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506 results for “assessment model”
Data from: Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model
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Data from: A novel technique to develop thoracic spinal laminectomy and a methodology to assess the functionality and welfare of the contusion SCI rat model
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Data from: Assessing cumulative impacts of forest development on the distribution of furbearers using expert-based habitat modeling
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Data from: A segmentation algorithm for characterizing Rise and Fall segments in seasonal cycles: an application to XCO2 to estimate benchmarks and assess model bias
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Runoff modeling of a coastal basin to assess variations in response to shifting climate and land use: Implications for managed recharge
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Supplementary material 2 from: Desvignes V, Buschhardt T, Guillier L, Sanaa M (2019) Quantitative microbial risk assessment for Salmonella in eggs. Food Modelling Journal 1: e39643. https://doi.org/10.3897/fmj.1.39643
Parameter settings
Supplementary material 1 from: Desvignes V, Buschhardt T, Guillier L, Sanaa M (2019) Quantitative microbial risk assessment for Salmonella in eggs. Food Modelling Journal 1: e39643. https://doi.org/10.3897/fmj.1.39643
QMRA_Salmonella_egg_Virginie.fskx
Figure 2 from: Desvignes V, Buschhardt T, Guillier L, Sanaa M (2019) Quantitative microbial risk assessment for Salmonella in eggs. Food Modelling Journal 1: e39643. https://doi.org/10.3897/fmj.1.39643
Figure 2 Predicted number of salmonellosis per million servings of eggs, according to the cooking method.
Datasets: New technologies in the mix: Assessing N-mixture models for abundance estimation using automated detection data from drone surveys
<p>These data set contains data from 11 surveys of radio-collared using remotely piloted aircraft systems (RPAS), thermal <br> imaging and automated detection.The MODELDEV .csv contains data points used to develop the modified Horvitz Thompson estimator models in the paper "New technologies in the mix: Assessing N-mixture models for abundance estimation using automated detection data from drone surveys" which is accepted into publication in the journal Ecology and Evolution as of 11/06/2020. The TESTING .csv contains data points used for model testing in in the same publication. </p>
Code for Individual Based Model to assess impact of KHV release on carp population
<p><b>1: </b>Common carp (<i>Cyprinus carpio</i>) is one of the top global invasive vertebrates and can cause significant ecological damage. The Australian Government's National Carp Control Program (NCCP) proposes to release Koi Herpesvirus (KHV) to eradicate feral carp in one of the largest ecological interventions ever attempted. Ecological and human health risks have been highlighted regarding the release of a highly pathogenic viral biocontrol for an aquatic species. The efficacy of KHV has also been questioned, and it has not been demonstrated to produce lasting population reductions.</p> <p> </p> <p>2. We developed an individual-based model (IBM) to examine the ecological and evolutionary response of a carp population after KHV release. This simulated the interaction between fish life history, viral epidemiology, host genetic resistance and population demography to critically evaluate the impact of KHV release under optimal conditions and a "best case scenario" for disease transmission.</p> <p> </p> <p>3. KHV will rarely result in prolonged reductions or population extinctions. Crucially, realistic scenarios result in a rapidly rebounding population of resistant individuals. Additional measures aimed to reduce carp population recovery rate (e.g. with genetic engineering) require rapid efficacy to significantly reduce carp numbers alongside KHV.<br> </p> <p>4. Fish fecundity has an overwhelming influence on viral efficacy as a biocontrol agent when combined with genetic resistance within a population. A high probability of population extinction is only met when carp fecundity is reduced to 1% of biological observations.<br> </p> <p><span>5.<i> Synthesis and applications. </i></span>We use an individual-based model to evaluate the efficacy of Koi Herpesvirus biocontrol in Common <a>Ca</a>rp, and find that high host fecundity combined with genetic resistance results in rapid population rebound after initial large fish-kills. Biocontrol approaches relying on natural selection lose efficacy over successive generations as resistance genes increases in frequency. Given the intense logistical effort and risks to ecosystems and human health associated with large fish kills after viral release, we suggest that sustained manual removal, alongside ecological restoration to favour recovery of native species, provides a risk-free approach to reducing populations.<br> </p>
Data from: Why we should care about movements: Using spatially explicit integrated population models to assess habitat source-sink dynamics
