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1,221 results for “Aggregators”
Dataset for publication Cuevas K., Chougan M., Martin F., Ghaffar SH, Stephan D., Sikora P. 3D printable lightweight cementitious composites with incorporated waste glass aggregates and expanded microspheres – Rheological, thermal and mechanical properties. Journal of Building Engineering (2021) 44, 102718
<p>Dataset consisting of G-code for 3D mortar specimen's printing path and particle size distribution (Origin file) of materials used in the study Cuevas K., Chougan M., Martin F., Ghaffar SH, Stephan D., Sikora P. 3D printable lightweight cementitious composites with incorporated waste glass aggregates and expanded microspheres – Rheological, thermal and mechanical properties. Journal of Building Engineering (2021) 44, 102718. <a href="https://doi.org/10.1016/j.jobe.2021.102718">https://doi.org/10.1016/j.jobe.2021.102718</a></p>
Grid Based Global Carbon Edge Regression Coefficients and Aggregations
<p>Grid cell based regression coefficients for predicting global biomass in the pantropics.</p> <p>To better account for the variability within a continent, we constructed 100-km grid cells throughout the pantropics. In grid cells where the majority of pixels were from forest biomes, we consider three candidate regression models to represent the relationship between biomass density and distance to forest edge. In particular, we consider:</p> <ol> <li>Asymptotic: <span class="math-tex">Biomass=θ1−θ2⋅exp(−θ3⋅Distance)</span>,</li> <li>Logarithmic: <span class="math-tex">Biomass=β0+β1ln⋅(Distance)</span> , or</li> <li>Linear: <span class="math-tex">Biomass=η0+η1⋅Distance</span></li> </ol> <p>Then, for each grid cell, the candidate with the highest R2 is used to best represent the relationship between density and distance to forest edge. Models (2) and (3) were deemed as suitable (and more simplistic) alternatives in cells where higher distances were generally not observed and as a result the forest core was not firmly established. We also note that in the vast majority of grid cells, model (1) was optimal. For each cell the magnitude and distance of the edge effect were again estimated. In cells using models (2) or (3) the forest core (<span class="math-tex">θ1</span>) was estimated as the average biomass density at the largest observed distance in the cell.</p> <p>This dataset also contains a shapefile parameter analysis of both proportion and total area of all forest landcover types (1-5).</p>
EARLS: European aggregated reconstruction for large-sample studies
<p>EARLS is an openly available pan-European runoff–reconstruction dataset.</p> <p>As of now it is structured in the following way: </p> <div> <ul> <li>The `<em>coordinates.csv`</em> file contains basin outlet information with 4 columns: basin id (idx), type, and estimated latitude (lat) and longitude (lon) of the outlet.</li> <li>The `<em>license.md`</em> file contains information about the licensing.</li> <li>The `<em>shapefile` </em>folder includes a shapefile with all basin boundaries (see: <a href="https://www.hydrosheds.org/products/hydrobasins">HydroBASINS</a>).</li> <li>The `<em>reconstructions`</em> folder contains CSV files. Each file is named after the basin id and has at least two columns: date and simulation. The simulations are given in mm. Additional columns can be used to provide more information. For the current EARLS we added two additional columns that provide the remaining parameters for the uncertainty estimation.</li> <li>The `<em>model-card`</em> folder contains 2 files: `<em>model-card.html`</em>, and `<em>earls-crest.png`</em>. The html document includes the png as logo and renders a model card. A <a href="https://arxiv.org/abs/1810.03993">model card </a>is a short summary of the model genesis, designed to increase transparency by communicating information about trained models to broad audiences. We include all three files in the dataset so that future extensions can adapt them with maximal ease. We will also host the markdown files on the main home so that the permanent identifier within the model card can be used to access the data from there.