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.
1,774
datasets available to search
ShareScore release 0.7.1
Dataset results
1,774 results for “Acceleration”
Will forest dynamics continue to accelerate throughout the 21st century in the Northern Alps?
Open the record for dataset details and reuse information.
Data from: Accelerating maximum likelihood phylogenetic inference via early stopping to evade (over-)optimization
Open the record for dataset details and reuse information.
Data from: Accelerating local extinction associated with very recent climate change
Open the record for dataset details and reuse information.
Data from: Active restoration accelerates recovery of tropical forest bird assemblages over two decades
Open the record for dataset details and reuse information.
Acceleration data reveal behavioural responses to hunting risk in Scandinavian brown bears
Open the record for dataset details and reuse information.
Data from: Independently evolved and gene flow‐accelerated pesticide resistance in two‐spotted spider mites
Open the record for dataset details and reuse information.
Supplementing enhanced weathering with organic amendments accelerates the net climate benefit in rangeland soils
Open the record for dataset details and reuse information.
Data from: Accelerated high-throughput imaging and phenotyping system for small organisms
Open the record for dataset details and reuse information.
Data from: The evolution of a placenta accelerates the evolution of post-copulatory reproductive isolation
Open the record for dataset details and reuse information.
Rapid Outer Radiation Belt Flux Dropouts and Fast Acceleration during the March 2015 and 2013 Storms: The Role of ULF Wave Ttansport From a Dynamic Outer Boundary
<p>Duplicate copy of the electron phase space density provided for the Geospace Environment Modeling (GEM) challenge event in March 2013 selected by the <em>Quantitative Assessment of Radiation Belt Modeling</em> focus group. The original copy of the data is available from <a href="https://drive.google.com/drive/u/0/folders/0ByNhSbWkAgdfaGt6TnJMcElhUTg">https://drive.google.com/drive/u/0/folders/0ByNhSbWkAgdfaGt6TnJMcElhUTg</a></p> <p> </p> <p>Data Providers:<br> Michael G. Henderson (LANL; mghenderson@lanl.gov)<br> Steven K. Morley (LANL; smorley@lanl.gov)</p> <p>This data product provides electron phase space density from the Van Allen Probes<br> ECT suite of instruments. The data are calculated similarly to the method described<br> in Morley et al. (2013), with some differences that are noted below.</p> <p>The files are provided in HDF5 format, so the files are self-describing and contain<br> ISTP-style metadata. The files should be directly readable with:<br> - SpacePy (http://sourceforge.net/p/spacepy)<br> - import the spacepy.datamodel module, use the function fromHDF5 to read the data<br> - Autoplot (http://autoplot.org)<br> - MatLab and IDL provide convience routines for reading HDF5</p> <p>Method<br> ------<br> Starting with directional differential flux data from HOPE, MagEIS and REPT, we<br> calculate the PSD as a function of energy, pitch angle, position and time.<br> Following the same basic method given by Morley et al., we transform this to phase <br> space density as a function of the three adiabatic invariants (M, K, L*); note that<br> where Morley et al. used a relativistic Maxwellian fit to the flux spectrum, these<br> data use a smoothing spline fit so that more complex spectral shapes can be<br> represented. Note also that Morley et al. only used REPT, where these files represent<br> the energy ranges of MagEIS and REPT, but also use HOPE to constrain the fit at low<br> energies.</p> <p>While the pitch angles are determined using the EMFISIS data, all three adiabatic <br> invariants are derived from a magnetic field model. These PSD data files use the<br> Tsyganenko and Sitnov (2005) model (aka TS04, T05 or TS05). The models were run using<br> the "definitive" Qin-Denton data files provided by the RBSP ECT-SOC. These files<br> should be made available through the QARBM google drive. </p> <p><br> Caveats<br> -------<br> These data should be considered preliminary. They have undergone a limited amount of<br> verification and prior to publication the data providers should be contacted. New<br> versions of these data may be generated at some point - we do not expect noticeable <br> changes to the data present.<br> Some gaps may be present in the files that are due to calculation of the adiabatic <br> invariants failing. The issues causing these gaps have been resolved in the underlying <br> software, but the data have not yet been regenerated.</p> <p><br> References<br> ----------<br> Morley, S. K., M. G. Henderson, G. D. Reeves, R. H. W. Friedel, and D. N. Baker (2013), <br> Phase Space Density matching of relativistic electrons using the Van Allen Probes: REPT results,<br> Geophys. Res. Lett., 40, 4798-4802, doi:10.1002/grl.50909.</p> <p>Tsyganenko, N. A., and M. I. Sitnov (2005), <br> Modeling the dynamics of the inner magnetosphere during strong geomagnetic storms, <br> J. Geophys. Res., 110, A03208, doi:10.1029/2004JA010798.</p> <p> </p> <p>Also included is the copy of the LANLgeoMag software used in the paper provided on <a href="https://github.com/drsteve/LANLGeoMag">https://github.com/drsteve/LANLGeoMag</a> </p> <p>Copyright (c) 2014, Los Alamos National Security, LLC All rights reserved. Copyright 2014. Los Alamos National Security, LLC. This software was produced under U.S. Government contract DE-AC52-06NA25396 for Los Alamos National Laboratory (LANL), which is operated by Los Alamos National Security, LLC for the U.S. Department of Energy. The U.S. Government has rights to use, reproduce, and distribute this software. NEITHER THE GOVERNMENT NOR LOS ALAMOS NATIONAL SECURITY, LLC MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LIABILITY FOR THE USE OF THIS SOFTWARE. If software is modified to produce derivative works, such modified software should be clearly marked, so as not to confuse it with the version available from LANL.</p> <p>Additionally, redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. Neither the name of Los Alamos National Security, LLC, Los Alamos National Laboratory, LANL, the U.S. Government, nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL LOS ALAMOS NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</p> <p><br> </p>
