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7,378 results for “case”
Case study in Ouray (Colorado, USA)
<div>The dataset is located in Ouray, Colorade, USA. It is the point clouds collected by an Optech ILRIS-3D laser scanner at four scan positions in 2004 from Lato et al., 2013. The scanning time was about 15 min, the resolution was about 2 cm, and there was a total of 1,515,722 points. </div>
A case study of the Chesapeake Bay using the CAFE framework
<p>This file includes nutrient budget data for the Chesapeake Bay watershed, organized by county, year, and system.</p>
Modelling input data for the case studies of the paper "Strategic bidding in light-robust day-ahead electricity markets".
<p><span>This data package includes the modelling input data to replicate the results of the case studies included in the paper "Strategic bidding in light-robust day-ahead electricity markets". </span></p> <p><span>This supplementary data package includes the following files:</span></p> <p><span><span>-<span> </span></span></span><span>Meta Data – Input data: Dataset containing the input data for the strategic bidding behavior problem. It includes bids from conventional, demand and stochastic players and the scenarios for system imbalance and real-time production.</span></p> <p><span><span>-<span> </span></span></span><span>Readme.txt: Includes a detailed description of the data packages</span></p> <p><span> </span></p> <p><span>Sources of data:</span></p> <p><span>* Ordoudis, C., Pinson, P., Morales, J. M., & Zugno, M. (2016). An updated version of the IEEE RTS 24-bus system for electricity market and power system operation studies. Technical University of Denmark.</span></p> <p><span>* Silva-Rodriguez, L., Sanjab, A., Fumagalli, E., Virag, A., & Gibescu, M. (2022). A light robust optimization approach for uncertainty-based day-ahead electricity markets. Electric Power Systems Research, 212, 108281. https://doi.org/10.1016/J.EPSR.2022.108281<span> </span></span></p> <p><span>* Derived (scaled down) from Elia. (2024). Open data. Retrieved from https://www.elia.be/en/grid-data/open-data<span> </span></span></p> <p><span>* Own data<span> </span></span></p> <p><span><span> </span></span></p>
Epidemiological Database of HIV/AIDS Cases (1983-2023) in Peru
<p>The database compiles aggregated time series data from the National Center for Epidemiology, Disease Prevention, and Control (CDC) of Peru. This comprehensive national data, collected annually, originates from the National Epidemiological Surveillance Network and the system's reporting channels. Time series have been constructed in parallel, covering the period from 1983 to 2023.</p> <div>The database includes the number of nationally reported HIV cases, organized annually. These cases are of individuals who have had two reactive screening tests (a rapid HIV test and/or an enzyme-linked immunosorbent assay [ELISA] for HIV) or a positive confirmatory test. Cases of HIV at the AIDS stage are also included, categorized by the year of diagnosis according to the national standard case definition, which includes clinical and laboratory criteria such as a low CD4 count (stage 3) and the presence of an opportunistic disease (stage C).</div>
Data from: Socio-ecological drivers of long-term ecosystem carbon stock trend: An assessment with the LUCCA model of the French case
Open the record for dataset details and reuse information.
Assessing the potential of camera traps for estimating activity pattern compared to collar-mounted activity sensors: A case study on Eurasian lynx (Lynx lynx) in South-Eastern Norway
<div> <div> <div> <div> <p>The diel activity patterns of animals convey information about physiology, ecological niches and animal behaviour relevant for both applied conservation and more theoretical research. However, these patterns are challenging to study in the field. The current gold-standard approach to quantify the movements and activity patterns of medium to large wildlife species is to use Global Positioning Systems (GPS) collars equipped with activity sensors (e.g., accelerometers). A more recent approach consists of inferring activity patterns from the time-stamped pictures of wildlife obtained from the camera traps now routinely used in wildlife monitoring projects. However, few studies have attempted to validate estimates of activity patterns obtained from camera traps against those obtained from activity sensors. In this study, we compared the diel activity pattern of the Eurasian lynx Lynx lynx inferred from detections by a network of over 300 camera traps active between 2010 and 2020, to activity patterns obtained from 18 GPS-collared lynx (8 females, 10 males) equipped with 2-axis accelerometer sensors, in the same area of southern Norway. Our results suggest that camera traps can be used to estimate diel activity curves that are comparable to those obtained from accelerometers. In our study 75 detections were sufficient to approximate the diel activity pattern obtained from accelerometer. Subsampling indicated that a low number of detections results in a coarser approximation of the diel activity pattern.</p> </div> </div> </div> </div>
