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256 results for “mass effects”
The Outer Stellar Mass of Massive Galaxies: A SimpleTracer of Halo Mass with Scatter Comparable to Richness and Reduced Projection Effects
<p>These are the data for reproducing the results of the publication titled "The Outer Stellar Mass of Massive Galaxies: A Simple Tracer of Halo Mass with Scatter Comparable to Richness and Reduced Projection Effects" by Song Huang et al.</p> <p>Please see the Python scripts and Jupyter notebooks provided in the <a href="https://github.com/dr-guangtou/jianbing">jianbing</a> repo for examples about how to use these data files. And please contact dr.guangtou@gmail.com if you have any questions about these data.</p> <p>-------------------------------------------------------------------------------------------------</p> <p>Here is a brief description of all the files:</p> <p><strong>Data from N-body simulation:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/mdpl2_halos_0.7333_reduced_logmvir_13.npy?versionId=1648006b-a91a-4300-aadf-c4746d6f3ef2">mdpl2_halos_0.7333_reduced_logmvir_13.npy</a> <ul> <li>Basic information about the dark matter halos from MDPL2 simulation</li> <li>For scale factor = 0.7333 (or z~0.4).</li> <li>Only for halos with logMvir > 13.0.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/mdpl2_particles_0.7333_72m.npy?versionId=ff7d5847-df44-46f5-9bcc-d8a7f3cc040d">mdpl2_particles_0.7333_72m.npy</a> <ul> <li>Particle catalog of the a=0.7333 snapshot from MDPL2</li> <li>This is a down-sampled version with 72 million particles.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/topn_theory_demo.pkl?versionId=7ed87c28-7adc-4987-9e00-b6223c744d42">topn_theory_demo.pkl</a> <ul> <li>These are the data used to create the theoretical demo of the TopN test.</li> <li>It is used for making the figures in <a href="https://github.com/dr-guangtou/jianbing/blob/master/notebooks/figure/fig1.ipynb">this notebook</a>.</li> </ul> </li> </ul> <p><strong>Catalogs of Galaxies or Galaxy Clusters:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/camira_s16a_cluster_use_bsm.fits?versionId=ca274c83-4025-41c4-b993-3cc9074f08b2">camira_s16a_cluster_use_bsm.fits</a> <ul> <li>The HSC S16A CAMIRA cluster catalog.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/redmapper_hsc_s16a_cluster_bsm.fits?versionId=11608e41-2427-4808-9060-a06139de165c">redmapper_hsc_s16a_cluster_bsm.fits</a> <ul> <li>The HSC S16A redMaPPer cluster catalog.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/redmapper_sdss_cluster_bsm.fits?versionId=b977c4ed-11c9-4751-b32f-60883d2e81b0">redmapper_sdss_cluster_bsm.fits</a> <ul> <li>The SDSS DR8 redMaPPer clusters in the HSC S16A footprint.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/s16a_massive_logm_11.2.fits?versionId=603cb17c-bb64-4aa7-ae05-5ec61c7ee861">s16a_massive_logm_11.2.fits</a> <ul> <li>0.2 <z < 0.5 massive galaxies in the HSC S16A footprint.</li> </ul> </li> </ul> <p><strong>Galaxy-Galaxy Lensing Data:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/s16a_weak_lensing_medium.hdf5?versionId=593c4ba0-6d7d-4b83-b8d9-01740a351fcd">s16a_weak_lensing_medium.hdf5</a> <ul> <li>A compilation of the weak lensing data to calculate the DeltaSigma profiles.</li> <li>This includes the weak lensing source catalog, photometric redshift calibration file, and the random catalog.</li> <li>"medium" here means we applied the medium criteria for selecting source galaxies. Please refer to <a href="https://ui.adsabs.harvard.edu/abs/2019MNRAS.490.5658S/abstract">Speagle et al. (2019)</a> for the exact meaning of these criteria.</li> <li>We also have a "basic" and "strict" version. Please send your request if you need them.</li> </ul> </li> <li><a href="https://zenodo.org/api/files/f10135d5-64ea-47c1-b292-bea86bbcdf08/topn_public_s16a_medium_precompute.hdf5?versionId=2216ecf9-b836-4dd5-a9dd-7e070e4977bf">topn_public_s16a_medium_precompute.hdf5</a> <ul> <li>A compilation of pre-computed lensing profiles for each individual object in a different galaxy or cluster samples for the TopN test.</li> <li>These are the data used to create the stacked DeltaSigma profiles.</li> <li>We also provide the "strict" and the "basic" versions if you want to test the robustness of the TopN tests against the different selections of source galaxies in weak lensing measurements. You just need these files to generate the stacked DeltaSigma profiles.</li> </ul> </li> </ul>
