regulation has become increasingly feasible. The Western Antarctic Peninsula (WAP) is characterized by complex oceanographic dynamics, where local conditions could act as barriers to population connectivity. Here, the notothenioid fish <em>Harpagifer antarcticus</em>, a demersal species with a complex life cycle (adults with poor swim capabilities and pelagic larvae), was used to assess connectivity along the WAP by combining biophysical modeling and population genomics methods. Both approaches showed congruent patterns. Areas of larvae retention and low potential connectivity, observed in the biophysical model output, coincide with four genetic groups within the WAP: (1) South Shetland Islands, (2) Bransfield Strait, (3) the central, and (4) the southern area of WAP (Marguerite Bay). These genetic groups exhibited limited gene flow between them, consistent with local oceanographic conditions, which would represent barriers to larval dispersal. The joint effect of geographic distance and larval dispersal by ocean currents, had a greater influence on the observed population structure, than each variable evaluated separately. The combined effect of geographic distance and a complex oceanographic dynamic would be generating limited levels of population connectivity in the fish <em>H. antarcticus</em>along the WAP. Based on this population connectivity estimations, priority areas for conservation were discussed, considering the Marine Protected Area proposed for this threatened region of the Southern Ocean.</p>
Swarm-C Neutral Density Data for Large-Scale Wave (LSW) Structures
Open the record for dataset details and reuse information.
Supplemental Figures - Detection of SARS-CoV-2-Specific Secretory IgA and Neutralizing Antibodies in the Nasal Secretions of Exposed Seronegative Individuals
<p>Figure S1: Flow diagram of exposed seronegative cohort.</p> <p>Figure S2: SARS-CoV-2-specific neutralization activity at Days 1 and 8 relative to enrollment in exposed seronegative nasal SIgA positive and infected participants. NPS SARS-CoV-2-specific neutralization activity is shown for exposed seronegative and infected participants with normalized OD490 at Day 1 and Day 8, respectively. Sample sizes (N) are indicated in parentheses. Wilcoxon signed-rank tests were used to determine if the median SARS-CoV-2 nasal SIgA neutralization activity differed significantly. A two-tailed p < 0.05 was considered significant.</p>
Dataset for "Study of reionization issues in the diagnostic neutral beam for the RFX-mod2 experiment"
<p>Dataset for the presentation <a href="../records/11368194">Study of reionization issues in the diagnostic neutral beam for the RFX-mod2 experiment</a></p>
State-resolved mutual neutralization of O$^+$ with $^1$H$^-$ and $^2$H$^-$ at collision energies below 100 meV
<p>The data files found here contain the data as obtained and displayed in : "State-resolved mutual neutralization of O$^+$ with $^1$H$^-$ and $^2$H$^-$ at collision energies below 100 meV" published in Physical Review A (2024). Each file contains an explanatory header. Header lines start with #.</p>
Data from: Invertebrate diversity in groundwater filled lava caves is influenced by both neutral and niche-based processes
<p><strong>Aim</strong>: Understanding which factors shape and maintain biodiversity is essential to understand how ecosystems respond to crises. Biodiversity in ecological communities is a result of the interaction of various factors which can be classified as neutral or niche-based. The importance of these processes has been debated, but many scientists believe that both processes are important. Here we examined the importance of neutral vs. niche-based factors for shaping invertebrate communities. We hypothesized that if neutral processes are the main drivers of community structure we would not see any clear relationship between the structure of community and ecological factors. If niche-based processes are important we should see clear relationships between community structure and variation in ecological variables.</p> <p><strong>Location</strong>: Groundwater-filled lava caves near Lake Mývatn, Iceland.