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252 results for “Variability Modelling”
Supplementary tables for: Dependent variable selection in phylogenetic generalized least squares regression analysis under Pagel's lambda model
<p class="MsoNormal"><span>Phylogenetic generalized least squares (PGLS) regression is widely used to detect evolutionary correlations. In contrast to the equal treatment of analyzed traits in conventional correlation methods such as Pearson and Spearman's rank tests, we must designate one trait as the independent variable and the other as the dependent variable. However, in our PGLS regression analyses (using Pagel's <em>λ</em> model) of both empirical and simulated datasets, switching independent and dependent variables yielded many conflicting results. A serious problem with PGLS regression that has not been noticed before is that selecting an inappropriate trait as the dependent variable will often result in an error. To assess correlations in simulated data, we established a gold standard by analyzing changes in traits along phylogenetic branches. Next, we tested seven potential criteria for dependent variable selection: log-likelihood, Akaike information criterion, <em>R</em><sup>2</sup>, <em>p</em>-value, Pagel's <em>λ</em>, Blomberg et al.'s <em>K</em>, and the estimated <em>λ</em> in <a name="_Hlk136010442"></a>Pagel's <em>λ</em> model. We determined that the last three criteria performed equally well in selecting the dependent variable and were superior to the other four. For practicality, we suggest using the trait with a higher <em>λ</em></span><span> or <em>K</em> </span><span>value as the dependent variable in future PGLS regressions. In analyzing the evolutionary relationship between two traits, we should designate the trait with a stronger phylogenetic signal as the dependent variable even if it could logically assume the cause in the relationship.</span></p>
On the variability of the slow solar wind: New insights from the modelling and PSP-WISPR observations.
<p>We analyse the signature and origin of transient structures embedded in the slow solar wind, and observed by the Wide-Field Imager for Parker Solar Probe (WISPR) during its first 10 passages close to the Sun. WISPR provides a new in-depth vision on these structures, which have long been speculated to be a remnant of the pinch-off magnetic reconnection occurring at the tip of helmet streamers.<br> We pursue the previous modelling works of Reville (2020b, 2022) that simulate the dynamic release of quasi-periodic density structures into the slow wind through a tearing-induced magnetic reconnection at the tip of helmet streamers. Synthetic WISPR white-light (WL) images are produced using a newly developed advanced forward modelling algorithm, that includes an adaptive grid refinement to resolve the smallest transient structures in the simulations. We analyse the aspect and properties of the simulated WL signatures in several case studies, typical of solar minimum and near-maximum configurations.<br> Quasi-periodic density structures associated with small-scale magnetic flux ropes are formed by tearing-induced magnetic reconnection at the heliospheric current sheet and within 3-7Rs. Their appearance in WL images is greatly affected by the shape of the streamer belt and the presence of pseudo-streamers. The simulations show periodicities on the ~90-180min, ~7-10hr and ~25-50hr timescales, which are compatible with WISPR and past observations.<br> This work shows strong evidence for a tearing-induced magnetic reconnection contributing to the long-observed high variability of the slow solar wind.</p>
[Supplementary Information] Model uncertainty versus variability in the life cycle assessment of commercial fisheries
<p>Supporting information from the manuscript: <em>Model uncertainty versus variability in the life cycle assessment of commercial fisheries</em>. The study analyses the life cycle assessment of fish species landed by Danish trawlers, comparing sources of uncertainty (such as modelling approaches) with sources of variability (vessel length and years).</p> <p>Supporting information 1: In depth description of the different models used in the study, the fuel disaggregation processes and the sensitivity analysis performed</p> <p>Supporting information 2: Contains the excel table with the datasets and related calculations to replicate the results described in the paper and the R code used to analyze the results.</p>