<p>1. Assessing the source-sink status of populations and habitats is of major importance for understanding population dynamics and for the management of natural populations. Sources produce a net surplus of individuals (per capita contribution to the metapopulation >1) and will be the main contributors for self-sustaining populations, whereas sinks produce a deficit (contribution < 1). However, making these types of assessments is generally hindered by the problem of separating mortality from permanent emigration, especially when survival probabilities as well as moved distances are habitat-specific.<br> 2. To address this long-standing issue, we propose a spatial multi-event Integrated Population Model (IPM) that incorporates habitat-specific dispersal distances of individuals. Using information about local movements, this IPM adjusts survival estimates for emigration outside the study area.<br> 3. Analyzing 24 years of data on a farmland passerine (the northern wheatear Oenanthe oenanthe) we assessed habitat-specific contributions, and hence the source-sink status and temporal variation of two key breeding habitats, while accounting for habitat- and sex-specific local dispersal distances of juveniles and adults. We then examined the sensitivity of the source-sink analysis by comparing results with and without accounting for these local movements.<br> 4. Estimates of first-year survival, and consequently habitat-specific contributions, were higher when local movement data were included. The consequences from including movement data were sex specific, with contribution shifting from sink to likely source in one habitat for males, and previously noted habitat differences for females disappearing.<br> 5. Assessing the source-sink status of habitats is extremely challenging. We show that our spatial IPM accounting for local movements can reduce biases in estimates of the contribution by different habitats, and thus reduce the overestimation of the occurrence of sink habitats. This approach allows combining all available data on demographic rates and movements, which will allow better assessment of source-sink dynamics and better informed conservation interventions.</p>
Figure 1 from: Miteva D, Solak A, Dyankova S, Nacheva I, Dimov K (2020) Assessment of allergenicity of irradiated dairy products in a Balb/c mice model. Pharmacia 67(3): 129-133. https://doi.org/10.3897/pharmacia.67.e53886
Figure 1 A model of food allergy in Balb/c mice with a period of sensitization, containing five time probe feeding with milk protein (MP) and adjuvant (CTB) at weekly intervals, and challenged after 6 weeks by intraperitoneally (i.p) applied МР.
Figure 2 from: Miteva D, Solak A, Dyankova S, Nacheva I, Dimov K (2020) Assessment of allergenicity of irradiated dairy products in a Balb/c mice model. Pharmacia 67(3): 129-133. https://doi.org/10.3897/pharmacia.67.e53886
Figure 2 Serum levels of total IgE. Sera from different groups of mice (n = 6) were obtained 45 minutes after challenge. Different letters indicate statistically significant differences (mean ± SD, one-way ANOVA followed by Tukey test, p < 0.05).
Data from: Bioclimatic variables derived from remote sensing: assessment and application for species distribution modeling
Remote sensing techniques offer an opportunity to improve biodiversity modeling and prediction worldwide. Yet, to date, the weather-station based WorldClim dataset has been the primary source of temperature and precipitation information used in correlative species distribution models. WorldClim consists of grids interpolated from in situ station data recorded primarily from 1960 to 1990. Those datasets suffer from uneven geographic coverage, with many areas of Earth poorly represented. Here, we compare two remote sensing data sources for the purposes of biodiversity prediction: MERRA climate reanalysis data and AMSR-E, a pure remote sensing data source. We use these data to generate novel temperature-based bioclimatic information and to model the distributions of 20 species of vertebrates endemic to four regions of South America: Amazonia, the Atlantic Forest, the Cerrado, and Patagonia. We compare the bioclimatic datasets derived from MERRA and AMSR-E information with in situ station data, and contrast species distribution models based on these two products to models built with WorldClim. Surface temperature estimates provided by MERRA and AMSR-E showed warm temperature biases relative to the in situ data fields, but the reliability of these datasets varied in geographic space. Species distribution models derived from the MERRA data performed equally well (in Cerrado, Amazonia, and Patagonia) or better (Atlantic Forest) than models built with the WorldClim data. In contrast, the performance of models constructed with the AMSR-E data was similar to (Amazonia, Atlantic Forest, Cerrado) or worse than (Patagonia) that of models built with WorldClim data. Whereas this initial comparison assessed only temperature fields, efforts to estimate precipitation from remote sensing information hold great promise; furthermore, other environmental datasets with higher spatial and temporal fidelity may improve upon these results.