</p> <p><strong>Methods</strong>: We collected various ecological variables from these caves. Invertebrate communities were collected on the hard bottom using stone scrubbing and from epibenthic traps. Results: Both communities were species-poor, with low densities of invertebrates, showing the resource-limited and oligotrophic nature of these systems. Unusually for Icelandic freshwater ecosystems, the benthic communities were not dominated by Chironomidae (Diptera) larvae, but rather by crustaceans, mainly Cladocera. The epibenthic communities were not shaped by environmental variables, suggesting that they may be structured primarily by neutral processes. The benthic communities were shaped by the availability of energy, and to some extent pH, suggesting that niche-based processes were important drivers of community structure, although neutral processes may still be relevant. </p> <p><strong>Main conclusions</strong>: The results suggest that both processes are important for invertebrate communities in freshwater, and research should focus on understanding both of these processes. The ponds we studied are representative of a number of freshwater ecosystems that are extremely vulnerable to human disturbance, making it even more important to understand how their biodiversity is shaped and maintained.</p>
TGF-β neutralization attenuates tumor residency of activated T cells to enhance systemic immunity in mice
<p>Deep TCR sequencing was performed using the TCR Profiling Kit from MiLaboratories (Mouse α/β TCR RNA; Kit MiLaboratories; TMMR-001). Deep TCR sequencing was analyzed using the MiXCR software from MiLaboratories per manufacturer's recommendations. The files correspond to the TCR-beta sequences.<br>The files are named as follows:</p> <p> </p> <table> <tbody> <tr> <td>file_name</td> <td>cell type sequenced</td> <td>tissue of origin</td> <td>treatment</td> <td>mouse_id</td> </tr> <tr> <td>21BA1dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>1</td> </tr> <tr> <td>23BA2dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>2</td> </tr> <tr> <td>25BA3dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>3</td> </tr> <tr> <td>27BA4dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>4</td> </tr> <tr> <td>29BA5dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>5</td> </tr> <tr> <td>22BA1SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>1</td> </tr> <tr> <td>24BA2SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>2</td> </tr> <tr> <td>26BA3SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>3</td> </tr> <tr> <td>28BA4SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>4</td> </tr> <tr> <td>30BA5SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>5</td> </tr> <tr> <td>31CON1dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>6</td> </tr> <tr> <td>33CON2dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>7</td> </tr> <tr> <td>35CON3dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>8</td> </tr> <tr> <td>37CON4dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>9</td> </tr> <tr> <td>39CON5dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>10</td> </tr> <tr> <td>32CON1SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>6</td> </tr> <tr> <td>34CON2SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>7</td> </tr> <tr> <td>36CON3SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>8</td> </tr> <tr> <td>38CON4SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>9</td> </tr> <tr> <td>40CON5SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>10</td> </tr> <tr> <td>1aPDL11dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>11</td> </tr> <tr> <td>3aPDL12dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>12</td> </tr> <tr> <td>5aPDL13dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>13</td> </tr> <tr> <td>7aPDL14dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>14</td> </tr> <tr> <td>9aPDL15dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>15</td> </tr> <tr> <td>2aPDL11SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>11</td> </tr> <tr> <td>4aPDL12SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>12</td> </tr> <tr> <td>6aPDL13SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>13</td> </tr> <tr> <td>8aPDL14SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>14</td> </tr> <tr> <td>10aPDL15SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>15</td> </tr> <tr> <td>11aTGFB1dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>16</td> </tr> <tr> <td>13aTGFB2dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>17</td> </tr> <tr> <td>15aTGFB3dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>18</td> </tr> <tr> <td>17aTGFB4dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>19</td> </tr> <tr> <td>19aTGFB5dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>20</td> </tr> <tr> <td>12aTGFB1SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>16</td> </tr> <tr> <td>14aTGFB2SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>17</td> </tr> <tr> <td>16aTGFB3SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>18</td> </tr> <tr> <td>18aTGFB4SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>19</td> </tr> <tr> <td>20aTGFB5SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>20</td> </tr> </tbody> </table>
