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506 results for “assessment model”
Data from: An integrated assessment model of seabird population dynamics: can individual heterogeneity in susceptibility to fishing explain abundance trends in Crozet wandering albatross?
1. Seabirds have been incidentally caught in distant-water longline fleets operating in the Southern Ocean since at least the 1970s, and breeding numbers for some populations have shown marked trends of decline and recovery concomitant with longline fishing effort within their distributions. However, lacking is an understanding of how forms of among-individual heterogeneity may interact with fisheries bycatch and influence population dynamics. 2. We develop a model that uses comprehensive data on the spatial and temporal distributions of fishing effort and seabird foraging to estimate temporal overlaps, fishery catchability and consequent bycatch. We apply a population model that is structured by age, sex, life stage and spatially to Crozet Island wandering albatross and explore how heterogeneity in susceptibility to capture may have influenced the population's demography over time. 3. A model where some birds were assumed to be more susceptible to fisheries bycatch was able to successfully replicate the observed trend in breeding pairs. Considerably poorer fits were found without this assumption. Results suggested that the more susceptible birds may have been removed from the population by the 1990s. 4. The model was also able to highlight areas, times and fleets prone to increased bycatch. Knowledge of these factors should assist fisheries and conservation management bodies to quantify and reduce seabird bycatch through spatial management and fleet-specific mitigation efforts. 5. Synthesis and application. Many seabirds show complex life histories that make them highly susceptible to additional incidental mortality from fishing vessels. By applying a population model that integrates key aspects of seabird and fishery dynamics, we were able to explain the observed trends in the breeding population of Crozet wandering albatross and identify key areas and fleets where further mitigation may be required. In addition, the potential removal of a category of birds that shows increased susceptibility to capture has important implications for the conservation management of this population and other iconic species incidentally caught by large-scale commercial fisheries.
Advanced methods for uncertainty assessment and global sensitivity analysis of a Eulerian atmospheric chemistry transport model
<p>Atmospheric chemistry transport models (ACTMs) are extensively used to provide scientific support for the development of policies to mitigate against the detrimental effects of air pollution on human health and ecosystems. Therefore, it is essential to quantitatively assess the level of model uncertainty and to identify the model input parameters that contribute the most to the uncertainty. For complex process-based models, such as ACTMs, uncertainty and global sensitivity analyses are still challenging and are often limited by computational constraints due to the requirement of a large number of model runs. In this work, we demonstrate an emulator-based approach to uncertainty quantification and variance-based sensitivity analysis for the EMEP4UK model (regional application of the European Monitoring and Evaluation Programme Meteorological Synthesizing Centre-West). A separate Gaussian process emulator was used to estimate model predictions at unsampled points in the space of the uncertain model inputs for every modelled grid cell. The training points for the emulator were chosen using an optimised Latin hypercube sampling design. The uncertainties in surface concentrations of O<sub>3</sub>, NO<sub>2</sub>, and PM<sub>2.5</sub> were propagated from the uncertainties in the anthropogenic emissions of NO<sub>x</sub>, SO<sub>2</sub>, NH<sub>3</sub>, VOC, and primary PM<sub>2.5</sub> reported by the UK National Atmospheric Emissions Inventory. The results of the EMEP4UK uncertainty analysis for the annually averaged model predictions indicate that modelled surface concentrations of O<sub>3</sub>, NO<sub>2</sub>, and PM<sub>2.5</sub> have the highest level of uncertainty in the grid cells comprising urban areas (up to ± 7%, ± 9%, and ± 9% respectively). The uncertainty in the surface concentrations of O<sub>3 </sub>and NO<sub>2</sub> were dominated by uncertainties in NO<sub>x</sub> emissions