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7,195 results for “SET”
Selecting for infectivity across metapopulations can increase virulence in the social microbe Bacillus thuringiensis:data set.
<p>Passage experiments that sequentially infect hosts with parasites have long been used to manipulate virulence. However, for many invertebrate pathogens passage has been applied naively without a full theoretical understanding of how best to select for increased virulence and this has led to very mixed results. Understanding the evolution of virulence is complex because selection on parasites occurs across multiple spatial scales with potentially different conflicts operating on parasites with different life-histories. For example, in social microbes, strong selection on replication rate within hosts can lead to cheating and loss of virulence, because investment in public goods virulence reduces replication rate. </p> <p>In this study<em> </em>we tested how varying mutation supply and selection for infectivity or pathogen yield (population size in hosts) affected evolution of virulence against resistant hosts in the specialist insect pathogen <em>Bacillus thuringiensis</em>, aiming to optimize methods for strain improvement against a difficult to kill insect target. We show that selection for infectivity using competition between sub-populations in a metapopulation prevents social cheating, acts to retain key virulence plasmids and facilitates increased virulence. Increased virulence was associated with reduced efficiency of sporulation, and possible loss of function in putative regulatory genes but not with altered expression of the primary virulence factors. Selection in a metapopulation provides a broadly applicable tool for improving the efficacy of biocontrol agents. Moreover, a structured host population can facilitate artificial selection on infectivity, while selection on life history traits such as faster replication or larger population sizes can reduce virulence in social microbes.</p>
Data set discussed in "Beyond Fortune 500: Women in a Global Network of Directors"
<p>Bipartite graph of directors and companies. Generated from information on the Financial Times website (<a href="https://markets.ft.com/data/equities/results">https://markets.ft.com/data/equities/results</a>), retrieved on 17 September 2016.</p> <p>Blank fields are used for missing data.</p> <p><strong>comp_nodes.csv:</strong></p> <ul> <li>id: unique identifier</li> <li>ft_country: name of the country</li> <li>ft_sector: segment of the economy in which a company operates</li> <li>ft_industry: specific business (i.e., subset of sector) in which a company operates</li> <li>ft_employees_num: number of company's employees. "NA" if the vertex represents a person or if the company's number of employees is unknown.</li> </ul> <p><strong>comp_people_edges.csv:</strong></p> <ul> <li>person_id:</li> <li>comp_id: company identifier. It matches the identifier in comp_nodes.csv</li> </ul> <p><strong>people_one_mode_edges.csv:</strong></p> <p>Edges in the one-mode projection, in which two directors are connected if and only if they sit together on at least one board. Numbers correspond to the identifiers in unique_people_nodes.csv.</p> <p><strong>unique_people_nodes.csv:</strong></p> <ul> <li>ID: unique identifier</li> <li>age: years of age</li> <li>gender_base: "Male" or "Female"</li> </ul>
Water temperature in the hidden, subglacial lake at Uruguay Island, Antarctic Peninsula region, 2020-2021, and additional data sets.
The dataset contains temperature measurements in a small subglicer (hidden) lake of Antarctic Peninsula region at several levels of depth. The measurements cover almost a full year and provide an understanding of the temperature and hydrological regime of the water body. Weather measurement data and statistics is provided additionally.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - BISC1 SET Surface Water level data from in Biscayne National Park, Florida, USA (2016-2025)
Surface water level data (m) was collected in Biscayne National Park (BISC) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2016 to 2025 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This dataset belongs to Site 1, known as BISC-SET-1 or BISC1. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - BISC2 SET Surface Water level data from in Biscayne National Park, Florida, USA (2017-2025)
Water level data (m) was collected in Biscayne National Park (BISC) by the National Park Service - South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017-2025 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This dataset belongs to Site 2, known as BISC-SET-2 or BISC2. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - SARI SET Surface Water level data from Salt River Bay National Historical Park and Ecological Preserve, St. Croix, US Virgin Islands.
