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285 results for “evolution models”
Novel modelling of ultracompact X-ray binary evolution - stable mass transfer from white dwarfs to neutron stars
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2017MNRAS.470L...6S/abstract">Novel modelling of ultracompact X-ray binary evolution - stable mass transfer from white dwarfs to neutron stars</a></p>
Modeling the early evolution of massive OB stars with an experimental wind routine. The first bi-stability jump and the angular momentum loss problem
<p>MESA run_star_extras associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2017A&A...598A...4K">Keszthelyi et al. (2017)</a>. MESA version 7624.</p> <p>Publication DOI: <a href="https://doi.org/10.1051/0004-6361/201629468">10.1051/0004-6361/201629468</a></p>
Evolution of Formal Model-based Assurance Cases for Autonomous Robots: Supplemental Material
<p>This report contains supplemental material for the paper Evolution of Formal Model-based Assurance Cases for Autonomous Robots accepted at Software Engineering and Formal Methods 2019 in Oslo. This material provides more details about the two discussed assurance case patterns, their implementation in Isabelle/SACM the instantiation of these patterns for the presented example, as well as Isabelle skripts for the theoretical part and the example.</p>
Reproduction package for the paper "The effects of surface fossil magnetic fields on massive star evolution: V. Models at low metallicity" by Keszthelyi et al. 2024
<p>This is a reproduction package for the paper "The effects of surface fossil magnetic fields on massive star evolution: V. Models at low metallicity" by <a href="https://ui.adsabs.harvard.edu/abs/2024MNRAS.tmp.1818K/abstract">Keszthelyi et al. 2024</a></p>
Model Fit Figures for: The 100 pc White Dwarf Sample in the SDSS Footprint II. A New Look at the Spectral Evolution of White Dwarfs
<p>Figures for the model atmosphere fits to the spectroscopically confirmed white dwarfs in the 100 pc sample and the SDSS footprint (<span>arXiv:2412.04611). </span></p>
Data used in "Revealing dominant patterns of aerosols regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations" (Li et al., Atmos. Chem. Phys. 2024)
<p>This dataset contains the processed EMAC simulation used as input to the clustering algorithm and the resulting regimes discussed in Li et al. (<em>Atmos. Chem. Phys.</em>, 2024).</p>
Dataset for "Climate and ice sheet evolutions from the last glacial maximum to the pre-industrial period with an ice sheet -- climate coupled model"
<p>This archive contains the source data of the figures presented in the manuscript "Climate and ice sheet evolutions from the last glacial maximum to the pre-industrial period with an ice sheet -- climate coupled model".</p> <p>Contact: aurelien.quiquet@lsce.ipsl.fr</p>
State-of-the-art evolution models for single, binary and magnetic massive stars
<p>The Universe is threaded by magnetic fields on all scales, from planetary systems to galaxy clusters. In massive stars, they play a pivotal and multifaceted role. They are thought to be crucial in transporting angular momentum throughout the stellar interior and maintaining the overall angular-momentum budget. They may also contribute to chemical mixing, can interact with convective fluid motions and may give rise to distinct seismic signatures. For example, the spin rates of white dwarfs, neutron stars and black holes are strongly determined by the coupling of a star’s core to its envelope. In this talk, I will discuss recent progress in our understanding of how magnetic fields affect single and binary stars, and what are possible origins of the different types of magnetic fields in massive stars. In particular, I will highlight connections to observations and how these can be used to further our understanding of how magnetic fields influence the evolution and final fates of stars.</p>
Analyzing disparity and rates of morphological evolution with model-based phylogenetic comparative methods
<p>Understanding variation in rates of evolution and morphological disparity is a goal of macroevolutionary research. In a phylogenetic comparative methods framework, we present three explicit models for linking the rate of evolution of a trait to the state of another evolving trait. This allows testing hypotheses about causal influences on rates of phenotypic evolution with phylogenetic comparative data. We develop a statistical framework for fitting the models with generalized least-squares regression, and use this to discuss issues and limitations in the study of rates of evolution more generally. We show that the power to detect effects on rates of evolution is low in that even strong causal effects are unlikely to explain more than a few percent of observed variance in disparity. We illustrate the models and issues by testing if rates of beak-shape evolution in birds are influenced by brain size, as may be predicted from a Baldwin effect in which presumptively more behaviorally flexible large-brained species generate more novel selection on themselves leading to higher rates of evolution. From an analysis of morphometric data for 645 species we find evidence that both macro- and microevolution of the beak are faster in birds with larger brains, but with the caveat that there are no consistent effects of relative brain size.</p>
A semi-empirical model of radiolytic gas bubble formation and evolution during criticality excursions in uranyl nitrate solutions for nuclear criticality safety assessment
<p>Raw data used to construct the figures found in the journal paper "A semi-empirical model of radiolytic gas bubble formation and evolution during criticality excursions in uranyl nitrate solutions for nuclear criticality safety assessment".</p>
Code for the population genetic models of the evolution of preference strength
