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72 results for “Collective Experiments”
Operating diagram of hatching module in Zoug jars, this system consists of a 300-litre temperature-controlled isothermal enclosure containing 10 one-litre Zoug jars, each able to accommodate several hundred eggs. An ascending current holds the eggs in suspension and carries the larvae to the surface. Another bottle connected to this device collects the larvae. The water circulating in the jars is independent of that used in the filtration circuit. A cooling unit and UV sterilizer complete the installation. in Reproduction of Zingel asper (Linnaeus, 1758) in controlled conditions: an assessment of the experiences realized since 2005 at the Besançon Natural History Museum
Operating diagram of hatching module in Zoug jars, this system consists of a 300-litre temperature-controlled isothermal enclosure containing 10 one-litre Zoug jars, each able to accommodate several hundred eggs. An ascending current holds the eggs in suspension and carries the larvae to the surface. Another bottle connected to this device collects the larvae. The water circulating in the jars is independent of that used in the filtration circuit. A cooling unit and UV sterilizer complete the installation.
Tracer gas (SF6 and Xe) migration data collected in 2018 as a part of the Diffusion experiment
<p>The dataset contains the results of the gas sampling performed following two injections of a mixture of the tracer gases (SF<sub>6</sub> and Xe). Two tracer gas injections were conducted in 2018 in Carroll, New Hampshire. Tracer gas injections were performed beneath the water table in two chemical-explosion generated cavities to compare the migration of sulfur hexafluoride (SF<sub>6</sub>) and xenon (Xe) through an explosion-generated fracture network and to study the influence of ground water on gas transport. A mixture of tracer gases (50% of SF<sub>6</sub> and 50% of Xe) was injected into each cavity. The first gas injection took place on September 8, 2018 and gas sampling continued until September 20, 2018. The second injection was performed on October 31, 2018 and gas sampling continued until November 8, 2018. The data were collected using an automatic sampling system. The data analysis was performed by using a gas chromatograph (Shimadzu GC-8A) with a Thermal Conductivity Detector (TCD). The gas concentrations measured at the surface from 4 sampling locations are provided.</p> <p>In addition, we provide measurements of the barometric pressure and temperature recorded using an Onset HOBO pressure transducer placed in the vicinity of the injection site approximately 1 m above ground and collecting pressure and temperature samples every 15 minutes for the duration of the experiment. The pressure and temperature data is provided in Tables S2 and S4.</p> <p> </p>
High-rate GNSS data collected during shake table experiment
<p>The dataset contains high-rate GNSS data collected during shake table experiment. A displacement-controlled experiment was designed and carried out at the UWM Olsztyn campus. The in-house developed shake table provided artificial dynamic displacements. The device induced forwardbackward uniaxial motion with dedicated speed and range, simulating a sin-wave displacement with constant frequency and amplitude. We have induced a few ~50-s long harmonic motions in the E-W direction of frequency in the 1-4 Hz range and amplitudes of 5-15 mm. A whole data collection period lasted approximately 1 hour, also including initial and inter excitations’ static periods.</p>
FIG. 12 in Récolnat Annotate-On: a tool to improve your experience with virtual collections
FIG. 12. — Workflow of the Annotate-On tool. A project allows the study, annotation and measurement of objects within images from the Récolnat database, URLs or any hard-drive to constitute a library. It uses one or more of the data models defined previously. Key words are used to select subsets within the library and the results can be exported to various external data processing tools.
FIG. 15 in Récolnat Annotate-On: a tool to improve your experience with virtual collections
FIG. 15. — Scales on Paris herbarium sheets. The vertical line on the left measures 10 mm, on the right the label of the linear barcodes measures 50 mm in length. In addition, the photos of the nomenclatural types have a scale.
FIG. 13 in Récolnat Annotate-On: a tool to improve your experience with virtual collections
FIG. 13. — Definition of a new character ("apex angle") for the model "Asparagus", here a physical measurement (angle unity: "°") into the group named "Cladode".