Data of Bayesian inference of non-linear multiscale model parameters accelerated by a Deep Neural Network
<pre>Data from title = "Bayesian inference of non-linear multiscale model parameters accelerated by a Deep Neural Network", journal = "Computer Methods in Applied Mechanics and Engineering", pages = "112693", year = "2020", issn = "0045-7825", doi = "https://doi.org/10.1016/j.cma.2019.112693", author = "Wu, Ling and Zulueta, Kepa and Major, Zoltan and Arriaga, Aitor and Noels, Ludovic" </pre>
Data and Code from Pritchard & Vallejo-Marin (2020) "Floral vibrations by buzz-pollinating bees achieve higher frequency, velocity and acceleration than flight and defence vibrations"
<p>Data and Code from Pritchard & Vallejo-Marin (2020) "Floral vibrations by buzz-pollinating bees achieve higher frequency, velocity and acceleration than flight and defence vibrations" Journal of Experimental Biology. doi: 10.1242/jeb.220541</p>
Supplementary Information for Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS
<p>Supplementary information for<br> Páll, S., Zhmurov, A., Bauer, P., Abraham, M., Lundborg, M., Gray, A., Hess, B, & Lindahl, E.. (2020). Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS. The Journal of Chemical Physics, 2020</p> <p>Contains benchmark methodology description as well as all inputs used in the application performance benchmarks included the paper.</p>
Acceleration of relativistic beams using laser-generated terahertz pulses
<p>Dataset for the figures contained in the manuscript entitled "Acceleration of relativistic beams using laser-generated terahertz pulses".</p>
Signals interpreted as archaic introgression are driven primarily by accelerated evolution in Africa
<p>Non-African humans appear to carry a few percent archaic DNA due to ancient inter-breeding. This modest legacy and its likely recent timing imply that most introgressed fragments will be rare and hence will occur mainly in the heterozygous state. I tested this prediction by calculating D statistics, a measure of legacy size, for pairs of humans where one of the pair was conditioned always to be either homozygous or heterozygous. Using coalescent simulations, I confirmed that conditioning the non-African to be heterozygous increased D while conditioning the non-African to be homozygous reduced D to zero. Repeating with real data reveals the exact opposite pattern. In African – non-African comparisons, D is near-zero if the African individual is held homozygous. Conditioning one of two Africans to be either homozygous or heterozygous invariably generates large values of D, even when both individuals are drawn from the same population. Invariably, the African with more heterozygous sites (conditioned heterozygous > unconditioned > conditioned homozygous) appears less related to the archaic. In contrast, the same analysis applied to pairs of non-Africans always yields near-zero D, showing that conditioning does not create large D without an underlying signal to expose. Large D values in humans are therefore driven almost entirely by heterozygous sites in Africans acting to increase divergence from related taxa such as Neanderthals. In comparison with heterozygous Africans, individuals that lack African heterozygous sites, whether non-African or conditioned homozygous African, always appear more similar to archaic outgroups, a signal previously interpreted as evidence for introgression. I hope these analyses will encourage others to consider increased divergence as well as increased similarity to archaics as mechanisms capable of driving asymmetrical base-sharing.</p>
Data from: Repeated evidence that the accelerated evolution of sperm is associated with their fertilization function
<p><span><span><span><span><span><span><span><span><span><span><span>Spermatozoa are the most morphologically diverse cell type, leading to the widespread assumption that they evolve rapidly. However, there is no direct evidence that sperm evolve faster than other male traits. Such a test requires comparing male traits that operate in the same selective environment, ideally produced from the same tissue, yet vary in function. Here we examine rates of phenotypic evolution in sperm morphology using two insect groups where males produce fertile and non-fertile sperm types (<i>Drosophila </i>species from the <i>obscura </i>group and Lepidoptera), where these constraints are solved. Moreover, in <i>Drosophila </i>we test the relationship between rates of sperm evolution and the link with the putative selective pressures of fertilization function and postcopulatory sexual selection exerted by female reproductive organs.We find repeated evolutionary patterns across these insect groups – lengths of fertile sperm evolve faster than non-fertile sperm. In <i>Drosophila</i>, fertile sperm length evolved faster than body size, but at the same rate as female reproductive organ length. We also compare rates of evolution of different sperm components, showing that head length evolves faster in fertile sperm while flagellum length evolves faster in non-fertile sperm. Our study provides direct evidence that sperm length evolves more rapidly in fertile sperm, likely because of their functional role in securing male fertility and in response to selection imposed by female reproductive organs.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Nitrogen enrichment accelerates mangrove range expansion in the temperate-tropical ecotone
