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93 results for “Assumption”
Data for: Klein et al., Viscosity of aqueous ammonium nitrate--organic particles: Equilibrium partitioning may be a reasonable assumption for most tropospheric conditions, egusphere-2024-1459
<p><strong>Experimental data </strong></p> <p>This folder contains the experimental and modelled data to the figures shown in the main manuscript and Appendix.</p> <p>Figure 3B AIOMFAC-VISC (AIOMFAC-VISC modelling of sucrose)</p> <p>Figure 3B Experimental (Viscosity measurements of sucrose)</p> <p>Figure 4 (Viscosity measurements of ammonium nitrate - sucrose - water mixtures)</p> <p>Figure 5 A and C (Viscosity estimations of ammonium nitrate - sucrose - water mixtures using mixing rules)</p> <p>Figure 5 B and D (Viscosity estimations of ammonium nitrate - sucrose - water mixtures using AIOMFAC-VISC)</p> <p>Figure 6 (Viscosity estimations of inorganic - sucrose - water mixtures using mixing rules)</p> <p>Figure 7 (Mixing times for ammonium nitrate - sucrose - water and Toluene SOA - sucrose - water aerosol particles for varies cities) </p> <p>Figure A2 (Viscosity estimations of ammonium nitrate - sucrose - water mixtures using a mass fraction based mixing rules)</p>
Global Macroeconomic Scenarios of the COVID-19 Pandemic: Epidemiological Assumptions
<p>Epidemiological Assumptions used for modelling the Global Macroeconomic Scenarios of the COVID-19 Pandemic</p>
Dataset - The influence of the crowding assumptions in biofilm simulations
<p><strong>Dataset simulated for the manuscript "The influence of the crowding assumptions in biofilm simulations" by Angeles-Martinez and Hatzimanikatis.</strong></p>
Test Collection Reliability: A Study of Bias and Robustness to Statistical Assumptions via Stochastic Simulation
<p>This archive contains the simulated collections, their diagnosis data, and the estimates of accuracy. For the full code and description, please refer to https://github.com/julian-urbano/irj2015-reliability</p>
The Impact of an Open Water Balance Assumption on Understanding the Factors Controlling the Long-term Streamflow Components
<p>The excel file <em>Attributes_manuscript.csv</em> contains the mean annual variables and the catchments' attributes used in the manuscript: "<strong>The Impact of an Open Water Balance Assumption on Understanding the Factors Controlling the Long-term Streamflow Components</strong>". Details of each attributes are indicated in the .txt file <em>Attributes_description.txt</em>.</p>
Data from: Skyline fossilized birth-death model is robust to violations of sampling assumptions in total-evidence dating
<p>Several total-evidence dating studies under the fossilized birth-death (FBD) model have produced very old age estimates, which are not supported by the fossil record. This phenomenon has been termed "deep root attraction (DRA)". For two specific datasets, involving divergence time estimation for the early radiations of ants, bees and wasps (Hymenoptera) and of placental mammals (Eutheria), it has been shown that the DRA effect can be greatly reduced by accommodating the fact that extant species in these trees have been sampled to maximize diversity, so called diversified sampling. Unfortunately, current methods to accommodate diversified sampling only consider the extreme case where it is possible to identify a cut-off time such that all splits occurring before this time are represented in the sampled tree but none of the younger splits. In reality, the sampling bias is rarely this extreme, and may be difficult to model properly. Similar modeling challenges apply to the sampling of the fossil record. This raises the question of whether it is possible to find dating methods that are more robust to sampling biases. Here, we show that the skyline FBD (SFBD) process, where the diversification and fossil-sampling rates can vary over time in a piecewise fashion, provides age estimates that are more robust to inadequacies in the modeling of the sampling process and less sensitive to DRA effects. In the SFBD model we consider, rates in different time intervals are either considered to be independent and identically distributed, or assumed to be autocorrelated following an Ornstein-Uhlenbeck (OU) process. Through simulations and reanalyses of the Hymenoptera and Eutheria data, we show that both variants of the SFBD model unify age estimates under random and diversified sampling assumptions. The SFBD model can resolve DRA by absorbing the deviations from the sampling assumptions into the inferred dynamics of the diversification process over time. Although this means that the inferred diversification dynamics must be interpreted with caution, taking sampling biases into account, we conclude that the SFBD model represents the most robust approach available currently for addressing DRA in total-evidence dating.</p>
