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4,028 results for “Behaviour”
Figure 3 in Behaviour of two predator fishes Esox lucius Linnaeus, 1758 and Silurus glanis Linnaeus, 1758 during two successive floods in the French Aisne River
Figure 3. –Boxplot characterizing the sizes ranges per behavioural group of northern pikes
Fig. 2 in Impact of ecotourism on the fish fauna of Bonito region (Mato Grosso do Sul State, Brazil): ecological, behavioural and physiological measures
Fig. 2. Image illustrating tourists at the beginning of the snorkeling excursion (Lima, 2008).
Figure 3 in Breeding and reproductive behaviour of the neo-tropical opossum, Didelphis marsupialis insularis, Allen 1902 under captive conditions
Figure 3. Photo of opossum breeding unit showing view from top of enclosure.
Fig. 2 in Behavioural and feeding observations of some Anthrenus Geoffroy, 1767 species (Coleoptera, Dermestidae) and identification using final larval instar cases
Fig. 2.- Location of collection sites, Mallorca, May 2023.
Fig. 3 in Behavioural and feeding observations of some Anthrenus Geoffroy, 1767 species (Coleoptera, Dermestidae) and identification using final larval instar cases
Fig. 3.- Anthrenus angustefasciatus on Cistus monspeliensis, Alcanada, Mallorca.
Fig. 12 - MSNM i28016. Short crab trackway crossing a in Anomuran and brachyuran trackways and resting trace from the Pliocene of Valduggia (Piedmont, NW Italy): environmental, behavioural, and taphonomic implications
Fig. 12 - MSNM i28016. Short crab trackway crossing a series of smooth ripplemarks (× 0.6).
Fig. 1 in Anomuran and brachyuran trackways and resting trace from the Pliocene of Valduggia (Piedmont, NW Italy): environmental, behavioural, and taphonomic implications
Fig. 1 - Geographical map of the fossiliferous locality (in red).
Fig. 14 - MSNM i28018 front. Crab trackway crossing a in Anomuran and brachyuran trackways and resting trace from the Pliocene of Valduggia (Piedmont, NW Italy): environmental, behavioural, and taphonomic implications
Fig. 14 - MSNM i28018 front. Crab trackway crossing a series of smooth ripplemarks (× 0.4).
Fig. 2 in Impacts of resource limitations on the reproduction behaviour in the Agile Frog (Rana dalmatina) on the territory of Natura park "Shumensko plato"
Fig. 2. Male and female Rana dalmatina in an artificial basin in amplexus for 12 days.
Fig. 1 in Impacts of resource limitations on the reproduction behaviour in the Agile Frog (Rana dalmatina) on the territory of Natura park "Shumensko plato"
Fig. 1. Registered egg-clutches out of the water near the ponds.
Supporting material for "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test"
<p>The data were uploaded to support the manuscript "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test" for the submission to Journal of Pharmacological and Toxicological Methods.</p>
Testing the feasibility of the behaviour-first route to deimatism
<p>These data are the latency for the model predators (domestic chicks, <em>Gallus gallus domesticus</em>) to attack prey after the activation of the prey display. The latencies were measured in milliseconds. </p>
static stress-strain behaviour of hardened and tempered steel 52100 (100Cr6)
<p>this file contains the recorded data (time, nominal stress, strain, actuator position) of a tensile test as long as the used strain gauge worked</p>
Bioacoustic monitoring reveals shifts in breeding songbird populations and singing behaviour with selective logging in tropical forests
<b>Description: </b><p>Counts of individual male songbirds, males and females, songs and duets and original WAV audio recordings used to generate them</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/131"><b>Population and behavioral responses of songbirds to logging and rain forest fragmentation</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3366104">here</a></p><p><b>Files: </b>This dataset consists of 13 files: Pillay_et_al_Songbirds_Acoustic_Counts_Vegetation_Cover.xlsx, 2013_B.zip, 2013_D.zip, 2013_E.zip, 2013_F.zip, 2013_OG1.zip, 2013_OG2.zip, 2014_B.zip, 2014_D.zip, 2014_E.zip, 2014_F.zip, 2014_OG1.zip, 2014_OG2.zip</p><p><b>Pillay_et_al_Songbirds_Acoustic_Counts_Vegetation_Cover.xlsx</b></p><p>This file contains dataset metadata and 5 data tables:</p><ol><li><p><b>CountsMale</b> (described in worksheet CountsMale)</p><p>Description: Counts of male individuals of songbird species</p><p>Number of fields: 