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32 results for “population wave”
The population of merging compact binaries inferred using gravitational waves through GWTC-3 - Data release
<p>Data associated with Figures, Tables, and population parameter samples associated with <br><strong>The population of merging compact binaries inferred using gravitational waves through GWTC-3 , </strong><br><strong><a href="https://dcc.ligo.org/LIGO-P2100239/public">LIGO DCC</a>, <a href="https://arxiv.org/abs/2111.03634">arXiv</a>, <a href="https://journals.aps.org/prx/abstract/10.1103/PhysRevX.13.011048">PRX</a>. </strong><br>This is v3, superseding v2. Please see the README.md for more information.</p>
Data for: From pattern to process? Dual travelling waves, with contrasting propagation speeds, best describe a self-organised spatio-temporal pattern in population growth of a cyclic rodent
<p>Centroid data used for the analysis in Roos et al. Eco Lett.</p> <p>Transects, up to 99 m in length (dependent on the field's length), were surveyed in linear stable landscape features (field, track or ditch margins) to estimate vole abundance from November 2011 until September 2017. Each transect was divided into 3 m sections (33 in total) and the presence or absence of one or more signs of vole activity (i.e., latrines by burrows, fresh vegetation clippings, and recent burrow excavations) in each section was noted. The proportion of sections with signs of vole presence per transect was then used as the abundance index. The number of surveys carried out at any time varied adaptively with the perceived risk of an outbreak (according to changes in estimated abundance in previous monitoring surveys).</p> <p>The response variable typically used in all models is proportional growth rate (r_{t,i}, where is the abundance index for site at time (Royama 1992; Berryman 2002). A benefit of using r_{t,i}, rather than ln(N_{t,i}), is that any multiplicative effects of site quality are cancelled out, provided they are constant over time. To calculate r_{t,i}, vole abundance indices are required at the same location in successive time periods (i.e., N_{t,i} and N_{t+1,i}). Given that exact transect locations were rarely reused in successive months, and all transect measurements took place throughout the year rather than discrete seasons, the data had to be aggregated to consistent locations and times to allow growth rate to be calculated. As such, transects were temporally aggregated into a respective yearly quarter (e.g., January to March 2014). Transects were spatially aggregated by sequentially selecting an unassigned transect as a reference point for the ith centroid and assigning all unassigned transects within a 5 km radius to the ith centroid, and repeating until all transects had been allocated (see Figure 2 for a summary of the number of transects assigned to each centroid, centroid locations, and time series of growth rate of each centroid). Once complete, the mean Julian day, X and Y UTM (Universal Transverse Mercator) and the mean index was calculated for all transects assigned to each centroid for each time period. Where a centroid had successive values of N_{t,i} and N_{t+1,i} available, the corresponding proportional growth rate was calculated.</p> <p>A constant of 3.03 was added to N_{t,i} to avoid zero entries (3.03 was the lowest non-zero value of <em>N</em> observed). The final dataset consisted of 3,751 observations.</p>
Supplementary data release for "Cosmology and modified gravitational wave propagation from binary black hole population models"
<p>We release the data products associated to the paper <a href="https://arxiv.org/abs/2112.05728">"Cosmology and modified gravitational wave propagation from binary black hole population models", </a><a href="https://journals.aps.org/prd/abstract/10.1103/PhysRevD.105.064030"><em>Phys.Rev.D</em> 105 (2022) 6 </a>.</p> <p>The data can be used in conjunction with the code <a href="https://github.com/CosmoStatGW/MGCosmoPop">MGCosmoPop</a> to reproduce the results of the paper. </p> <p>The data product contains the following folders:</p> <p>* injections_GWTC3: injections used to analyze the GWTC3 catalog, generated with the code <a href="https://github.com/CosmoStatGW/MGCosmoPop">MGCosmoPop</a> . Injections are available separately for O1-O2, O3a, O3b for minimum SNR of 10, 11, 12 (folder names are self-explicative). Each folder contains a file named selected.h5 with the injections. For loading them, refer to the tutorial of the code <a href="https://github.com/CosmoStatGW/MGCosmoPop">MGCosmoPop</a> .</p> <p>* mock_BPL_5yr_GR : mock data for 5 years of aLIGO observations, with fiducial cosmological model set to General Relativity (see the paper for details)</p> <p>* mock_BPL_5yr_MG : mock data for 5 years of aLIGO observations, with fiducial cosmological model set to a modified gravity model with modified gravitational-wave propagation (see the paper for details)</p> <p>* injections_mock : injections for analyzing the mock datasets above</p>
Data release: Searching for binary black hole sub-populations in gravitational wave data using binned Gaussian processes