"Power system investment optimization to identify carbon neutrality scenarios for Italy", scripts and data
<p>Script and data to reproduce the main results of "Power system investment optimization to identify carbon neutrality scenarios for Italy"</p>
Audio-recodings of criticism, praise, and neutral comments
<p>An auditory instrument of 100 criticisms, 100 praises, and 100 neutral comments was developed following the conventions for expressed emotion (EE)-criticism and EE-positive comments (Leff & Vaughn, 1985) and following the themes contained in the criticism and praise from an earlier study (Premkumar, et al., 2013). In addition to criticism and praise, neutral comments were designed as a general non-emotional control, and related to topics such as the weather, historical facts, and scientific facts. For example, ‘Today’s weather forecast suggests outbreaks of rain across the north, gradually easing with places becoming dry with sunny spells.’ The number of words per comment ranged from 18 to 20. A male actor and a female actor recorded the comments on a digital voice recorder. The male (AD) and female actors (PP) had a similar age and a similar length of experience in conducting psychological research. When the comments were delivered, the actors were trained to vary the prosodic variables (tone and pitch) to emphasise affective differences between the three types of comments. This was achieved by practising the tone of the voice for each comment type prior to recording. One actor (PP) was trained to rate EE using the CFI, and assessed the consistency of affect between the actors. The actors re-recorded the comments to address any differences in affective expression. </p>
Neutral-current DIS event samples at leading order with $E_e = 27.5\,{\rm GeV}$, $E_p = 920\,{\rm GeV}$, and $\mu_{\rm F}^2 = \mu_{\rm R}^2 = Q^2$
<p>Neutral-current DIS multi-jet event samples at parton level in the HDF5 event format.</p> <p>Beam energies: $E_e = 27.5\,{\rm GeV}$, $E_p = 920\,{\rm GeV}$</p> <p>Renormalisation and factorisation scale: $\mu_{\rm F}^2 = \mu_{\rm R}^2 = Q^2$ with seven-point scale variation</p> <p>PDF: NNPDF40_lo_pch_as_01180</p> <p>Generation cuts: $Q^2 > 2\,{\rm GeV}^2$, $k_{\rm T} > 2\,{\rm GeV}$ in the $k_{\rm T}$-algorithm with $D=1.0$</p> <p>Generated with <a href="https://gitlab.com/hpcgen/me" target="_blank" rel="noopener">Sherpa</a> using the run cards below.</p>
Neutral-current DIS event samples at leading order with $E_e = 27.5\,{\rm GeV}$, $E_p = 820\,{\rm GeV}$, and $\mu_{\rm F}^2 = \mu_{\rm R}^2 = Q^2$
<p>Neutral-current DIS multi-jet event samples at parton level in the HDF5 event format.</p> <p>Beam energies: $E_e = 27.5\,{\rm GeV}$, $E_p = 820\,{\rm GeV}$</p> <p>Renormalisation and factorisation scale: $\mu_{\rm F}^2 = \mu_{\rm R}^2 = Q^2$ with seven-point scale variation</p> <p>PDF: NNPDF40_lo_pch_as_01180</p> <p>Generation cuts: $Q^2 > 2\,{\rm GeV}^2$, $k_{\rm T} > 2\,{\rm GeV}$ in the $k_{\rm T}$-algorithm with $D=1.0$</p> <p>Generated with <a href="https://gitlab.com/hpcgen/me" target="_blank" rel="noopener">Sherpa</a> using the run cards below.</p>
Appendix 3 of "Analyses of three-dimensional species associations reveal departures from neutrality in a tropical forest"
<p>Temporal changes in three-dimensional structure of crowns in Luquillo, Puerto Rico. Each axis represents the overlap of one species over the other, measured as standardized effect sizes (SES). That is, deviations from a null model that randomizes crown three-dimensional positions. A high value of "SES of <em>Guarea guidonia</em> over <em>Psychotria brachiata</em>" means that <em>Guarea guidonia</em> shades <em>Psychotria brachiata</em> more than expected by chance, and so on.<br> <br> The coloured dots in the background of the figure represent all the observed relationships between species. Gray dots represent random relationships between pairs of species (i.e. similar to the expected by the null model). Black dots represent horizontal segregation between species. Blue dots represent horizontal aggregation but vertical segregation between species. Red dots represent three-dimensional aggregation between species.<br> <br> The larger green or red dots connected by lines represent the temporal changes observed for the relationship between the two target species in each figure. There are four censuses represented. Larger dots represent the more recent censuses. The green dots reflect the relationship between the two target species in the low-disturbance area within the Luquillo Forest Dynamics Plot. The red dots reflect the relationship between the two target species in the high-disturbance area within the Luquillo Forest Dynamics Plot.</p>