Data from: Evolutionary déjà vu? A case of convergent evolution in an ant-plant association
<p>Obligatory ant-plant symbioses often appear to be single evolutionary shifts within particular ant lineages; however, convergence can be revealed once natural history observations are complemented with molecular phylogenetics. Here we describe a remarkable example of convergent evolution in an ant-plant symbiotic system. Exclusively arboreal, <em>Myrmelachista</em> species can be generalized opportunists nesting in several plant species or obligately symbiotic, live-stem nesters of a narrow set of plant species. Instances of specialization within <em>Myrmelachista</em> are known from northern South America and throughout Middle America. In Middle America, a diverse radiation of specialists occupies understory treelets of lowland rainforests. The morphological and behavioural uniformity of specialists suggests that they form a monophyletic assemblage, diversifying after a single origin of specialization. Using ultraconserved element phylogenomics and ancestral state reconstruction, we show that shifts from opportunistic to obligately symbiotic evolved independently in South and Middle America. Furthermore, our analyses strongly support a remarkable case of convergence within the Middle American radiation, with two independently evolved specialist clades, arising nearly simultaneously from putative opportunistic ancestors during the late Pliocene. This repeated evolution of a complex phenotype suggests similar mechanisms behind trait shifts from opportunists to specialists, generating further questions about the selective forces driving specialization.</p>
Datasets and source code for case study on Pomerini, Tanzania
Open the record for dataset details and reuse information.
Geostatistical inverse modeling with large atmospheric data: data files for a case study from OCO-2
<p>The files in this data repository provide the inputs required to run an inverse modeling case study. This case study will estimate CO<sub>2</sub> fluxes across North America for July 2015 using synthetic observations that have been created to resemble observations from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite.</p> <p>This data repository is specifically linked to a GitHub code repository (http://doi.org/10.5281/zenodo.3241524 or <a href="https://github.com/greenhousegaslab/geostatistical_inverse_modeling">https://github.com/greenhousegaslab/geostatistical_inverse_modeling</a>). That GitHub repository provides scripts for constructing a geostatistical inverse model that will estimate greenhouse gas fluxes or air pollution emissions using atmospheric observations. The GitHub repository includes a case study that can be run out-of-the-box; the case study provides users an opportunity to test out and explore the inverse modeling code. All of the input data files for that case study are provided for download here.</p> <p>Here is a brief explanation of the different files included in this data repository, but refer to the linked GitHub repository for greater details. All of these files are in a ".mat" file that can be read into Matlab using the <em>load</em> function or can be read into R using the <em>R.matlab</em> package.</p> <ul> <li><strong>H.tar.gz</strong>: This tar file contains the <strong>H</strong> matrices or sensitivity matrices required by the inverse model. These inputs were generated using the Stochastic Time-Inverted Lagrangian Transport (STILT) model as part of NOAA's CarbonTracker-Lagrange program (<a href="https://www.esrl.noaa.gov/gmd/ccgg/carbontracker-lagrange/">https://www.esrl.noaa.gov/gmd/ccgg/carbontracker-lagrange/</a>). The <strong>H</strong> matrix is too large to store in a single file. We have therefore split up the matrix into 328 different files (all contained within H.tar.gz). Each file contains a vertical strip of the <strong>H</strong> matrix that corresponds to a different time period of fluxes to be estimated as part of the inverse model.