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1,221 results for “Aggregators”
[Raw data collection] - Granular skeleton optimisation and influence of the cement paste content in bio-based oyster shell mortar with 100% aggregate replacement
<h1>Raw data collection</h1> <h2>Associated paper information</h2> <p>- Year: 2024 <br>- Journal: Sustainability <br>- DOI/link: https://doi.org/10.3390/su16062297 <br>- Title: Granular skeleton optimisation and influence of the cement paste content in bio-based oyster shell mortar with 100% aggregate replacement <br>- Authors: Ana Cláudia Pinto Dabés Guimarães (1,2), Olivier Nouailletas (3), Céline Perlot (2,3,4) and David Grégoire (1,3,4,*) <br>- Affiliation: <br> (1) Universite de Pau et des Pays de l’Adour, E2S UPPA, CNRS, LFCR, Anglet, France, <br> (2) Universite de Pau et des Pays de l’Adour, E2S UPPA, SIAME, Anglet, France, <br> (3) Universite de Pau et des Pays de l’Adour, E2S UPPA, ISA BTP, Anglet, France, <br> (4) Institut Universitaire de France, Paris, France, <br> * Correspondence: david.gregoire@univ-pau.fr</p>
Data for the research article "High-Temperature Deformation of Enstatite-Olivine Aggregates" published in JGR Solid Earth
<p>The data available in this repository is the original data presented in the research article: Bystricky, M., Lawlis, J., Mackwell, S., & Heidelbach, F. (2024). High-temperature deformation of enstatite-olivine aggregates, Journal of Geophysical Research: Solid Earth, 129, e2023JB027699. https://doi.org/10.1029/2023JB027699.</p> <p>Version v1: data at time of original submission (2023)</p> <p>Version v2: data at time of publication (2024)</p>
With or without you: Gut microbiota does not predict aggregation behavior in European earwig females
<p>The reasons why some individuals are solitary and others gregarious are the subject of ongoing debate as we seek to understand the emergence of sociality. Recent studies suggest that the expression of aggregation behaviors may be linked to the gut microbiota of the host. Here, we tested this hypothesis in females of the European earwig. This insect is ideal for addressing this question, as adults both naturally vary in the degree to which they live in groups and show inter-individual variation in their gut microbial communities. We video-tracked 320 field-sampled females to quantify their natural variation in aggregation and then tested whether the most and least gregarious females had different gut microbiota. We also compared the general activity, boldness, body size, and body condition of these females and examined the association between each of these traits and the gut microbiota. Contrary to our predictions, we found no difference in the gut microbiota between the most and least gregarious females. There was also no difference in activity, boldness, and body condition between these two types of females. Independent of aggregation, gut microbiota was overall associated with female body condition, but not with any of our other measurements. Overall, these results demonstrate that a host's gut microbiota is not necessarily a major driver or a consequence of aggregation behavior in species with inter-individual variation in group living and call for future studies to investigate the determinants and role of gut microbiota in earwigs.</p>
Results from simulated drift trajectories of driting Fish Aggregating Devices used in Figures for paper Escalle et al., (2024) Simulating drifting fish aggregating device trajectories to identify potential interactions with endangered sea turtles
<p>Escalle et al., (2024) Simulating drifting fish aggregating device trajectories to identify potential interactions with endangered sea turtles<br><span><a href="../doi/10.5281/zenodo.10815559">https://zenodo.org/doi/10.5281/zenodo.10815559</a></span></p> <p>Results data description<br>The above doi contains simulation output data generated from passive drift simulations of drifting FADs in the Pacific ocean. We refer the reader to the main text of the paper for details and definitions of the different zones and simulation experiments.</p> <p>All data files are matrices stored in comma-delimited files (.csv), where the first provides the column names of the matrix, and the first column provides the row names. The first cell in row 1, column 1 is simply a placement value that describes the nature of the matrix. </p> <p>When this value is a hash symbol (#), it denotes that the matrix represents a spatial density of virtual particles under a particular drift scenario and over a particular period of time. Column names provide the latitude indices of each cell, and row names are the longitude indices. Values are the proportion of all particules in the domain that passed through this cell, during the drift-time window of this results file (see below).</p> <p>When the first cell value is a hash followed by a code (e.g. # EqZ), it denotes that the file represents a connectivity matrix between the zones given by the code (e.g. Equatorial Zones EqZ or Fishing Zones FZ) and defined in the row names of the matrix, and the turtle zones defined by the column names. Values are the proportion of particules beginning the zone defined by the row name at the start of the simulation, which are now present in the zone defined by the column name.</p> <p>Files name follow a convention describing the deployment and drift-time scenario they represent.</p> <p>For spatial density matrices:<br>[Origin Zones]_[Subset]_Density_[Drift Time]_....csv</p> <p>For connectivity/transition matrices:<br>[Origin Zones]_[Drift Time]_[Number of Simulations Run]_TransitionMatrix_....csv</p>
Fig. 7 in New Species Of The Genus Pachyrhynchus Germar (Coleoptera, Curculionidae, Entiminae) From The Greater Mindanao Pleistocene Aggregate Island Complex (Philippines)
Fig. 7. Distribution map of Pachyrhynchus ''absurdus'' group.