Climate change and nutrient enrichment are two phenomena impacting coastal ecosystems. In coastal wetlands, mangroves in temperate-tropical ecotones are encroaching on adjacent saltmarshes, a pattern that is primarily attributed to warmer winter temperatures. Climate change is also expected to increase the vulnerability of coastal wetlands to eutrophication, and increases in nutrient availability may further mediate the rate of mangrove expansion. We investigated the consequences of nutrient enrichment on coastal wetlands in the mangrove-saltmarsh ecotone near the temperate edge of mangrove distribution along the northeast coast of Florida. We tested the hypothesis that nutrient enrichment enhances the ongoing, climate-driven expansion of mangroves into areas historically dominated by saltmarshes by increasing mangrove growth and cover, allowing them to outcompete and overgrow adjacent saltmarsh plants. We manipulated nitrogen (N) and phosphorus (P) availability and measured the effects on growth, cover, diversity, leaf traits and nutrient dynamics of Avicennia germinans. We found that A. germinans shrubs growing in the saltmarsh-mangrove ecotone in northern Florida grew taller, increased their canopies, and had higher reproductive output when enriched with N compared to control plants and P-enriched plants. Nutrient enrichment did not alter Sarcocornia perennis growth, and increased Batis maritima height but did not alter density or biomass. Nitrogen addition caused an increase in A. germinans cover and decreases in B. maritima cover and Simpson's index of diversity, suggesting that N enrichment, an ongoing phenomenon, can hasten the invasion of mangroves into saltmarshes by favoring mangrove growth and reproduction without significantly enhancing saltmarsh plant growth.
Accelerated landings in stingless bees are triggered by visual threshold cues
<p>Most flying animals rely primarily on visual cues to coordinate and control their trajectory when landing. Studies of visually-guided landing typically involve animals that decrease their speed before touchdown. Here, we investigate the control strategy of the stingless bee <i>Scaptotrigona depilis</i>, which instead accelerates when landing on its narrow hive entrance. By presenting artificial targets that resemble the entrance at different locations on the hive, we show that these accelerated landings are triggered by visual cues. We also found that <i>S. depilis</i> initiated landing and extended their legs when the angular size of the target reached a given threshold. Regardless of target size, the magnitude of acceleration was the same and the bees aimed for the same relative position on the target suggesting that <i>S. depilis</i> use a computationally simple but elegant 'stereotyped' landing strategy that requires few visual cues.</p>
Supplement to : Accelerated Snow Melt in the Russian Caucasus Mountains After the Saharan Dust Outbreak in March 2018
<p>These datasets contains all the data used in Accelerated Snow Melt in the Russian Caucasus Mountains After the Saharan Dust Outbreak in March 2018 by Dumont et al., in Journal of Geophysical Research.<br> This dataset includes : Sentinel-2 cloud masks, snow depth measurements, snow surface impurity content estimated from Sentinel-2, Sentinel-2 surface reflectances and digital elevation models.</p> <p>Dumont, M., Tuzet, F., Gascoin, S., Picard, G., Kutuzov, S., Lafaysse, M., et al. (2020). Accelerated snow melt in the Russian Caucasus mountains after the Saharan dust outbreak in March 2018. Journal of Geophysical Research: Earth Surface, 125, e2020JF005641. <a href="https://doi.org/10.1029/2020JF005641">https://doi.org/10.1029/2020JF005641</a></p>
Renoir: Accelerating Blockchain Validation using State Caching
<p>A Blockchain system such as Ethereum is a peer to peer network<br> where each node works in three phases: creation, mining, and validation phases. In the creation phase, it executes a subset of locally<br> cached transactions to form a new block. In the mining phase, the<br> node solves a cryptographic puzzle (Proof of Work - PoW) on the<br> block it formed. On receiving a block from another peer, it starts the<br> validation phase, where it executes the transactions in the received<br> block in order to validate it. Since transactions depend on the state<br> that previously executed transactions have created, a node must<br> validate each newly arrived block before creating a new block on<br> top of it. A long block validation time lowers the system’s overall<br> throughput and brings the well known Verifier’s dilemma into play.<br> Additionally, this leads to wasted mining power utilization (MPU).<br> <br> In this work, we present Renoir a novel mechanism that<br> caches state from transaction execution during the block creation<br> phase and reuses it to enable nodes to skip (re)executing these transactions during block validation. Renoir artifact consists of two parts: First, the extensive measurement from the production Ethereum network to check the extent of redundancy in the transaction execution during block creation and validation phase. Second, Evaluation of Renoir using different metrics(Throughput, Mining Power Utilization and Validation time) on a 50 node testbed mimicking the top 50 Ethereum miners.</p>
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.