<p>The data required to reproduce the analyses of "Searching for binary black hole sub-populations in gravitational wave data using binned Gaussian processes" (<a href="https://arxiv.org/abs/2404.03166" target="_blank" rel="noopener">arxiv:2404.03166</a>). The main inference code can be found at <a href="https://github.com/AnaryaRay1/gppop/tree/spin-dev" target="_blank" rel="noopener">https://github.com/AnaryaRay1/gppop/tree/spin-dev </a> (commit: <a href="https://github.com/AnaryaRay1/gppop/commit/ee5ffc421e2c96eeed15a0e0d3839da42b982842">ee5ffc</a>). To reproduce the analyses, follow the instructions at <a href="https://github.com/AnaryaRay1/bbh-subpopulations-scripts">https://github.com/AnaryaRay1/bbh-subpopulations-scripts</a> (commit <a href="https://github.com/AnaryaRay1/bbh-subpopulations-scripts/commit/de88f931d8c1a2cb31ad2fa9d6fdf9a5a00a3c3b">de88f93</a>). Frozen versions of these repositories that were used to generate all the results are available as part of this data release, in the files "gppop_spin_dev_ee5ffc421.tar.gz" and "bbh-subpopulations-scripts_de88f931.tar.gz" respectively.</p>
Data from: Prior heat waves improve survival of field but not domesticated populations of tobacco hornworm exposed to repeated bacterial infections
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Backward Population Synthesis: Mapping the Evolutionary History of Gravitational-Wave Progenitors dataset
<p>Dataset release accompanying Backward Population Synthesis: Mapping the Evolutionary History of Gravitational-Wave Progenitors.</p> <p>Note that A22_02_rerun.hdf, A22_5_rerun.hdf, A22_rerun.hdf, KW_rerun.h5 are not directly used in generating the plots in the paper.</p>
The Large Magellanic Cloud Revealed in Gravitational Waves with LISA: Population Release
<p>The Large Magellanic Cloud (LMC)’s binary populations for study by the <em>Laser Interferometer Space Antenna (LISA)</em> as generated by Keim et al. in a paper submitted to MNRAS (Keim, M. A., Korol, V., Rossi, E. M. The Large Magellanic Cloud Revealed in Gravitational Waves with LISA. <em>Monthly Notices of the Royal Astronomical Society</em>, 2022, submitted). The files include all current double white dwarfs in the LISA band (‘LISABand’), all which will be detectable with a S/N>7 after 4 yrs (‘Detect’), and all which are detached/non-accreting, i.e. sure LISA sources (‘Detached’). This release represents a 2.7*10^9 stellar mass LMC, and includes distribution models based on observation (‘M1’) and simulation (‘M3’). For more information, please refer to Keim et al. (2022). We request that researchers utilising any of these populations cite Keim et al. (2022).</p> <p>The data columns are as follows:</p> <p>Column 1 = Right Ascension (Degrees)</p> <p>Column 2 = Declination (Degrees)</p> <p>Column 3 = Age (Myr, since formation of Main Sequence Pair)</p> <p>Column 4 = Mass of White Dwarf One (Msun)</p> <p>Column 5 = Mass of White Dwarf Two (Msun)</p> <p>Column 6 = Radius of White Dwarf One (Rsun)</p> <p>Column 7 = Radius of White Dwarf Two (Rsun)</p> <p>Column 8 = Orbital Radius (Rsun)</p> <p>Column 9 = Frequency (Hz)</p> <p>Column 10 = Chirp (Hz^2)</p> <p>Column 11 = Latitude (Radians)</p> <p>Column 12 = Longitude (Radians)</p> <p>Column 13 = Amplitude (Defined with a prefactor of 2)</p> <p>Column 14 = Inclination (Radians)</p> <p>Column 15 = Polarization (Radians)</p> <p>Column 16 = Orbital Phase (Radians)</p> <p>Column 17 = Distance (kpc)</p> <p>Column 18 = Mass Transfer (1= Yes, i.e. Roche Lobe Overfill, 0= No)</p>
Genetic Population Structure of the Waved Whelk (Buccinum undatum) in the western North Atlantic
<p>R studio script files that includes original SNP data files used to determine the spatial genetic structure of <strong><em>Buccinum undatum </em></strong>in the western North Atlantic. Attached R-code is used to generate population genetic analyses, including a pairwise F<sub>ST</sub> heatmap, principal component analyses, and admixture analyses.</p>
Gravitational Wave Memory Imprints on the CMB from Populations of Massive Black Hole Mergers
<p>Visualisation videos of the effect of gravitational wave (GW) memory onto photons from the cosmic microwave background (CMB).</p>
Different waves of postglacial recolonisation and genomic structure of bank vole population in NE Poland
<p><span>Previous studies indicated that in some species phylogeographic patterns obtained in analyses of nuclear and mitochondrial DNA (mtDNA) markers can be different. Such mitonuclear discordance can have important evolutionary and ecological consequences. In the present study, we aimed to check if there was any discordance between mitochondrial and nuclear DNA in the bank vole population in the contact zone of its two mtDNA lineages. We analysed the population genetic structure of bank voles using genome-wide genetic data (SNPs) and diversity of sequenced heart transcriptomes obtained from selected individuals from three populations inhabiting areas outside the contact zone. The SNP genetic structure of the populations confirmed the presence of at least two genetic clusters, and such division was concordant with the patterns obtained in analyses of other genetic markers and functional genes. However, genome-wide SNP analyses revealed a more detailed structure of the studied population, consistent with more than two bank vole recolonisation waves, as previously recognised in the study area. We did not find any significant differences between individuals representing two separate mtDNA lineages of the species in </span><span>functional genes </span><span>coding for protein-forming complexes, which are involved in the process of cell respiration in mitochondria. We concluded that the contemporary genetic structure of the populations and the width of the contact zone were shaped by climatic and environmental factors rather than by genetic barriers. The studied populations were likely isolated in separate Last Glacial Maximum refugia for an insufficient amount of time to develop significant genetic differentiation.</span></p>
