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3,673 results for “Temporal”
Data and analysis scripts of "Predictability awareness rather than mere predictability enhances the perceptual benefits for targets in auditory rhythms over targets following temporal cues"
<p>These are the data and the analysis scripts accompanying the publication </p> <p>"Predictability awareness rather than mere predictability enhances the perceptual benefits for targets in auditory rhythms over targets following temporal cues". </p> <p>Check the readMe for an instruction.</p>
Mixoplankton spatio-temporal diversity and its environmental drivers in the North Sea [Supplementary Material]
<p>Supplementary Material of the PhD [Mixoplankton spatio-temporal diversity and its environmental drivers in the North Sea [Supplementary Material]</p> <p> </p>
A temporally consistent 8-day 0.05° gap-free snow cover extent dataset over the Northern Hemisphere for the period 1981–2019
<p>Northern Hemisphere (NH) snow cover extent (SCE) is one of the most important indicator of climate change for its unique surface property. However, short temporal coverage, coarse spatial resolution, and different snow discrimination approach among published SCE products hampers its detailed studies. Using the Advanced Very High Resolution Radiometer Surface Reflectance (AVHRR-SR) Climate Data Record (CDR) and several ancillary datasets, this study generated a temporally consistent 8-day 0.05° gap-free NH terrestrial SCE product for the period 1981–2019 as part of the Global LAnd Surface Satellite dataset (GLASS) product suite. This process consistent of five steps. First, a decision tree algorithm with multiple threshold tests was applied to detect SCE from daily AVHRR-SR CDR. Second, we merge two existing daily SCE products to take advantage of their spatial coverage. Third, an aggregation process was used to detect the maximum SCE in each 8-day periods. Forth, the GLASS SCE was generated with the help of snow cover probability climatology. Fifth, the validation process was carried out to evaluate the quality of GLASS SCE. Validation results by using 562 Global Historical Climatology Network stations during 1981–2017 (r=0.61, p<0.05) and MOD10C2 during 2001–2019 (r=0.97, p<0.01) proved that the GLASS SCE product is credible in snow cover frequency monitoring. Moreover, cross-comparison between GLASS SCE and surface albedo during 1982–2018 further confirmed its values in climate changes studies.</p> <p>The GLASS SCE data set provides binary maps of snow cover for the Northern Hemisphere from September 1981 to the December 2019. The data are organized by year and provided in GeoTIFF formats. The gridcells were flagged as “0” if classified as "Non-snow", "1" if retrieved from AVHRR satellite observations, and "2" if filled by IMS snow climatology.</p> <p>Spatial Coverage: N: 90, S: 0, E: 180, W: -180<br> Spatial Resolution: 0.05 deg x 0.05 deg<br> Samples = 7200<br> Lines = 1800<br> Temporal Coverage: September 1981 to December 2019<br> Temporal Resolution: 8-day</p>
Automated Reasoning in Temporal DL-Lite
<p><strong>Automated Reasoning in Temporal DL-Lite*</strong></p> <p>We investigate the feasibility of automated reasoning over temporal DL-Lite (TDL-Lite) knowledge bases (KBs). We translate TDL-Lite KBs into a fragment of First Order temporal logic and then into LTL, and apply off-the-shelf LTL and FO-based reasoners for checking the satisfiability. We conduct various experiments to analyse the size of the LTL translation as well as the runtime performance of different reasoners on toy scenarios and on randomly generated TDL-Lite KBs. To improve the reasoning performance when dealing with large ABoxes, our work also proposes an approach for abstracting temporal assertions in KBs. We run several experiments with this approach to assess the effectiveness of the technique by measuring the gain in terms of the size of the translation, and the number of both ABox assertions and individuals. We also measure the runtime of the solvers on such abstracted KBs. Lastly, in an effort to make the usage of TDL-Lite KBs a reality, we present a fully-fledged tool with a graphical interface to design and reason over them. Our interface is based on conceptual modeling principles and it is integrated with our translation tool and a temporal reasoner.</p> <p>(*) This work has been submitted to the Journal of Automated Reasoning</p>
Temporal and spatial changes in benthic invertebrate trophic networks along a taxonomic richness gradient