FIG. 9 in Récolnat Annotate-On: a tool to improve your experience with virtual collections
FIG. 9. — Annotation of a categorical character "apex shape" with the character state or nominal value "accuminate" (red arrow).
FIG. 1 in Récolnat Annotate-On: a tool to improve your experience with virtual collections
FIG. 1. — Examples of mean (M) and standard deviation (SD). Two characters: blade length (FII L) and blade width (fll- larg), number of measures (#). First line: image measures; second line: batch measures (global value).
Beyond Coverage Path Planning: Can UAV Swarms Perfect Scattered Regions Inspections? - Data Collected and Presented for the Experiments
<p>This dataset contains images collected (and processed) for the experiments of Beyond Coverage Path Planning: Can UAV Swarms Perfect Scattered Regions Inspections?" journal article, a work that defines a new path planning problem for UAVs - the Fast Inspection of Scattered Regions (FISR) - and introduces a novel method that deals with this problem - the multi-UAV Disjoint Areas Inspection (mUDAI) method. For the validation of the introduced methodology, two sets of real-world experiments were executed, one small-scale in Galatsi, Athens, were two mUDAI missions were depolyed, with two different optimization objectives for the data collection procedure (Mazimized Coverage Objective - MCO, and Balanced Coverage Objective - BCO), and one large scale in ZEP-Kissos, Thessaloniki, where a Coverage Path Planning (CPP) mission, and 2 mUDAI missions, one with a single and one with two UAVs, using both the MCO criterion for the data collection, were deployed. Regarding the CPP mission, both the collected images, and the processed results (to generate 2D, 3D, elevation, and plant health maps) are included.</p> <p>In this <a title="mUDAI - ChoosePath platform guide" href="https://sites.google.com/view/mudai-platform/" target="_blank" rel="noopener">page</a> you can find a guide for the on-line platform hosting demo instances of the algorithms used for the deployment of all experiments.</p> <p>In case you use this data, please cite the article:<br>(Article under review - more information to be included soon)</p>
Linked collectors and determiners for: Connecticut Agricultural Experiment Station Arthropod Collection.
Natural history specimen data linked to collectors and determiners held within, "Connecticut Agricultural Experiment Station Arthropod Collection". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/a42d07b3-e34d-4a65-b7e3-6aafa9f8f27b">https://bionomia.net/dataset/a42d07b3-e34d-4a65-b7e3-6aafa9f8f27b</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/a42d07b3-e34d-4a65-b7e3-6aafa9f8f27b">https://gbif.org/dataset/a42d07b3-e34d-4a65-b7e3-6aafa9f8f27b</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Bumble bees collected in a large-scale field experiment in power line clearings, southeast Norway.
Natural history specimen data linked to collectors and determiners held within, "Bumble bees collected in a large-scale field experiment in power line clearings, southeast Norway". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/78822c79-7646-448d-aac2-35700498c147">https://bionomia.net/dataset/78822c79-7646-448d-aac2-35700498c147</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/78822c79-7646-448d-aac2-35700498c147">https://gbif.org/dataset/78822c79-7646-448d-aac2-35700498c147</a>. Formatted as a Frictionless Data package.
Inorganic nitrogen, microbial ecoenzymatic activities, and organic matter in soils collected from the Monsoon Rainfall Manipulation Experiment (MRME), Sevilleta National Wildlife Refuge, New Mexico during the 2014 growing season
Drylands are characterized by a pulse dynamics framework in which episodic rain events trigger brief pulses of biological activity and resource availability that regulate primary production in these ecosystems. Relatively small rain events can stimulate microbial processes like decomposition that release inorganic nitrogen needed by plant processes, which typically also depend on soil moisture received from larger rain events. Little is known how changes in rainfall patterns may affect plant available nitrogen in dryland soils, particularly across temporal scales. Therefore, we conducted a study to examine the daily and seasonal responses of plant available nitrogen to rain events that differed in size and frequency throughout a summer monsoon in a northern Chihuahuan Desert grassland located in the Sevilleta National Wildlife Refuge, New Mexico, USA. This data package, which accompanies an associated manuscript (Brown et al. 2022), contains measurements of inorganic nitrogen, nitrogen-acquiring microbial ecoenzymatic activities, and organic matter in soils collected from the Monsoon Rainfall Manipulation Experiment (MRME) during the 2014 summer growing season.