combined from non-dominant sectors (i.e. all sectors excluding energy production and road transport) and shipping emissions. Additionally, uncertainty in O<sub>3</sub> was driven by uncertainty VOC emissions combined from sectors excluding solvent use. Uncertainties in the modelled PM<sub>2.5</sub> concentrations were mainly driven by uncertainties in primary PM<sub>2.5</sub> emissions and NH<sub>3</sub> emissions from the agricultural sector. Uncertainty and sensitivity analyses were also performed for five selected grid sells for monthly averaged model predictions to illustrate the seasonal change in the magnitude of uncertainty and change in the contribution of different model inputs to the overall uncertainty. Our study demonstrates the viability of a Gaussian process emulator-based approach for uncertainty and global sensitivity analyses, which can be applied to other ACTMs. Conducting these analyses helps to increase the confidence in model predictions. Additionally, the emulators created for these analyses can be used to predict the ACTM response for any other combination of perturbed input emissions within the ranges set for the original Latin hypercube sampling design without the need to re-run the ACTM, thus allowing fast exploratory assessments at significantly reduced computational costs.</p> <p>The upload contains the uncertainty and sensitivity data together with the analysis scripts.</p>
Integrated machine learning and GIS-based bathtub models to assess the future flood risk in the Kapuas River Delta, Indonesia
<p>To use the data and the code, please cite the following article: </p> <p>Joko Sampurno, Randy Ardianto, Emmanuel Hanert; Integrated machine learning and GIS-based bathtub models to assess the future flood risk in the Kapuas River Delta, Indonesia. <em><em>Journal of Hydroinformatics</em></em> 2022; jh2022106. DOI: <a href="https://doi.org/10.2166/hydro.2022.106">https://doi.org/10.2166/hydro.2022.106</a></p>
An Empirical Study Assessing Software Modeling in Alloy
<p>VM for the Formalise Artifact 2023</p>
Assessing acetone for the GISS ModelE2.1 Earth system model
<p>The simulated three-dimensional distributions of acetone from each simulation described in the paper (Baseline, sensitivity simulations in Table 1, and Nudged_ATom) are available in the zip files below, grouped by simulation:</p> <p>Each zip file contains a series of netCDF format files with filenames: {month}_5yrAvg_Acetone_{simulation}.nc, for example, <a href="https://urldefense.proofpoint.com/v2/url?u=http-3A__JUN-5F5yrAvg-5FAcetone-5FChem-5FPar2.0.nc&d=DwMFaQ&c=009klHSCxuh5AI1vNQzSO0KGjl4nbi2Q0M1QLJX9BeE&r=AW5CBwXzwRZfFpcXrchhGJYviihO8BJyAZekNlH15N4&m=tMBMWYi2ngTehrdwTk8qd9ZLcw3W5QqDEOLFI-OsoUHkrSSiiBk6fUbSw2OBQdRa&s=Yeqlp_vtfNOpWQcBGoIeiEDlbA_pc1JwfYT8ghUFVgA&e=">JUN_5yrAvg_Acetone_Chem_Par2.0.nc</a>, where each file is a climatological average over 5 years of repeated forcing conditions.</p> <p>The exception is the transient-forcing simulation "Nudged_ATom", which contains single-month averages of acetone from JUL 2016 through MAY 2018, to cover the ATom observational period. The file names for that simulation are of the form: {month}_{year}_Acetone_Nudged_ATom.nc. Acetone is in ppbv units and given on the model's native grid and vertical levels. These are hybrid sigma levels, but nominal pressure middles and edges are given in the plm and ple variables, respectively, and the grid box surface areas are also provided.</p> <p> </p> <p>GISS_MODELE_Acetone_Work.tar.gz contains:</p> <p>GISS_MODELE_Acetone_Work/ = the GISS ModelE directory used to perform simulations. With model codes in model/ and run instructions (called “rundecks”) in decks/. That decks directory also contains each simulation’s pre-compiled executable.</p> <p>The mapping of paper simulation name to the rundeck is as follows:</p> <table> <tbody> <tr> <td> <p>Paper Simulation Name</p> </td> <td> <p>ModelE “rundeck”</p> </td> </tr> <tr> <td> <p>Baseline</p> </td> <td> <p>E3acetOn3g.R</p> </td> </tr> <tr> <td> <p>Nudged_ATom</p> </td> <td> <p>E3acetOn3g_tranAtom.R</p> </td> </tr> <tr> <td> <p>Chem_Par2.0</p> </td> <td> <p>E3acetOn3g_ParDbl.R</p> </td> </tr> <tr> <td> <p>Chem_Terp0</p> </td> <td> <p>E3acetOn3g_Terp0.R</p> </td> </tr> <tr> <td> <p>Chem_Par0.5</p> </td> <td> <p>E3acetOn3g_ParHalf.R</p> </td> </tr> <tr> <td> <p>Dep_f<sub>0</sub>0</p> </td> <td> <p>E3acetOn3g_f00.R</p> </td> </tr> <tr> <td> <p>Ocn_2.0</p> </td> <td> <p>E3acetOn3g_Ocn30.R</p> </td> </tr> <tr> <td> <p>Veg_0.7</p> </td> <td> <p>E3acetOn3g_Meg07.R</p> </td> </tr> <tr> <td> <p>Chem_Cl0</p> </td> <td> <p>E3acetOn3i.R</p> </td> </tr> <tr> <td> <p>BB_2.0</p> </td> <td> <p>E3acetOn3g_bbDbl.R</p> </td> </tr> </tbody> </table> <p> </p> <p>INPUT_FILES.tar.gz contains: the modelE chemistry input instruction tables referenced in the (*.R) rundecks. </p> <p> </p> <p>SCRIPTS.tar.gz contains:</p> <p>SCRIPTS/extract_and_convert.ksh = used to extract model output to provide in the zip files in this archive.