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1,600 results for “input”
Model configuration and input files for: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea"
<p>This collection hosts the configuration and input files to reproduce the regional CESM/MOM6 simulation in: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea". <br><br>The initial, open boundary conditions and monthly means for the sponge layers were generated from the GLORYS12V1 reanalysis: <a href="https://doi.org/10.3389/feart.2021.698876">https://doi.org/10.3389/feart.2021.698876</a></p> <p>The tidal amplitudes and phases were generated from the TPXO model: <a href="https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2">https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2 </a></p> <p>The monthly Chlorophyll-a climatology was generated from the SeaWifs mission dataset: <a href="10.5067/ORBVIEW-2/SEAWIFS/L3M/CHL/2018">10.5067/ORBVIEW-2/SEAWIFS/L3M/CHL/2018</a></p> <p>The river runoff to ocean was generated from the GloFAS dataset: <a href="https://doi.org/10.24381/cds.a4fdd6b9">https://doi.org/10.24381/cds.a4fdd6b9 </a></p> <p>The topography was generated from the Shuttle Radar Topography Mission: <a href="https://doi.org/10.1029/2019EA000658">https://doi.org/10.1029/2019EA000658</a> and smoothed with a Cressman weighted interpolation scheme.</p> <p>This collection does not include the JRA55-do atmospheric forcing dataset: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.ocemod.2018.07.002" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ocemod.2018.07.002</a> </p> <p>Steps to setup a regional configuration of CESM/MOM6 can be found here: <a href="https://github.com/NCAR/regional_cesm_mom6.git">https://github.com/NCAR/regional_cesm_mom6.git</a> </p> <p> </p>
Model output for: "Freshwater input from glacier melt outside Greenland alters modeled northern high-latitude ocean circulation"
<p>NEMO-ANHA4 and OGGM model output files used in the article: "Freshwater input from glacier melt outside Greenland alters modeled northern high-latitude ocean circulation".</p> <p> </p> <p>halfsolid.zip and noOGGM.zip contain output of the runs called <em>halfsolid</em> and <em>noOGGM</em> in the article. output_data_OGGM.zip contains the output files of OGGM runs.</p>
Input files for molecular dynamics simulations of holo CaM tagged with Alexa Fluor 488 and Texas Red dyes using Amber20
<p>Here we share the input files for molecular dynamics simulations of holo CaM tagged with Alexa Fluor 488 and Texas Red dyes using Amber20, as well as the TrESP charges used in TrESP-MMPol electronic coupling calculations of FRET properties. Links to the TrADA tool used to derive TrESP charges and the Trespcoup software used to compute electronic couplings for FRET are indicated below:</p> <div> <div> <div> <p>Cupellini, L., Jurinovich, S., & Mennucci, B. (2024). TraDA - Transition Density Analyzer. Zenodo. https://doi.org/10.5281/zenodo.10966411</p> <p>Cupellini, L., Lipparini, F., & Cignoni, E. (2024). trespcoup - Software to compute TrEsp couplings. Zenodo. https://doi.org/10.5281/zenodo.10966391</p> </div> </div> </div>
GIST: Generated Inputs Sets Transferability in Deep Learning (Part 2)
<p>Part2 of the Replication Package for the paper "GIST: Generated Inputs Sets Transferability in Deep Learning"</p> <p>Contains RoBERTa models and data for the KMNC property.</p> <p>Github link: https://github.com/FlowSs/GIST</p> <p>Part1 can be found here: https://zenodo.org/records/10028594</p> <p>Abstract:</p> <p> To foster the verifiability and testability of Deep Neural Networks (DNN), an increasing number of methods<br>for test case generation techniques are being developed.<br> When confronted with testing DNN models, the user can apply any existing test generation technique.<br>However, it needs to do so for each technique and each DNN model under test, which can be expensive.<br>Therefore, a paradigm shift could benefit this testing process: rather than regenerating the test set independently<br>for each DNN model under test, we could transfer from existing DNN models.<br> This paper introduces GIST (Generated Inputs Sets Transferability), a novel approach for the efficient<br>transfer of test sets. Given a property selected by a user (e.g., neurons covered, faults), GIST enables the<br>selection of good test sets from the point of view of this property among available test sets. This allows the<br>user to recover similar properties on the transferred test sets as he would have obtained by generating the<br>test set from scratch with a test cases generation technique. Experimental results show that GIST can select<br>effective test sets for the given property to transfer. Moreover, GIST scales better than reapplying test case<br>generation techniques from scratch on DNN models under test.</p>
STREAMICE code and inputs for "The West Antarctic Ice Sheet may not be vulnerable to Marine Ice Cliff Instability during the 21st Century"