Different waves of postglacial recolonisation and genomic structure of bank vole population in NE Poland
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Correlation between estimated pulse wave velocity values from two equations in healthy and under cardiovascular risk populations
<p><strong>Introduction </strong><strong>: </strong>Equations can calculate pulse wave velocity (ePWV) from blood pressure values (BP) and age. The ePWV predicts cardiovascular events beyond carotid-femoral PWV. We aimed to evaluate the correlation between four different equations to calculate ePWV.</p> <p><strong>Methods: </strong>The ePWV was estimated utilizing mean BP (MBP) from office BP (MBP<sub>OBP</sub>) or 24-hour ambulatory BP (MBP<sub>24-hBP</sub>). We separated the whole sample into two groups: individuals with risk factors and healthy individuals. The e-PWV was calculated as follows: </p> <p>We calculated the concordance correlation coefficient (Pc) between e1-PWV<sub>OBP</sub> vs e2-PWV<sub>OBP</sub>, e1-PWV<sub>24-hBP</sub> vs e2-PWV<sub>24-hBP</sub>, and mean values of e1-PWV<sub>OBP</sub>, e2-PWV<sub>OBP</sub>, e1-PWV<sub>24-hBP, </sub>and e2-PWV<sub>24-hBP </sub>. The multilevel regression model determined how much the ePWVs are influenced by age and MBP values.</p> <p><strong>Results:</strong> We analyzed data from 1541 individuals; 1374 ones with risk factors and 167 healthy ones. The values are presented for the entire sample, for risk-factor patients and for healthy individuals, respectively. The correlation between e1-PWV<sub>OBP</sub> with e2-PWV<sub>OBP</sub> and e1-PWV<sub>24-hBP </sub>with e2-PWV<sub>24-hBP</sub> was almost perfect. The Pc for e1-PWV<sub>OBP</sub> vs e2-PWV<sub>OBP</sub> was 0.996 (0.995-0.996), 0.996 (0.995-0.996), and 0.994 (0.992-0.995); furthermore, it was 0.994 (0.993-0.995), 0.994 (0.994-0.995), 0.987 (0.983-0.990) to the e1-PWV<sub>24-hBP </sub>vs e2-PWV<sub>24-hBP</sub>. There were no significant differences between mean values (m/s) for e1-PWV<sub>OBP</sub> vs e2-PWV<sub>OBP</sub> 8.98±1.9 vs 8.97±1.8; p=0.88, 9.14±1.8 vs 9.13±1.8; p=0.88, and 7.57±1.3 vs 7.65±1.3; p=0.5; mean values are also similar for e1-PWV<sub>24-hBP </sub>vs e2-PWV<sub>24-hBP</sub>, 8.36±1.7 vs 8.46±1.6; p=0.09, 8.50±1.7 vs 8.58±1.7; p=0.21 and 7.26±1.3 vs 7.39±1.2; p=0.34. The multiple linear regression showed that age, MBP, and age² predicted more than 99.5% of all four e-PWV.</p> <p><strong>Conclusion: </strong>Our data presents a nearly perfect correlation between the values of two equations to calculate the estimated PWV, whether utilizing office or ambulatory blood pressure.</p>
Figure 5 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)
Figure 5. Mean number of barricades per burrow in Ilyoplax pusilla at six localities (bar indicates SD). Localities arranged according to latitude. Shared alphabetical letters indicate no significant difference (p.0.05) by Tukey's honestly significant difference test.
Figure 2 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)
Figure 2. Cheliped path movement in Ilyoplax pusilla: circular type and vertical type. Arrows indicate wave path.
Figure 6 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)
Figure 6. Parsimony network of mitochondrial DNA cytochrome oxidase subunit I (COI) haplotypes of Ilyoplax pusilla. Haplotypes correspond to Table 5. Single solid line indicates one base. Circle size indicates number of each haplotype. Largest circle, n542; second largest, n514 or 15; third, n58; fourth, n54 or n55; fifth, n52; smallest circle, n51.
Figure 1 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)
Figure 1. Geographic distribution of Ilyoplax pusilla in Japan (broken line) from Wada et al. (1992), and six localities studied.
Figure 4 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)
Figure 4. Proportion of extended waves in 30 waving motions of Ilyoplax pusilla at six localities (bar indicates SD). Localities arranged according to latitude. Shared alphabetical letters indicate no significant difference (p.0.05) by Tukey's honestly significant difference test.
Figure 3 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)
Figure 3. Maximum cheliped extension during waving movements in Ilyoplax pusilla: extended type and non-extended type.
The expansion wave of an invasive predator leaves declining waterbird populations behind
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Correlation between estimated pulse wave velocity values from two equations in healthy and under cardiovascular risk populations
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