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48 results for “analytic modelling”
Analytic dataset informing modeling of winter species distributions of North American bat species
<p>The fungal pathogen <i>Pseudogymnoascus destructans</i> and resultant white-nose syndrome (WNS) continues to advance across North America, infecting new bat populations, species, and hibernacula. Western North America hosts the highest bat diversity in the U.S. and Canada, yet little is known about hibernacula and hibernation behavior in this region. An improved understanding of where bats hibernate and the conditions that create suitable hibernacula is critical if land managers are to anticipate and address the conservation needs of WNS-susceptible species in regions yet to be infected. We estimated suitability of potential winter hibernaculum sites across the ranges of five bat species occurring in western North America. We estimated winter survival capacity from a mechanistic survivorship model based on bat bioenergetics and climate conditions. Leveraging the Google Earth Engine platform for spatial data processing, we used boosted regression trees to relate these estimates, along with key landscape attributes, to bat occurrence data in a hybrid correlative-mechanistic approach. Winter survival capacity, topography, land cover, and access to caves and mines were important predictors of winter hibernaculum selection, but the shape and relative importance of these relationships varied among species. This suggests that the occurrence of bat hibernacula can, in part, be predicted from readily mapped above-ground features, and is not only dictated by below-ground characteristics for which spatial data are lacking. Furthermore, our mechanistic estimate of winter survivorship was, on average, the third strongest predictor of winter occurrence probability across focal species. Winter distributions of North American bat species were driven by their physiological capacity to survive winter conditions and duration in a given location, as well as selection for topographic and other landscape features, but in species-specific ways. The influence of winter survivorship on several species' distributions, the underlying influence of climate conditions on winter survivorship, and the anticipated influence of WNS on bats' hibernation physiology and survivorship together suggest that North American bat distributions may undergo future shifts as these species are exposed to not only WNS, but climate change. We anticipate that the models presented here may offer a valuable baseline for assessing the potential species-level impacts of these stressors.</p>
Parameter estimation and identifiability analysis for a bivalent analyte model of monoclonal antibody-antigen binding
<p>Data for non-regenerative bivalent analyte binding interaction between CH505 transmitted founder gp120 and CH31 monoclonal antibody, an HIV-1 mAb with CD4-binding site specificity.</p> <p>This data set is submitted as part of the manuscript titled "Parameter estimation and identifiability analysis for a bivalent analyte model of monoclonal antibody-antigen binding"</p>
Models and data for "Guaranteed safe controller synthesis for switched systems using analytical solutions"
<p>Models and data for the paper "Guaranteed safe controller synthesis for switched systems using analytical solutions" presented at the 7th IEEE Conference on Control Technology and Applications, Barbados, August 16-18, 2023.</p> <p> </p>
Analytic dataset informing modeling of winter species distributions of North American bat species
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Data supplement for: Agreement of analytical and simulation-based estimates of the required land depth in climate models
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Semi-analytical modeling of rate-dependent relative permeability in heterogeneous formations
<p>Numerical codes and results for MS: Semi-analytical modeling of rate-dependent relative permeability in heterogeneous formations</p>
Data from: A new analytical approach to landscape genetic modeling: least-cost transect analysis and linear mixed models
Landscape genetics aims to assess the effect of the landscape on intraspecific genetic structure. To quantify interdeme landscape structure, landscape genetics mostly uses landscape resistance surfaces and least-cost paths or straight-line transects. However, both approaches have drawbacks. Parameterization of resistance surfaces is a subjective process, and least-cost paths represent a single migration route. A transect-based approach might oversimplify migration patterns by assuming rectilinear migration. To overcome these limitations, we combined these two methods in a new landscape genetic approach: least-cost transect analysis (LCTA). Habitat-matrix resistance surfaces were used to create least-cost paths, which were subsequently buffered to form transects in which the abundance of several landscape elements was quantified. To maintain objectivity, this analysis was repeated so that each landscape element was in turn regarded as migration habitat. The relationship between landscape predictor variables and genetic distances was then assessed following a mixed modeling approach to account for the non-independence of values in distance matrices. Subsequently, predictor variables were selected making use of the R_β^2 statistic. We applied LCTA and the mixed model approach to an empirical genetic dataset on the endangered damselfly, Coenagrion mercuriale. We compared the results to those obtained from traditional least-cost, effective and resistance distance analysis and showed that LCTA not only outperforms existing methods in a statistical way, but also provides more information about the migration ecology of the focal species. Although we believe the statistical approach to be an improvement for the analysis of distance matrices in landscape genetics, more stringent testing is needed.
