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5,805 results for “Data model”
Data and modeling results for publication: Landscape genetics indicate recently increased habitat fragmentation in African forest-associated chafers
<ul> <li>DNA sequences: <em>cox1</em> and ITS1 alignments</li> <li>spatial records (in hypervolume archive)</li> <li>spatial principal component 1-3 used for <em>hypervolume</em> models (in hypervolume archive)</li> <li>Present and past species distribution models (SDMs): <ul> <li><em>biomod2</em> ensemble SDMs <ul> <li>Present</li> <li>Holocene Altithermal</li> <li>Last Glacial Maximum</li> </ul> </li> <li><em>biomod2</em> SDMs for single PMIP3 models <ul> <li>Present</li> <li>Holocene Altithermal</li> <li>Last Glacial Maximum</li> </ul> </li> <li><em>hypervolume</em> SDMs</li> </ul> </li> <li>landscape connectivity models <ul> <li>circuitscape (for F0, F1, and F2)</li> <li>least cost corridors and paths (for F0, F1, and F2)</li> </ul> </li> </ul>
Standard Model effective field theory global fit using electroweak data
<p>These are files that can be used to reproduce the fit results in 10.1007/JHEP09(2016)157 and arXiv:1610.01783<strong>.</strong></p> <p> </p>
Artificial viscosity model to mitigate numerical artefacts at fluid interfaces with surface tension (Supporting data)
<p>This data accompanies the paper "Artificial viscosity model to mitigate numerical artefacts at fluid interfaces with surface tension", published in Computers & Fluids.</p>
Analyzing the sensitivity of a flood risk assessment model towards its input data, twelve damage scenarios
<p>This dataset contains the output shapefiles of twelve different risk assessment scenarios for the case study of Annotto Bay, Jamaica. These assessments were performed in the context of the research 'Analyzing the sensitivity of a flood risk assessment model towards its input data', published in the journal Natural Hazards and Earth System Sciences. More information on the input data and methodology can be found in this paper.</p>
Dataset (CryoSat-2 altimetry data over Brahmaputra River, river masks, model cross sections) used in Schneider et al., 2017. doi:10.5194/hess-2016-243
<p>Dataset used in</p> <p>Schneider, R., Nygaard Godiksen, P., Villadsen, H., Madsen, H., Bauer-Gottwein, P., 2017. Application of CryoSat-2 altimetry data for river analysis and modelling. Hydrol. Earth Syst. Sci.rticle. doi:10.5194/hess-2016-243</p> <p>The dataset contains</p> <ul> <li>CryoSat-2 satellite altimetry data over the Brahmaputra River from 2010 to 2013</li> <li>River masks, derived from Landsat NDVI imagery, used to filter the CryoSat-2 data</li> <li>Results from the cross section calibration described in Schneider et al., 2017</li> </ul> <p>All data is provided as a .zip file which includes a README.txt with more details on the data.</p> <p> </p>
Data and results for manuscript "Flow dynamics in hyper-saline aquifers: hydro-geophysical monitoring and modeling"
<p>The paper presents a general methodology that will help understand how freshwater and saltwater may interact in natural porous media, with a particular view at practical applications such as the storage of freshwater underground in critical areas such as semi-arid zones around the Mediterranean sea. The methodology is applied to a case study in Sardinia and shows how a mix of advanced monitoring and mathematical modeling tremendously advance our understanding of these systems.</p> <p>This package contains the raw cross-hole time-lapse ERT data, additional field data, the ERT inversion results of the field data as well as the modeling data in terms of the concentration distribution of the density-dependent flow and transport model and the inverted synthetic ERT monitoring results.</p>
Illustrative dataset for the article: Vieira, R., McDonald, S., Araujo-Soares, V., Sniehotta, F., Henderson, R. (2017) "Dynamic modelling of n-of-1 data: Powerful and flexible data analytics applied to individualised studies"