</li> <li>Additional data/folders are optional, but can be used to provide background information. For instance, the EARLS contains an `<em>inputs`</em> folder, which comprises the basin-aggregated dynamic and static inputs: <br> <ul> <li>For the dynamic inputs (derived from <a href="https://www.ecad.eu/download/ensembles/download.php">E-OBS</a>) we use precipitation in mm per day, daily minimum/maximum/average temperature in °C.</li> <li>For the static inputs (derived form <a href="https://www.hydrosheds.org/hydroatlas">HydroATLAS</a>) we use basin area in square kilometers, average elevation in meter, average slopes in degrees, average stream gradient in decimeter per kilometer, average long-term air temperature in degrees Celsius, minimum long-term air temperature in °C, maximum long-term air temperature in °C, a global aridity index, a global climate moisture index, average fraction of sand in %, average fraction of clay in %, average fraction of silt in %, and average organic carbon content in tons per hectar.</li> </ul> </li> </ul> <h2>Changelog</h2> <p><strong>v0.3</strong></p> <ul> <li>Introduced a changelog. yay. </li> <li>Little corrections (spelling mistakes etc.) and nicer formatting in the technical data description. </li> <li>Corrected streamflow and variance normalization from hours to daily (affected versions: v0.0 and v.0.2; thanks to Corinna Frank).</li> <li>Corrected technical description of the area from m2 to km2 (thanks to Corrina Frank).</li> <li>Introduced an example data-file with a single basin (thanks to Juliane Mai).</li> </ul> </div>
Dataset for: Cattle aggregations at shared resources create potential parasite exposure hotspots for wildlife
<p>Globally rising livestock populations and declining wildlife numbers are likely to dramatically change disease risk for wildlife and livestock, especially at resources where they congregate. However, limited understanding of interspecific transmission dynamics at these hotspots hinders disease prediction or mitigation. In this study, we combined gastrointestinal nematode density and host foraging activity measurements from our prior work in this system with three estimates of parasite-sharing capacity to investigate how interspecific exposures alter the relative riskiness of an important resource – water – among cattle and five dominant herbivore species in an East African tropical savanna. </p> <p>We found that due to their high parasite output, water dependence, and parasite-sharing capacity, cattle greatly increased potential parasite exposures at water sources for wild ruminants. When untreated for parasites, cattle accounted for over two-thirds of total potential exposures around water for wild ruminants, driving 2–23-fold increases in relative exposure levels at water sources. Simulated changes in wildlife and cattle ratios showed that water sources become increasingly important hotspots of interspecific transmission for wild ruminants when the relative abundance of cattle parasites increases. These results emphasize that livestock have significant potential to alter the level and distribution of parasite exposures across the landscape for wild ruminants.</p>
Selfish herd effects in aggregated caterpillars and their interaction with warning signals
<p>Larval Lepidoptera gains survival advantages by aggregating, especially when combined with aposematic warning signals, yet reductions in predation risk may not be experienced equally across all group members. Hamilton's selfish herd theory predicts that larvae that surround themselves with their group mates should be at lower risk of predation, and those on the periphery of aggregations experience the greatest risk, yet this has rarely been tested. Here, we expose aggregations of artificial 'caterpillar' targets to predation from free-flying, wild birds to test for marginal predation when all prey are equally accessible, and for interaction between warning colouration and marginal predation. We find that targets nearer the centre of the aggregation survived better than peripheral targets and nearby targets isolated from the group. However, there was no difference in survival between peripheral and isolated targets. We also find that grouped targets survived better than isolated targets when both are aposematic, but not when they are non-signalling. To our knowledge, our data provide the first evidence to suggest that avian predators preferentially target peripheral larvae from aggregations, and that prey warning signals enhance predator avoidance of groups.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 2023