Source data for Neutralization of SARS-CoV-2 variants by convalescent and BNT162b2 vaccinated serum
<p>This dataset contains the source data used in the publication: "Neutralization of SARS-CoV-2 variants by convalescent and BNT162b2 vaccinated serum" published in Nature communications on August 26, 2021 (10.1038/s41467-021-25479-6).</p>
Dataset associated to paper: Nanoscaffold effects on the performance of air-cathodes for microbial fuel cells: Sustainable Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions
<p>This file contains the dataset associated to the published research article "Nanoscaffold effects on air-cathode performance in microbial fuel cells: Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions". The dataset contains X-ray powder diffraction, Inductively Coupled Plasma Emission Spectroscopy, elemental analysis, measurements of the specific surface area, transmission electron microscopies, x-ray photoelectron microscopy, electrochemistry and microbial fuel cells power outputs data from their relative instruments. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No. 799175 (HiBriCarbon) and No. 748968 (EDGE-FREEMAB). The results of this publication reflect only the authors' view and the Commission is not responsible for any use that may be made of the information it contains. This publication has also emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213 and 19/FFP/6761. SI kindly acknowledges support by the Department of Social Justice State Government of Maharashtra, India. </p>
Effects of nutrient pulses on exotic species shift from positive to neutral with decreasing water availability
<p>Temporal fluctuation in nutrient availability generally promotes the growth of exotic plant species and has been recognized as an important driver of exotic plant invasions. However, little is known about how the impact of fluctuating nutrients on exotic species depends on the availability of other resources, although most ecosystems are experiencing dramatic variations in a wide variety of resources due to global change and human disturbance. Here, we explored how water availability mediates the effect of nutrient pulses on the growth of six exotic and six native plant species. We subjected individual plants of exotic and native species to well-watered or water-stressed conditions. For each level of water availability, we added equivalent amounts of nutrients at a constant rate, as a single large pulse or in multiple small pulses. Under well-watered conditions, nutrient pulses promoted exotic plant growth relative to nutrients supplied constantly, while they had no significant effect on natives. In contrast, under water-stressed conditions, water deficiency inhibited the growth of all exotic and native species. More importantly, nutrient pulses did not increase plant growth relative to nutrients supplied constantly and these phenomena were observed for both exotic and native species under water-stressed conditions. Taken together, our study shows that the impact of fluctuating nutrient availability on the growth of exotic plant species strongly depends on the variation of other resources and that the positive effect of nutrient pulses under well-watered conditions disappears under water-stressed conditions. Our findings suggest that variation of multiple resources may have complex feedback to exotic plant invasions, and therefore it is critical to encompass multiple resources for the evaluation of fluctuating resource availability effects on exotic plant species. This will allow us to project the invasive trajectory of exotic plant species more accurately under future global change and human disturbance.</p>
Silver Standard of quantified positive, negative and neutral German noun phrases
<p>Repository: silver standard quantified (simple) noun phrases</p> <p>43,842 positive (+), negative (-) or neutral (0) NPs, </p> <p>e.g. "ein notorischer Verführer -5.625" is highly negative (-5.625)</p> <p>see References LREC for a description of the data</p> <p>Format: tsv</p> <p>References:</p> <p>@inproceedings{LREC,<br> month = {Juni},<br> author = {Manfred Klenner and Anne G{\"o}hring},<br> booktitle = {Proceedings of the Language Resources and Evaluation Conference},<br> address = {Marseille, France},<br> title = {Animacy Denoting {G}erman Nouns: Annotation and Classification},<br> publisher = {European Language Resources Association},<br> pages = {1360--1364},<br> year = {2022},<br> language = {english},<br> url = {https://doi.org/10.5167/uzh-219148},<br> abstract = {In this paper, we introduce a gold standard for animacy detection comprising almost 14,500 German nouns that might be used to denote either animate entities or non-animate entities. We present inter-annotator agreement of our crowd-sourced seed annotations (9,000 nouns) and discuss the results of machine learning models applied to this data.}<br> }<br> </p>