Data from: Correlations of behavioral deficits with brain pathology assessed through longitudinal MRI and histopathology in the HDHQ150/Q150 mouse model of Huntington's disease
A variety of mouse models have been developed that express mutant huntingtin (mHTT) leading to aggregates and inclusions that model the molecular pathology observed in Huntington's disease. Here we show that although homozygous HdhQ150 knock-in mice developed motor impairments (rotarod, locomotor activity, grip strength) by 36 weeks of age, cognitive dysfunction (swimming T maze, fear conditioning, odor discrimination, social interaction) was not evident by 94 weeks. Concomitant to behavioral assessments, T2-weighted MRI volume measurements indicated a slower striatal growth with a significant difference between wild type (WT) and HdhQ150 mice being present even at 15 weeks. Indeed, MRI indicated significant volumetric changes prior to the emergence of the "clinical horizon" of motor impairments at 36 weeks of age. A striatal decrease of 27% was observed over 94 weeks with cortex (12%) and hippocampus (21%) also indicating significant atrophy. A hypothesis-free analysis using tensor-based morphometry highlighted further regions undergoing atrophy by contrasting brain growth and regional neurodegeneration. Histology revealed the widespread presence of mHTT aggregates and cellular inclusions. However, there was little evidence of correlations between these outcome measures, potentially indicating that other factors are important in the causal cascade linking the molecular pathology to the emergence of behavioral impairments. In conclusion, the HdhQ150 mouse model replicates many aspects of the human condition, including an extended pre-manifest period prior to the emergence of motor impairments.
Data from: Assessing parameter identifiability in phylogenetic models using Data Cloning
The success of model-based methods in phylogenetics has motivated much research aimed at generating new, biologically informative models. This new computer-intensive approaches to phylogenetics demands validation studies and sound measures of performance. To date such work has consisted only of simulation studies, estimation of known phylogenies and difficult mathematical analyses assessing the estimability of parameters. Little practical guidance has been available to practitioners and theoreticians alike as to when and why the parameters in a particular model can be identified reliably. Here, we illustrate how Data Cloning (DC), a recently developed methodology to compute the Maximum Likelihood estimates along with their asymptotic variance, can be used to diagnose structural parameter non-identifiability (NI) and distinguish it from other parameter estimability problems including the case where parameters are structurally identifiable, but are not estimable in given data set (INE), and the case where parameters are identifiable, and estimable, but only weakly so (WE). The application of the DC theorem uses well-known and widely used Bayesian computational techniques. With the DC approach, practitioners can use any Bayesian phylogenetics software to be able to diagnose non-identifiability. Theoreticians and practitioners alike now have a powerful tool to detect non-identifiability while investigating complex modeling scenarios, where getting closed-form expressions in a probabilistic study is complicated. Furthermore, here we also show how DC can be used as a tool to examine and eliminate the influence of the priors, in particular if the process of prior elicitation is not straightforward. Finally, when applied to phylogenetic inference, DC can be used to study at least two important statistical questions: assessing identifiability of discrete parameters, like the tree topology, and developing efficient sampling methods for computationally expensive posterior densities.
R scripts for data simulation and model assessment in ShuqingNTeng MEE 2017
<p>R scripts for reproducing results in ShuqingNTeng MEE 2017</p>
CHOOSING THE DEVELOPMENT MODEL OF AGRO-TOURISM ACTIVITY IN THE REGIONS BASED ON ASSESSMENT OF THE EFFECTS OF FACTORS
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Wildfire Risk Assessment for Strategic Forest Management in the Southern United States: a Bayesian Network Modeling Approach
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Supplementary material 1 from: Keck F, Hürlemann S, Locher N, Stamm C, Deiner K, Altermatt F (2022) A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess richness of mayflies, stoneflies and caddisflies in rivers. Metabarcoding and Metagenomics 6: e79351. https://doi.org/10.3897/mbmg.6.79351
Figures S1–S5
ScienceDex guides
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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.