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2023.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
Molecular Insights into the Effects of F16L and F19L Substitutions on the Conformation and Aggregation Dynamics of Human Calcitonin
<p><a name="_Hlk145518059"></a><span>Human calcitonin (hCT) regulates calcium-phosphorus metabolism, but its amyloid aggregation disrupts physiological activity, increases thyroid carcinoma risk, and hampers its clinical use for bone-related diseases like osteoporosis and Paget’s disease. Improving hCT with targeted modifications to mitigate amyloid formation while maintaining function holds promise as a strategy. Understanding how each residue in hCT's amyloidogenic core affects its structure and aggregation dynamics is crucial for designing effective analogs. Mutants F16L-hCT and F19L-hCT, where Phe residues in the core are replaced with Leu as in non-amyloidogenic salmon calcitonin, showed different aggregation kinetics. However, the molecular effects of these substitutions in hCT are still unclear. Here, </span><a name="OLE_LINK4"></a><span><span>we systematically investigated the folding and self-assembly conformational dynamics of hCT, F16L-hCT, and F19L-hCT through multiple long-timescale independent atomistic discrete molecular dynamics (DMD) simulations. </span></span><span><span>Our results indicated that the hCT monomer primarily assumed unstructured conformations with dynamic helices around residues 4-12 and 14-21. During self-assembly, the amyloidogenic core of hCT<sub>14-21</sub> converted from dynamic helices to β-sheets. However, substituting F16L did not induce significant conformational changes, as F16L-hCT exhibited similar characteristics to wild-type hCT in both monomeric and oligomeric states. In contrast, F19L-hCT exhibited substantially more helices and fewer β-sheets than hCT, irrespective of their monomers or oligomers. The substitution of F19L significantly enhanced the stability of the helical conformation for hCT<sub>14-21</sub>, thereby suppressing the helix-to-β-sheet conformational conversion. Overall, our findings elucidate the molecular mechanisms underlying hCT aggregation and the effects of F16L and F19L substitutions on the conformational dynamics of hCT, highlighting the critical role of F19 as an important target in the design of amyloid-resistant hCT analogs for future clinical applications.</span></span></p>
Fig. 2 in New Species Of The Genus Pachyrhynchus Germar (Coleoptera, Curculionidae, Entiminae) From The Greater Mindanao Pleistocene Aggregate Island Complex (Philippines)
Fig. 2. Male genitalia of P. ilgas. A – aedegal body in lateral view; B – aedegal body in frontal view; C – sternite IX; D – tegmine. Scale 1mm.
Fig. 6 in New Species Of The Genus Pachyrhynchus Germar (Coleoptera, Curculionidae, Entiminae) From The Greater Mindanao Pleistocene Aggregate Island Complex (Philippines)
Fig. 6. Lateral view of habitus; A – P. absurdus; B – P. orientalis; C – P. occidentalis; D – P. neoabsurdus. All females.
Fig. 3 in New Species Of The Genus Pachyrhynchus Germar (Coleoptera, Curculionidae, Entiminae) From The Greater Mindanao Pleistocene Aggregate Island Complex (Philippines)
Fig. 3. Male genitalia of P. orientalis; A – aedegal body in lateral Fig. 4. Female genitalia of P. view; B – aedegal body in frontal view; C – sternite IX; D – tegmen. orientalis. Scale 1mm. Scale 1mm.
Fig. 1 in New Species Of The Genus Pachyrhynchus Germar (Coleoptera, Curculionidae, Entiminae) From The Greater Mindanao Pleistocene Aggregate Island Complex (Philippines)
Fig. 1. Dorsal habitus of A- P. occidentalis, male; B – female; C – P. ilgas, male; D – P. orientalis, male; E – female; F – P. neoabsurdus, female.
