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619 results for “configuration”
TARDIS configuration and emulator weights and training data for "1991T-Like Type Ia Supernovae as an Extension of the Normal Population"
<p>This dataset contains two archives of data related to the paper "1991T-Like Type Ia Supernovae as an Extension of the Normal Population"<br> <br> The first dataset, <a href="https://zenodo.org/api/files/de696fe0-3280-44f2-8ef4-975b92fad260/TARDIS_Emulator_Config.tar.gz">TARDIS_Emulator_Config.tar.gz </a>, contains the atomic data used to run TARDIS and a template configuration file from which samples are generated including the flags for the physics implementation used.</p> <p>The second dataset, InferenceScripts.tar.gz, contains the trained probabilistic neural network, the training/validation data (Under NNData), and scripts used to train the model and load and evaluate the model. Scripts that perform inference on spectra, as well as a folder of observed spectra (Under CorrectedSpectra), are included as well. A conda environment yaml file is included to rebuild the Python environment required to run all of the scripts. For questions please email John O'Brien.</p>
Effect of magnetic configuration on real-time wall conditioning in DIII-D
<p>Using EMC3-EIRENE modeling, the impact of parallel impurity forces on the edge transport of injected material and ionized impurities, including scrape-off layer (SOL) main ion flows, has been investigated. The study involved comparing impurity powder injections in different divertor configurations, namely DIII-D lower single null, upper single null, and double null configurations, with plasma edge transport and dust migration and ablation modeling. The injections, which were in powder and granular form, were conducted for real-time wall conditioning, ELM control, and divertor power exhaust at DIII-D [1]. Divertor configuration changes resulted in a redirection of SOL flows, which affected the conditioning of plasma-facing components on either the low field side or the high field side. Moreover, the injection location's poloidal shifts could modify the injected materials' penetration depths and trajectories in the plasma boundary. These changes had an impact on the local deposition of materials on plasma-facing components, which is essential for active conditioning and replenishment of functional coatings in future long-pulse scenarios.</p> <p>[1] F. Effenberg <em>et al</em> 2022 <em>Nucl. Fusion</em> <strong>62</strong> 106015 <strong>DOI</strong> 10.1088/1741-4326/ac899d</p>
Scenario Configurations for Simulating Organic Aerosol in Delhi using WRF-Chem and a VBS Approach
<p>Parameter configuration files for a study into the sensitivity of model predictions (in this case WRF-Chem) of organic aerosol mass loadings, and composition, to organic aerosol production processes.</p> <p>The production processes for both anthropogenic (ANTH) and biomass burning (BB) generated organic aerosols are investigated. 5 production processes are perturbed for each, making a total of 10 parameters for the whole study.</p> <p>The production processes are:</p> <ol> <li>VBS aging rate (VBS_AGERATE): the reaction rate of VBS compounds with OH. Expressed as a reaction rate in cm<sup>3</sup> molec.<sup>-1</sup> s<sup>-1</sup>.</li> <li>SVOC volatility distribution (SVOC_VOLDIST): expressed in terms of an equivalent age (dimensionless between 0-1). This is translated using a simple aging model into a volatility distribution for the emitted VBS compounds.</li> <li>SVOC oxidation rate (SVOC_OXRATE): the degree of oxidation that occurs with, or is induced by, each reaction with an OH molecule. Range is 0.075 (one extra oxygen atom) to 0.45 (six extra oxygen atoms).</li> <li>IVOC scaling (IVOC_SC): scaling factor for emissions of IVOC's alongside the SVOC's. Initial IVOC emitted amount is taken to be x1.5 the non-volatile OA mass in the emission inventory. This scaling factor, ranging from 0 to 3, modifies that initial emitted amount, to give the final IVOC fraction to add.</li> <li>SVOC scaling (SVOC_SC): scaling factor for emissions of SVOCs. This applied to the volatility distribution generated from the SVOC volatility distribution. For anthropogenic emissions this ranges from 0.1 to 4. For biomass burning emissions this ranges from 0.5 to 4.</li> </ol> <p>SVOC_VOLDIST, IVOC_SC, and SVOC_SC combine to give the VBS_FRAC_[X] fractional volatility distributions. These volatility bins start at Ci*=-2 , and increase decadally to Ci*=6.</p> <p>The template namelist into which these parameters are inserted is included too. This is for a modified version of WRF-Chem 3.8.1 - it will not work with the standard WRF-Chem model.</p> <p> </p>
Replication Package: A Systematic Mapping Study on Security in Configurable Safety-critical Systems Based on Product-Line Concepts