Surface water level data (m) was collected in Salt River Bay National Historic Park and Ecological Preserve (SARI) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - Mary's Point SET Surface Water level data from Virgin Islands National Park, St. John, US Virgin Islands
Surface water level data (m) was collected in Virgin Islands National Park, Mary's Point (MARY) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - Water Creek SET Surface Water level data from Virgin Islands National Park, St. John, US Virgin Islands
Surface water level data (m) was collected in Virgin Islands National Park, Water Creek (WACR) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
California's Central Valley Project Improvement Act Predation Contact Point Study - 2022: Predator-prey interactions under low artificial lighting in a laboratory setting
The highest rates of piscivorous predation in the field have been recorded during crepuscular light levels associated with sunrise and sunset or artificial lighting at night (ALAN). We conducted a laboratory study where groups of predator-naïve, hatchery-raised juvenile rainbow trout (Oncorhynchus mykiss) were exposed to natural-origin piscivorous largemouth bass (Micropterus salmoides) under three light treatments representative of brighter crepuscular periods or direct ALAN illumination (“high” treatment), dimmer crepuscular periods or sky glow from ALAN (“medium” treatment), and night or no ALAN (“low” treatment). We then statistically evaluated potential associations between light treatment, prey group cohesion, and predator activity.
Survey of pond habitats and aquatic diversity of Madison, Wisconsin from May to Aug 2019 and 2020 Data Set
1) Urbanization may lead to changes in local richness (alpha diversity) or in community composition (beta diversity), although the direction of change can be challenging to predict. For instance, introduced species may offset the loss of native specialist taxa, leading to no change in alpha diversity in urban areas, but decreased beta diversity (i.e., more homogenous community structure). Alternatively, because urban areas can have low connectivity and high environmental heterogeneity between sites, they may support distinct communities from one another over small geographic distances. 2) Wetlands and ponds provide critical ecosystem services and support diverse communities, making them important systems in which to understand consequences of urbanization. To determine how urban development shapes pond community structure, we surveyed 68 ponds around Madison, Wisconsin, USA, which were classified as urban, greenspace, or rural based on surrounding land use. We evaluated the influence of local abiotic factors, presence of nonnative fishes, and landscape characteristics on alpha diversity of aquatic plants, macroinvertebrates, and vertebrates. We also analyzed whether surrounding land cover was associated with changes in community composition and/or the presence of specific taxa. 3) We found a 23% decrease in mean richness (alpha diversity) from rural to urban pond sites, and a 15% decrease in richness from rural to urban greenspace pond sites. Among landscape factors, observed pond richness was negatively correlated with adjacent developed land and mowed lawns, as well as greater distances to other waterbodies. Among pond level factors, habitat complexity was associated with increased richness, while the presence of invasive fish was associated with decreased richness. 4) Beta diversity was relatively high for all ponds due to turnover in composition between sites. Urban ponds supported more introduced species, lacked a subset of native species found in rural ponds,
Change in marsh surface elevation measured with a Surface Elevation Table (SET) at control and fertilized plots at Spartina alterniflora, S.patens and Typha sp. marshes, Plum Island Ecosystems LTER, MA (1999-2025).
A Surface Elevation Table (SET) is used to measure changes in the elevation of the marsh surface at three long term marsh control and fertilization experimental research sites. The sites include one Typha-dominated brackish marsh, one Spartina alterniflora-dominated salt marsh, and one S. patens-dominated salt marsh. Sites are located on the Rowley and upper Parker Rivers in the Plum Island Ecosystems (PIE) LTER.
Surface Elevation Table (SET) data (pin heights) from control and fertilized plots at Spartina alterniflora, S. patens and Typha sp. marshes, Plum Island Ecosystems LTER, MA (1999-2025).
A Surface Elevation Table (SET) is used to measure changes in the elevation of the marsh surface at three long term marsh fertilization experimental research sites. The sites include one Typha-dominated brackish marsh, one Spartina alterniflora-dominated salt marsh, and one S. patens-dominated salt marsh. Sites are located on the Rowley and upper Parker Rivers in the Plum Island Ecosystems (PIE) LTER site.