Impact of the aggregate of 11 global threats on countries
<p>The vulnerability of 134 countries to the impact of a set of the most important threats to humanity in the first half of the 21st century were assesed. Data of 2005-2022 were considered. </p> <p> </p> <p> </p>
Aggregate Dataset on Descriptive Representation in the French National Assembly (2012-2022)
<p>This is the dataset aggregated at the legislature/party level by the CSIC team from the individual-level data provided by the Sciences Po and CSIC teams on descriptive representation in the French lower chamber of Parliament for WP4 of the ActEU project. </p>
Aggregate Dataset on Descriptive Representation in the Italian Parliament (2013-2018)
<p>This is the dataset aggregated at the legislature/party level by the CSIC team from the individual-level data provided by the Sciences Po and CSIC teams on descriptive representation in the Italian lower chamber of Parliament for WP4 of the ActEU project. </p>
Aggregating gut: on the link between neurodegeneration and bacterial functional amyloids - Datasets
<p>This repository contains data from work "Aggregating gut: on the link between neurodegeneration and bacterial functional amyloids"<br><br></p> <p><a href="https://zenodo.org/api/records/14016809/draft/files/BFA.fasta/content" target="_blank" rel="noopener noreferrer">BFA.fasta</a> - fasta file containing sequences of bacterial functional amyloids used as a query for identification of novel bacterial functional amyloids in UHGP dataset</p> <p><a href="https://zenodo.org/api/records/14016809/draft/files/UHGPAmyloids.fasta/content" target="_blank" rel="noopener noreferrer">UHGPAmyloids.fasta </a>- fasta file containing sequences of amyloids identified in UHGP dataset</p> <p><a href="https://zenodo.org/api/records/14016809/draft/files/UHGPAmyloids.csv/content" target="_blank" rel="noopener noreferrer">UHGPAmyloids.csv</a> - csv file containing information about amyloids identified in UHGP</p> <p>Columns:<br>query_id - Uniprot id of the protein from BFA<br>query_gene_name - gene name of the protein from BFA<br>target_id - UHGP id of the found homolog<br>ProbabilityAMYPred-FRL - score obtained for the target_id sequence according to AMYPred-FRL<br>Archcandy - Prediction of beta arch motif for identified amyloid<br>Genome - UHGP genome id of the target_id<br>Localization - predicted subcellular localization with BUSCA for target_id sequence<br>Lineage - full taxonomy of the target_id sequence (which bacteria produced this specific sequence) </p> <p><a href="https://zenodo.org/api/records/14016809/draft/files/PPIPositivePredictionsBetween_UHGPAmyloids_And_HPAIntestine_filtered.csv/content" target="_blank" rel="noopener noreferrer">PPIPositivePredictionsBetween_UHGPAmyloids_And_HPAIntestine_filtered.csv</a> - csv file contining inforamtions about predicted protein-protein interactions between UHGPAmyloids and human proteins expressed in guts</p> <p>Columns:<br>UHGPAmyloids_id - UHGPAmyloids id (same as target_id in UHGPAmyloids.csv)<br>hp_uniprot_name - Uniprot name of a human protein<br>negative and score - scores returned by ProteinPrompt softwawre for prediction of PPI<br>hp_uniprot_id - Uniprot id of a human protein<br>BFA_sp_uniprot_id - Uniprot id of a BFA source protein<br>BFA_sp_uniprot_name - gene name of a BFA source protein<br>UHGPAmyloids_localization - predicted subcellular localization with BUSCA for UHGPAmyloids_id sequence<br>UHGPAmyloids_lineage - full taxonomy of the UHGPAmyloids_id sequence (which bacteria produced this specific sequence) </p>
Dataset of "Critical role of H-aggregation for high-efficiency photoinduced charge generation in pristine pentamethine cyanine salts"
<p>Dataset underpinning the published article:</p> <p>Critical role of H-aggregation for high-efficiency photoinduced charge generation in pristine pentamethine cyanine salts Phys. Chem. Chem. Phys. 2021, 23, 23886-23895. DOI: 10.1039/D1CP03251H</p>
Data from: Intense upper ocean mixing due to large aggregations of spawning fish