Modelling assumptions and input dataset for the case study of the paper "Societal Effects of Large-Scale Energy Storage in the Current and Future Day-Ahead Market: A Belgian Case Study"
<p>This data package includes the modelling assumptions and input data to replicate the results of the case study included in the paper "Societal Effects of Large-Scale Energy Storage in the Current and Future Day-Ahead Market: A Belgian Case Study". This paper is part of the 18th International Conference on the European Energy Market (EEM22).</p> <p>The case study models the Belgian day-ahead electricity market, in which the existing storage is considered, in addition to large-scale battery energy storage systems of different sizes for varying renewable energy shares. A detailed description of the case study is provided in the readme file. </p> <p>This supplementary data package includes the following files: </p> <p> --Belgium Model Input Data.xlsx: Dataset used as input in the case study of the mentioned paper<br> --Modelling Assumptions.pdf: Modelling assumptions considered in the case study<br> --readme.txt (this file): Includes a detailed description of the data package</p> <p> </p> <p>The data included in this dataset was collected from public open sources [1]-[2]. Please notice that this dataset does not replace the original open access information. For accessing the data, please visit the following websites:</p> <p>[1] “ENTSO-E Transparency Platform.” [Online]. Available: https://transparency.entsoe.eu/dashboard/show. [Accessed: 06-Jul-2022].<br> [2] “Grid data.” [Online]. Available: https://www.elia.be/en/grid-data. [Accessed: 06-Jul-2022].</p> <p><br> </p> <p> </p>
Supplementary material and supplementary data files for: Handling logical character dependency in phylogenetic inference: Extensive performance testing of assumptions and solutions using simulated and empirical data
<p>Logical character dependency is a major conceptual and methodological problem in phylogenetic inference of morphological datasets, as it violates the assumption of character independence that is common to all phylogenetic methods. It is more frequently observed in higher-level phylogenies or in datasets characterizing major evolutionary transitions, as these represent parts of the tree of life where (primary) anatomical characters either originate or disappear entirely. As a result, secondary traits related to these primary characters become "inapplicable" across all sampled taxa in which that character is absent. Various solutions have been explored over the last three decades to handle character dependency, such as alternative character coding schemes and, more recently, new algorithmic implementations. However, the accuracy of the proposed solutions, or the impact of character dependency across distinct optimality criteria, has never been directly tested using standard performance measures. Here, we utilize simple and complex simulated morphological datasets analyzed under different maximum parsimony optimization procedures and Bayesian inference to test the accuracy of various coding and algorithmic solutions to character dependency. This is complemented by empirical analyses using a recoded dataset on palaeognathid birds. We find that in small, simulated datasets, absent coding performs better than other popular coding strategies available (contingent and multistate), whereas in more complex simulations (larger datasets controlled for different tree structure and character distribution models) contingent coding is favored more frequently. Under contingent coding, a recently proposed weighting algorithm produces the most accurate results for maximum parsimony. However, Bayesian inference outperforms all parsimony-based solutions to handle character dependency due to fundamental differences in their optimization procedures—a simple alternative that has been long overlooked. Yet, we show that the more primary characters bearing secondary (dependent) traits there are in a dataset, the harder it is to estimate the true phylogenetic tree, regardless of the optimality criterion, owing to a considerable expansion of the tree parameter space.</p>
Experimental data for Distributed parametric model checking timed automata under non-Zenoness assumption