<p>Species interactions underlie most ecosystem functions and are important for understanding ecosystem changes. Representing one type of species interaction, trophic networks were constructed from biodiversity monitoring data and known trophic links to assess how ecosystems have changed over time. The Baltic Sea is subject to many anthropogenic pressures, and low species diversity makes it an ideal candidate for determining how pressures change food webs. In this study, we used benthic monitoring data from 20 years (1980-1989 and 2010-2019) from the Swedish coast of the Baltic Sea and Skagerrak to investigate changes in benthic invertebrate trophic interactions. We constructed food webs and calculated fundamental food web metrics evaluating network horizontal and vertical diversity, as well as stability that were compared over space and time. Our results show that the west coast of Sweden (Skagerrak) suffered a reduction in benthic invertebrate biodiversity by 32 % between the 1980's and 2010's, and that the number of links, generality of predators, and vulnerability of prey, have been significantly reduced. The other basins (Bothnian Sea, Baltic Proper and Bornholm Basin) do not show any significant changes in species richness or consistent significant trends in any food web metrics investigated, demonstrating resilience at a lower species diversity. The decreased complexity of the Skagerrak food webs indicates vulnerability to further perturbations and pressures should be limited as much as possible to ensure continued ecosystem functions.</p>
Multi-temporal Structure from Motion ponit clouds of riparian vegetation
<p>the dataset consists of three pointclouds and two NIR orthomosaics generated through a Structure from Motion standard workflow of the same forested area. The study area is typical riparian habitat vegetation. The data were acquired in different phenological stages:</p> <p>the first acquisition was realised in leaves-off conditions (march 2020)</p> <p>The second acquisition was realised in June 2020</p> <p>the third acquisition was realised in July 2020.</p> <p>Reference system: WGS84/32N [EPGS: 32632]</p> <p>For further information regarding the data processing please refer to https://doi.org/10.3390/rs13091756<br> </p>
Data set of manuscript entiteld Sigma Oscillations Protect or Reinstate Motor Memory Depending on their Temporal Coordination with Slow Waves
<p>Data set of manuscript entiteld Sigma Oscillations Protect or Reinstate Motor Memory Depending on their Temporal Coordination with Slow Waves</p> <p>EEG files : Brainvision</p> <p>*.dat; *.edf : eeg files of the experimental nap </p> <p>*.vhdr: corresponding header files</p> <p>*.vmrk: corresponding marker files time starting from recording sample</p> <p>*._Pauselog.txt: markers with condition in the stimulation computer time</p> <p>Sleep Scores: </p> <p>Scores by the sleep technician (one file per participants). </p> <p>Surveys:</p> <p>General survey (first screening) and complete survey (for inclusion). Code correspondance is provided in ID_correspondance.txt</p> <p>BehavData:</p> <p>For each participant, a text file with all the cues and responses logged for each tasks. *_raw.txt are present when an issue arised during experiment and a task needed to be re-started. </p> <p> </p>
Data_Temporal_and_inter-farm_variability
<p>Data belonging to the manuscript "Temporal and inter-farm variability of economic and environmental farm performance: a resilience perspective on potato producing regions in the Netherlands?"</p>
HTW Berlin weather data with a temporal resolution of 1 Hz and 1/60Hz (2017-2021)
<p>These data sets from 2017-2021 contain the weather data measured on the roof at the University of Applied Sciences for Engineering and Economics in Berlin (HTW Berlin). <br> The data sets have a resolution of 1 Hz and 1/60 Hz and are stored in a Matlab .mat and .csv files.<br> <br> The data sets contain the solar irradiance, wind speed (x,y,z), air pressure, air temperature and humidity.<br> The documentation has more detailed information about the equipment used and the data collected.</p> <p>The homepage of our research group: https://solar.htw-berlin.de/</p>
Data and code repository for Science Advances submission: Uncovering the biological basis of control energy: structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
<p>Data and codes related to the findings reported in the manuscript, "Uncovering the biological basis of control energy: structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy", are deposited. Please refer to the notes located within each folder for further descriptions.</p>
Gastruloids as in vitro models of embryonic blood development with spatial and temporal resolution
<p>Rawdata (images and flow cytometry) for the manuscript "Gastruloids as in vitro models of embryonic blood development with spatial and temporal resolution". <br> </p>
Code: A model of wild bee populations accounting for spatial heterogeneity and climate induced temporal variability of food resources at the landscape level