12</p><p>Number of data rows: 5700</p><p>Fields: </p><ul><li><b>year</b>: Year of Survey (Field type: id)</li><li><b>ftype</b>: Forest Type (Field type: categorical)</li><li><b>block</b>: Unique ID of Blocks within which Sampling Plots are located (Field type: id)</li><li><b>location</b>: Unique ID of Sampling Plots (Field type: location)</li><li><b>fragment</b>: Future fragments within which sampling plots in logged forest plots were located; not applicable for unlogged forest plots (Field type: id)</li><li><b>species</b>: Species Identity (Field type: taxa)</li><li><b>day</b>: Days 1 to 2 of sampling in each plot (Field type: numeric)</li><li><b>date</b>: Date of Sampling (Field type: date)</li><li><b>jul.date</b>: Julian Date of Sampling (Field type: numeric)</li><li><b>time1-6AM</b>: Counts of male individuals for 6:00-6:05 AM; detection histories generated by collapsing counts to 1/0 data (Field type: numeric)</li><li><b>time2-7AM</b>: Counts of male individuals for 7:00-7:05 AM; detection histories generated by collapsing counts to 1/0 data (Field type: numeric)</li><li><b>time3-8AM</b>: Counts of male individuals for 8:00-8:05 AM; detection histories generated by collapsing counts to 1/0 data (Field type: numeric)</li></ul></li><li><p><b>CountsMaleFemale</b> (described in worksheet CountsMaleFemale)</p><p>Description: Counts of male plus female individuals of songbird species</p><p>Number of fields: 12</p><p>Number of data rows: 1000</p><p>Fields: </p><ul><li><b>year</b>: Year of Survey (Field type: id)</li><li><b>ftype</b>: Forest Type (Field type: categorical)</li><li><b>block</b>: Unique ID of Blocks within which Sampling Plots are located (Field type: id)</li><li><b>location</b>: Unique ID of Sampling Plots (Field type: location)</li><li><b>fragment</b>: Future fragments within which sampling plots in logged forest plots were located; not applicable for unlogged forest plots (Field type: id)</li><li><b>species</b>: Species Identity (Field type: taxa)</li><li><b>day</b>: Days 1 to 2 of sampling in each plot (Field type: numeric)</li><li><b>date</b>: Date of Sampling (Field type: date)</li><li><b>jul.date</b>: Julian Date of Sampling (Field type: numeric)</li><li><b>time1-6AM</b>: Counts of male and female individuals for 6:00-6:05 AM; detection histories generated by collapsing counts to 1/0 data (Field type: numeric)</li><li><b>time2-7AM</b>: Counts of male and female individuals for 7:00-7:05 AM; detection histories generated by collapsing counts to 1/0 data (Field type: numeric)</li><li><b>time3-8AM</b>: Counts of male and female individuals for 8:00-8:05 AM; detection histories generated by collapsing counts to 1/0 data (Field type: numeric)</li></ul></li><li><p><b>CountsSong</b> (described in worksheet CountsSong)</p><p>Description: Counts of songs</p><p>Number of fields: 9</p><p>Number of data rows: 2850</p><p>Fields: </p><ul><li><b>year</b>: Year of Survey (Field type: id)</li><li><b>ftype</b>: Forest Type (Field type: categorical)</li><li><b>block</b>: Unique ID of Blocks within which Sampling Plots are located (Field type: id)</li><li><b>location</b>: Unique ID of Sampling Plots (Field type: location)</li><li><b>fragment</b>: Future fragments within which sampling plots in logged forest plots were located; not applicable for unlogged forest plots (Field type: id)</li><li><b>species</b>: Species Identity (Field type: taxa)</li><li><b>day3-6AM</b>: Counts of songs for 6:00-6:05 AM on day 3 or third consecutive day of sampling in each plot (Field type: numeric)</li><li><b>day3-7AM</b>: Counts of songs for 7:00-7:05 AM on day 3 or third consecutive day of sampling in each plot (Field type: numeric)</li><li><b>day3-8AM</b>: Counts of songs for 8:00-8:05 AM on day 3 or third consecutive day of sampling in each plot (Field type: numeric)</li></ul></li><li><p><b>CountsDuet</b> (described in worksheet CountsDuet)</p><p>Description: Counts of duets</p><p>Number of fields: 9</p><p>Number of data rows: 500</p><p>Fields: </p><ul><li><b>year</b>: Year of Survey (Field type: id)</li><li><b>ftype</b>: Forest Type (Field type: categorical)</li><li><b>block</b>: Unique ID of Blocks within which Sampling Plots are located (Field type: id)</li><li><b>location</b>: Unique ID of Sampling Plots (Field type: location)</li><li><b>fragment</b>: Future fragments within which sampling plots in logged forest plots were located; not applicable for unlogged forest plots (Field type: id)</li><li><b>species</b>: Species Identity (Field type: taxa)</li><li><b>day3-6AM</b>: Counts of duets for 6:00-6:05 AM on day 3 or third consecutive day of sampling in each plot (Field type: numeric)</li><li><b>day3-7AM</b>: Counts of duets for 7:00-7:05 AM on day 3 or third consecutive day of sampling in each plot (Field type: numeric)</li><li><b>day3-8AM</b>: Counts of duets for 8:00-8:05 AM on day 3 or third consecutive day of sampling in each plot (Field type: numeric)</li></ul></li><li><p><b>VegetationCover</b> (described in worksheet VegetationCover)</p><p>Description: Vegetation cover data</p><p>Number of fields: 6</p><p>Number of data rows: 50</p><p>Fields: </p><ul><li><b>location</b>: Unique ID of Sampling Plots (Field type: location)</li><li><b>forest.type</b>: Forest Type (Field type: categorical)</li><li><b>udens</b>: Proportion understory cover (Field type: numeric)</li><li><b>cc</b>: Proportion canopy cover (Field type: numeric)</li><li><b>can.ht</b>: Average canopy height (Field type: numeric)</li><li><b>max.canopy</b>: Maximum height of standing vegetation (Field type: numeric)</li></ul></li></ol><p><b>2013_B.zip</b></p><p>Description: WAV files from 2013 for site B</p><p><b>2013_D.zip</b></p><p>Description: WAV files from 2013 for site D</p><p><b>2013_E.zip</b></p><p>Description: WAV files from 2013 for site E</p><p><b>2013_F.zip</b></p><p>Description: WAV files from 2013 for site F</p><p><b>2013_OG1.zip</b></p><p>Description: WAV files from 2013 for site OG1</p><p><b>2013_OG2.zip</b></p><p>Description: WAV files from 2013 for site OG2</p><p><b>2014_B.zip</b></p><p>Description: WAV files from 2014 for site B</p><p><b>2014_D.zip</b></p><p>Description: WAV files from 2014 for site D</p><p><b>2014_E.zip</b></p><p>Description: WAV files from 2014 for site E</p><p><b>2014_F.zip</b></p><p>Description: WAV files from 2014 for site F</p><p><b>2014_OG1.zip</b></p><p>Description: WAV files from 2014 for site OG1</p><p><b>2014_OG2.zip</b></p><p>Description: WAV files from 2014 for site OG2</p><p><b>Date range: </b>2013-04-09 to 2014-07-26</p><p><b>Latitudinal extent: </b>4.6881 to 4.7530</p><p><b>Longitudinal extent: </b>116.9477 to 117.6249</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Aves <br> -  -  -  -  Passeriformes <br> -  -  -  -  -  Timaliidae <br> -  -  -  -  -  -  <i>Stachyris</i> <br> -  -  -  -  -  -  -  <i>Stachyris maculata</i> <br> -  -  -  -  -  -  -  <i>Stachyris erythroptera</i> <br> -  -  -  -  -  -  -  <i>Stachyris poliocephala</i> <br> -  -  -  -  -  -  <i>Macronus</i> <br> -  -  -  -  -  -  -  <i>Macronus bornensis</i> <br> -  -  -  -  -  -  -  <i>Macronus ptilosus</i> (as synonym: <i>Macronous ptilosus</i>)<br> -  -  -  -  -  -  <i>Stachyridopsis</i> <br> -  -  -  -  -  -  -  <i>Stachyridopsis rufifrons</i> (as synonym: <i>Stachyris rufifrons</i>)<br> -  -  -  -  -  -  <i>Pomatorhinus</i> <br> -  -  -  -  -  -  -  <i>Pomatorhinus montanus</i> <br> -  -  -  -  -  Pellorneidae <br> -  -  -  -  -  -  <i>Trichastoma</i> <br> -  -  -  -  -  -  -  <i>Trichastoma bicolor</i> <br> -  -  -  -  -  -  <i>Alcippe</i> <br> -  -  -  -  -  -  -  <i>Alcippe brunneicauda</i> <br> -  -  -  -  -  -  <i>Pellorneum</i> <br> -  -  -  -  -  -  -  <i>Pellorneum capistratum</i> <br> -  -  -  -  -  -  <i>Malacocincla</i> <br> -  -  -  -  -  -  -  <i>Malacocincla malaccensis</i> <br> -  -  -  -  -  -  <i>Malacopteron</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnirostre</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnum</i> <br> -  -  -  -  -  -  -  <i>Malacopteron cinereum</i> <br> -  -  -  -  -  -  -  <i>Malacopteron affine</i> <br> -  -  -  -  -  Pycnonotidae <br> -  -  -  -  -  -  <i>Alophoixus</i> <br> -  -  -  -  -  -  -  <i>Alophoixus bres</i> <br> -  -  -  -  -  -  -  <i>Alophoixus phaeocephalus</i> <br> -  -  -  -  -  -  <i>Tricholestes</i> <br> -  -  -  -  -  -  -  <i>Tricholestes criniger</i> <br> -  -  -  -  -  -  <i>Iole</i> <br> -  -  -  -  -  -  -  <i>Iole olivacea</i> <br> -  -  -  -  -  -  <i>Pycnonotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus atriceps</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus simplex</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus eutilotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus brunneus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus erythropthalmos</i> <br> -  -  -  -  -  Stenostiridae <br> -  -  -  -  -  -  <i>Culicicapa</i> <br> -  -  -  -  -  -  -  <i>Culicicapa