<p>This is the experimental data mentioned in the paper "Distributed parametric model checking timed automata under non-Zenoness assumption", published in FMSD (Formal Methods in System Design), 2022.</p> <p>Experiments were conducted using the distributed version of IMITATOR 2.9.2 (Butter Incaberry) on two Intel Xeon Silver 4114 at 2.2GHz (20 cores in total), and 96GiB of memory, running under Ubuntu 16.04 LTS 64-bit.</p>
Deep learning models challenge the prevailing assumption that face-like effects for objects of expertise support domain-general mechanisms
<p>The question of whether perceptual expertise is mediated by general-expert or domain-specific processing mechanisms has been debated for decades. Because humans are experts in face recognition, face-like neural and cognitive effects for objects of expertise were considered to support for the general-expertise hypothesis. Conversely, stronger effects for faces than objects of expertise were considered to support the domain-specific hypothesis. However, the effects of domain, experience, and level of categorization, are confounded in human studies, which may lead to erroneous inferences. To overcome these limitations, we used computational models of perceptual expertise and tested different domains (objects, faces, birds) and levels of categorization (basic, sub-ordinate, individual) in isolation, matched for amount of experience. Like humans, the models generated a larger inversion effect for faces than for objects. Importantly, a face-like inversion effect was found for individual-based categorization of non-faces (birds) but only in a network specialized for that domain. Thus, contrary to prevalent assumptions, face-like effects in objects of expertise may originate from domain-specific rather than domain-general processing mechanisms. More generally, we show how deep learning algorithms can be used to isolate the effects of factors that are inherently confounded in the natural environment of biological organisms.</p>
Deep learning models challenge the prevailing assumption that face-like effects for objects of expertise support domain-general mechanisms
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Data from: Skyline fossilized birth-death model is robust to violations of sampling assumptions in total-evidence dating
Open the record for dataset details and reuse information.
Supplementary material and supplementary data files for: Handling logical character dependency in phylogenetic inference: Extensive performance testing of assumptions and solutions using simulated and empirical data
Open the record for dataset details and reuse information.
Data from: Are skyline plot-based demographic estimates overly dependent on smoothing prior assumptions?
<p>In Bayesian phylogenetics, the coalescent process provides an informative framework for inferring changes in the effective size of a population from a phylogeny (or tree) of sequences sampled from that population. Popular coalescent inference approaches such as the Bayesian Skyline Plot, Skyride and Skygrid all model these population size changes with a discontinuous, piecewise-constant function but then apply a smoothing prior to ensure that their posterior population size estimates transition gradually with time. These prior distributions implicitly encode extra population size information that is not available from the observed coalescent data i.e. the tree. Here we present a novel statistic, Ω, to quantify and disaggregate the relative contributions of the coalescent data and prior assumptions to the resulting posterior estimate precision. Our statistic also measures the additional mutual information introduced by such priors. Using Ω we show that, because it is surprisingly easy to over-parametrise piecewise-constant population models, common smoothing priors can lead to overconfident and potentially misleading inference, even under robust experimental designs. We propose Ω as a useful tool for detecting when posterior estimate precision is overly reliant on prior choices.</p>
Our Lady of The Assumption, Bethnal Green E2
Catholic Church, Our Lady of The Assumption in Bethnal Green. Priory entry. Test scan captured with Phab2 Pro and Google Constructor Developer Tool (Project Tango). Source: Objaverse 1.0 / Sketchfab
Data for testing the assumption of fractal scaling in canopy surfaces across a diverse range of forest types