Alaskan Peatland Experiment (APEX): Ammonium Uptake Experiment I - Uptake Data Collected in 2016 at Lowland Bog Sites in the Bonanza Creek Experimental Forest near Fairbanks, Alaska
This dataset contains data from an ammonium uptake experiment conducted at the APEX Beta site in the BCEF. Data includes ammonium uptake of Carex aquatilis roots from porewater spiked with (NH4)2SO4 for 4 and 8 hours after excavation from thermokarst bogs. Comparisons involve deep vs shallow roots and roots excavated from the edge and centre of thermokarst bogs.
Plant biomass collection on the Biodiversity Experiment at the Kellogg Biological Station, Hickory Corners, MI (2001 to 2011)
Dataset Abstract The biodiversity gradient experiment is an additional long-term study located within the LTER Main Site complex, in which a series of 21 different experimental treatments vary in plant species diversity. Treatments range from bare soil to single-crop rotations to multiple-crop rotations to annually fallowed fields with early successional plant communities. Plant species richness thus varies from 0 to >15 in any given 3-year rotation cycle. Treatment plots are 9.1×27.4 meters (30×90 feet) replicated in each of 4 randomized blocks. The study site was established in 2000. original data source http://lter.kbs.msu.edu/datasets/112
multiple food patch collective foraging experiments
<p>This dataset contains .mp4 video files of experimental recordings for the following publication: https://doi.org/10.1101/744649.</p> <p>The .mp4 files (100x sped up) are contained within the zipped folder, and the .csv file contains the metadata for the dataset. </p> <ul> <li><strong>strains</strong> : DA609 and N2</li> <li><strong>timestamp</strong> : from 20170615 to 20170626</li> <li><strong>strain_description</strong> : DA609: npr-1(ad609)X. N2: lab reference strain.</li> <li><strong>sex</strong> : hermaphrodite</li> <li><strong>stage</strong> : adult</li> <li><strong>number_worms: </strong>40</li> <li><strong>media</strong> : NGM agar low peptone</li> <li><strong>arena</strong> : <ul> <li><strong>style</strong> : petri</li> <li><strong>size</strong> : 35 mm</li> </ul> </li> <li><strong>food</strong> : OP50, diluted OD = 0.75, freshly seeded</li> <li><strong>who</strong> : S. Serena Ding</li> <li><strong>protocol</strong> : Method in Ding, Schumacher et al. (2019) <a href="https://doi.org/10.7554/eLife.43318">https://doi.org/10.7554/eLife.43318</a>. Alternatively, visit dx.doi.org/10.17504/protocols.io.vybe7sn for a step-by-step protocol.</li> <li><strong>lab</strong> : <ul> <li><strong>name</strong> : Behavioural Genomics</li> <li><strong>location</strong> : London, United Kingdom</li> </ul> </li> <li><strong>days_of_adulthood</strong> : 1</li> <li><strong>total time (s)</strong> : 3600 per file</li> <li><strong>playback speed: </strong>100x</li> </ul>
Behavioral flexibility in solitary foraging ants: how experience, colony size and food distribution shape individual and collective performance
<p>To deal with the unpredictability of available food resources, animals must adjust their behavior to optimize foraging efficiency. Various mechanisms can influence an individual’s food acquisition behaviour, and thus our knowledge of their combined impact on foraging efficiency remains limited. In this study, we conducted laboratory experiments with seven colonies of the solitary foraging ant Dinoponera quadriceps. Foragers were individually observed in semi-controlled experiments where food was offered in aggregated or dispersed distributions. During the experiments, individual participation was voluntary (i.e. ants were free to enter or not the experimental arena), giving us an opportunity to assess internal processes such as motivation. Besides, behavioral traits such as foraging