<p><span>The viability of wild bee populations and the pollination services that they provide are driven by the availability of food resources during their activity period and within the surroundings of their nesting sites. Changes in climate and land use influence the availability of these resources and are major threats to declining bee populations. Because wild bees may be vulnerable to interactions between these threats, spatially explicit models of population dynamics that capture how bee populations jointly respond to land use at a landscape scale and weather are needed. Here, we developed a spatially and temporally explicit theoretical model of wild bee populations aiming for a middle ground between the existing mapping of visitation rates using foraging equations and more refined agent-based modelling. The model is developed for <em>Bombus</em> sp. and captures within-season colony dynamics. The model describes mechanistically foraging at the colony level and temporal population dynamics for an average colony at the landscape level. Stages in population dynamics are temperature-dependent triggered with a theoretical generalized seasonal progression, which can be informed by growing degree days (GDD). The purpose of the LandscapePhenoBee model is to evaluate the impact of systematic changes and within-season variability in resources on bee population sizes and crop visitation rates. In a simulation study, we used the model to evaluate the impact of the shortage of food resources in the landscape arising from extreme drought events in different types of landscapes (ranging from different proportions of semi-natural habitats and early and late flowering crops) on bumblebee populations.</span></p>
Transformed crane data from: Balancing structural complexity with ecological insight in spatio-temporal species distribution models
<p>The potential for statistical complexity in species distribution models (SDMs) has greatly increased with advances in computational power. Structurally complex models provide the flexibility to analyse intricate ecological systems and realistically messy data, but can be difficult to interpret, reducing their practical impact. Founding model complexity in ecological theory can improve insight gained from SDMs. </p> <p>Here, we evaluate a marked point process approach, which uses multiple Gaussian random fields to represent population dynamics of the Eurasian crane (<em>Grus grus</em>) in a spatio-temporal species distribution model. We discuss the role of model components and their impacts on predictions, in comparison with a simpler binomial presence/absence approach. Inference is carried out using Integrated Nested Laplace Approximation (INLA) with inlabru, an accessible and computationally efficient approach for Bayesian hierarchical modelling, which is not yet widely used in SDMs. </p> <p>Using the marked point process approach, crane distribution was predicted to be dependent on the density of suitable habitat patches, as well as close to observations of the existing population. This demonstrates the advantage of complex model components in accounting for spatio-temporal population dynamics (such as habitat preferences and dispersal limitations) that are not explained by environmental variables. However, including an AR1 temporal correlation structure in the models resulted in unrealistic predictions of species distribution; highlighting the need for careful consideration when determining the level of model complexity.</p> <p>Increasing model complexity, with careful evaluation of the effects of additional model components, can provide a more realistic representation of a system, which is of particular importance for a practical and impact-focused discipline such as ecology (though these methods extend to applications for a wide range of systems). Founding complexity in contextual theory is not only fundamental to maintaining model interpretability, but can be a useful approach to improving insight gained from model outputs. </p>
Anthropogenic noise and light alter temporal but not spatial breeding behavior in a wild frog
<p><span>Increasing urbanization has led to large scale land-use changes, exposing persistent populations to drastically altered environments. Sensory pollutants, including low-frequency anthropogenic noise and artificial light at night (ALAN), are typically associated with urban environments and known to impact animal populations in a variety of ways. Both ALAN and anthropogenic noise can alter behavioral and physiological processes important for survival and reproduction, including communication and circadian rhythms. Although noise and light pollution typically co-occur in urbanized areas, few studies have addressed their combined impact on species' behavior. Here we assessed how anthropogenic noise and ALAN can influence spatial and temporal variation in breeding activity of a wild frog population. By exposing artificial breeding sites inside a tropical rainforest to multiple sensory environments, we found that both anthropogenic noise and ALAN impact breeding behavior of túngara frogs (<em>Engystomops pustulosus</em>), albeit in different ways. Males arrived later in the night at their breeding sites in response to anthropogenic noise. ALAN, on the other hand, led to an increase in calling effort. We found no evidence that noise or light pollution either attracted frogs to or repelled frogs from</span> <span>breeding sites. Thus, anthropogenic noise may negatively affect calling males by shifting the timing of sexual signaling. Conversely, ALAN may increase the attractiveness of calling males. These changes in breeding behavior highlight the complex ways that urban multisensory pollution can influence behavior and suggest that such changes may have important ecological implications for the wildlife that are becoming increasingly exposed to urban multisensory pollution.</span></p>