<p>This is a collection of scripts and research data for a study on whether canopy surfaces follow fractal scaling laws across a diverse range of forest types. The article citation is: <span>Fischer, F. J.</span>, & <span>Jucker, T.</span> (<span>2024</span>). <span>No evidence for fractal scaling in canopy surfaces across a diverse range of forest types</span>. <em>Journal of Ecology</em>, <span>112</span>, <span>470</span>–<span>486</span>. <a href="https://doi.org/10.1111/1365-2745.14244">https://doi.org/10.1111/1365-2745.14244</a>.</p> <p>As data, we use canopy height models (CHMs) from 9 Australian research sites belonging to the Terrestrial Ecosystem Research Network (TERN). Their extent is 5 km x 5 km throughout. The underlying data can be found here: https://portal.tern.org.au/metadata/TERN/4ff0b4c9-cfa0-4d09-9520-b5402adc583f. Climatic data are extracted from the CHELSA climatology 1981-2010 (Brun et al. 2022: Global climate-related predictors at kilometer resolution for the past and future. Earth System Science Data, 14(12), 5573–5603. https://doi.org/10.5194/essd-14-5573-2022; Karger et al. 2017: Climatologies at high resolution for the earth's land surface areas. Scientific Data, 4(1), 170122. https://doi.org/10.1038/sdata.2017.122).</p> <p>Each uploaded zip-file corresponds to a folder within a common repository. To reproduce our analysis, unpack into the same folder, upholding naming conventions and overall structure. Please note that some parts of the analysis require external software, e.g., GRASS GIS for the generation of simulated fractal surfaces. Paths need to be reset accordingly. </p> <p><strong>rscripts.zip:</strong> </p> <ul> <li>the overall R script ("areforestsfractals_v3.R") used to generate fractal surfaces, calculate fractal statistics from CHMs and simulated surfaces, and to carry out the analysis</li> <li>various summary statistics saved both as RData and csv files</li> </ul> <p><strong>TERN.zip:</strong></p> <ul> <li>data within this folder are ordered by site name</li> <li>for each site, we include several CHMs, their corresponding DSMs (digital surface models) and DTMs (digital terrain models), as well as ancillary layers (pulse densities of laser scans)</li> <li>for each site and each CHM/DSM, we also save the fractal scaling properties in separate csv files</li> </ul> <p><strong>TERNtrees.zip:</strong></p> <ul> <li>data within this folder are ordered by site name</li> <li>for each site, we include manual delineations of the largest trees per 1 km x 1 km square (25 in total)</li> <li>for each site, we include subplots of the CHM (200 m x 200 m) centred around the largest tree</li> </ul> <p><strong>climate.zip:</strong></p> <ul> <li>climate layers from CHELSA for precipitation and site water balance</li> </ul> <p><strong>terrain_fractal.zip:</strong></p> <ul> <li>simulated fractal surfaces, based on different generating algorithms</li> <li>fractal scaling properties of simulated fractal surfaces in separate csv files</li> </ul> <p><strong>sites_coordinates.csv</strong></p> <ul> <li>lon/lat coordinates of each site</li> </ul> <p> </p> <p> </p>
LNT Model is not an "Assumption": Re-Analysis of Epidemiological Data Empirically Supports LNT
<p><em>Introduction:</em> In “Keeping ICRP Recommendations Fit for Purpose”[1], LNT model is described as “LNT is the most appropriate evidence-based assumption to use for radiological protection purposes (p.10).” According to our critical literature survey on radiological epidemiology[2], some limitations were identified: (1) aggregation of individual level data, (2) model formulation, (3) model estimation, (4) model selection, (5) results interpretation. In this paper we focus (4) model selection and demonstrate LNT was the best model.</p> <p><em>Data and Method:</em> Using “Life Span Study Report 14. Cancer and non-cancer disease mortality data, 1950-2003 [3]”, solid cancer mortality was re-analyzed. In addition to the L, Q, LQ, hadn searched threshold model, kinked–at-2Gy model that assumes LQ for less than 2Gy and L for larger than 2 Gy, and Linear model with threshold as a parameter were estimated. Following [3], Poisson regression model was applied and model fit was compared with AIC and BIC.</p> <p><em>Results</em>: Among estimated models, Linear (BIC=18317.9) and grid search threshold at 20mSv (BIC=18318.1) was selected as the best models. Directly estimated threshold was -23.2 mSv and it was statistically insignificant (z=-0.087,p>0.1). Model fit of kinked-at-2Gy was poorer than these models (BIC=18321.2).</p> <p><em>Conclusion:</em> Based on these results, we can conclude LNT model is the best model for a-bomb survivor solid cancer mortality. According to our literature survey, LNT is supported Description of LNT model in “Keeping ICRP Recommendations Fit for Purpose” should be modified accordingly: “LNT is the scientifically supported model, it is reasonable LNT to use for radiological protection purposes.”</p>