16545_2019_07_16_aggregates_CTP_switch_2_0glu_0_0glu_URA7young_URA8young_URA8old_secondRun_01 (part 2)
High throughput time lapse experiment. Details can be found on the 'txt' files inside.
16545_2019_07_16_aggregates_CTP_switch_2_0glu_0_0glu_URA7young_URA8young_URA8old_secondRun_01 (part 1)
High throughput time lapse experiment. Details can be found on the 'txt' files inside.
1100_2023_03_12_aggregates_downUpshift_glu_2_0_twice_gcd2_gcd6_gcn3_gcd7_sui2_00 (part 2)
High throughput time lapse experiment. Details can be found on the 'txt' files inside.
1100_2023_03_12_aggregates_downUpshift_glu_2_0_twice_gcd2_gcd6_gcn3_gcd7_sui2_00 (part 1)
High throughput time lapse experiment. Details can be found on the 'txt' files inside.
921_2023_03_01_aggregates_starve_twice_glu_2_0_gcd2_gcd6_gcd7_gcn3_sui2_00 (part 2)
High throughput time lapse experiment. Details can be found on the 'txt' files inside.
921_2023_03_01_aggregates_starve_twice_glu_2_0_gcd2_gcd6_gcd7_gcn3_sui2_00 (part 1)
High throughput time lapse experiment. Details can be found on the 'txt' files inside.
Mitochondrial oxidant stress promotes alpha-synuclein aggregation and spreading in mice with mutated glucocerebrosidase
<p>These are the data sets and plasmid sequences of the viral vectors used in the study "Mitochondrial oxidant stress promotes alpha-synuclein aggregation and spreading in mice with mutated glucocerebrosidase"</p>
Source data for Chen et al (2024) entitled "Motor Cortical Neuronal Hyperexcitability Associated with α-Synuclein Aggregation"
<div> </div> <div>--------------------</div> <div>GENERAL INFORMATION </div> <div>--------------------</div> <div>This readme file was generated on [2024-01-15] by [Liqiang Chen].</div> <div> </div> <div>Title of Dataset:</div> <div>Description of Dataset: </div> <div>Principal Investigator: Hong-Yuan Chu, hc948@georgetown.edu, ORCID: 0000-0003-0923-683X. </div> <div>Date of Data Collection: 2023-04-01 to 2024-11-10 </div> <div>Software Dependencies: Excel and Image J.</div> <div> </div> <div>-------------</div> <div>FILE OVERVIEW </div> <div>-------------</div> <div>Directory of Files: Source data, Electrophysiology trace data, and Microscopy images.</div> <div>Relationship Between Files: Source data is used to make figures in GraphPad. Electrophysiology trace data is used to plot electrophysiology traces. Microscopy images are used for representative images. </div> <div>File Formats: Microsoft Excel Worksheet (.xlsx) and confocal images (.nd2)</div> <div>File Naming Convention: Based on file formats.</div> <div> </div> <div>----------------------------------------</div> <div>DATA SPECIFIC INFORMATION FOR [Source data]</div> <div>Date of Creation: 2024-08-13</div> <div>Description of Data: Source data is used to make figures in GraphPad.</div> <div>A. Missing data are represented n/a.</div> <div>B. Abbreviations (Primary cortex: M1; Secondary cortex: M2; α-Synulein: αSyn; intratelencephalic neurons: ITNs; corticospinal neurons: CSNs).</div> <div>C. Figure 5B data (ITN-Sholl analysis-Intersections-5 µm Radius) can not organized as tidy format because of too many data points in each group. </div> <div> </div> <div>DATA SPECIFIC INFORMATION FOR [Electrophysiology trace data]</div> <div>Date of Creation: 2024-08-13</div> <div>Description of Data: Electrophysiology trace data is used to plot electrophysiology traces.</div> <div>A. Electrophysiology traces can be plotted using Excel.</div> <div>B. Traces are plotted in Electrophysiology trace data file.</div> <div> </div> <div>DATA SPECIFIC INFORMATION FOR [Microscopy images]</div> <div>Date of Creation: 2024-08-13</div> <div>Description of Data: Microscopy images are used to make representative images. </div> <div>A. Microscopy images can be opened using Image J. </div> <div>B. Microscopy images are named based on experimental group, animal ID, and figure number in the manuscript. </div> <div> </div> <div> </div> <div>-----------</div> <div>METHODOLOGY</div> <div>-----------</div> <div>Description of methods used for data collection: Electrophysiology data is collected using MultiClamp 700B amplifier and Digidata 1550B. pClamp 11 software is used. Microscopy images are collected using an confocal microscope. </div> <div> </div> <div>Description of methods used for data processing: </div> <div>A. Electrophysiology data is processed using clampfit software, including measure the peak of EPSC, count the number of action potentials, measure the width/rise time/decay time of action potential.