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Dataset results
66 results for “local density”
CO excitation, molecular gas density and interstellar radiation field in local and high-redshift galaxies
<p>This dataset includes the SED fitting figures and full sample table produced in the study of Liu et al. (2020, ApJ). Two example figures are shown in the Figure 1 of the paper. And selected columns of the full sample table is shown in the Table 1 of the paper. </p> <p> </p>
Supplementary materials for "TUJI1 Dataset: Multi-device dataset for indoor localization with high measurement density"
<p>Supplementary materials for "TUJI1 Dataset: Multi-device dataset for indoor localization with high measurement density"</p> <p> </p> <p>For more information please refer to the data descriptor available at: https://www.sciencedirect.com/science/article/pii/S2352340924003251</p> <p>Please cite as:</p> <p>Klus, L., Klus, R., Lohan, E.S., Nurmi, J., Granell, C., Valkama, M., Talvitie, J., Casteleyn, S. and Torres-Sospedra, J., 2024. TUJI1 Dataset: Multi-device dataset for indoor localization with high measurement density. <em>Data in Brief</em>, p.110356.</p> <p> </p>
Earth-scattering likelihoods: Likelihood and p-value tables for reconstructing the local Dark Matter Density
<p>Tables of likelihoods, p-values and best-fits associated with the EarthScatterLikelihood code - <a href="https://github.com/bradkav/EarthScatterLikelihood">https://github.com/bradkav/EarthScatterLikelihood</a> - released alongside the paper "<em>Measuring the local Dark Matter density in the laboratory</em>" (<a href="https://arxiv.org/abs/2004.01621">arXiv:2004.01621</a>).</p> <p>Examples for how to load the files are given in 'EarthScatterLikelihood/plotting'. Simply extract the folders into 'EarthScatterLikelihood/results' in https://github.com/bradkav/EarthScatterLikelihood. </p>
Enabling spectrally resolved single-molecule localization microscopy at high emitter densities: Dataset
<p>The data in this dataset accompanies the various figures present in the publication 'Enabling spectrally resolved single-molecule localization microscopy at high emitter densities'. Contained are tiff files used to create the figures 2-4 and Supplementary figures 1 and 2, as well as csvs after processed with the steps described in the paper (and contained in protocol text files).</p>
Figure 2 in Local concentration of foraging noctule bats (Nyctalus noctula) as a possible tool to assess the density of bats in large forest complexes
Figure 2. Insects (white dots) in camera flash at the observation point (lens directed vertically into the sky).
Figure 3 in Local concentration of foraging noctule bats (Nyctalus noctula) as a possible tool to assess the density of bats in large forest complexes
Figure 3. Fluctuation in daily temperature 1 month before and after the first observation (2 July 2012). Black arrows show dates of the first and second controls.
Density maps of seismic localization with a low phase coherence at 13 Hz on Argentière glacier
<p>This dataset is associated with the paper:</p> <p>----------</p> <p><strong>Dynamic imaging of glacier structures at high-resolution using source localization: a dense seismic array experiment.</strong></p> <p> </p> <p><em>Ugo Nanni<sup>1,*</sup>, Philippe Roux<sup>2</sup>, Florent Gimbert<sup>1</sup> and Albanne Lecointre<sup>2</sup></em></p> <p> </p> <p><em><sup>1</sup> IGE, Univ. Grenoble Alpes, CNRS, IRD, Grenoble, France</em></p> <p><em><sup>2</sup> ISTerre, Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IRD, IFSTTAR, Grenoble, France</em></p> <p><em>---------</em></p> <p>It contains 32 maps of seismic localization associated with low phase coherence and frequency of 13 Hz, and represents the events originating from transverse crevasses (see details in the paper).</p> <p>An image of the glacier is also provided to compare the localization to the glacier structure.</p> <p>Dataset is in .mat format</p> <p> </p>
Effects of local density dependence and temperature on the spatial synchrony of marine fish populations
<ol> <li><span>Disentangling empirically the many processes affecting spatial population synchrony is a challenge in population ecology. Two processes that could have major effects on the spatial synchrony of wild population dynamics are density dependence and variation in environmental conditions like temperature. Understanding these effects is crucial for predicting the effects of climate change on local and regional population dynamics.