Terrain variables used for ensemble distribution modelling of vulnerable marine ecosystems indicator taxa on data-limited seamounts of Cabo Verde (NW Africa)
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Supplementary tables for: Dependent variable selection in phylogenetic generalized least squares regression analysis under Pagel’s lambda model
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Data from: Hidden variable models reveal the effects of infection from changes in host survival
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Data and simulation model files for: Variable-stiffness morphing wheel inspired by the surface tension of a liquid drop
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Code: A model of wild bee populations accounting for spatial heterogeneity and climate induced temporal variability of food resources at the landscape level
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Climate model experiments of regional-scale tree die-off replaced by shrubs (select variables at daily time resolution): Part 4
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Climate model experiments of regional-scale tree die-off replaced by grass (select variables at daily time resolution): Part 2
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Individual variability and versatility in an eco-evolutionary model of avian migration
<p>Seasonal migration is a complex and variable behavior with the potential to promote reproductive isolation. In Eurasian blackcaps (<em>Sylvia atricapilla</em>), a migratory divide in central Europe separating populations with southwest and southeast autumn routes may facilitate isolation, and individuals using new wintering areas in Britain show divergence from Mediterranean winterers. We tracked 100 blackcaps in the wild to characterize these strategies. Blackcaps to the west and east of the divide used predominantly SW and SE directions, respectively, but close to the contact zone many individuals took intermediate (S) routes. At 14.0ºE, we documented a sharp transition from SW to SE migratory directions across only 27 (10–86) km, implying a strong selection gradient across the divide. Blackcaps wintering in Britain took northwesterly migration routes from continental European breeding grounds. They originated from a surprisingly extensive area, spanning 2000 km of the breeding range. British winterers bred in sympatry with SW-bound migrants but arrived 9.8 days earlier on the breeding grounds, suggesting some potential for assortative mating by timing. Overall, our data reveal complex variation in songbird migration and suggest that selection can maintain variation in migration direction across short distances while enabling the spread of a novel strategy across a wide range.</p>
First release of the time-variable gravity model over North China (NC-IGP01T).
<p>Time-variable gravity model over North China (NC-IGP01T)</p>
BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performance
<p>This Zenodo repository contains 100 copies of the model BERT fine-tuned on the MNLI dataset, created for the paper "BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performance." Please see the project GitHub page for more details about using these models and how to cite any such usage: https://github.com/tommccoy1/hans/tree/master/berts_of_a_feather</p>
Spin-up time and internal variability analysis for overlapping time slices in a regional climate model
<p>In order to increase computational efficiency, several long-term regional climate simulations were split into overlappings time slices. These overlappings slices were used to explore the relative role of spin-up time and internal variability in the discontinuities that are produced once the slices are joined.</p> <p>This dataset was generated using the Weather Research and Forecasting (WRF) model and includes two sets of time slices for the periods 2002-2006 and 2006-2010 over the CORDEX South American domain at 0.44º horizontal resolution (SAM-44), regular on a rotated latitude-longitude projection. The data was forced by the scenario RCP 8.5 and driven by the Canadian Earth System model (CanESM2). The model configuration files are also attached.</p>
Crustal thicknesses, Moho depths and 3-D density anomaly model for GJI paper: Crustal structure of onshore-offshore Atlantic Canada and environs from constrained 3-D gravity inversion using variable mesh depths by J. Kim Welford