Group size effects and critical mass in public goods games
<pre>This dataset accompanies the paper "Group size effects and critical mass in public goods games", https://doi.org/10.1038/s41598-019-41988-3 It records participant decisions in a set of binary one-shot Public Goods Games with curvilinear payoff function (see details in the paper). The explanation of the data fields is present also in the metadata of the file: # Cooperation: 0=defection, 1=cooperation, 99=the participant did not make the decision # Group: interacting group size (N) # Treatment: Critical Mass Nc # dropout: 1=the participant did not make the decision, 0=the participant made the decision # incompleted: 1=participant did not make all the decisions of the experiment; 0=participant did made all the decisions of the experiment # female: 1=female, 0=male </pre> <p> </p>
Revisiting Interior Water Mass Responses to Surface Forcing Changes and the Subsequent Effects on Overturning in the Southern Ocean
<p>This dataset contains processed model data used in</p> <p>Tesdal, J.-E., A. MacGilchrist, G., Beadling, R. L., Griffies, S. M., Krasting, J. P., & Durack, P. J. (2023). Revisiting interior water mass responses to surface forcing changes and the subsequent effects on overturning in the Southern Ocean. Journal of Geophysical Research: Oceans, 128, e2022JC019105. <a href="https://doi.org/10.1029/2022JC019105">https://doi.org/10.1029/2022JC019105</a>.</p> <p>The above publication uses two coupled climate models (AOGCMs), GFDL-CM4 and GFDL-ESM4, to assess the impact of perturbations in wind stress and Antarctic ice sheet melting on the Southern Ocean meridional overturning circulation (SO MOC) and associated water mass transformations (WMT).</p> <p>The attached archive includes netCDF files to recreate all figures and tables in <a href="https://doi.org/10.1029/2022JC019105">Tesdal et al. (2023)</a>, including overturning streamfunction (moc), volume storage change (dVdt), surface water mass transformation (swmt), meridional volume transports (mvt) zonal mean potential density referenced to 2000 dbar (sigma2) and mixed layer depth (mld). These variables are derived from preindustrial control (piControl) and idealized perturbation runs of Antarctic melting (Antwater), wind stress (Stress), as well as the combination (Antwater-Stress) using the Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) protocol.</p> <p>The FAFMIP protocol (<a href="https://doi.org/10.5194/gmd-9-3993-2016">Gregory et al., 2016</a>) involves adding perturbations to the surface fluxes that are computed within the atmosphere-ocean general circulation model (AOGCM) from the state of the system (<a href="https://doi.org/10.1029/2005JC003421">Lowe and Gregory, 2006</a>; <a href="https://doi.org/10.1088/1748-9326/9/3/034004">Bouttes and Gregory, 2014</a>). The perturbations in this dataset were technically added as a flux adjustment similar to that formerly used in AOGCMs (<a href="https://doi.org/10.1007/BF01053472">Sausen et al., 1988</a>).</p> <p>The data files contain processed model output and do not include any raw model output. Model data from the piControl runs of CM4 and ESM4 are available at the Earth System Grid Federation archive (<a href="https://esgf-node.llnl.gov/projects/cmip6">https://esgf-node.llnl.gov/projects/cmip6</a>). The forcing fields (perturbations) used in the perturbation experiments can be found at <a href="https://github.com/becki-beadling/Beadling_et_al_2022_JGROceans">https://github.com/becki-beadling/Beadling_et_al_2022_JGROceans</a>. Python scripts and Jupyter notebooks to reproduce the tables and figures can be accessed at <a href="https://github.com/jetesdal/Tesdal_et_al_2023_JGROceans">https://github.com/jetesdal/Tesdal_et_al_2023_JGROceans</a>.