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.
1,899
datasets available to search
ShareScore release 0.9.0
Dataset results
1,899 results for “Running”
Figure 4 in Run to the nest: A parody on the Iron Maiden song by Corotoca spp. (Coleoptera, Staphylinidae)
Figure 4. Bar plots of the average speeds of the two beetle species (bars represent the standard errors of the means). Lighter bars represent V1 (the out of nest velocity) while the darker bars represent V2 (the return speed). Higher speed spindle as are observed when returning to the nest.
Figure 2 in Run to the nest: A parody on the Iron Maiden song by Corotoca spp. (Coleoptera, Staphylinidae)
Figure 2. Scheme of the collection methodology: (A) Corotoca spp. leaves the nest to follow the host foraging trail. It is closely observed until stopping; the distance from the nest to where the beetle stops is measured and the time required is recorded; (B) When the beetle stops, the stopwatch is paused while larval extrusion occurs; (C) After larval the position, the return time of the beetle to the nest is recorded.
Figure 5 in Run to the nest: A parody on the Iron Maiden song by Corotoca spp. (Coleoptera, Staphylinidae)
Figure 5. This model-chart represents the numbers of individuals leaving the nests each hour, by species (individuals leaving the nests during the 60 minutes that compose a given hour are grouped within the same hour).
Figure 1 in Run to the nest: A parody on the Iron Maiden song by Corotoca spp. (Coleoptera, Staphylinidae)
Figure 1. São João do Cariri Experimental Station (ESSJC). The station is located in a semiarid environment with some ongoing processes of desertification. Efforts are currently being made to aid the recovery of the local fauna and flora.
Running Example Datasets - DiRo2C
<p>The two datasets are used to simulate two different black boxes that are supposed to predict different results in certain data areas.</p> <p>Dataset diro2c_running_example_dataset.csv:</p> <p>Two-dimensional dataset with the continuous features x1 and x2. It contains 300 instances with the following properties: min = − 293.39, max = 437.35, µ = − 2.92, and σ = 187.69 for feature x1 and min = − 251.96, max = 316.10, µ = − 3.23, and σ = 101.08 for feature x2. The instances of the datasets are classified into two classes “0” and “1”. The instances are generated by the sklearn “make_classification” function with the following parameters: make_classification(n_samples = 300, n_features = 2, n_informative = 1, n_redundant = 0, n_classes = 2, random_state = 2, n_clusters_per_class = 1, class_sep = 1.8, flip_y = 0, scale = 100).</p> <p>Dataset diro2c_running_example_manipulated_dataset.csv:</p> <p>This dataset is manipulated on the basis of the first dataset as follows:</p> <p> (x1 <= 0 and x2 <= −100 : y = 0), (x1 > 0 and x2 <= −100 : y = 1), (x1 < 150 and x2 > −100 and x2 < 100 : y = 0),<br> (x1 >= 150 and x2 > −100 and x2 < 100 : y = 1), (x1 = −200 and x2 >= 100: y = 0), (x1 > −200 and x2 >= 100 : y = 1)</p>
Figs. 26–27 in New species of fast-running flies (Diptera: Empidoidea, Hybotidae, Tachydromiinae) from mangroves in Singapore
Figs. 26–27. Elaphropeza melanuroides, new species, male habitus: 26, lateral; 27, dorsal.
Fig. 35–36 in New species of fast-running flies (Diptera: Empidoidea, Hybotidae, Tachydromiinae) from mangroves in Singapore
Fig. 35–36. Elaphropeza pallida, new species, male habitus: 35, lateral; 36, dorsal.
Fig. 12 in New species of fast-running flies (Diptera: Empidoidea, Hybotidae, Tachydromiinae) from mangroves in Singapore
Fig. 12. Elaphropeza bakau, new species, male habitus lateral.
Figs. 1–2 in New species of fast-running flies (Diptera: Empidoidea, Hybotidae, Tachydromiinae) from mangroves in Singapore
Figs. 1–2. Elaphropeza albicornis, new species, male 1, habitus lateral; 2, habitus dorsal.