Derivative products from "Spherical Harmonic Representation of Energetic Neutral Atom Flux Components Observed by IBEX" by Swaczyna, Dayeh, & Zirnstein
<p>This dataset includes derivative data products obtained using the method described in: Swaczyna, Dayeh, & Zirnstein (2023), <em>Spherical Harmonic Representation of Energetic Neutral Atom Flux Components Observed by IBEX</em></p> <p>The products have been derived from IBEX Data Release #16 (https://ibex.princeton.edu/DataRelease16). </p> <ul> <li>hvset_tabular_ram_cg.zip - results for ram-only Compton-Getting and survival probability corrected IBEX maps</li> <li>hvset_tabular_antiram_cg.zip - results for antiram-only Compton-Getting and survival probability corrected IBEX maps</li> </ul> <p>Each archive includes the following files:</p> <ul> <li><em>com</em>_flux_<em>yyyy</em>_esa_<em>e</em>.txt - reconstructed flux map from spherical harmonic coefficients using the standard IBEX pixelization</li> <li><em>com</em>_fvar_<em>yyyy</em>_esa_<em>e</em>.txt - reconstructed flux variance map from spherical harmonic coefficients using the standard IBEX pixelization</li> <li><em>com</em>_ylm_coeff_<em>yyyy</em>_esa_<em>e</em>.txt - coefficients of the spherical harmonic representation</li> <li><em>com</em>_ylm_mat_<em>yyyy</em>_esa_<em>e</em>.txt - covariance matrix providing uncertainties of the coefficients</li> <li>mask_ribbon_esa_<em>e</em>.txt - ribbon mask</li> <li>matrix_y.txt - matrix transforming the spherical harmonic coefficients into values in IBEX pixels</li> </ul> <p>where:</p> <ul> <li><em>com </em>- indicate the included component of the ENA flux: <ul> <li>gdf - Globally DIstirbuted Flux</li> <li>rib - IBEX ribbon</li> <li>tot - both components (total maps)</li> </ul> </li> <li><em>e</em> - enumerates IBEX energy steps (<em>e</em> = 2, 3, ... 6)</li> <li><em>yyyy</em> - indicates map year (<em>yyyy</em> = 2009, 2010, ..., 2019 or 'single' for the time-combined map)</li> </ul>
Output data: China's energy-water-land system co-evolution under carbon neutrality goal and climate impacts
<p>Outputs for Wang, J., Duan, Y., Wang, C., 2023. China’s energy-water-land system co-evolution under carbon neutrality goal and climate impacts. (In progress)</p> <p>Folder demeter contains the spatially downscaled land use/land cover datasets.<br> Folder tethys contains the spatially downscaled water withdrawal datasets.</p> <p>The sub-folder names correspond to the scenarios described in the paper.</p> <p>For landcover datasets, land type ratios in each grid are presented. Land types include water, forest, shrub, grass, urban, snow, sparse and crops.</p> <p>For water withdrawal datasets, “wd” = “water withdrawal spatially downscaled”, “twd” = “water withdrawal spatially and temporally downscaled”, “dom”=”domestic/municipal sector”, “elec”=”electricity sector”, ”irr”=”irrigation sector”, “liv”=”livestock sector”, “mfg”=”manufacturing/industry sector”, “min”=”mining/primary energy sector”, “nonag”=”non-agricultural sector”, “total”=”all sectors”.<br> </p>
Case study result data set for Energy Systems (submitted) article "Influence of hydrogen import prices on hydropower systems in climate-neutral Europe"
<p>The data set contains result data for the European system in a long term climate-neutral European energy system (scenario year 2050) as described in the publication "Influence of hydrogen import prices on hydropower systems in climate-neutral Europe". The results have been generated with the model SCOPE SD of Fraunhofer Institute for Energy Economics and Energy System Technology IEE. </p> <p><strong>Abbreviations:</strong></p> <ul> <li>BEV - Battery Electric Vehicles</li> <li>CCGT - Combined Cycle Gas Turbine</li> <li>CHP - Combined heat and power</li> <li>con - consumption</li> <li>gen - generation</li> <li>HighCLEQ - High import prices / clustered-equivalent hydropower units</li> <li>HighEQ - High import prices / equivalent hydropower units</li> <li>LowCLEQ - Low import prices / clustered-equivalent hydropower units</li> <li>LowEQ - Low import prices / equivalent hydropower units</li> <li>MedCLEQ - Medium import prices / clustered-equivalent hydropower units</li> <li>MedEQ - Medium import prices / equivalent hydropower units</li> <li>OCGT - Open Cycle Gas Turbine</li> <li>PHEV - Plug-In Hybrid Vehicles</li> <li>PS - Pumped Storage</li> <li>w/ - with</li> <li>w/o - without</li> <li>yr - year</li> </ul>
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.