</p> <p><strong>Contents</strong>:</p> <ul> <li>Overturning streamfunction (moc)</li> <li>Volume storage change (dVdt)</li> <li>Surface water mass transformation (swmt)</li> <li>Meridional volume transports (mvt) </li> <li>Zonal-mean potential density referenced to 2000 dbar (sigma2)</li> <li>Mixed layer depth (mld) </li> <li>Antarctic shelf mask</li> <li>Static grid files</li> </ul> <p><strong>Models</strong>:</p> <ul> <li>GFDL-CM4</li> <li>GFDL-ESM4</li> </ul> <p><strong>Simulations</strong>:</p> <ul> <li>Preindustrial control (piControl)</li> <li>Experiment with a 0.1 Sv freshwater perturbation entering at the Antarctic coast (Antwater)</li> <li>Experiment with zonal and meridional wind stress perturbations (Stress)</li> <li>Experiment with combined perturbation of both Antarctic melting and wind stress (Antwater-Stress)</li> </ul> <p><strong>NetCDF file name structure</strong>:<br> <model>_<simulation>_<member_id>_<domain>_<time_period>_<variable>.nc</p> <ul> <li>model: CM4, ESM4</li> <li>simulation: control, antwater, stress, antwaterstress</li> <li>member_id (only for antwater, stress, antwaterstress): 251, 290, 332 (CM4), 101, 151, 201 (ESM4)</li> <li>domain: global, so</li> <li>time_period: yyyy-yyyy (first year to last year)</li> <li>variable: e.g., moc_rho2_online_lores, dVdt_rho2_online_lores, swmt_sigma2_005, sigma2_jmd95_zmean</li> </ul>
Paper data and code of manuscript: Intraspecific variation on heat tolerance in a model ectotherm: effects of body mass, cell size, oxygen and sex
<p>When using the data or code from this manuscript, please cite it as:</p><p><strong>Leiva FP</strong>, Santos M, Rezende E, & Verberk WCEP. 2021. Paper data and code of manuscript: Intraspecific variation on heat tolerance in a model ectotherm: effects of body mass, cell size, oxygen and sex. Zenodo. <a href="https://doi.org/10.5281/zenodo.5120028">https://doi.org/10.5281/zenodo.5120028</a>.</p>
The Missing Link Between Black Holes in High-Mass X-ray Binaries and Gravitational-Wave Sources: Observational Selection Effects
<p>Data tables containing the calculated binary parameters used to acquire all results in <a href="https://arxiv.org/abs/2210.01825v1">arXiv:2210.01825v1</a>. The file "xrb_params_illustris_z0.05_sample.csv" contains data for the z<0.05 sampled population and the file xrb_params_illustris_z20_sample.csv contains data for the z<20 sampled population.</p>
Constraining the dense matter equation of state with new NICER mass-radius measurements and new chiral effective field theory constraints: prior and posterior samples and scripts for generating plots
<p>Full reproduction package accompanying the paper: <em>Constraining the dense matter equation of state with new NICER mass-radius measurements and </em><em>new chiral effective field theory inputs</em></p> <p> </p> <p><em>*Note, the changes made from version to version are made visible in the CHANGELOG.rst file</em></p>
Figure 5. Sentinel 3 in Marine mucilage in the Sea of Marmara and its effects on the marine ecosystem: mass deaths
Figure 5. Sentinel 3 imagery of the chlorophyll-a concentration in the study area on April 22, 2021.
Figure 3 in Marine mucilage in the Sea of Marmara and its effects on the marine ecosystem: mass deaths
Figure 3. Some dead species were collected during sampling. The orange circle indicates Atherina sp., and the yellow square indicates other affected species.
Figure 2 in Marine mucilage in the Sea of Marmara and its effects on the marine ecosystem: mass deaths
Figure 2. Regional map and sampling stations in the southern of Sea of Marmara (1: Misakça, 2: Şirinçavuş, 3: Narlı, 4: Tatlısu)
Figure 1 in Marine mucilage in the Sea of Marmara and its effects on the marine ecosystem: mass deaths
Figure 1. Mucilage aggregation examples on the water surface in the Sea of Marmara, a) on April 23, 2021, on the coast of Misakça and b) on May 25, 2021, in Erdek Harbor.