</div> <div>B. Microscopy images are processed using Image J software, including measure the α-Synulein pathologic area in motor cortex, quantify the TH staining, and verify the co-localization of pS129 and biocytin. </div> <div>C. All data after processed through clampfit and Image J is put into GraphPad to make figures.</div> <div> </div> <div>-----------------------</div> <div>DATA ACCESS AND SHARING</div> <div>-----------------------</div> <div>This research was funded in part by </div> <div>1. Aligning Science Across Parkinson’s (ASAP-020572) through the Michael J. Fox Foundation for Parkinson’s Research (MJFF).</div> <div>2. National Institute of Neurological Disorders and Stroke (R01NS121374).</div> <div>3. Congressionally Directed Medical Research Programs (W81XWH-21-1-0943).</div> <p> </p>
A data repository for the study of Alpha-synuclein aggregates trigger anti-viral immune pathways and RNA editing in human astrocytes
<p><span>This repository contains data associated with the study:</span></p> <p><span><strong>"Alpha-synuclein Aggregates Trigger Anti-Viral Immune Pathways and RNA Editing in Human Astrocytes"</strong></span></p> <p><span>Published as a <strong>bioRxiv preprint</strong>: <a href="https://doi.org/10.1101/2024.02.26.582055"><span>DOI: 10.1101/2024.02.26.582055</span></a></span></p>
Additional data repository for the study of Alpha-synuclein aggregates trigger anti-viral immune pathways and RNA editing in human astrocytes
<p>Zip file 1: astrocytes calcium data measured using Fura 2</p> <p>Zip file2: astrocytes ROS measured using DHE (Dihydroethidium)</p> <p>Zip file 3: astrocytes cell death measured using Sytox green</p>
Condensate targeting as a strategy to prevent irreversible protein aggregation: implications for ALS and FTD | Talk - I PhasAGE International Conference
<p>The <strong>I PhasAGE international conference</strong> brought together members of the PhasAGE consortium as well as outstanding international speakers showcasing high impact achievements in the field of liquid-liquid phase separation in aging and late-onset diseases.</p> <p>For details on conference program please see: https://phasage.eu/phasage-conference-1/ </p>
Master Thesis Replication Package for: Empirical Scalability Evaluation of Hopping Window Aggregation Methods in Distributed Stream Processing
<p>Master Thesis Replication Package for: Empirical Scalability Evaluation of Hopping Window Aggregation Methods in Distributed Stream Processing</p> <p>A detailed description can be found in the <em>README.md</em>.</p>
Community patch‐dynamics governs direct and indirect nutrient recycling by aggregated animals across spatial scales
<p>Animals can have pervasive effects on ecosystems as they modify their biogeochemical and physical environments. In particular, when animals occur in high densities these effects can result in dramatic changes in the physical environment and biogeochemical hotspots or hot moments. While most research to date has focused on the direct role of animals in biogeochemical cycles, few have examined how animals indirectly influence biogeochemical cycles across scales.</p> <p>Freshwater mussels occur as spatially heterogeneous, dense and species-rich aggregations in many river ecosystems worldwide. Here we examined how mussel communities (1) directly influence the flux of particulate and dissolved nutrients and (2) indirectly effect the flux of N<sub>2</sub> production, via denitrification, across a gradient of mussel biomass and differences in community composition at the patch- (0.25 m<sup>2</sup>) and stream reach-scales (60-80 m).