<p>This repository contains all inputs and code to carry out the STREAMICE calving experiments run for the manuscript "The West Antarctic Ice Sheet may not be vulnerable to Marine Ice Cliff Instability during the 21st Century" using the modelling framework MITgcm.</p> <p>MITgcm-front_retreat/ contains a branch of the MITgcm code that enables calving front advance and retreat in the STREAMICE model, and is a branch of checkpoint 68d. Please see https://github.com/MITgcm/MITgcm/blob/master/LICENSE.txt for the MITgcm open source license detail.</p> <p>code/ contains experiment-specific code for the runs detailed in the manuscript</p> <p>input_fwd/ contains all binary and parameter input files for the runs detailed in the manuscript</p> <p>archer_scripts/ contains shell scripts written for the ARCHER2 UK supercomputer to demonstrate how the model is compiled</p> <p> </p> <p> </p>
Input files for elPaSo for the paper: Efficient Solution Strategies for Cabin Noise Assessment of wave-resolving Aircraft Fuselage Models
<div> <div>This dataset showcases the input and output data for the paper: "Efficient Solution Strategies for Cabin Noise Assessment of wave-resolving Aircraft Fuselage Models".</div> <div> </div> The model data are made available in the folder "models" and contain the three models corresponding to the frequency-dependent mesh of the aircraft fuselage model. <div>Three frequency-dependent meshes are placed in subfolders, where the number indicates up to which frequency in Hz the respective model can be used. Here, the ".cub5" files are the mesh files created by the meshing tool Coreform Cubit. For the application of the FEM elPaSo is used. Here, the ".hdf5" files serve as the elPaSo input.</div> <div>Once computed, the results are written in the "eGenOutput*.hdf5" files. The results for the degrees of freedom across the frequency domain can be found here.</div> </div>
Vortex and MetaModel Manager input files -- Exploring impacts of declining sea-ice on ice-dependent species in the Arctic
<p>Input files for Vortex PVA models and for MetaModel Manager used in publication:</p> <p><span>Lacy, Robert C., Kit M. Kovacs, Christian Lydersen, and Jon Aars</span></p> <p><span>Linking PVA models into metamodels to explore impacts of declining sea ice on ice-dependent species in the Arctic: the ringed seal, bearded seal, polar bear complex</span></p> <p> </p>
Dataset related to article "Polynomial Chaos Expansion of SAR and temperature increase variability in 3 T MRI due to stochastic input data"
<p>Dataset related to simulations described in article:</p> <p>Polynomial Chaos Expansion of SAR and temperature increase variability in 3 T MRI due to stochastic input data. Article citation: Bottauscio et al 2024 <em>Phys. Med. Biol.</em> <a href="https://doi.org/10.1088/1361-6560/ad5070" target="_blank" rel="noopener">https://doi.org/10.1088/1361-6560/ad5070</a></p>
Modelling input data for the case study of the paper "Uncertainty-Based Market-Clearing Models: A Comparative Analysis of the Dutch, French, and German Markets".
<p>This data package includes the modelling input data to replicate the results of the case study included in the paper "Uncertainty-Based Market-Clearing Models: A Comparative<br>Analysis of the Dutch, French, and German Markets". </p> <p>The case study models the Dutch, French and German day-ahead electricity markets, in which the existing capacities of electricity generation and upward- and downward reserve capacities are considered, in addition to 105 wind output realization scenarios for each simulation day. 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>- Meta Data – Netherlands.xlsx: Dataset containing the meta data for the Dutch case study</p> <p>- Meta Data – France.xlsx: Dataset containing the meta data for the French case study</p> <p>- Meta Data – Germany.xlsx: Dataset containing the meta data for the German case study</p> <p>- Readme.txt: Includes a detailed description of the data packages</p>
Excessive Firing of Dyskinesia-Associated Striatal Direct Pathway Neurons is Gated By Dopamine and Excitatory Synaptic Input
<p>This folder contains data associated with a submitted manuscript: Ryan, Girasole et al, which was first posted on BioRxiv in 2022. https://www.biorxiv.org/content/10.1101/2022.10.31.514594v1.</p> <p><strong>Files associated with each figure: </strong></p> <p><strong>Figure 1 & Supp Figure 1: </strong></p> <ul> <li>Summary.mat</li> <li>Behavior.mat</li> <li>Data.mat</li> <li>TRAP_InVivo_Analysis.m</li> <li>TRAP_Remove_INs.m</li> </ul> <p><strong>Figure 2 & Supp Figure 2: </strong></p> <ul> <li>See BioStudies for rabies dataset: <a href="https://www.ebi.ac.uk/biostudies/studies/S-BSST1374?key=9a1b2103-25a6-49ed-b257-0269d3ea19a6" target="_blank" rel="noopener">https://www.ebi.ac.uk/biostudies/studies/S-BSST1374?key=9a1b2103-25a6-49ed-b257-0269d3ea19a6</a></li> </ul> <p><strong>Figure 3 & Supp Figure 3 & Supp Figure 4: </strong></p> <ul> <li> <p>Fig3_FigS3_FigS4_Data.xlsx</p> </li> </ul> <p><strong>Figure 4 & Supp Figure 5: </strong></p> <ul> <li>Fig4Data.xlsx</li> <li>RNAscopeAnalysis_D1_D2.m</li> <li>RNAdata.mat</li> <li>RNAscopeAnalysis_D1_pDyn.m</li> <li>RNAScopeAnalysis.m</li> <li>pDynRNAdata.mat</li> <li>pDynSummary.mat</li> </ul> <p><strong>Contributions</strong>: </p> <p>Behavioral data was collected and analyzed by Ally Girasole, Michael Ryan, and Emily Twedell.</p> <p>In vivo electrophysiological data was collected and analyzed by Michael Ryan and Ally Girasole.</p> <p>Ex vivo electrophysiological data was collected and analyzed by Ally Girasole, Michael Ryan, Emily Twedell, and Alexandra Nelson.</p> <p>Anatomical tracing and histology data was collected and analyzed by Ron Paletzki, Chip Gerfen, Michael Ryan, Ally Girasole and Rea Brakaj.</p> <p>RNA Scope data was collected and analyzed by Andrew Flores, Mike Ryan, and Tom Hnasko.</p>