A Dataset of Synthetic Images of Outdoor Scenes Taken from Sidewalks, for Temporal Semantic Segmentation Applications
<p>This dataset has been generated using the CARLA simulator (release 0.9.11), an open-source 3D simulator for experiments in autonomous vehicle, based on the Unreal Engine game engine. It comes with pre-made city environment maps. CARLA is distributed with several integrated maps as well as parameters to increase the variety in the dataset. In the release that we have used, there are 13 semantic segmentation classes: None, Building, Fence, Other, Pedestrian, Pole, Lane-marking, Road, Sidewalk, Vegetation, Vehicle, Wall, and Traffic sign. The "None" category corresponds to textures that are not part of an object, such as lawns which are not part of "Vegetation", or sky. In the “Other” category are found objects that are not included in the other classes like plant and flower pots. For smart mobility applications, the “Sidewalks” and “Road” classes are of particular importance to find the way forward, as well as “Buildings” and “Poles” for obstacle avoidance. Sequences are made of 4 images. The dataset is composed of 46436 frames (11609 sequences) partitioned in 41024 frames (10256 sequences) for train, 2696 frames (674 sequences) for validation, and 2716 for test (679 sequences). The size of the images is 800 x 600 (resp. width x height).</p> <p>Additionaly, we have generated another smaller dataset with images taken from 2 different viewpoints: one located on the road and the other located on the sidewalk. The number of frames for train/validation/test is respectively 7288 (1822 sequences) partitioned in 6344 (1687 sequences) for train, 416 frames (104 sequences) for validation, and 424 for test (106 sequences). This smaller dataset is aimed at showing the importance of the viewpoint in the result of semantic segmentation. This can be done by cross-validation: learning on images taken from a viewpoint located on the road and test on images with a viewpoint located on the sidewalk, and vice versa.</p>
Multi-scale temporal variation of marine femtoplankton and picoplankton: the role of size and environment
<p>Supplementary Material of the article "Multi-scale temporal variation of marine femtoplankton and picoplankton: the role of size and environment":</p> <p>- Supplementary Table 1: Raw environmental data: sea surface temperature (°C), salinity, dissolved oxygen (ml.l<sup>-1</sup>), pH, phosphate (mM), nitrite (mM), nitrate (mM), ammonia (mM), chl-a, b, c and pheopigments (mg/m<sup>3</sup>). </p> <p>- Supplementary Table 2: Cell abundance (cell.mL<sup>-1</sup>) of <em>Synechococcus</em> spp. (SYN) and picoeukaryotes (PEUK), and abundance of Virus-like particles for each sample and their respective anomalies, after normalization.</p>
Fig. 4 in Spatio-Temporal Structure And Reproductive Success In A Rook (Corvus Frugilegus) Colony
Fig. 4. Distance of the newly built nests from the centre of the colony, from the edge of the colony (metres) and number of neighbouring nests within 6 metres (medians, full circles) and those of the randomly selected points (medians, empty squares) at each sampling date. 100 random points were selected for each date, sample sizes of the observed nests are shown above the medians. In the marked (*) cases the values of the observed nests dif- fered significantly from the values of the ran- dom points (Mann-Whitney test, P <0.05)
The impact of cerebellar transcranial direct current stimulation (tDCS) on sensorimotor and inter-sensory temporal recalibration
<p>Data related to the study "The impact of cerebellar transcranial direct current stimulation (tDCS) on sensorimotor and inter-sensory temporal recalibration".</p>
Supporting information for the paper: The temporal relationship between Terrestrial Gamma-ray flashes and associated optical pulses from lightning
<p>Supporting information for the paper: The temporal relationship between Terrestrial Gamma-ray flashes and associated optical pulses from lightning, consisting of 2 data files and 221 presentations of TGF-Optical emission events observed by ASIM between end of March 2019 and November 2020.</p> <p>See 0_READ_ME for information about the individual files and variables.</p>
Spatial and temporal variability of phytoplankton photophysiology in the Atlantic Southern Ocean
<p>The datasets in this repository are part of the manuscript entitled "<strong>Spatial and temporal variability of phytoplankton photophysiology in the Atlantic Southern Ocean</strong>".</p>
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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.