</p> <p>We combined measurements of ammonia (N) and soluble reactive phosphorous (P) excretion and C, N, and P biodeposition rates for ten species with biomass and distribution estimates for seven mixed-species aggregations to quantify direct mussel contributions to biogeochemical cycling and the spatial heterogeneity of their impact. Additionally, we sampled sediments at a fine spatial scale to determine how mussel biomass and richness influence potential denitrification (indirect flux) rates at the patch- and reach-scales.</p> <p>We predicted that increasing mussel biomass would lead to greater direct and indirect fluxes of nutrients, manifesting in heterogeneous nutrient redistribution within and among stream reaches. We also predicted that variation in community composition would result in differential nutrient excretion and egestion stoichiometries.</p> <p>Our results indicate that mussel aggregations directly influence soluble and particulate nutrient fluxes with community composition, particularly phylogenetic tribe composition, controlling the stoichiometry. Mussel aggregations also indirectly influenced nutrient fluxes as greater mussel biomass and species richness resulted in higher denitrification rates as mediated by their interactions with the sediments and enhancement of nutrient availability. Our results underscore the importance of patchy communities in acting as biogeochemical control points.</p>
Individual and species variation in mixed-species aggregations of harvestmen
<p>This dataset is associated with the published paper Escalante, I, M Domínguez, D Gómez-Ruiz, and G Machado. Benefits and costs of multi-specific aggregations in harvestmen (Arachnida: Opiliones). Frontiers in Ecology and Evolution (DOI 10.3389/fevo.2021.766323). Please refer to the paper for the extensive explanations on the collection, analysis, presentation, and analyses of the data. </p> <p>We provide the first description of mixed-species roosting aggregations of seven species of the genus <em>Prionostemma </em>from Costa Rica. We surveyed several plants (trees and palms) for the presence of harvestmen of seven different species across time (14 days). These harvestmen are frequently found in aggregations. Hence, we also counted the number of individuals in each aggregation. Additionally, we counted the number of legs in each harvestmen, as well as the number of parasitic mite larvae found in the harvestmen's bodies. With all of this information, we were able to explore the effects of the roosting status (solitary/aggregated), the aggregation size, and the species composition of the aggregations (single- or multi-species aggregations) with potential benefits (less damage, i.e., individuals with all of their legs) and costs (a higher parasitic infection).</p>
Dataset: "I Can't Keep It Up." A Dataset from the Defunct Voat.co News Aggregator
<p>This is the dataset released with the <a href="https://arxiv.org/abs/2201.05933">paper </a>titled: "I Can’t Keep It Up." A Dataset from the Defunct Voat.co News Aggregator. <br> The dataset consists of 15,133 <a href="http://ndjson.org/">Newline delimited JSON</a> files (ndjson). More specifically, 7,616 files for submission data, 7,515 for comment data, 1 for user data, and 1 for subverse data. Each line in the ndjson files consists of a JSON object. The JSON objects contain all the key/values we collect through the Voat API and the custom parser of the Internet Archive Wayback Machine Voat snapshot release.<br> For the detailed description of every <em>key </em>in the JSON structure, along with the type of the <em>value</em>, please read the readme.pdf file provided with this dataset.</p> <p> </p> <p>If you find our dataset useful, please cite our paper:</p> <blockquote> <pre>@inproceedings{mekacher2022can, title={"I Can't Keep It Up." A Dataset from the Defunct Voat.co News Aggregator}, author={Mekacher, Amin and Papasavva, Antonis}, booktitle={16th International Conference on Web and Social Media}, year={2022} }</pre> </blockquote>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.