Assessing the fate and behaviour of plant nutrients in aquaponic systems by chemical equilibrium modelling: A meta-analytical approach
<p>Cleaned dataset and Visual MINTEQ input files (without and without assumed presence of dissolved organic matter) for each record in the dataset.</p>
Data and Codes of the Research 《An Analytical Spectral Model for Infragravity Waves over Topography in Intermediate and Shallow Water》
<p>This is the dataset and codes prepared for the submission of the research in the title.</p> <p>Please run the script Main.m directly after unzipping the package. For a detailed guidance of how to use it, please see the Guide.html in the UserGuide folder.</p>
OA eBook Usage Data Analytics Reporting Service Business Model Canvas
<p>This initial business model canvas was created to inform technical and governance roadmap discussions pertaining to the dashboard and analytics elements of the <em>Developing a Data Trust for Open Access Ebook Usage</em> project. </p>
Modeling the Organic Carbon Oxidation and Redox Sequence under the Partial- Equilibrium Approach: a Discussion by means of a Semi-Analytical Solution
<p>Filename: Analytical_solution.xls<br> File format: Excel<br> Description: It contains the calculation of the analytical model, programmed by means of excel. The sheet "advection" contains the calculation of the advection model and the sheet "diffusion" that of the diffusion model. The sheet "Phreeqc results" contains the results of the Phreeqc batch model (see Batch.pqi). Input data are highlighted in yellow.</p> <p>Filename: Batch.pqi<br> File format: Phreeqc<br> Description: It contains the input file for the calculation of the batch model by Phreeqc. It requires the Phreeqc database file Phreeqc.dat</p> <p>Filename: PEA_om_adv.pqi<br> File format: Phreeqc<br> Description: It contains the input file for the numerical calculation of the advection model by Phreeqc using the PEA (Partial Equilibrium Assumption). It requires the Phreeqc database file Phreeqc.dat</p> <p>Filename: PEA_om_dif.pqi<br> File format: Phreeqc<br> Description: It contains the input file for the numerical calculation of the diffusion model by Phreeqc using the PEA (Partial Equilibrium Assumption). It requires the Phreeqc database file Phreeqc.dat</p> <p>Filename: KIN_om_adv.pqi<br> File format: Phreeqc<br> Description: It contains the input file for the numerical calculation of the advection model by Phreeqc using the fully kinetic approach. It requires the Phreeqc database file PhreeqcKIN.dat</p> <p>Filename: KIN_om_dif.pqi<br> File format: Phreeqc<br> Description: It contains the input file for the numerical calculation of the diffusion model by Phreeqc using the fully kinetic approach. It requires the Phreeqc database file PhreeqcKIN.dat</p> <p>Filename: phreeqc.dat<br> File format: Phreeqc database<br> Description: It contains thermodynamic data for the batch model (see Batch.pqi) and the PEA models (see PEA_om_adv.pqi and PEA_om_dif.pqi). It is the default thermodynamic database of Phreeqc, dat), from which we removed ammonium to avoid the unrealistic reduction of NO3- and N2 to NH4+</p> <p>Filename: phreeqcKIN.dat<br> File format: Phreeqc database<br> Description: It contains thermodynamic data for the fully kinetic models (see KIN_om_adv.pqi and KIN_om_dif.pqi). It is the default thermodynamic database of Phreeqc, dat), from which we removed the relevant equilibrium redox reaction, so that they can be treated kinetically.</p> <p> </p> <p> </p>
an analytical switching model of SiC MOSFET
<p>An analytical switching model of SiC MOSFET considering the junction temperature characteristics, built in MATLAB.</p>
35 Years of the Technology Acceptance Model: Insights from Meta-analytic Structural Equation Modelling
<p>The data files are scripts for R software.</p>
Analytical Hall Thruster Model