Effects of population density on static allometry between horn length and body mass in mountain ungulates
<p class="MsoNoSpacing">Little is known about the effects of environmental variation on allometric relationships of condition-dependent traits, especially in wild populations. We estimated sex-specific static allometry between horn length and body mass in four populations of mountain ungulates that experienced periods of contrasting density over the course of the study. These species displayed contrasting sexual dimorphism in horn size; high dimorphism in <i>Capra ibex</i> and <i>Ovis canadensis</i> and low dimorphism in <i>Rupicapra rupicapra</i> and <i>Oreamnos americanus</i>. The effects of density on static allometric slopes were weak and inconsistent while allometric intercepts were generally lower at high density, especially in males from species with high sexual dimorphism in horn length. These results confirm that static allometric slopes are more canalized than allometric intercepts against environmental variation induced by changes in population density, particularly when traits appear more costly to produce and maintain.</p>
Online Supplemental Tables - An atlas of genome-wide gene expression and metabolite associations and possible mediation effects towards body mass index
<p>Summary statistics of metabolite-gene expression associations and mediation analyses of effects on body mass index.</p> <p>The corresponding publication is currently under revision.</p> <ul> <li><strong>Online Supplemental Table 1</strong>: Gene expression-metabolite association summary statistics from 97 metabolites and metabolite ratios and up to 15175 genes calculated seperately in the LIFE-Adult, LIFE-Heart, LIFE-AMI and the Sorb studies. Associations were adjusted for six covariates.</li> <li><strong>Online Supplemental Table 2</strong>: Random-effects meta-analyzed gene expression-metabolite association summary statistics. P-Values were adjusted for multiple testing using a hierarchical adjustment procedure both on local (within phenotypes) and on global (across phenotypes) level.</li> <li><strong>Online Supplemental Table 3</strong>: Single-study association results needed for checking mediation analysis assumptions and for calculating mediation statistics. Only gene expression probe-metabolite pairs that associated significantly at hierarchical FDR=5% in the gene-expression-metabolite association meta-analysis qualified for these associations.The following Associations were tested: gene expression probes ~ metabolites, log-BMI ~ metabolites log-BMI ~ gene expression, log-BMI ~ gene expression + metabolite. Associations were adjusted for six covariates. P-values</li> <li><strong>Online Supplemental Table 4</strong>: Meta-analyzed association results needed for checking mediation analysis assumptions and for calculation mediation statistics.</li> <li><strong>Online Supplemental Table 5: </strong>Mediation analysis summary statistics. Mediations of gene expression effects (exposure) via metabolite effects (mediatior) and of metabolite effects (exposure) via gene expression effects (mediator) on body mass index (outcome) were tested.</li> </ul> <p> </p>
Effects of population density on static allometry between horn length and body mass in mountain ungulates
Open the record for dataset details and reuse information.
Data from: The effects of body mass on immune cell concentrations of mammals
Theory predicts that body mass should affect the way organisms evolve and use immune defenses. We investigated the relationship between body mass and blood neutrophil and lymphocyte concentrations among 250+ terrestrial mammalian species. We tested whether existing theories (e.g., Protecton Theory, immune system complexity, and rate of metabolism) accurately predicted the scaling of immune cell concentrations. We also evaluated the predictive power of body mass for these leukocyte concentrations compared to sociality, diet, life history, and phylogenetic relatedness. Phylogeny explained >65% of variation in both lymphocytes and neutrophils, and body mass appeared more informative than other interspecific trait variation. In the best-fit mass-only model, neutrophils scaled hypermetrically (b = 0.11) with body mass whereas lymphocytes scaled isometrically. Extrapolating to total cell numbers, this exponent means that an African elephant circulates 13.3 million times the neutrophils of a house mouse, whereas their masses differ by only 250k-fold. We hypothesize that such high neutrophil numbers might offset the i) higher overall parasite exposure that large animals face and/or ii) the higher relative replication capacities of pathogens to host cells.