<p>This dataset includes data collected during the cruise REMEDIOS-TL in the Ría de Pontevedra (NW Iberia) at station P2 (42.357°N, 8.773°W) from 29 June to 18 July 2018 onboard of the Research Vessel Ramón Margalef belonging to the Spanish Institude of Oceanography. The REMEDIOS project is funded by the Spanish Ministry of Economy and Inno-445vation under the research project REMEDIOS (CTM2016-75451-C2-1-R) and leaded by Beatriz Mouriño Carballido.</p> <p>The archived data are described in a manuscript entitled "Intense upper ocean mixing due to large aggregations of spawning fish" by Fernández Castro et al. published in Nature Geoscience:</p> <p>Fernández Castro, B., Peña, M., Nogueira, E. <em>et al.</em> Intense upper ocean mixing due to large aggregations of spawning fish. <em>Nat. Geosci.</em> <strong>15, </strong>287–292 (2022). https://doi.org/10.1038/s41561-022-00916-3</p> <p>The manuscript presents evidence that night-time aggregations of anchovies produce intense ocean turbulence and mixing. All the data needed to support the conclusions of the article are included in this dataset.</p> <p>The dataset includes:</p> <p>- Microstructure profiles collected with a MSS Sea&Sun profiler during the three intensive samplings of the cruise (I01, I02, I03)</p> <p>- Ocean currents measured with a bottom moored RD Instruments acoustic Doppler profiler (ADCP, 300Khz) for the duration of the cruise</p> <p>- Acoustic backscatter from a ship-borne echosounder Simrad EK80 for the frequencies 18, 38, 70, 120 and 200 KHz and the three intensive samplings of the cruise (I01, I02, I03)</p> <p>- European anchovy (Engraulis encrasicolus) egg counts from plankton hauls samplings.</p>
Dataset related to article. "Nonphosphorylated tau slows down Aβ1–42 aggregation, binds to Aβ1–42 oligomers, and reduces Aβ1–42 toxicity"
<p>Figures presented in the paper and their data can be found in the corresponding prism files (www.graphpad.com).<br> The raw data and the picture files for most of the figures can be found in the folder with the corresponding figure name.</p>
Dataset 2 for: Multi-eGO: an in-silico lens to look into protein aggregation kinetics at atomic resolution
<p><strong>Dataset</strong></p> <p>Molecular dynamics simulation trajectories of TTR peptide aggregation kinetics:</p> <ul> <li>multi-eGO-XXmM-Y: aggregation kinetics simulations of TTR using the multi-eGO force field at XXmM concentration replicate Y.</li> </ul>
Quadtree aggregations of WHEEL forecast model
<p>World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) is a model obtained from a multiplicative log-linear combination of TEAM with the Smoothed Seismicity (KJSS) model of Kagan and Jackson (2011).</p> <p>The forecast model is proposed and described in the following publication:</p> <p>Bayona, J.A., Savran, W., Strader, A., Hainzl, S., Cotton, F. and Schorlemmer, D., 2021. Two global ensemble seismicity models obtained from the combination of interseismic strain measurements and earthquake-catalogue information. <em>Geophysical Journal International</em>, <em>224</em>(3), pp.1945-1955.</p> <p>Multi-resolution grids are generated using Quadtree. The grids are generated based on earthquake catalog data and strain data points. Each file in the repository represents a forecast aggregated on a particular grid. The forecast files are naming is derived from the criteria used to generate the grid. For example, 'N' stands for number earthquakes, 'SN' stands for Strain data points, and 'L' stands for maximum zoom-level allowed for the grid. </p> <p>The forecast is represented in the following format:</p> <table align="center"> <tbody> <tr> <td>Tile</td> <td>depth_min</td> <td>depth_max</td> <td>5.95</td> <td>6.05</td> <td>6.15</td> <td>6.25</td> <td> ... </td> </tr> <tr> <td>'000'</td> <td>0.0</td> <td>70.0</td> <td>0.00715</td> <td>0.00693</td> <td>0.00628</td> <td>0.00573</td> <td> ...</td> </tr> </tbody> </table>
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.