ceylonensis</i> <br> -  -  -  -  -  Muscicapidae <br> -  -  -  -  -  -  <i>Cyornis</i> <br> -  -  -  -  -  -  -  <i>Cyornis superbus</i> <br> -  -  -  -  -  -  -  <i>Cyornis unicolor</i> <br> -  -  -  -  -  -  <i>Rhinomyias</i> <br> -  -  -  -  -  -  -  <i>Rhinomyias umbratilis</i> <br> -  -  -  -  -  -  <i>Trichixos</i> <br> -  -  -  -  -  -  -  <i>Trichixos pyrropygus</i> <br> -  -  -  -  -  -  <i>Copsychus</i> <br> -  -  -  -  -  -  -  <i>Copsychus stricklandii</i> <br> -  -  -  -  -  Monarchidae <br> -  -  -  -  -  -  <i>Terpsiphone</i> <br> -  -  -  -  -  -  -  <i>Terpsiphone paradisi</i> <br> -  -  -  -  -  -  <i>Hypothymis</i> <br> -  -  -  -  -  -  -  <i>Hypothymis azurea</i> <br></div><p></p>
Dataset for article 'How users' knowledge of advertisements influences their viewing and selection behaviour in search engines'
<p>This study examines how users’ understanding of search-based advertising influences search results viewing behaviour the PC and the smartphone. To investigate this, we used a mix of methods consisting of interview, eye-tracking experiment and questionnaire with n=100 subjects. We show that participants with a low level of knowledge on search advertising are more likely to click on ads than subjects with a high level of knowledge. Moreover, subjects with little knowledge show less willingness to scroll down to the organic results. Regarding the device, there are significant differences in viewing behaviour. These can be attributed to the influence of the direct visibility of search results on both devices tested. We recommend, depending on the device, that advertisers ensure their ads appear in the instantly visible area ("above the fold"). Future studies should investigate the motivations of searchers when clicking on ads.</p>
SmartLife smart clothing gamification to promote energy-related behaviours among adolescents
<p>Inactivity and high sedentary behavior among adolescents are main societal problems. Unhealthy lifestyles place a large burden on society and promoting healthy lifestyles is thus key for health, wellness and economic prosperity. These non-communicable diseases and unhealthy lifestyles furthermore occur more often among lower socio-economic groups, which indicates a need for healthy lifestyle promotion programs to help reduce health inequalities and improve social inclusion. The SmartLife project aims to create a mobile game that requires lower body movement, and is personalized by physiological feedback measured by smart textiles. Personalization via smart textiles can present a game challenge achievable for the current fitness level of the player and can adjust this based on activity levels during game play. This approach can improve current exergames to achieve a higher level of intensity in physical activity, needed to create a health impact, and can do so considering what is achievable for the person and hence reduce drop-out and injury risks.</p>
Spanwise cylinder wake hydrodynamics and fish behaviour: Data
<p>Spanwise cylinder wake hydrodynamics and fish behaviour: Data</p> <p>Presents experimental data for the study of the effects of spanwise cylinder hydrodynamics on fish swimming behaviour. The data includes details of the fish and results of from a step velocity test, along with processed ADV measurements in the cylinder wake. </p> <p> </p> <p> </p>
Post-revision data and R Script for Murtagh et al. 'The scent of enrichment: Exploring the effect of odour and biological salience on behaviour during enrichment of kennelled dogs.'
<p>Data and analysis file (written in R studio) for the paper Murtagh et al. 'The scent of enrichment: Exploring the effect of odour and biological salience on behaviour during enrichment of kennelled dogs.' Updated based on reviewer comments and additional analyses requested (master data and analysis filed labelled with 'rev' suffix).</p>
Figure 5 in A comparative study of the diurnal behaviour of the Northern Shoveller (Anas clypeata) during the wintering season at Garaet Hadj-Tahar (North-East Algeria) and Garaet Timerganine (Algerian highlands)
Figure 5. (continued).
Figure 2 in A comparative study of the diurnal behaviour of the Northern Shoveller (Anas clypeata) during the wintering season at Garaet Hadj-Tahar (North-East Algeria) and Garaet Timerganine (Algerian highlands)
Figure 2. Photograph of general view of Garaet Hadj-Tahar, Skikda (January 2008).
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.