MLC supervised signature files for the 1st and 2nd cycles of the Q-XRMA analytical runs
<p>At this link we make available all the MLC supervised signature files for the 1st and 2nd cycles of the Q-XRMA analytical runs applied to volcanic products of the July 3 and August 28, 2019 paroxysmal eruptions occurred at Stromboli volcano.</p>
ECCO-Darwin ED-SBS model and running instructions for "Biogeochemical river runoff drives intense coastal Arctic Ocean outgassing"
<p>Here is the model code and instructions file to run the ED-SBS simulations of "Biogeochemical river runoff drives intense Arctic Ocean outgassing" article.</p> <p>For more informations follow the instructions in the README.md file.</p>
Model run scripts and data used for analyses in Zhang et. al. (2023, JAMES)
<p>This archive contains run scripts for CLUBB single-column model (SCM) simulations and post-processed data and analysis scripts used in Zhang et al. (2023, JAMES) entitled "removing numerical pathologies in a turbulence parameterization through convergence testing". The versions of the CLUBB-SCM code used for the simulations can be found on Zenodo under <a href="https://doi.org/10.5281/zenodo.7439423">10.5281/zenodo.7439423</a>, which includes two branches: </p> <p>1. clubb_release-clubb_paper_base.zip: contains the version of the CLUBB code directly from the master branch, which is the standpoint of the code for our paper. </p> <p>2. clubb_release-clubb_paper_code.zip: contains the version of the CLUBB code with all revisions discussed in our paper. These code changes have not been merged to CLUBB master branch during the publication period </p> <p>The code modifications in the above branches were based on the CLUBB’s source code available at <a href="https://github.com/larson-group/clubb_release">https://github.com/larson-group/clubb_release</a>.</p>
Data for: Roots originating from different shoot parts are functionally different in running bamboo, Phyllostachys glauca
<p>Running bamboos are a group of clonal plants exhibiting rapid and widespread expansion. They possess two root subsystems, arising from different shoot parts, culm roots and rhizome roots. To date, it remains unclear what the functional differences are between the two root subsystems and what their relation is to the remarkably competitive ability of running bamboos. A typical running bamboo, <em>Phyllostachys glauca</em>, which dominates in a highly heterogenous habitat of limestone hills, was sampled to compare the morphology, architecture, anatomy, chemical composition, mechanics, and nutrient acquisition of the two root subsystems to explore their differences in functional traits. Compared with rhizome roots, culm roots possessed greater tensile strength, modulus of elasticity, stele diameter to root diameter ratio, root tissue density, root length density, rooting depth, basal diameter of shoot-borne roots, and more lignified cells. Culm roots also had a higher phosphorus (P) concentration (>0.4 mg g<sup>-1</sup>), which was nearly twice that of rhizome roots. By contrast, rhizome roots exhibited a greater specific root area, specific root length, cortex thickness to root radius ratio, total branch order, and greater P-uptake capacity than culm roots. Our findings revealed distinct differences in functional traits between culm roots and rhizome roots in <em>P. glauca</em>. Culm roots are considered to primarily provide anchorage, but also function in resource acquisition and nutrient storage, while rhizome roots mainly play a role in resource acquisition. Except for the anchorage and resource acquisition of culm roots, the extra resource acquisition by rhizome roots and the high concentration of a limiting nutrient (P) in culm roots enhance the performance in a highly heterogenous habitat which offers a physiological explanation for <em>P. glauca</em> dominating on limestone hills. The functional differentiation between culm roots and rhizome roots provides insight into the mechanism underpinning the remarkable expansion of running bamboos and offers a new perspective to explain the strong competitive ability of clonal plants with dimorphic roots.</p>
A 'Get-Save-Return' process continuum runs on phosphorus economy among subtropical tree species
1. Plants allocate nutrients to new leaves via making a cost-benefit trade-off between root nutrient absorption ('get') and leaf nutrient resorption ('save'). This active trade-off in nutrient acquisition pathways may cause a passive trade-off between resorption and decomposition ('return'). However, whether these nutrient-associated processes are linked and form a 'get-save-return' (GSR) continuum, and its linkages with the aboveground leaf economics spectrum (LES) and the belowground mycorrhizal association remain unclear. 2. Here, we present the first empirical evidence of a direct link among multiple nutrient-associated processes and tested this continuum hypothesis by synchronously integrating root nutrient absorption, leaf nutrient resorption, and leaf litter decomposition of 15 co-occurring tree species hosting either arbuscular mycorrhizal or ectomycorrhizal fungi in subtropical forests of China. 