</span></li> <li><span>We quantified the direct contribution of local temperature and density dependence to spatial synchrony in the population dynamics of nine fish species inhabiting the Barents Sea. First, we estimated the degree to which the annual spatial autocorrelations in density are influenced by temperature. Second, we estimated and mapped the local effects of temperature and strength of density dependence on annual changes in density. Finally, we measured the relative effects of temperature and density dependence on the spatial synchrony in changes in density. </span></li> <li><span>Temperature influenced the annual spatial autocorrelation in density more in species with greater affinities to the benthos and to warmer waters. Temperature correlated positively with changes in density in the eastern Barents Sea for most species. Temperature had a weak synchronising effect on density dynamics, while increasing strength of density dependence consistently desynchronised the dynamics. </span></li> <li><span>Quantifying the relative effects of different processes affecting population synchrony is important to better predict how population dynamics might change when environmental conditions change. Here, high degrees of spatial synchrony in the population dynamics remained unexplained by local temperature and density dependence, confirming the presence of additional synchronizing drivers, such as trophic interactions or harvesting. </span></li> </ol>
Effects of local density dependence and temperature on the spatial synchrony of marine fish populations
Open the record for dataset details and reuse information.
coverage and density of eeg source localization
<p>The file contains the lead field matrices of atlas and subject specific head models and coordinate files of HydroCel EEG nets. </p>
Localization densities of the Nup84 complex models
<p>Localization densities of models of the Nup84 subcomplex of the <em>Saccharomyces cerevisiae </em>Nuclear Pore Complex.</p> <p>While the original modeling included generation of localization densities, these were not aligned with the models themselves. The densities here have been regenerated from the complete ensemble and should be correctly aligned.</p>
Data from: Fine-scale genetic structure in the orchid Gymnadenia conopsea is not associated with local density of flowering plants
<p><span><strong>Premise</strong>:</span><span> Density-dependent pollinator visitation can lead to density-dependent mating patterns and within-population genetic structure. In Gymnadenia conopsea, individuals in low-density patches receive more self-pollen than individuals in high-density patches, suggesting higher relatedness at low density. Ongoing fragmentation is also expected to cause more local matings, potentially leading to biparental inbreeding depression.</span></p> <p><span><strong>Methods</strong>: </span><span>To evaluate whether relatedness decreases with local density, we analysed 1315 SNP loci in 113 individuals within two large populations. We quantified within-population genetic structure in one of the populations, recorded potential habitat barriers, and visualized gene flow using estimated effective migration surfaces (EEMS). We further estimated the magnitude of biparental inbreeding depression that would result from matings restricted to within 5 m.</span></p> <p><span><strong>Results</strong>: </span><span>There was no significant relationship between local density and relatedness in any population. We detected significant fine-scale genetic structure consistent with isolation-by-distance, with positive kinship coefficients at distances below 10 m. Kinship coefficients were low, and predicted biparental inbreeding depression resulting from matings within the closest 5 m was a modest 1–3%.</span> <span>EEMS suggested that rocks and bushes may act as barriers to gene flow within a population.</span></p> <p><span><strong>Conclusions</strong>: </span><span>The results suggest that increased self-pollen deposition in sparse patches does not necessarily cause higher selfing rates, or that inbreeding depression results in low establishment success of inbred individuals. The modest relatedness suggests that biparental inbreeding depression is unlikely to be an immediate problem following fragmentation of large populations. The results further indicate that habitat structure may contribute to governing fine-scale genetic structure in <em>G. conopsea</em>.</span></p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh outward facing state (OFS) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh outward facing state (OFS) conformation at apo condition, imaged from the cytoplasmic side, in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state closed (IFSclosed) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state closed (IFSclosed) conformation at apo condition, imaged from the cytoplasmic side, in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open (IFSopen) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open (IFSopen) conformation at apo condition, imaged from the cytoplasmic side , in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open, kinetically locked, (IFSopen-1) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open, kinetically locked, (IFSopen-1) conformation at apo condition, imaged from the cytoplasmic side , in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