activity, exploration of food patches, and performance were recorded across repeated trials. We found that solitary foragers of D. quadriceps were highly efficient (retrieving food in 77.38% of the trips), especially when exploiting aggregated and abundant food resources. However, individual foraging success declined when more conspecific foragers were present and with longer foraging experience. Foragers increased their exploration levels in environments with larger numbers of dispersed prey items. Individual foraging activity was higher with more experience and in smaller colonies with fewer foragers. Furthermore, foragers and colonies exhibited low but consistent differences in levels of activity, exploration, and success rates. These findings provide a comprehensive view of how different factors combine to give rise to complex behaviors such as foraging. Additionally, they emphasize the importance of individual traits for effective task performance within social groups, an understudied topic.</p>
Environmental and AIS data collected during the EUMarineRobots Trans-National Access activities experiments using the NATO STO-CMRE Littoral Ocean Observatory Network testbed (Release 2)
<p>Environmental and AIS data collected during the second phase of EUMR TNA experiments using the CMRE LOON testbed. Environmental data consists of temperature measured across the water column; sound velocity measured close to the surface and close to the sea bottom; meteorological data at the surface (i.e., pressure, temperature, wind speed and direction, humidity and rain). The environmental dataset is complemented with Automatic Identification System (AIS) data for the ships transiting close to the LOON area (Gulf of La Spezia, Italy)</p> <p>Temperature measured across the water column in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for:<br> i) June 9-11, 17-18, 25-26 - 2021<br> ii) July 5-7, 21-27, 30-31 - 2021<br> iii) August 3-5, 10-14, 19-21, 23-24, 28-30 - 2021</p> <p><br> Meteorological data at the surface (i.e., pressure, temperature, wind speed and direction, humidity and rain) in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for:<br> i) June 9-11, 17-18, 25-26 - 2021<br> ii) July 5-7, 21-27, 30-31 - 2021<br> iii) August 3-5, 10-14, 19-21, 23-24, 28-30 - 2021</p> <p><br> Sound velocity measured close to the surface (SVP1) and close to the sea bottom (SVP2) in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for:<br> i) June 9-11, 17-18, 25-26 - 2021<br> ii) July 5-7, 21-27, 30-31 - 2021<br> iii) August 3-5, 10-14, 19-21, 23-24, 28-30 - 2021</p> <p>SVP1 data missing for June 17-18 (2021) and July 5-7 (2021).</p> <p><br> Automatic Identification System (AIS) data for the ships transiting close to the LOON area (Gulf of La Spezia, Italy). The dataset includes AIS data for:<br> i) June 9-11 - 2021</p> <p>AIS recorded data not available after June 11, 2021</p> <p>For reference, see: "Environmental data collected on the CMRE LOON tested during the EUMR project: dataset description", Petroccia, Roberto; Zappa, Giovanni; Cimino, Giampaolo; Grati, Alberto; Alves, João. CMRE-DA-2021-001. July 2021, available at https://www.cmre.nato.int/research/publications/latest-techreports/1638-cmre-da-2021-001</p>
FIG. 11. — Adding a in Récolnat Annotate-On: a tool to improve your experience with virtual collections
FIG. 11. — Adding a cartel label on an image.
FIG. 2 in Récolnat Annotate-On: a tool to improve your experience with virtual collections
FIG. 2. — Example of measurements: linear (green line) or non-linear (red line).
FIG. 6 in Récolnat Annotate-On: a tool to improve your experience with virtual collections
FIG. 6. — Example of the use of rectangle of interest (ROI) to show features on a specimen image.
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.