Impact of model assumptions on the inference of the evolution of ectomycorrhizal symbiosis in fungi
<p>Ectomycorrhiza (ECM) is a symbiotic relation between plant and fungi that is essential for nutrient uptake of many stand forming trees. There are two conflicting views about the evolution of ECM in fungi suggesting (1) relatively few transitions to ECM followed by reversals to non-ECM, or (2) many independent origins of ECM and no reversals. In this study, we compare these, and other, hypotheses and test the impact of different models on inference. We assembled a dataset of five marker gene sequences (nuc58, nucLSU, nucSSU, rpb1, and rpb2) and 2,174 fungal taxa covering the three subphyla: Agaricomycotina, Mucoromycotina and Pezizomycotina. The fit of different models, including models with variable rates in clades or through time, to the pattern of ECM fungal taxa was tested in a Bayesian framework, and using AIC and simulations. We find that models implementing variable rates are a better fit than models without rate shift, and that the conclusion about the relative rate between ECM and non-ECM depend largely on whether rate shifts are allowed or not. We conclude that standard constant-rate ancestral state reconstruction models are not adequate for the analysis of the evolution of ECM fungi, and may give contradictory results to more extensive analyses. </p>
Additional Figures for winning models for sample in A Comparative L-dwarf Sample Exploring the Interplay Between Atmospheric Assumptions and Data Properties
<p>Additional Figures for winning models for sample in <em>A Comparative L-dwarf Sample Exploring the Interplay Between Atmospheric Assumptions and Data Properties (<a href="https://arxiv.org/pdf/2209.02754.pdf">https://arxiv.org/pdf/2209.02754.pdf</a>).</em></p> <p>Model naming key: NC = cloud-free, d2_89 = power-law deck cloud</p> <p>SDSS J1416+1348A: Winning model: power-law deck cloud</p> <p>Spectral Type Comparison J1526+2043 Winning model: Cloud-free</p> <p>Temperature Comparisons</p> <p>J1539-0520 Winning model: Power-law deck cloud and cloud-free tied.</p> <p>J0539-0059 Winning model: Power-law deck cloud and cloud-free tied. </p> <p><br> </p>
Testing the assumption of environmental equilibrium in an invasive plant species over a 130 year history
Invasive plants are an increasing threat to global biodiversity. Effective management depends on accurate predictions of their spread. However, modelling the geographic distribution of invasive species, particularly with correlative species distribution models (SDMs), is challenging. SDMs assume that species are in equilibrium with their environment (i.e., they occur in all suitable environments); this assumption is likely to be violated for a species that is actively invading new environments. This assumption is rarely assessed, and when violated can have consequences for model reliability. Using the invasive vine Vincetoxicum rossicum, we tested the hypotheses that: 1) invasive species' distribution in environmental and geographic space increase to a plateau over time; 2) this plateau is a useful proxy for equilibrium distribution, a key assumption underlying SDMs. We compare V. rossicum's expansion in environmental and geographic space between historical and current time periods and infer equilibrium when its distribution has remained stable for an extended period. We also compare the performance of SDMs from historical time periods in predicting the current geographic distribution of V. rossicum. We found that V. rossicum has reached equilibrium in environmental space, but is still expanding its geographic distribution. SDM performance was poor in the first 30 years following introduction, but improved as V. rossicum approached environmental equilibrium. Our findings demonstrate the power of including temporal dynamics and the need to consider environmental and geographic equilibrium separately when modelling the distribution of invasive species. In light of our findings, we address shortcomings of the current approach to defining an equilibrium distribution and present a new perspective for reconciling the potentially confounding influence of dispersal limitation when assessing equilibrium distribution.
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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.