<p>This dataset is supplementary material of the manuscript "Dynamic modelling of n-of-1 data: Powerful and flexible data analytics applied to individualised studies. McDonald et al. (2016) presents a series of novel n-of-1 studies that intended to explore the relationship between physical activity change during the retirement transition. The file contains the data of one participant. The column names correspond to the following variables:</p> <p>time: duration of follow-up (minutes);<br> minute: time of day (hours and minutes);<br> day_num: day since beginning of follow-up (the first two days were considered as adaptation phase and therefore removed); <br> PAscore: accelerometer raw score; <br> startBout: 1 (a bout of PA was initiated in this minute) or 0 (a bout of PA wasn't <br> initiated in this minute); <br> nPAbouts_day: number of PA bouts per day; <br> nPAbouts_day.l1: number of PA bouts in previous day (lag 1); <br> nPAbouts_day.l2: number of PA bouts two day before (lag 2); <br> nBoutsLast2hours: number of PA bouts in previous 2 hours; <br> retirement: 0 (before retirement) or 1 (after retirement)<br> weekday: 0 (workday) or 1 (weekend)<br> sleepLength: number of hours of sleep last night<br> sleepLength.l1: number of hours of sleep the night before<br> sleepLength.l2: number of hours of sleep two nights before<br> pers: personalised measure of partner's influence (scale 0-1)<br> periodDay: morning, evening or afternoon</p> <p>McDonald, S., Vieira, R., O'Brien, N., White, M., & Sniehotta, F. F. (2016). Does physical activity and sedentary behavior change during the retirement transition? Findings from a series of novel n-of-1 natural experiments. <em>International Journal of Behavioral Medicine, 23</em>, S261-S261.</p> <p> </p>
Individual-based simulation model of annual movement paths for the Darwin's frog (R code and data)
<p>Desprition of the R code</p> <p>I constructed an individual-based simulation model that describes the movement path of an individual<em> Rhinoderma darwinii</em> through 3-month displacement steps. This model was primarily developed to evaluate the age-specific movement behaviour of Darwin's frogs, however, I also used it to provide better estimates (i.e. alleviating for movement censoring) of age-specific annual displacements in the species. I developed several variations of this model through a combination of different random walk sub-models for juveniles and adults: uncorrelated non-stationary random walks (NRW), correlated non-stationary random walks (CRW), and stationary random walks (SRW). The NRW and CRW were modelled as a first-order Markovian process where the location of an individual <em>i</em> in time<em> t</em> depends on its spatial location in <em>t </em>- 1. The NRW is unbiased, i.e., there is no preferred direction in each movement step. In contrast, the CRW includes persistence in the directionality of movement, so there is a correlation between successive step orientations. Finally, the SRW assumes that individuals have an activity centre to which all their spatial locations are related.</p> <p>Related data are provided (y.txt, x.txt and age.txt)</p>
Supporting data for "Mammalian species abundance across a gradient of tropical land-use intensity: A hierarchical multi-species modelling approach"
<p>Combined camera trap and live trap dataset underlying the analyses in a Biological Conservation paper (https://doi.org/10.1016/j.biocon.2017.05.007), provided in .csv format. This spatially- and temporally-replicated dataset is suitable for occupancy modelling.</p> <p>The first 3 columns in the dataset are:</p> <p>1) Trap location name – old-growth forest, logged forest and oil palm plantation locations have the prefixes "Old", "Log" and "Palm", respectively</p> <p>2) Sampling occasion number – camera trap and live trap occasions have the prefixes “Lvtrap” and “Ctrap”, respectively, and are defined in the paper</p> <p>3) Calendar year in which sampling took place (most locations were sampled in > 1 calendar years)</p> <p>Following these 3 columns, there are 66 columns for each of the mammal species detected during the study (species common names are used). The values for each species represent the number of independent captures, as defined in the paper. This can be reduced to detection/non-detection data (zeroes and ones), if needed, for occupancy modelling.</p>
Supporting data for "Quantum simulation of a Fermi-Hubbard model using a semiconductor quantum dot array"
<p>Supporting data and analysis scripts for Fig. 3b of "Quantum simulation of a Fermi-Hubbard model using a semiconductor quantum dot array", ArXiv:1702.07511 (preprint) and 10.1038/nature23022 (publication)</p> <p>This dataset contains a readme file as well as three zipped folders that contain (1) raw data sets of all relevant measurements, as well as (2) matlab files to plot fitted data and the extracted parameters and (3) the code that uses the extracted parameters to plot the fan diagram.</p>
MEHRA data and model for the English regions