<p>Sexual selection has a rich history of mathematical models that consider why preferences favor one trait phenotype over another (for population genetic models) or what specific trait value is preferred (for quantitative genetic models). Less common is exploration of the evolution of choosiness or preference strength: that is, by how much a trait is preferred. We examine both population and quantitative genetic models of the evolution of preferences, specifically developing "baseline models" of the evolution of preference strength during the Fisher process. Using a population genetic approach based on the classic model of Kirkpatrick (1982), we find selection for stronger and stronger preferences when trait variation is maintained by mutation. However, this force is quite weak and likely to be swamped by drift in moderately-sized populations. In a quantitative genetic model based on Lande (1981), unimodal preferences will generally not evolve to be increasingly strong without bounds when male traits are under stabilizing viability selection, but evolve to extreme values when viability selection is directional. Our results highlight that different shapes of fitness and preference functions lead to qualitatively different trajectories for preference strength evolution ranging from no evolution to extreme evolution of preference strength.</p>
Data from: Modeling the evolution of rates of continuous trait evolution
<p>Rates of phenotypic evolution vary markedly across the tree of life, from the accelerated evolution apparent in adaptive radiations to the remarkable evolutionary stasis exhibited by so-called "living fossils". Such rate variation has important consequences for large-scale evolutionary dynamics, generating vast disparities in phenotypic diversity across space, time, and taxa. Despite this, most methods for estimating trait evolution rates assume rates vary deterministically with respect to some variable of interest or change infrequently during a clade's history. These assumptions may cause underfitting of trait evolution models and mislead hypothesis testing. Here, we develop a new trait evolution model that allows rates to vary gradually and stochastically across a clade. Further, we extend this model to accommodate generally decreasing or increasing rates over time, allowing for flexible modeling of "early/late bursts" of trait evolution. We implement a Bayesian method, termed "evolving rates" (evorates for short), to efficiently fit this model to comparative data. Through simulation, we demonstrate that evorates can reliably infer both how and in which lineages trait evolution rates varied during a clade's history. We apply this method to body size evolution in cetaceans, recovering substantial support for an overall slowdown in body size evolution over time with recent bursts among some oceanic dolphins and relative stasis among beaked whales of the genus Mesoplodon. These results unify and expand on previous research, demonstrating the empirical utility of evorates.</p>
The Cauchy Process on phylogenies: a tractable model for pulsed evolution
<p>Phylogenetic comparative methods use random processes, such as the Brownian Motion, to model the evolution of continuous traits on phylogenetic trees. Growing evidence for non-gradual evolution motivated the development of complex models, often based on Lévy processes. However, their statistical inference is computationally intensive and currently relies on approximations, high dimensional sampling, or numerical integration. We consider here the Cauchy Process (CP), a particular pure-jump Lévy process in which the trait increment along each branch follows a centered Cauchy distribution with a dispersion proportional to its length. In this work, we derive an exact algorithm to compute both the joint probability density of the tip trait values of a phylogeny under a CP and the ancestral trait values and branch increments posterior densities in quadratic time. A simulation study shows that the CP generates patterns in comparative data that are distinct from any Gaussian process and that Restricted Maximum Likelihood (REML) parameter estimates and root trait reconstruction are unbiased and accurate for trees with 200 tips or less. The CP has only two parameters but is rich enough to capture complex pulsed evolution. It can reconstruct posterior ancestral trait distributions that are multimodal, reflecting the uncertainty associated with the inference of the evolutionary history of a trait from extant taxa only. Applied to empirical datasets taken from the Evolutionary Ecology and Virology literature, the CP suggests nuanced scenarios for the body size evolution of Greater Antilles Lizards and for the geographical spread of the West Nile Virus epidemics in North America, both consistent with previous studies using more complex models. The method is efficiently implemented in C with an R interface in package cauphy, which is open source and freely available online.</p>
Graph models underlying templates for annotating a study in ecology and evolution
<p><em>Schematic representation of the graph models, resources and links to ontologies underlying a set of templates designed to annotate studies in invasion biology, and more generally ecology or evolution. The main template is the “General scoping” template, while each other box would allow a more detailed description of Dataset, Study system, Study design, and research question and hypotheses in Invasion biology. This figure was presented during the <a href="https://hiknowledgeworkshops.com/workshop-2/">June 2023 workshop of the Hi Knowledge initiative</a>. </em></p>
A test of the Grant-Stebbins pollinator shift model of floral evolution
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Quality-quantity tradeoffs drive functional trait evolution in a model microalgal “climate change winner”
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Finite element models from: Mechanical compensation in the evolution of the early hominin feeding apparatus
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Functional evolution of antibody Fc domains: SAXS plots and models
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Evolution towards increasing complexity through functional diversification in a protocell model of the RNA world
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Data from: Modeling the evolution of rates of continuous trait evolution
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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.