3. Across species, there was an active trade-off between phosphorus (P) absorption and resorption, which further caused a passive trade-off between P resorption and leaf litter decomposition, indicating that the GSR continuum exists and runs on P economy. However, these processes associated with nitrogen economy were not well-linked. Interestingly, the loading scores of species on the LES were positively correlated with root P absorption, negatively with leaf P resorption, and positively with leaf litter decomposition. These linkages indicate that species running in the 'fast lane' had greater root P absorption, lower leaf P resorption, and faster leaf litter decomposition than species running in the 'slow lane', and that the process-based GSR continuum follows the trait-based 'fast-slow' LES. Furthermore, the continuum on P economy emerged evidently in the ectomycorrhizal tree species rather than in the arbuscular mycorrhizal tree species, indicating critical control of mycorrhizal association over the continuum. 4. Synthesis. Overall, these results demonstrate the existence of the GSR continuum on tree P economy, which conforms to the economics spectrum theory but varies with mycorrhizal association type. Our findings provide a process-based framework for mechanistic understanding of the whole plant nutrient economy and ecosystem nutrient cycling, and facilitate improved predictions of biogeochemical models. --
Runs of homozygosity reveal past bottlenecks and contemporary inbreeding across diverging populations of an island-colonizing bird
<p>Genomes retain evidence of the demographic history and evolutionary forces that have shaped populations. Across island systems, contemporary patterns of genetic diversity reflect complex population demography, including colonisation events, bottlenecks, gene flow and genetic drift. Here, we investigate whether island founder events have prolonged effects on genome-wide diversity and runs of homozygosity (ROH) distributions, using whole genome resequencing from six populations across three archipelagos of Berthelot's pipit (<em>Anthus</em> <em>berthelotii</em>) – a passerine which has undergone island speciation relatively recently. Pairwise sequential Markovian coalescent (PSMC) analyses estimated divergence from its sister species approximately two million years ago. Results indicate that all Berthelot's pipit populations had shared ancestry until approximately 50,000 years ago, when the Madeiran archipelago populations were founded, while the Selvagens were colonised within the last 8,000 years. We identify extensive long ROH (>1 Mb) in genomes in the most recently colonised populations of Madeira and Selvagens which have experienced sequential island founder events and population crashes. Population expansion within the last 100 years may have eroded long ROH in the Madeiran archipelago, resulting in a prevalence of short ROH (<1 Mb). Extensive long and short ROH in the Selvagens reflects strong recent inbreeding, small contemporary effective population size and past bottleneck effects, with as much as 37.7% of the autosomes comprised of ROH >250 kb in length. These findings highlight the importance of demographic history, as well as selection and genetic drift, in shaping contemporary patterns of genomic diversity across diverging populations. </p>
waggle run phase sound during honeybee waggle dance
<p>Acoustic files of waggle run phase sound produce during the honeybee waggle dance</p>
EECCA runs for ozone flux, SEIrv4_test files
<p>EMEP results from ozone flux modelling (though all pollutants in all nc files), 2008-2012</p>
Run of digital pathology tissue/tumor prediction workflow
<p>This dataset is an <a href="https://www.researchobject.org/ro-crate/">RO-Crate</a> representation of an execution of the tissue/tumor prediction workflow for digital pathology from <a href="https://github.com/crs4/deephealth-pipelines/tree/c54840df08742e3aa454394e0e74d15fbd640f07">crs4/deephealth-pipelines</a>. It follows the <a href="https://w3id.org/ro/wfrun/provenance/0.1">Provenance Run Crate</a> profile. The workflow has been run with <a href="https://github.com/common-workflow-language/cwltool/tree/3.1.20230213100550">cwltool</a>, using the --provenance option to generate a <a href="https://doi.org/10.1093/gigascience/giz095">CWLProv</a> RO bundle, and then converted to an RO-Crate using <a href="https://github.com/ResearchObject/runcrate/tree/755fb7f0a8ba6fc238a2cb7a3218175644eb78b5">runcrate</a>. The input dataset is <a href="https://openslide.cs.cmu.edu/download/openslide-testdata/Mirax/Mirax2-Fluorescence-2.zip">Mirax2-Fluorescence-2</a> by Yves Sucaet, from the <a href="https://openslide.cs.cmu.edu/download/openslide-testdata/Mirax/">MIRAX test data</a>.<br> </p>
Run of an example Galaxy collection workflow
<p>This dataset is an <a href="https://www.researchobject.org/ro-crate/">RO-Crate</a> representation of an execution of an example Galaxy workflow, making use of some of Galaxy's platform specific features. It follows the <a href="https://w3id.org/ro/wfrun/workflow/0.1">Workflow Run Crate</a> profile. The workflow has been run with <a href="https://docs.galaxyproject.org/en/latest/index.html">Galaxy version 23.0</a> and exported using the implemented <a href="https://galaxyproject.org/news/2023-02-23-structured-data-exports-ro-bco/">export invocation to RO-crate feature</a>.</p>
Energetics of human locomotion near the walk-run transition speed.