</li> <li><strong>Z.mat</strong>: This file contains the synthetic OCO-2 observations used in the case study. </li> <li><strong>areas_us.mat</strong>: This file lists the area of each model grid box used in the case study in units of meters<sup>2</sup>. This file only includes grid box area for model grid boxes that fall within the continental United States. We estimate CO<sub>2</sub> fluxes across terrestrial North America on a 1 degree latitude by 1 degree longitude grid as part of the case study. Each of these model grid boxes will have a different area, depending upon the latitude of that model grid box. </li> <li><strong>distmat.mat</strong>: This file contains a matrix that lists the distance (in kilometers) between the center of each model grid box used in the case study. </li> <li><strong>land_mask.mat</strong>: We only estimate CO<sub>2</sub> fluxes for terrestrial regions of North America as part of the case study. This land mask is used to convert the fluxes estimated by the inverse model to a latitude-longitude grid that can then be plotted.</li> <li><strong>H_all_OCO2.mat</strong>: This file contains the H matrices summed across differnt time periods. I.e., this file is the sum of all the individual H files contained within H.tar.gz.</li> <li><strong>Xvar.tar.gz</strong>: This file contains different environmental variables from ERA5 meteorology that have been reformatted to match the H footprint matrices. These different variables can be used as predictors of CO2 fluxes in an inverse model. The different variables included in this file are as follows: <ul> <li>Xvar_e.mat Evaporation</li> <li>Xvar_msdwswrf.mat Mean surface downward short-wave radiation flux</li> <li>Xvar_q.mat Specific humidity</li> <li>Xvar_stl1.mat Soil temperature level 1</li> <li>Xvar_stl3.mat Soil temperature level 3</li> <li>Xvar_swvl1.mat Volumetric soil water layer 1</li> <li>Xvar_t2m.mat 2 metre temperature</li> <li>Xvar_tp.mat Total precipitation</li> <li>Xvar_mer.mat Mean evaporation rate</li> <li>Xvar_pev.mat Potential evaporation</li> <li>Xvar_r.mat Relative humidity</li> <li>Xvar_swvl3.mat Volumetric soil water layer 1</li> <li>Xvar_tcc.mat Total cloud cover</li> </ul> </li> </ul>
Where is the heat threat in a city? Different perspectives on people-oriented and remote sensing methods: the case of Prague
<p>This is supplementary data for a paper called ‘Where is the heat threat in a city? Different perspectives of people-oriented and remote sensing methods, the case of Prague’ to be submitted to the journal Heliyon. Dataset contains three folders:</p> <ol> <li><strong>LST</strong> <br>– Layer Landsat_ecostress_data = vector polygon layer containing fishnet which includes values from 15 sattelite images from 3 different sources - ECOSTRESS, Landsat 8 and Landsat 9<br>Attribute percent_av contains mean percentile from all 15 images</li> <li><strong>Participatory mapping</strong><br>Raw data from participatory mapping campaign held on August 2022 in Prague-Holešovice</li> <li><strong>Thermal walk</strong><br>Layer Data_app = Raw data from thermal walk held on August 3rd 2022 (Declared time in the attribute table is UTC)<br>Layer DataApp_corr = Corrected coordinates from thermal walk (For these corrections, precisely prepared routes were used. Data were post-processed using an algorithm for a minimization of the distance between the measured and expected point location. The measured point was moved using its normal on-route position and his distance was compared with the previous point. If the distance was larger than 115% of expected, the point was moved closer, and when the distance was smaller than 85% of expected, the point was moved forward.)</li> </ol> <p> </p> <p><em>Acknowledgements: This work was supported by the Faculty of Science, Palacký University Olomouc internal grant IGA_PrF_2024_022 – Novel approaches to studying the human thermal environment in urban areas. This work was also supported by Strategy AV21 project ‘City as Lab of changes’, financed by the Czech Academy of Sciences.</em></p>
Fig 2 in Opportunities and its challenges in fish production: The case of Lake Koka, East Showa Zone, Oromia National Regional State, Ethiopia
Fig 2: Expansion of water hyacinth in Lume district at Koka Lake, February, 2020
Fig 1 in Opportunities and its challenges in fish production: The case of Lake Koka, East Showa Zone, Oromia National Regional State, Ethiopia
Fig 1: Targeted fish species at Lake Koka
FLIP-KG: Enriching Automated Knowledge Graph Extraction with Tacit Knowledge. The Case of Lyrical Implicatures within Poems
<p>FLIP-KG: Enriching Automated Knowledge Graph Extraction with Tacit Knowledge. The Case of Lyrical Implicatures within Poems. Dataset for the task force "Vulcan" from ISWS 2024 led by Aldo Gangemi and Andrea Poltronieri</p>
Figure 2 in From Eradication to Containment: Invasion of French Polynesia by Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) and Releases of Two Natural Enemies: A 17-Year Case Study
Figure 2. Monthly captures of B. dorsalis in methyl eugenol traps on Moorea.