Data from: Widespread bird species show idiosyncratic responses in residual body mass to selective logging and edge effects in the Colombian Western Andes
<p>This dataset consists of banding data (N = 1589 captures, 129 bird species), including morphological and breeding biology measures, collected from understory birds in subtropical cloudforest at roughly 2000 m.a.s.l. in the municipality of El Cairo in Colombia's Western Andes (Serrania de los Paraguas range). Roughly 8,350 net hours were divided into two three-month field seasons (June-August 2017 and January-March 2018), both corresponding to local dry seasons. Birds were banded along 500-meter transects in forest interior across a gradient of forest fragment patch sizes (N = 8 fragments, area range = 10-173 ha) and a private ~750 ha reserve (Reserva Natural Cerro El Ingles) in the same landscape. Each non-hummingbird capture was fitted with an aluminum leg band with a unique combination, and we collected data on mass, tarsus length, wing chord, pectoral muscle score, cloacal protuberance and brood patch score, and age and sex (where possible due to plumage differences). We captured 101 species (including 6 boreal migrants) in 844 captures (53%) during the January-March sampling period and 102 species in 745 captures during the June-August sampling period; each site was sampled during both sampling periods. The most captured bird families were Trochilidae (24 spp., 36% of total captures), Thraupidae (17 spp.), Tyrannidae (16 spp.), Furnariidae (14 spp.), and Turdidae (6 spp.).</p> <p>A subset of these data (uploaded as a separate file) were used to calculate body condition indices for 20 species of commonly captured birds (N = 984 captures) that occured across much of the patch size gradient (at least 8 out of 14 transects), and were related to fragment area and measures of edge and selective logging effects (see Jones et al. 2022). In this file, we include all predictor variables necessary to run the generalized linear mixed models in Jones et al. (2022), including proportion forest cover within 1 km (a proxy for patch size), edge density, average distance to forest edge from the netting transect, average canopy cover and height along the transect, multivariate measures of understory plant density, large-diameter tree density, and vertical vegetation structure, elevation of each transect, and average yearly rainfall for each transect.</p>
Effectiveness of seasonal malaria chemoprevention administered in a mass campaign in the Kedougou region of Senegal in 2016: a Case-control study
<p><strong><span>Context</span></strong></p> <p><span>Seasonal malaria chemoprevention (SMC) with Sulfadoxine-Pyrimethamine plus Amodiaquine (SPAQ) is a malaria prevention strategy recommended since 2012 by the World Health Organization (WHO) for children under 5 years of age. In Senegal, the scaling up of the SMC has started since 2013 in the south-eastern regions of the country with an extension of the target to 10 years old children. The scaling up of SMC requires a regular evaluation of the strategy as recommended by the WHO. This study was conducted to evaluate the effectiveness of SMC. </span></p> <p><strong><span>Methodology </span></strong></p> <p><span>A case-control study was conducted in some villages of the health districts of Saraya and Kedougou in the Kedougou region from July to December 2016. A "case" was a sick child, aged 3 months to 10 years, seen in consultation and with a positive RDT. The "control" was a child of the same age group with a negative RDT and living in the same compound as the case or in a neighbouring compound. Each case was matched with two controls. Exposure to SMC was assessed by interviewing the mothers/caretakers and by checking the SMC administration card.</span></p> <p><strong><span>Results</span></strong></p> <p><span>A total of 492 children, including 164 cases and 328 controls, were recruited for our study. Their mean ages were 5.32 (+/- 2.15) and 4.44 (+/-2.25) years for the cases and the controls respectively. Male children predominated in both cases (55.49%) and controls (51.22%) (p=</span><span>0.18)</span><span>. Net ownership was 85.80% among cases and 90.85% among controls (p=0.053). The proportion of controls who received SMC was higher than that of cases (98.17% vs 85.98%; (p=1.10<sup>-7</sup>)). The protective effectiveness of SMC was 89% </span><span>(IC 95% = 84–93%)</span><span> </span><span>(OR=0.11).</span></p> <p><strong><span>Conclusion </span></strong></p> <p><span>SMC is therefore an effective strategy in the control of malaria in children. Case-control studies are a good approach for monitoring the efficacy of drugs administered during SMC.</span></p>
Photon Pressure with an Effective Negative Mass Microwave Mode
<p>Data and measurements scripts for the paper "Photon Pressure with an Effective Negative Mass Microwave Mode".</p>
Nowcast of Aerospace Ionizing Radiation System (NAIRAS) simulation of the effect of the 2024-05-11 coronal mass ejection and solar particle event on Earth's atmosphere
<p>The effect of the CME on the cutoff rigidity and the dose at different altitude as computed by NAIRAS.</p> <p>The neutron monitor data from OULU and the DSCOVR data for solar wind density and speed are put as a reference for when the Forbush decrease happens and when the CME arrives.</p> <p> </p> <p>The version 2 added files with shorter lead time before the CME arrival and bigger labels</p>
Effects of Rotation on the Minimum Mass of Primordial Progenitors of Pair-instability Supernovae
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2012ApJ...748...42C/abstract">Chatzopoulos & Wheeler (2012)</a>. MESA version 3647.</p> <p>Publication DOI: <a href="https://doi.org/10.1088/0004-637X/748/1/42">10.1088/0004-637X/748/1/42</a></p>
Low-mass X-ray binaries: the effects of the magnetic braking prescription
<p>MESA inlists associated with Formation of <a href="https://ui.adsabs.harvard.edu/?#abs/2019MNRAS.483.5595V/abstract">Low-mass X-ray binaries: the effects of the magnetic braking prescription</a></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.