<p>The files are provided as ascii text files in terms of both latitudes/longitudes and eastings/northings. For the 3-D density anomaly model, it is provided with columns of x, y, z, and absolute density. The conversions from latitudes/longitudes to eastings/northings for all of the models and maps in this work are computed with ellipsoid WGS-84 and UTM zone 19 using Generic Mapping Tools.</p>
CFS model monthly mean diurnal cycles of ocean and atmosphere variables at TAO mooring locations
<p>v0.1.3</p> <p>cfsm501_ocn_2002_2006_TAOpoints_hourly.tgz -- contains netCDF files of hourly ocean variables: one ocean file per month over 4 years (2002-2006).</p> <p>Each file contains water temperature with dimensions (time, depth, lat, lon) at TAO locations. If joining multiple files together, concatenate along the time axis.</p> <p>-------------------------</p> <p>v0.1.2</p> <p>cfsm501_atmo_2002_2006_TAOpoints_3D_monthlyMeanDiurnalCycle.tgz -- contains netCDF files of monthly mean diurnal cycle of atmosphere variables: one atmosphere file per month over 4 years (2002-2006).</p> <p>Each file contains multiple variables with dimensions (time, hour, plev, lat, lon) at TAO locations. The dimension "time" is of length 1 in all files. If joining multiple files together, concatenate along the time axis. The "hour" dimension represents the 24 hours of the diurnal cycle.</p> <p>Note that this version of the data has NOT had the 3-day high pass filter applied before the diurnal cycle calculation.</p> <p>-------------------------</p> <p>v0.1.1</p> <p>cfsm501_atmo_2002_2006_TAOpoints_hourly.tgz -- contains netCDF files of hourly atmosphere variables: one atmosphere file per month over 4 years (2002-2006).</p> <p>Each file contains multiple variables with dimensions (time, lat, lon) at TAO locations. If joining multiple files together, concatenate along the time axis.</p> <p>-------------------------</p> <p>v 0.1.0</p> <p>cfsm501_atmo_ocn_2002_2006_TAOpoints_monthlyMeanDiurnalCycle.tgz -- contains netCDF files of monthly mean diurnal cycle of ocean and atmosphere variables: one atmosphere and one ocean file per month over 4 years (2002-2006).</p> <p>Each file contains multiple variables with dimensions (time, hour, [depth,] lat, lon) at TAO locations. The dimension "time" is of length 1 in all files. If joining multiple files together, concatenate along the time axis. The "hour" dimension represents the 24 hours of the diurnal cycle.</p> <p>Note that this version of the data has NOT had the 3-day high pass filter applied before the diurnal cycle calculation.</p>
A matter of scale: Identifying the best spatial and temporal scale of environmental variables to model the distribution of a small cetacean
<p>The importance of scale when investigating ecological patterns and processes is recognised across many species. In marine ecosystems, the processes that drive species distribution have a hierarchical structure over multiple nested spatial and temporal scales. Hence, multi-scale approaches should be considered when developing accurate distribution models to identify key habitats, particularly for populations of conservation concern. Here, we propose a modelling procedure to identify the best spatial and temporal scale for each modelled and remotely sensed oceanographic variable to model harbour porpoise (<em>Phocoena phocoena</em>) distribution. Harbour porpoise sightings were recorded during dedicated line-transect aerial surveys conducted in the summer of 2016, 2021 and 2022 in the Northeast Atlantic. Binary generalised additive models were used to assess the relationships between porpoise presence and oceanographic variables at different spatial (5, 20 and 40 km) and temporal (daily, monthly and across survey period) scales. Selected variables included sea surface temperature, thermal fronts, chlorophyll-a, sea surface height, mixed layer depth and salinity. A total of 30,514 km was covered on-effort with 216 harbour porpoise sightings recorded. Overall, the best spatial scale corresponded to the coarsest resolution considered in this study (40 km), while porpoise presence showed stronger association with oceanographic variables summarised at a longer temporal scale (monthly and averaged over survey period). Habitat models including covariates at coarse spatial and temporal scales may better reflect the processes driving availability and abundance of prey resources at the large scales covered during the surveys. These findings support the hypothesis that a multi-scale approach should be applied when investigating species distribution. Identifying suitable spatial and temporal scale would improve the functional interpretation of the underlying relationships, particularly when studying how a small marine predator interacts with its environment and responds to climate and ecosystem changes. </p>