Surface Elevation (SET) Data for Brownsville Forest at the Virginia Coastal Reserve, 2019-2025
This dataset contains data from Surface Elevation Tables (SETs) located in the Brownsville Forest at the Virginia Coastal Reserve. These research plots were set up in 2019 as a part of a larger forest disturbance project. Marker Horizons and Shallow SETs were installed in 2020 but have not yet been measured. Tyler Messerschmidt has made all measurements of these SETs
Software Developer Expertise GitHub and Stack Overflow data sets
<p>Cross-Platform Software Developer Expertise Learning by Norbert Eke</p> <p>This data set is part of my Master's thesis project on developer expertise learning by mining Stack Overflow (SOTorrent) and Github (GHTorrent) data. Check out my portfolio website at norberte.github.io</p>
Data set for Global quantitative synthesis of ecosystem functioning across climatic zones and ecosystem types
<p>Dataset used in the publication: " Global quantitative synthesis of ecosystem functioning across climatic zones and ecosystem types". The dataset gathers estimates of ecosystem standing stocks (biomass, organic carbon, detritus), fluxes (GPP, ER, NEP) and process rates (decomposition and carbon uptake rates) for eight broad ecosystem types (forest, grassland, agroecosystem, desert, stream, lake, pelagic and benthic marine ecosystems) in five broad climatic zones (arctic, boreal, arid, temperate, tropical, arid).</p> <p>The scripts to produce the figures and the statistics of the publication are released along with the txt version of the data, which file is uploaded when running the script.</p>
Obtaining Problem Statements and Transformation into Ideas - Workshop Data Set
<p>In order to enable members of a socio-technical evolutionary-teal organization to design their technical component, we conducted a workshop that structures the collaboration between technical trained participants and non-trained participants. F general challenges in the form of “problem statements” have been gathered. Afterwards, these are transformed into ideas for organizational and technical change.</p> <p>The design thinking workshop is set up as a standalone, roughly five-hour group discussion, following the principles of participatory design. It has been recorded in video and this data set contains a textual German transcript and transcripts of the moderation cards that have been created during the workshop.</p> <p>We hope that the material can be used to (a) comprehend the interpretation used in our qualitative research, (b) to adapt the workshop model by other volunteers of our case study Viva con Agua de St. Pauli e.V. (https://www.vivaconagua.org/), and (c) investigate other interesting research questions.</p>
Input files for Dispa-SET for the JRC report "Power System Flexibility in a variable climate"
<p><strong>Input files for Dispa-SET for the JRC report "Power System Flexibility in a variable climate"</strong></p> <p>Here you can find the input files needed to reproduce the results of the <a href="https://doi.org/10.2760/75312">report</a>:</p> <pre><code>De Felice, M., Busch, S., Kanellopoulos, K., Kavvadias, K. and Hidalgo Gonzalez, I., Power system flexibility in a variable climate, EUR 30184 EN, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-76-18183-5 (online), doi:10.2760/75312 (online), JRC120338. </code></pre> <p>The results in the report are generated with the Dispa-SET power system model, available and explained at <a href="https://www.dispaset.eu/">www.dispaset.eu</a>.</p> <p>A description of the data sources with the references can be found into the report.</p> <p><strong>How to use this dataset</strong></p> <p>This dataset can be used as input data for the Dispa-SET model. We refer to the <a href="https://doi.org/10.2760/75312">report</a> and the <a href="https://www.dispaset.eu">official model documentation</a> for information about the data and the model.</p> <p><strong>Description of the dataset</strong></p> <p>The file <code>EnVarClim.yml</code> is a template of the YAML configuration file used by Dispa-SET. To run a specific climate year the <code>XXXX</code> present in some input files must be replaced with the year.</p> <p><strong>Availability factors</strong></p> <p>In the folder <code>AvailabilityFactors</code> there are the availability factors (from 0 to 1) for the power plants and the renewable generation. There is a subfolder for each simulated zone and inside a file for each climate year: from <code>emh_and_cc_availability_1990.csv</code> to <code>emh_and_cc_availability_2015.csv</code>.</p> <p><strong>Cross-border transmission</strong></p> <p>In the folder <code>DayAheadNTC</code> there is the file <code>merged_constant_NTC.csv</code> containing the capacity (in MW).