Counterintuitive scaling between population abundance and local density: implications for modelling transmission of infectious diseases in bat populations
<p>1. Models of host-pathogen interactions help to explain infection dynamics in wildlife populations and to predict and mitigate the risk of zoonotic spillover. Insights from models inherently depend on the way contacts between hosts are modelled, and crucially, how transmission scales with animal density.</p> <p>2. Bats are important reservoirs of zoonotic disease and are among the most gregarious of all mammals. Their population structures can be highly heterogenous, underpinned by ecological processes across different scales, complicating assumptions regarding the nature of contacts and transmission. Although models commonly parameterise transmission using metrics of total abundance, whether this is an ecologically representative approximation of host-pathogen interactions is not routinely evaluated.</p> <p>3. We collected a 13-month dataset of tree-roosting <i>Pteropus </i>spp. from 2,522 spatially referenced trees across eight roosts to empirically evaluate the relationship between total roost abundance and tree-level measures of abundance and density – the scale most likely to be relevant for virus transmission. We also evaluate whether roost features at different scales (roost-level, subplot-level, tree-level) are predictive of these local density dynamics.</p> <p>4. Roost-level features were not representative of tree-level abundance (bats per tree) or tree-level density (bats per m<sup>2</sup> or m<sup>3</sup>), with roost-level models explaining minimal variation in tree-level measures. Total roost abundance itself was either not a significant predictor (tree-level 3-D density) or only weakly predictive (tree-level abundance).</p> <p>5. This indicates that basic measures, such as total abundance of bats in a roost, may not provide adequate approximations for population dynamics at scales relevant for transmission, and that alternative measures are needed to compare transmission potential between roosts. From the best candidate models, the strongest predictor of local population structure was tree density within roosts, where roosts with low tree density had a higher abundance but lower density of bats (more spacing between bats) per tree.</p> <p>6. Together, these data highlight unpredictable and counterintuitive relationships between total abundance and local density. More nuanced modelling of transmission, spread and spillover from bats likely requires alternative approaches to integrating contact structure in host-pathogen models, rather than simply modifying the transmission function.</p>
Local male breeding density affects extra‐pair paternity in a south temperate population of grass wrens Cistothorus platensis
<p>Demographic factors can affect the frequency of extra-pair paternity (EPP) in birds, as the distribution and availability of potential mates in both space and time influence the rate of encounters between females and males. Over three breeding seasons, we intensively studied the breeding system of a south temperate population of grass wrens <i>Cistothorus platensis</i> by genotyping 73 broods (319 nestlings) and estimating EPP rates for those broods. Using five different radii (80, 160, 240, 320, and 400 m) around each nest with assigned paternity, we examined the effects of local breeding synchrony, male breeding density, and adult sex ratio (ASR) on the EPP rate. The majority of extra-pair offspring (~80%) were sired by neighboring males. Neither local breeding synchrony nor ASR consistently explained the EPP rate variation as their effects were only statistically significant within 320 m and 400 m. However, the EPP rate increased as the local male breeding density increased within every radius category, strongly suggesting that neighboring male abundance might play an important role in the extra-pair mating behavior in this species. Our study also highlights the relevance of using a local scale approach when studying mating behavior.</p>
Data for 'Normalization procedure for obtaining the local density of states from high-bias scanning tunneling spectroscopy'
<p>This folder contains all the raw data needed to generate the figures in the paper '<em>Normalization procedure for obtaining the local density of states from high-bias scanning tunneling spectroscopy.</em>' The data are seperated by the figures in which they appear, with a text folder in each folder that contains any relevant additional information. </p>
Simulation results for "Localized statistics decoding: A parallel decoding algorithm for quantum low-density parity-check codes"
<p>This dataset contains simulations results presented in the paper "Localized statistics decoding: A parallel decoding algorithm for quantum low-density parity-check codes".</p> <p>The files are in `csv` file format, with data easily processable using the python library `sinter`.</p>
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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.