<p><strong>Welcome to the public repository for the additional content of the paper "A Systematic Mapping Study on Security in Configurable Safety-critical Systems Based on Product-Line Concepts", accepted at the ICSOFT 2023.</strong></p> <p>This repository provides additional information to the conducted mapping study, including the following files:</p> <ul> <li>fetched_results_ICSOFT2023.csv: sheet containing all papers fetched from IEEEXplore, Scopus, and the ACM Guide to Computing Literature.</li> <li>excluded_paper.csv: sheet containing all excluded papers related to safety-critical systems but not referring to security.</li> <li>analysis_sheet_ICSOFT2023.csv: sheet containing information regarding the analysis results of 44 included papers based on the extraction criteria.</li> </ul>
Database of intercrop configurations and agroecosystems for cabbages
<p>This database was created for the Sureveg project. It collects existing data on cabbage intercropping regarding the configuration of the system and the productivity and product quality provisioning services.<br> It was used in a meta-analyses to study the effect of intercropping on the provisioning services of cabbage.</p>
WP 8 LCOE of the Final LiftWEC configuration
<p>The LCOE data sheet includes the cost and performance data used to calculate the cost of energy of the final LiftWEC configuration. The original LCOE tool has been developed by Julia Fernández Chozas, and during the LIFTWEC project developed further incorporating additional features in co-operation with the LIFTWEC project partners. For further information please see Liftwec Deliverable 8.6 "LW-D08-06-3x2 LCOE estimate of final configuration_final" also attached.</p>
WRF model configuration and data used for the NHESS manuscript "Heat wave characteristics: evaluation of regional climate model performances for Germany"
<p>The file contains:</p> <ul> <li>the namelist.input document with the description of the WRF model configuration used in Warscher et al. (2019)</li> <li>WRF simulation outputs from the reanalysis run: daily values of maximum temperature for the time period 1980-2009 from the innermost (5 km grid resolution) and second innermost (15 km) domain; from both domains the same section, relevant for the study, was taken; the data was bilineraily interpolated to 12.5 km horizontal grid resolution to match the EUR-11 CORDEX format</li> </ul>
DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space
<p>We present <em>Deep learning for Collective Variables</em> (DeepCV), a computer code that provides an efficient and customizable implementation of the deep autoencoder neural network (DAENN) algorithm that has been developed in our group for computing collective variables (CVs) and can be used with enhanced sampling methods to reconstruct free energy surfaces of chemical reactions. DeepCV can be used to conveniently calculate molecular features, train models, generate CVs, validate rare events from sampling, and analyze a trajectory for chemical reactions of interest. We use DeepCV in an example study of the conformational transition of cyclohexene, where metadynamics simulations are performed using DAENN-generated CVs. The results show that the adopted CVs give free energies in line with those obtained by previously developed CVs and experimental results. DeepCV is open-source software written in Python/C++ object-oriented languages, based on the TensorFlow framework and distributed free of charge for noncommercial purposes, which can be incorporated into general molecular dynamics software. DeepCV also comes with several additional tools, i.e., an application program interface (API), documentation, and tutorials.</p>
H2020 ENODISE: RWTH Numerical Aeroacoustic Database Configuration B1
<p>This RWTH dataset contains numerical data for aerodynamics and acoustics of configuration B1, which was defined in the H2020 ENODISE project (<a href="https://www.vki.ac.be/index.php/about-enodise">https://www.vki.ac.be/index.php/about-enodise</a>). In this configuration, three 6-bladed XPROP-S propellers are installed side-by-side on the leading edge of a wing with an airfoil shape of NLF-Mod22(B).</p> <p>The investigated operating point is:</p> <ul> <li>The incoming flow velocity <em>U∞</em> = 30 m/s, the wing angle of attack <em>AoA </em>= 2 deg, the propeller advance ratio <em>J</em> = 0.8, and the relative blade phase angle between propellers <em>∆Φ </em>= 0.</li> </ul> <p>Wall-resolved Large eddy simulations (LES) of the configuration are performed based on the multiphysics flow solver m-AIA of RWTH. The far-field noise is predicted by the Ffowcs-Williams and Hawkings (FW-H) method. The data set contains the time-averaged aerodynamic results predicted by the LES simulation and the aeroacoustic results calculated by the FW-H method. It should be noted that the aeroacoustic data is only a preliminary result and it will be updated soon.</p> <p>More details of the simulation and measurement setups are explained in the attached document ENODISE_B1_RWTH.pptx.</p>
H2020 Enodise: Experimental dataset of configuration C VKI