</p> <p><strong>NOTE</strong>: due to an error in the pre-processing code there are some additional lines for the Western Balkans countries ending with a <code>1</code> (e.g. <code>GR -> MK1</code>). Those lines are ignored by the model because are not associated to any simulated zone.</p> <p><strong>Cross-border historical flows</strong></p> <p>In the file <code>CC_L_flows.csv</code> under the folder <code>Flows</code> are contained the hourly flows between the simulated zones and their neighbours (RU, TR, UA).</p> <p><strong>Fuel prices</strong></p> <p>In the folder <code>FuelPrices</code> are contained a set of files containing the hourly prices for the fuels (biomass, coal, lignite, gas, oil) and CO2 emissions. It is worth noting that in spite of their hourly resolution the time-series are constant through the year.</p> <p><strong>Hourly load</strong></p> <p>In the folder <code>Load_RealTime</code> there are hourly load time-series for each zone considering a different climate year. For the Western Balkans countries we use the same time-series for each climate year.</p> <p><strong>Outage factors</strong></p> <p>The files <code>CC_L_outages.csv</code> in the folder <code>OutageFactors</code> contain the outage factor (from 1, full outage, to 0) for the various generation units. Whenever a simulation zone is missing the model assumes the absence of outages.</p> <p><strong>Power plants data</strong></p> <p>In the folder <code>PowerPlants</code> there is a file named <code>CC_L_plants.mip.csv</code> for each simulated zone. The CSV files contain the data <a href="http://www.dispaset.eu/en/latest/data.html#power-plant-data">needed by Dispa-SET</a>.</p> <p><strong>Water storage levels</strong></p> <p>The folder <code>ReservoirLevel</code> contains the storage level (values from 0 to 1 relative to the size of the storage) for all the simulated zones. The levels have been computed for each climate year using a different inflow using the <a href="http://www.dispaset.eu/en/latest/mid_term.html">mid-term scheduler</a> recently implemented in Dispa-SET. For the Western Balkans countries we use the same time-series for each climate year.</p> <p><strong>Hydro-power inflows</strong></p> <p>In the folder <code>ScaledInflows</code> are contained the inflows used for the hydro-power generation. The values in the CSV files describes how much energy is available for hydro-power generation compared to the installed capacity.</p> <p><strong>Linked resources</strong></p> <ul> <li>Model output files:<strong> </strong>https://zenodo.org/record/3778133</li> <li>Source code for the figures: https://github.com/energy-modelling-toolkit/figures-JRC-report-power-system-and-climate-variability</li> </ul>
Thematic/Taxonomic Analogy Task Data Set
<p>A classic analogy paradigm (A:B::C:?) was developed to test children's understanding of thematic and taxonomic categorization of offd in children aged between 3 and 6 years old. Participants' level of food rejection disposition was also measured using the Child Food Rejection Scale (CFRS; Rioux, Lafraire, Picard, 2017) to determine how food rejection affects children's categorization ability in the food domain. </p> <p>Data sets for: children's food rejection scores, children's responses for thematic and taxonomic conditions of food categorization analogy task, and children's responses for stimuli identification task</p> <p>Supplemental material: Stimuli overview</p>
Labelled magnetic reconnection simulation data set
<p>Numerical simulations have been performed on Marconi at CINECA (Italy) under the ISCRA initiative. The corresponding data can be found at: <a href="https://doi.org/10.5281/zenodo.3935887">https://doi.org/10.5281/zenodo.3935887</a></p>
Data set and code supporting Marshall et al. 2020. No room to roam: King Cobras reduce movement in agriculture.
<p>Data and code used in the publication:</p> <p>Marshall, B.M., Crane, M., Silva, I., Strine, C.T., Jones, M.D., Hodges, C.W., Suwanwaree, P., Artchawakom, T., Waengsothorn, S., Goode, M. (2020). No room to roam: King Cobras reduce movement in agriculture. <em>Mov Ecol</em> <strong>8, </strong>33 (2020). https://doi.org/10.1186/s40462-020-00219-5</p> <p>Marshall, B.M., Crane, M., Silva, I., Strine, C.T., Jones, M.D., Hodges, C.W., Suwanwaree, P., Artchawakom, T., Waengsothorn, S., Goode, M. (2020). No room to roam: King Cobras reduce movement in agriculture. bioRxiv 2020.03.24.006676; doi: https://doi.org/10.1101/2020.03.24.006676</p> <p>Including: telemetry data, habitat shapefile and derived rasters, ISSF and JAGS model specification and results, code to reproduce analysis and generate figures. </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.