Leveraging interindividual variability in threat conditioning of inbred mice to model trait anxiety
<p><strong>Abstact</strong></p> <p>Trait anxiety is a major risk factor for stress-induced and anxiety disorders in humans. However, animal models accounting for the inter-individual variability in stress vulnerability are largely lacking. Moreover, the pervasive bias of using mostly male animals in preclinical studies poorly reflects the increased prevalence of psychiatric disorders in women. Using the threat imminence continuum theory, we designed and validated an auditory aversive conditioning-based pipeline in both female and male mice. We operationalized trait anxiety by harnessing the naturally occurring variability of defensive freezing responses combined with a model-based clustering strategy. While sustained freezing during prolonged retrieval sessions was identified as an anxiety-endophenotype biomarker in both sexes, females were consistently associated with an increased freezing response. RNA-sequencing of CeA, BLA, ACC and BNST revealed massive differences in phasic and sustained responders’ transcriptomes, correlating with transcriptomic signatures of psychiatric disorders, particularly PTSD. Moreover, we detected significant alterations in the excitation/inhibition balance of principal neurons in the lateral amygdala. These findings provide compelling evidence that trait anxiety in inbred mice can be leveraged to develop translationally relevant preclinical models to investigate mechanisms of stress susceptibility in a sex-specific manner.</p> <p><strong>Remarks</strong></p> <p>This submission contains the analysis code and source data to fully reproduce the behavioural, electrophysiology and RNA-seq analysis described in Kovlyagina et al. </p> <p> - Navigate to the <em>behaviour_ephys</em> directory and run the scripts to reproduce the behavioural and electrophysiology analysis</p> <p>- Navigate to the <em>RNAseq</em> directory and run the script to reproduce the RNA-seq analysis</p> <p> </p>
Output files for Variable-Resolution Community Earth System Model (VR-CESM) simulations with highest resolutions over the Euro-Mediterranean
<p>Output files for Variable-Resolution Community Earth System Model (VR-CESM) simulations with highest resolutions over the Euro-Mediterranean and notebooks created for analyses and visualization.</p> <p>Configuration names:</p> <ul> <li>ne30_n</li> <li>ne30x4_n</li> <li>ne30x4_t</li> <li>ne30x8_t</li> </ul> <p>Variables at single level: PHIS,PRECC,PRECL,PS,TREFHT,LHFLX,SWCF,LWCF,TMQ,SNOWHLND</p> <p>Variables at pressure levels:U,V,OMEGA,RELHUM,Z3,Q</p>
Dataset and source code for "Explanation and optimizing multi-model blending algorithm using random variables theory"
<p>this dataset contain: </p> <ol> <li>2m temperature de-biased model forecast data on station location, ECMWF, NCEP, JP and CMA</li> <li>2m temperature observaton data, obs_t2m</li> <li>24H QPF model forecast data on station location, ECMWF, NCEP, CMA-GFS, in raw_data_r24.zip</li> <li>24H precipitation data, in raw_data_r24.zip</li> <li>source code (in python)</li> </ol> <p> </p> <p>how to use it: </p> <p>1. prepare data and python environment<br> 1.1 if you want to run [Station_FCST_MMWB.py] or [Station_FCST_MMWB_r24.py] , please download the station forecast and observation data<br> 1.2 neet meteva package to read/write micaps-3 format data: https://github.com/nmcdev/meteva<br> 1.3 need cartopy to draw picture FigS01. </p> <p>2. try the 2m temperature blending methods <optional><br> 2.1 unzip the [CMA.zip, ECMWF.zip, jp.zip, NCEP.zip, obs_t2m.zip] file into ./raw_data/<br> 2.2 run the Station_FCST_MMWB.py in python environment </p> <p>3. try the 24h QPF multi blending methods <optional><br> 3.1 unzip the [raw_data_r24.zip] file into ./raw_data_r24/<br> 3.2 run the Station_FCST_MMWB_r24.py in python environment</p> <p>4. draw figures<br> 4.1 run Fig01.py in python environment <br> 4.2 run Fig02.py in python environment <br> 4.3 run Fig03.py in python environment <br> 4.4 run FigA01.py in python environment <br> 4.5 run FigS01.py in python environment </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)
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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.