<p>This database includes experimental aerodynamic and acoustic data for configuration C as defined in the H2020 ENODISE project (https://www.vki.ac.be/index.php/about-enodise). Single and contra-rotating propeller loads and far-field noise were measured in anechoic facility ALCOVES at von Karman Institute for Fluid Dynamics, Belgium. The description of the experimental tests is reported in the associated technical file.</p>
Collection of user-specific configuration files (also known as dotfiles)
<p>A collection of dotfiles repositories collected from GitHub</p> <p> </p> <p>Also includes card sorting results based on 400 sampled commits from the dotfiles repositories.</p>
Data for: Ecosystem connectivity and configuration can mediate instability at a distance in metaecosystems
<ol> <li><span>Ecosystems are connected by flows of nutrients and organisms. Changes to connectivity and nutrient enrichment may destabilise ecosystem dynamics far from the nutrient source.</span></li> <li><span>We used gradostats to examine the effects of trophic connectivity (movement of consumers and producers) versus nutrient-only connectivity on the dynamics of <em>Daphnia</em> <em>pulex</em> (consumers) and algae (resources) in two metaecosystem configurations (linear vs. dendritic). </span></li> <li><span>We found that <em>Daphnia</em> peak population size and instability (coefficient of variation; CV) increased as distance from the nutrient input increased, but these effects were lower in metaecosystems connected by all trophic levels compared to nutrient-only connected systems and/or in dendritic compared to linear systems. </span></li> <li><span>We examined the effects of trophic connectivity (i.e. both trophic levels move rather than one or the other) using a generic model to qualitatively assess whether the expectations align with the ecosystem dynamics we observed. </span></li> <li><span>Analysis of our model shows that increased <em>Daphnia</em> population sizes and fluctuations in consumer-resource dynamics are expected with nutrient connectivity, with this pattern being more pronounced in linear rather than dendritic systems. </span></li> <li><span>These results confirm that connectivity may propagate and even amplify instability over a metaecosystem to communities distant from the source disturbance, and suggest a direction for future experiments, that recreate conditions closer to those found in natural systems.</span></li> </ol>
Molecular dynamics simulations of hyaluronan octamer–tetrapeptide mixtures (PDB configurations)
<p>Extracted PDB configurations from MD simulations of hyaluronan octamer (HA8) with R4 and K4 tetrapeptides. Simulated explicit water was removed for clarity.</p> <p>See <a href="https://doi.org/10.5281/zenodo.8028600">10.5281/zenodo.8028600</a> for more details about simulated systems.</p>
Supplementary material for: "Missing nurses cause missed care: is that it? Non-Trivial Configurations of Reasons Associated with Missed Care in Austrian hospitals – A qualitative comparative analysis"
<p>Dataset with calibrated data to reproduce the Qualitative Comparative Analysis in our article. </p><p>This dataset was generated by Ana Cartaxo. It contains 81 variables with 401 observations (complete data), which were included in the MISSCARE-Austria Study and were generated using the revised MISSCARE Austria instrument (Cartaxo et al., 2022). The original data were calibrated as described in the article in preparation of performing Qualitative Comparative Analysis – variables regarding contextual factors (Nurse Characteristics, Unit Characteristics, Hospital Characteristics), reasons for missed nursing care (Demand for patient care, Relationship and communication factors, Labor resources allocation, Material resources allocation) and outcomes of missed nursing care are included in the csv. file. </p><p>The R Script (R-Code.R) was created by Ana Cartaxo, João Cartaxo und Johannes Bergmann. It contains the different functions and analysis steps to reproduce the Qualitative Comparative Analysis reported on the article above, using the dataset made available ("Calibrated_Data_Set.csv").</p>
Fixation of Fractures at Anterior Transition Zone Using Three Different Miniplates Configurations
ClinicalTrials.gov study NCT07058597. IPD Sharing: YES. Countries: 1. Publications: 0.
Neighborhood benthic configuration reveals hidden social diversity: classified benthic data
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Molecular models of the FtsQ-FtsL-FtsB-FtsW-FtsI complex (FtsQLBWI) in mono- and diprotomeric configurations
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Data from: Landscape composition, configuration, and trophic interactions shape arthropod communities in rice agroecosystems
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Conservation in post-industrial cities: how does vacant land management and landscape configuration influence urban bees?
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Developmental change in predators drives different community configurations
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.