<p><strong>Energetics of human locomotion near the walk-run transition speed.</strong></p> <p> </p> <p>This dataset includes the raw metabolic and mechanical data of 28 young subjects during locomotion at variable speed, walking and running on a treadmill at different speeds and gaits.</p> <p>Characteristics of the experimental group:</p> <p>- Sex: 28 Males - Age: 32. 53 (10.99SD)- height: 175.0 cm (0.008 SD)- weight: 72.96 kg (9.51 SD)</p> <p>Equipment:</p> <p>- Cosmed K5 portable metabolic analyzer- Cosmed Omnia Software v.1.6.5</p> <p>- Vicon Nexus 2.14 (Vicon Motion Systems Ltd, Oxford, UK)</p> <p>Experimental Design: The walking stroke transition speed (W-R Ts) was determined experimentally. Each subject was asked to perform 3 trials on a treadmill (GE T2100, General Electric, USA), with an escalating speed ladder protocol. The ramp was designed to start with a comfortable ride (3.0 km h-1), and to increase speed by 0.5 km.h-1 every 15 s. When the subject began to run, the ramp stopped and the speed was marked on a worksheet. The mean or modal transition speed was taken as the T of the subject. All treadmill tests were performed at the Biomechanics and Motion Analysis Research Laboratory (LIBiAM) of the University of the Republic in Paysandú (Uruguay), at a controlled temperature of 25ºC.</p> <p>The theoretical transition velocity tTs was calculated according to the Froude number equation (Alexander. 1976): v = (nFr g LL) 0.5, where v is the theoretical velocity, g is gravity, LL is the leg length, and nFr the Froude number, which was set to the constant value of 0.5, corresponding to the W-R transition (Alexander & Jayes, 1983; Alejandro, 2003; Bona et al., 2019).</p> <p>Experimental speed ramp:</p> <p>-A custom ascending and descending speed ramp was designed, focused on the transition speed and varied from (Ts = Transition Speed) Ts-20% to Ts+20%, each step with a duration of 5 s. Each ramp cycle lasted 50 s, and was repeated 5 times, for a total test time of 250 s. The trial was repeated twice.</p> <p> </p> <p><em>Mechanical Work (Mechanical cost of transport)</em></p> <p>The time course of the trajectory by <em>BcoM</em> was used to infer changes in the mechanical energies (potential and kinetics) involved. The horizontal work (<em>W<sub>h</sub></em>) was defined as the sum of the increments of the kinetic energy of the <em>BcoM</em> along the forward and mediolateral axes; the vertical work (<em>W<sub>v</sub></em>) was determined by the sum of the increments of gravitational potential energy and kinetic energy along the vertical axis; the external work (<em>W</em><sub>ext</sub> ), the mechanical work done to lift and accelerate the <em>BcoM</em>, was computed as the sum of the increments of the total mechanical energy of the <em>BcoM</em> (potential plus kinetic) (Cavagna et al., 1976; Willems et al., 1995). The internal work (<em>W</em><sub>int</sub>), the work necessary to accelerate the body segments with respects to the <em>BcoM</em>, was estimated with the methodology proposed by Cavagna & Kaneko (1977). <em>W</em><sub>int</sub> and <em>W</em><sub>ext</sub> were summed to give the total mechanical work (<em>W<sub>tot</sub></em>) (Cavagna & Kaneko, 1977; Willems et al., 1995). </p> <p>During locomotion cycles, especially in W, part of the potential energy of the <em>BcoM</em> is converted into kinetic energy, and vice versa, so that the sum of <em>W<sub>h</sub></em> and <em>W<sub>v</sub></em> is greater than the actual work done (<em>W<sub>ext</sub></em>). The difference, expressed as percentage, corresponds to the energy recovery R% (Cavagna et al., 1976), which formula is:</p> <p>R% = (<em>W</em><sub>h</sub> +<em> Wv</em> -<em> W</em><sub>ext</sub>) (<em>W</em><sub>h</sub> + <em>Wv</em>)</p> <p><em> Cost of transport (Metabolic transport cost)</em></p> <p>Oxygen uptake and respiratory quotient were measured breath-by-breath by a portable metabolimeter (K5, Cosmed, Italy). Reference resting values were measured during 5 min in orthostatic quiet position. Each trial was started when the metabolic parameters were near the reference resting values.