Data from: Challenging trophic position assessments in complex ecosystems: calculation method, choice of baseline, trophic enrichment factors, season and feeding guild do matter. A case study from Marquesas Islands coral reefs
<p>Assessments of ecosystem functioning are a fundamental ecological challenge and an essential foundation for ecosystem-based management. An understanding of species trophic positions (TP) is essential to characterize food web architecture. However, despite the intuitive nature of the concept, empirically estimating TP is a challenging task due to the complexity of trophic interaction networks. Various alternative methods are proposed to assess TPs, including different approaches to account for the different sources of organic matter at the base of the food web (the "baseline"). However, it is often not clear which methodological approach and which baseline choices are the most reliable. Using an ecosystem-wide assessment of a tropical reef (Marquesas Islands, French Polynesia, with available data for 70 coral reef invertebrate and fish species), we tested whether different commonly used TP estimation methods yield similar results and, if not, whether it is possible to identify the most reliable method. We found significant differences in TP estimates of up to 1.7 TP for the same species, depending on the method and the baseline used. When using bulk stable isotope data, the choice of the baseline significantly impacted TP values. Indeed, while δ<sup>15</sup>N values of macroalgae led to consistent TP estimates, those using phytoplankton generated unrealistically low TP estimates. The use of a conventional enrichment factor (i.e. 3.4 ‰) or a "variable" enrichment factor (i.e. according to feeding guilds) also produced clear discrepancies between TP estimates. Regarding the use of different calculation methods, TPs obtained with δ<sup>15</sup>N values of source amino acids (compound specifics isotope analysis) were close to those assessed with macroalgae, but evidenced the opposite seasonal pattern, with significantly lower TPs in winter than in summer for the majority of assessed species, with particularly pronounced differences for lower TP species. We use the observed differences to discuss possible drivers of the diverging TP estimates and the potential ecological implications.</p>
The evaluation of climate change competitiveness via DEA models and Shannon's entropy: EU regions case
<p>Supplementary materials for the article titled “The evaluation of climate change competitiveness via DEA models and Shannon’s entropy: EU regions case”.</p> <p><span>The data was collected under project provided by the National Science Centre, Poland; Grant No. 2019/35/B/HS5/01548.</span></p> <div> <div> <div> <p> </p> </div> </div> </div> <p> </p>
Fig 3 in Opportunities and its challenges in fish production: The case of Lake Koka, East Showa Zone, Oromia National Regional State, Ethiopia
Fig 3: Waste disposal canal to Lake Koka from Ethiopian tannery, February, 15/2020
Considerations for high-resolution regional meteorological wind modelling over complex terrain: a typhoon case study for assessing forestry damage (data)
<p>This is the experiment data.</p> <p>The Weather Research and Forecasting (WRF) model is a popular and easily used as a numerical weather prediction (NWP) model, but configuring WRF to produce accurate results can be time-consuming. This is especially so when simulating extreme events, over complex terrain, or at high resolutions. In this study, a strong wind event from Tropical Cyclone (TC) Thad in year 1981 was simulated at 200 m resolution over an experiment forest in a mountainous region of Hokkaido island, Japan. The simulation configuration is challenging, in order to cover a larger area to produce a TC with appropriate track and intensity, and at the same time to resolve the smallest domain of sub-km grid spacing with computational stability. A mixed nesting method was applied with two-way nesting up for the first three domains, followed a separate simulation over the smallest domain. The mixed method could produce 10 min wind speed distributions similar to that of the full simulation with two-way nesting of all four domains, if a 30-minute boundary update interval was used for the separate simulation. Mixed nesting improves the efficiency of the simulation process, since the larger phenomenon scale and smaller human impact scale can be tuned separately. </p>
FIG. 1 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest
FIG. 1. — Number of bryophyte species in the four types of substrates considered.
Data for publication of "Gaussian process regression-based Bayesian optimisation (G-BO) of model parameters - a WRF model case study of southeast Australia heat extremes"
<p>Implementation of Gaussian process regression-based Bayesian optimisation (G-BO) using the emcee package (<a href="https://emcee.readthedocs.io/en/stable/" rel="nofollow">https://emcee.readthedocs.io/en/stable/</a>).</p> <p>For more information about the implementation of G-BO in optimising the Weather Research and Forecasting (WRF) model parameters, please refer to the paper - <a href="https://essopenarchive.org/doi/full/10.22541/essoar.171292045.52489731" rel="nofollow">Gaussian process regression-based Bayesian optimisation (G-BO) of model parameters - a WRF model case study of southeast Australia heat extremes</a>.</p> <p><code>G-BO_script.ipynb</code> implements the GPR-based Bayesian optimisation using the Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler.</p> <ul> <li><strong>QMC_sobol_samples</strong>: This file contains the 128 parameter samples across the parameter space of three sensitive parameters utilizing the Quasi Monte-Carlo (QMC) Sobol sequence design.</li> <li><strong>nmae_all_128_ens_T_Rh</strong>: This file contains the normalised mean absolute error (NMAE) values of temperature (T) and relative humidity (Rh) of the 128 parameter sample WRF simulations. For more details, please refer to <a href="https://essopenarchive.org/doi/full/10.22541/essoar.171292045.52489731" rel="nofollow">this link</a>.</li> </ul>
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.