<p>Datasets correspond to theoretical model results and experimental data from the research paper:</p> <p>T. Lafleur and P. Chabert, "Analytical Hall Thruster Model", under review (2024).</p> <p>In each file, sheet names correspond to the respective figures in the paper above. Each column in the datasets is labelled and corresponds to a specific variable which is displayed in the figures. In the dataset named "Experimental_Data.xlsx", data has been taken from the following references:</p> <ul> <li>J. Adam, J.-P. Boeuf, N. Dubuit, M. Dudeck, L. Garrigues, D. Gresillon, A. Heron, G. Hagelaar, V. Kulaev, N. Lemoine, et al., "Physics, simulation and diagnostics of hall effect thrusters", Plasma Physics and Controlled Fusion 50, 124041 (2008).</li> <li>J. M. Sankovic, J. A. Hamley, and T. W. Haag, "Performance evaluation of the russian spt-100 thruster at nasa lerc", in IEPC Conference, IEPC-93-094 (1994).</li> </ul>
Matlab code for 'Analytical model for the out-of-plane response of vertically spanning unreinforced masonry walls'
<p>This repository contains the Matlab scripts needed to reproduce the results shown in the article:</p> <blockquote> <p>Godio M, Beyer K. Analytical model for the out-of-plane response of vertically-spanning unreinforced masonry walls. Earthquake Engng Struct Dyn. 2017;46:2757-2776. <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/eqe.2929">DOI:10.1002/eqe.2929</a></p> </blockquote> <p>Version history:<br> V1: Matlab code needed to reproduce the plots of Figure 4 of the article is added<br> V2: content PDF-file is added</p>
A semi-analytical interpretation model of pulse decay measurement on ultra-tight rocks
<p>This contribution presents a new semi-analytical model for the evaluation of the initial (early time) stage of pulse decay permeability tests, i.e. before reaching quasi-steady state flow conditions and prior to a significant pressure increase in the downstream reservoir. The analytical model considers gas compressibility and slippage effects. In order to validate the proposed method, measurements were performed on a core sample of the Cretaceous Eagle Ford shale, Texas, USA, under different pore and confining pressures. Helium was used as the test fluid to minimize effects from adsorption. Permeability coefficients obtained from this new approach agree well with those from the classical pulse decay evaluation while the duration of tests was reduced from hours to minutes. The present model is a good supplement for the pulse decay method and suitable for measurements of ultra-low-permeability rocks.</p>
Computational modeling and analytical validation of singular geometric effects in fault data using a combinatorial approach - Input and processed data
<p>The archive contains the input and processed data for the companion manuscript.</p> <p>The input data contains XYZ coordinates of points documenting the investigated interfaces. The output datasets contain directional data from applying the combinatorial algorithm to point data sets.</p> <p>We have also included .VTU and .PVSM files for visualization of the geological settings in ParaView.</p>
RDF models and SPARQL queries for decoupled analytics demonstration
<p>This directory contains the following:</p> <p>- Two sets of RDF triples using different ontologies, modeling the same "MZVAV-2" air handling unit from the data inventory by Granderson et al. [1].</p> <p>- SPARQL queries for retrieving inputs to APAR [2] rules.</p> <p>- SPARQL queries for discovering "data links" from the models, connecting data points to time series providers.</p> <p>The models were created by manually writing the triples. For details, see included README.md</p> <p> </p> <p>[1] J. Granderson, G. Lin, A. Harding, P. Im, Y. Chen, Building fault detection data to aid diagnostic algorithm creation and performance testing, Scientific Data. 7 (2020) 65. https://doi.org/10.1038/s41597-020-0398-6.</p> <p>[2] J.M. House, H. Vaezi-Nejad, J.M. Whitcomb, An expert rule set for fault detection in air-handling units, ASHRAE Transactions. 107 (2001) 858–871.</p>
Data from: A new analytical approach to landscape genetic modeling: least-cost transect analysis and linear mixed models
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Data from: The evolution of marine larval dispersal kernels in spatially structured habitats: analytical models, individual-based simulations, and comparisons with empirical estimates
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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.