<p><strong>M</strong>ulti-dimensional <strong>E</strong>nvironment-<strong>H</strong>ealth <strong>R</strong>isk <strong>A</strong>nalysis (<strong>MEHRA</strong>) data and model for the English regions</p> <p>This archive contains 4 objects in RDS (R Data Storage) format:</p> <ul> <li><strong>Training </strong>and <strong>testing</strong> datasets - These have been assembled to carry out the experiments described in the paper 'Modelling air pollution, climate and health data using Bayesian Networks: a case study of the English regions' by Vitolo et al. (currently under review)</li> <li><strong>BN model </strong>and <strong>DAG</strong> - These are the bayesian network and DAG resulting from the experiment described in the paper 'Modelling air pollution, climate and health data using Bayesian Networks: a case study of the English regions' by Vitolo et al. (currently under review)</li> </ul> <p>The paper contains full details of the features, below is a short summary:</p> <ul> <li>Data were collected in England (United Kingdom) from 1981 to 2014.</li> <li>Mortality counts were obtained from the Office for National Statistics (ONS)</li> <li>The counts were standardized based on yearly regional population estimates obtained from the MYEDE dataset.</li> <li>Data from air quality monitoring stations were obtained from the UK Air Information Resource service hosted by the Department for Environment, Food & Rural Affairs (DEFRA).</li> <li>Weather variables derive from ECMWF ERA-Interim (global re-analysis dataset)</li> </ul>
Model Data for "Increased Ocean Heat Convergence into the High Latitudes with CO2-Doubling Enhances Polar-Amplified Warming."
<p>This is the data repository for the following published study:</p> <p>Singh HA, Rasch PJ, and Rose BEJ. "Increased Ocean Heat Convergence into the High Latitudes with CO<sub>2</sub>-Doubling Enhances Polar-Amplified Warming", Geophysical Research Letters, Oct 2017, doi: 10.1002/2017GL074561.</p> <p>Please see 'README.txt' for further details on the data files included.</p>
Code and supplementary plots for "Flexible distributed lag models for count data using mgcv"
<p>R code and supplementary plots accompanying the paper: "Flexible distributed lag models for count data using mgcv".</p>
Data and code for the paper "Precision Groundwater Modeling: when cokriging meets evolutionary and iterative algorithms"
<ul> <li>exemplary dataset for 2019 yearly water table measurements in Northeaster Italy</li> <li>MATLAB code for the pre-processing GA-driven and the post-processing iterative validation part</li> </ul>
Data and code for "Assessment of the accuracy in UV index modelling using the UVIOS2 system during the UVC-III campaign"
<p>Datasets nd codes that have been used for the paper with tittle "Assessment of the accuracy in UV index modelling using the UVIOS2 system during the UVC-III campaign"</p>
Research data - taxonomy for revenue models of platform business models (C2E)
<p>Research data to develop a taxonomy of revenue models for platform business models following a conceptual-to-empirical approach.</p>
Research data - taxonomy for platform revenue models (E2C)
<p>Research data to develop a taxonomy of revenue models for platform business models following an empirical-to-conceptual approach.</p>
Data package for paper "DeepGlow: an efficient neural-network emulator of physical afterglow models for gamma-ray bursts and gravitational-wave events
<p>This is a data package accompanying the paper "DeepGlow: an efficient neural-network emulator of physical afterglow models for gamma-ray bursts and gravitational-wave events".</p>
Raw dataset and additional data for article "Nonmotor symptoms associated with progressive loss of dopaminergic neurons in a mouse model of Parkinson's disease"
<p>Dataset from the project investigating the presence of nonmotor symptoms of Parkinson's disease in a mouse model of progressive loss of dopaminergic neurons (namely,TIF-IADATCreERT2 strain). Mice were tested for executive and cognitive functions (males: Operant Sensation Seeking test, OSS; females: Probabilistic Reversal Learning Task in Intellicages), olfactory acuity (males: buried food test), saccharin preference (males and females), and motor performance (males and females: test using CatWalk apparatus).</p><p>The dataset includes files used to perform statistical analyses but their names may vary from the ones used in the scripts. For the purpose of recreating our analyses, please refer to the GitHub page, where both scripts and input data file names (in 'Raw data files' section) are compliant: https://github.com/annaradli/tif-pd-behavior.