</p> <p>SCRIPTS/PLOTTING/ = python programs used to make the paper figures</p> <p> </p> <p>MODELE_RAW_OUTPUT_VARIABLES.tar.gz contains: the modelE output files used as input to the plotting/analysis programs.</p>
Assessing the Accuracy of 2-D Planetary Evolution Models against the 3-D Sphere
<p><strong>Datasets concerning isoviscous simulations:</strong><br> Tables containing the time averaged (on the last 10% of the run) values for all the outputs and geometry studied. There is one table per Ra number with a given heating mode. In total there are 15 tables for each scenarios (i.e., three different heating modes and five different Ra numbers)</p> <p><strong>Datasets concerning temperature dependent simulations:</strong><br> Tables containing the time averaged (on the last 10% of the run) values for all the outputs and geometry studied for temperature dependent viscosity simulations. Only one Ra is investigated. In total three tables, for three heating modes.</p> <p><strong>Datasets concerning thermal evolution simulations with and without crust:</strong><br> Tables containing dimensional present day values of all the investigated outputs for different geometries and planet scenarios for cases with and without crust. In total six tables, for three planets.</p>
Supplementary material 1 from: McCulloch-Jones EJ, Kraaij T, Crouch N, Faulkner KT (2023) Assessing the invasion risk of traded alien ferns using species distribution models. NeoBiota 87: 161-189. https://doi.org/10.3897/neobiota.87.101104
Supplementary information
A case study: assessing the efficacy of the revised dosage regimen via prediction model for recurrent event rate using biomarker data
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AI Risk Assessment Model for Complication Prevention in Plastic Surgery (Artificial Intelligence)
ClinicalTrials.gov study NCT06507384. IPD Sharing: YES. Countries: 1. Publications: 0.
Assessing a Risk Model for G6PD Deficiency
ClinicalTrials.gov study NCT03337152. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Clinical Study to Assess the Efficacy of IMM-124E (Travelan®) in a Controlled Human Infection Model
ClinicalTrials.gov study NCT05933525. IPD Sharing: NO. Countries: 1. Publications: 0.
STRONGER 60+: Assessing the Clinical Effectiveness and Delivery of an Adapted FINGER Model for Brain Health in Primary Care
ClinicalTrials.gov study NCT07117916. IPD Sharing: NO. Countries: 0. Publications: 0.
Assess the Efficacy and Safety in Volunteers of DCF100, TIB200 and SPR300 vs. Placebo and Control(s) in a UV Pain Model
ClinicalTrials.gov study NCT02666846. IPD Sharing: NO. Countries: 1. Publications: 0.
Development and Assessment of a Simulation Model of Focused and Ongoing Professional Practice Evaluations
ClinicalTrials.gov study NCT03229226. IPD Sharing: UNDECIDED. Countries: 0. Publications: 7.
Research on Risk Assessment and Early Warning Models for Adverse Clinical Outcomes in Critically Ill Patients
ClinicalTrials.gov study NCT07317817. IPD Sharing: NO. Countries: 1. Publications: 0.
Model for the Integral Assessment of Chronic Disease Management Supported in Information Technology and Communication.
ClinicalTrials.gov study NCT02447562. IPD Sharing: Not stated. Countries: 0. Publications: 3.
Building of Prognosis Model for Patients With Cirrhosis Based on Sarcopenia Assessed by Deep Learning
ClinicalTrials.gov study NCT06531200. IPD Sharing: Not stated. Countries: 0. Publications: 29.
Effect of Predictive Model on ED Physician Assessments of Patient Disposition
ClinicalTrials.gov study NCT06434220. IPD Sharing: NO. Countries: 0. Publications: 5.
The Model and Effect Assessment of Training General Practitioner for Dementia Early Recognition
ClinicalTrials.gov study NCT02782000. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Analytical Modeling Framework to Assess the Economic and Environmental Impacts of Residential Deliveries, and Evaluate Sustainable City Logistics Strategies
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.