</p> <p>The <sub>2</sub> (mlO<sub>2</sub>.kg<sup>-1</sup>.min<sup>-1</sup>) and RQ of the last 50 s of each recorded trial, corresponding to the last complete ramp, were averaged. The reference resting <sub>2</sub> was subtracted to the measured one to obtain the net oxygen uptake. VO<sub>2NET</sub> was then converted to mass-specific metabolic rate (W kg<sup>-1</sup>) using a RQ based energetic equivalent(P. E. Di Prampero et al., 2015). The C (J kg<sup>-1</sup> m<sup>-1</sup>) was finally obtained by dividing the metabolic rate for the average speed: </p> <p> </p> <p> (2)</p> <p> </p> <p><em>Apparent Mechanical Efficiency (AE)</em></p> <p>The AE was calculated as proposed by Cavagna and Kaneko, ie,</p> <p>AE = <em>W</em><sub>to</sub> C</p> <p>where <em>W</em><sub>tot</sub> is the total mechanical work and C the cost of transport (G. A. Cavagna & Kaneko, 1977).</p> <p> </p> <p><em>Data processing and calculation</em></p> <p>Image preprocessing was performed in Vicon Nexus 2.14 (Vicon Motion Systems Ltd, Oxford, UK), kinematic variable calculation performed with Python 2.7 and ProCalc 1.6 (Vicon Motion Systems Ltd, Oxford, UK), the calculation of mechanical variables was implemented in MatLab (The MathWorks, Inc., California, USA). The calculation of C was performed in Microsoft Excel (Microsoft Office 365).</p> <p> </p> <p>Note: Not all subjects performed the entire protocol. In particular, some data lack follow-up.</p> <p>Analysis of the cost of transportation:</p> <p>All participants signed an informed consent. The protocol was approved by the University's Ethics Committee (#311170-000921-19).<br> </p> <p>The legend of the dataset.</p> <p>There are 3 excel sheets where each row is associated with subjects from 1 to 28.</p> <p>Energy sheet:</p> <p>Subject: Subject</p> <p>Age</p> <p>Weigth</p> <p>Heigth(m)</p> <p>IMC</p> <p>Km x week: kilometers per week</p> <p>Background: history of injuries</p> <p>INT1 km/h: attempt 1</p> <p>INT2 km/h: attempt 2</p> <p>INT3 km/h: Attempt 3</p> <p>Average transition (km/h): average walk-race transition speed</p> <p>Froude estimated PST(m/s)</p> <p>Froude Estimated PST(km/h)</p> <p>Basal Vo2: Basal oxygen consumption in orthostasis</p> <p>VO2/kg/min: Oxygen consumption in the test</p> <p>RQ: RQ in the test</p> <p>VO2 Net VO2kg/min): VO2 net in the test</p> <p>VO2/kg/s</p> <p>J/kg/s = W/kg</p> <p>C (J/kg/m): transport cost obtained in the test</p> <p> </p> <p>Test: test performed</p> <p>Gait: type of gait that has been evaluated</p> <p>ASC/DESC: place on the ramp (ascending or descending)</p> <p>Stride: stride identification for each type of gait</p> <p>Duty Factor_tr: duty factor</p> <p>Stride Frequency_tr: stride frequency</p> <p>Stride Time_tr: stride time</p> <p>Time: time in the stride</p> <p>Speed in treadmill : speed that occurs in treadmill</p> <p>Distance: distance traveled by the stride</p> <p>Step frequency: frequency of passage</p> <p>Wext: External Work</p> <p>Rec: recovery</p> <p>Wv: trabajo vertical</p> <p>Wh: horizontal work</p> <p>WintTOT: Total internal work</p> <p> </p> <p> </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.