</p><p><strong>Description of files:</strong></p><p><i>Raw data files:</i></p><ul><li>animals_info.csv - animals data: genotype, sex, age, Intellicage tag identifier</li><li>catwalk_run_statistics_all_females.csv - data recorded in CatWalk apparatus for females</li><li>catwalk_run_statistics_all_males.csv - data recorded in CatWalk apparatus for males</li><li>females_weight_raw_data_revised.csv - females' body weight (revised for containing Polish words)</li><li>intellicage_raw_data.csv - data recorded in IntelliCage exported to .csv format</li><li>intellicage_raw_data_R.RData - data recorded in IntelliCage in .RData format</li><li>males_weight_raw_data.csv - males' body weight</li><li>olfactory_time_digging_raw_data.csv - time to start digging at the right place in the buried food test</li><li>olfactory_time_retrieve_raw_data.csv- time to retrieve cracker in the buried food test</li><li>oss_raw_data.csv - data recorded in the OSS test</li><li>saccharin_preference_males_raw_data.csv - saccharin preference test results for males</li><li>snvta_cells_count.csv - number of TH+ cells in SN and VTA in male mice (3+3) 14 weeks after tamoxifen treatment</li></ul><p><i>Additional data files:</i></p><ul><li>all_anova.xlsx - summary of two-way ANOVAs of all behavioral tests and weight measurements for males and females</li><li>catwalk_complete.xlsx - CatWalk complete dataset with datapoints</li><li>catwalk_correlation_between_paws.xlsx - correlation coefficients of CatWalk parameters between the left and right paws</li><li>catwalk_reduced.xlsx - CatWalk parameters used in linear regression model reduction of data</li><li>intelli.xlsx - IntelliCage data summarized in bins</li><li>oss.xlsx - operant sensation-seeking data</li></ul><p>v2 contains the corrected 'animals_info.csv' file without an unnecessary column.</p><p>v3 has a revised version of file containing females' weight measurements and also added a file with midbrain cell counts</p><p>v4 has a whole section of 'Additional data files' added</p>
Data and code for: Acute heat priming promotes short-term climate resilience of early life stages in a model sea anemone
<p>Across diverse taxa, sublethal exposure to abiotic stressors early in life can lead to benefits such as increased stress tolerance upon repeat exposure. This phenomenon, known as hormetic priming, is largely unexplored in early life stages of marine invertebrates, which are increasingly threatened by anthropogenic climate change. To investigate this phenomenon, larvae of the sea anemone and model marine invertebrate <em>Nematostella vectensis</em> were exposed to control (18°C) or elevated (24°C, 30°C, 35°C, or 39°C) temperatures for 1 hour at 3 days post-fertilization (DPF), followed by return to control temperatures (18°C). The animals were then assessed for growth, development, metabolic rates, and heat tolerance at 4, 7, and 11 DPF. Priming at intermediately elevated temperatures (24°C, 30°C, or 35°C) augmented growth and development compared to controls or priming at 39°C. Indeed, priming at 39°C hampered developmental progression, with around 40% of larvae still in the planula stage at 11 DPF, in contrast to 0% for all other groups. Total protein content, a proxy for biomass, and respiration rates were not significantly affected by priming, suggesting metabolic resilience. Heat tolerance was quantified with acute heat stress exposures, and was significantly higher for animals primed at intermediate temperatures (24°C, 30°C, or 35°C) compared to controls or those primed at 39°C at all time points. To investigate a possible molecular mechanism for observed changes in heat tolerance, the expression of heat shock protein 70 (HSP70) was quantified at 11 DPF. Expression of HSP70 significantly increased with increasing priming temperature, with the presence of a doublet band for larvae primed at 39°C, suggesting persistent negative effects of priming on protein homeostasis. Interestingly, primed larvae in a second cohort cultured to 6 weeks post-fertilization continued to display hormetic growth responses, whereas benefits for heat tolerance were lost; in contrast, negative effects of short-term exposure to extreme heat stress (39°C) persisted. These results demonstrate that some dose-dependent effects of priming waned over time while others persisted, resulting in heterogeneity in organismal performance across ontogeny following priming. Overall, these findings suggest that heat priming may augment the climate resilience of marine invertebrate early life stages via the modulation of key developmental and physiological phenotypes, while also affirming the need to limit further anthropogenic ocean warming.</p>
ScienceDex guides
Understand access before you commit
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.