Melosh model of Acoustic Fluidisation, input files
<p>Input files for companion papers submitted to JGR: Planets</p> <p>1) Hay et al., 2024. "<em>Complex crater collapse: A comparison of the Block </em><em>and Melosh Acoustic Fluidization Models of transient </em><em>target weakening</em>".</p> <p>2) Rajšić et al., 2024. "<em>Using the Melosh model of Acoustic fluidization to</em><em> </em><em>simulate impact crater collapse on the Earth and Moon</em>".</p>
Input files, parameter files, topology files for pure gas, gas-water, and lipid nanobubble systems(parameters); scripts for generating lipid nanobubbles (AA-LNB. py).
<p>Input files, parameter files, topology files for pure gas, gas-water, and lipid nanobubble systems(parameters); scripts for generating lipid nanobubbles (AA-LNB. py).</p>
Medium spiny neuron electrophysiological properties across male rats and female rats in different estrous cycle phases in the nucleus accumbens core: Excitatory synaptic input, action potential, and intrinsic properties
<p>This dataset presents electrophysiological properties from whole-cell patch clamped nucleus accumbens core medium spiny neurons from male rats and female rats recorded in different estrous cycle phases. Excitatory synaptic input, action potential, and intrinsic properties are presented in an analyzed format, as well as the original electrophysiological recordings of each neuron. These data were originally presented across two different papers (Proaño et al., 2018, 2020) and further analyzed in an additional paper (Long et al., 2024), all of which are cited below. These data were key for establishing that nucleus accumbens neuron electrical function changed across the estrous cycle in response to its associated hormones, programming a phase-dependent sex difference in adulthood. This finding provided a new framework for understanding how biological sex and hormone cyclicity regulate the neurons implicated in motivated behaviors and related functions and disorders.</p>
The input data of the multi-patch geometries used in: M. Kapl, A. Kosmač, V. Vitrih, Isogeometric collocation for solving the biharmonic equation over planar multi-patch domains, Computer Methods in Applied Mechanics and Engineering 424 (2024) 116882; DOI: 10.1016/j.cma.2024.116882
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MITgcm input data for experiments in Trencham et al. 2024
<p>This dataset includes the input and configuration files for simulations performed using the MITgcm, published in Trencham et al. 2024 (The Impact of Oceanic Feedbacks on Stratosphere-Troposphere Coupling in an Idealised Model). It includes data for fixed-SST experiments (fixed_sst_runs), slab-ocean experiments (slab_ocean_runs), and fully coupled atmosphere-ocean runs (coupled_runs). The latter folder also includes model pickup files corresponding to the last few decades that the control fully coupled simulation was run until, after over 2000 years of model adjustment. The fixed-SST and slab-ocean runs are run from cold using the initial potential temperature and humidity profiles included (theta_cs_a47.bin and q_cs_a47.bin), and take approximately 200 days and 10 years to equilibriate respectively. For further details, see Trencham et al. 2024 and/or contact the corresponding author.</p>
CE-QUAL-W2 model input files (Evaluating the performance of CE-QUAL-W2 sediment diagenesis model)
<p>These files contain the initial conditions, parameters, constants, and forcing datasets used in developing the following manuscript: '<strong>Evaluating the performance of the CE-QUAL-W2 sediment diagenesis model</strong>'</p>
Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands
<p><span>The supporting data for raw data, geographic location of the experimental sites, grid-level maps showing the predicted NCE (%) of global cropland</span></p>
Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands
<p>In-situ observations collected from publications, grid-level maps showing the predicted NCE (%) of global cropland and data-driven model codes</p>
Soil organic carbon formation efficiency from straw/stover and manure input and its drivers: Estimates from long-term data in global croplands
<p>In-situ observations collected from publications, grid-level maps showing the predicted NCE (%) of global cropland and data-driven model codes</p>
Physiological Characteristics of Neurons in the Mammillary Bodies align with Topographical Organization of Subicular Inputs
<p>Batch data is deposited in cell explorer format</p> <p>Please refer to https://cellexplorer.org/ for additional explanation about the data structure </p> <p>See https://github.com/buzsakilab/buzcode for code </p> <p> </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)
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.