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3,673 results for “Temporal”
Fig. 1 in Spatio-temporal variation of the invasive copepod Oithona davisae in the zooplankton community of Kavala harbour Abstract
Fig. 1: A) Map of Greece, B) Map of the sampling stations in Kavala's harbour.
Fig. 1 in Fig. 7 in Coexistence of Juvenile with Adult at Culebra Beach, Panama: A Temporal-spatial Partitioning Compromise.
Fig. 1. Beach profile showing the burrow zones of Ocypode gaudichaudii at Culebra Beach.
Fig. 4 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA
Fig. 4. (continued).
Fig. 4 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA
Fig. 4. (continued).
Fig. 4 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA
Fig. 4. (continued).
Fig. 4 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA
Fig. 4. (continued).
Fig. 4 in Spatio-temporal variation in prevalence and intensity of trematodes responsible for waterfowl die-offs in faucet snail-infested waterbodies of Minnesota, USA
Fig. 4. (continued).
Spatio-temporal distribution of LSD outbreaks in the Balkan region since deecember 2016 until November 2017 and cattle density (animals/square km)
<p>The European Food Safety Authority (EFSA), under request of the European Commission, performed an epidemiological analysis of the lumpy skin disease (LSD) epidemics based on the data collected from the affected and at-risk Member States and non-EU countries in south-eastern Europe. Spatial and temporal (monthly) distribution of LSD outbreaks reported in the Balkan region between December 2016 and November 2017 and cattle density (animals/square km) shown as green shade (for Bosnia and Herzegovina data at regional level are not available). LSD outbreaks were reported in this time frame only in Albania, the former Yugoslav Republic of Macedonia and Greece. Red and grey dots indicate new and past outbreaks, respectively.</p> <p>*This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo Declaration of Independence</p>
High temporal resolution microclimate records
<b>Description: </b><p>Microclimate records collected at very high temporal resolution (10 sec) at a small number of sites</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/111"><b>Microclimate stratification in modified forests</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=52">here</a></p><p><b>Data worksheets: </b>There are 1 data worksheets in this dataset:</p><ol><li><p><b>High temporal resolution microclimate records</b> (Worksheet Data)</p><p>Dimensions: 229330 rows by 7 columns</p><p>Description: Microclimate records collected at very high temporal resolution (10 sec) at a small number of sites</p><p>Fields: </p><ul><li><b>Plot</b>: Location of record (Field type: Location)</li><li><b>time</b>: Date and time of record (Field type: Datetime)</li><li><b>Temp</b>: Air temperature 1 m above ground (Field type: Numeric)</li><li><b>RH</b>: Relative humidity. (Field type: Numeric)</li><li><b>LoggerType</b>: Make of datalogger that was used (Lascar or iButton) (Field type: ID)</li><li><b>LoggerID</b>: Unique reference number for the datalogger (Field type: ID)</li></ul><br></li></ol><p><b>Date range: </b>2015-12-11 to 2016-12-07</p><p><b>Latitudinal extent: </b>4.7104 to 4.7523</p><p><b>Longitudinal extent: </b>116.9484 to 117.6278</p>
Data from: Individual Movement - Sequence Analysis Method (IM-SAM): characterising spatio-temporal patterns of animal trajectories across scales and landscapes
<p>Dataset included in Zenodo supports the analyses performed in "<em>Individual Movement - Sequence Analysis Methods (IM-SAM) characterising spatio-temporal patterns of animal trajectories across scales and landscapes.</em>"</p> <p>The dataset includes one RDS file, that can be easily loaded into R using the readRDS function. The RDS file consists out of a list including two objects per animal:</p> <ul> <li>Object 1 contains a data frame with the real and simulated sequences for an animal. e.g., ls[[1]][[1]] </li> <li>Object 2 contains the home range in raster format of an animal. e.g., ls[[1]][[2]]</li> </ul> <p>The data frames in object 1 contain real habitat use sequences and corresponding simulated habitat use sequences generated in the home range of the specific individual (900 simulated sequences: 6 habitat selection rules x 3 selection coefficients x 50 repetitions). Open and closed habitats are respectively encoded by 0 and 1. The first 96 columns of each row in a data frame represent a 16-day habitat use sequence, with a fixed 4-hour relocation interval (0, 4, 8, 12, 16 and 20h). Column names are named as follows: Day_1_0h, Day_1_4h,..., Day_16_20h. In the next columns we provide the selection coefficients (columns 97-99), the habitat selection rules (or pattern, columns 100-102) and the number of missing values (mvs, columns, 103-104) for each of the real and simulated sequences. Note that simulated sequences have no missing values (i.e. values are always 0.00) and for real sequences there is no selection coefficient or habitat selection rule (i.e. values are always xxx).</p> <p>Rownames of simulated sequences are composed out of the habitat selection rule (c, o, a24, a33, a42 and u), the selection coefficient (5, 10, 50) and the replicate (1 to 50), separated by dashes. For example, the first simulated sequence in the first data frame (ls[[1]][[1]][1,]) is described as a24_10_1. The rownames of real sequences instead are composed out of the individuals' identifier, the biweekly period (1 to 23) and the year. For example, the first real sequence in the first data frame (ls[[1]][[1]][901,]) is described as 1_5_2006.</p> <p><br> </p>
Envixlab/OpenMICE: OpenMICE: an open spatial and temporal data set of small mammals in south-central Italy based on owl pellet data
<p>Provided in support of the Data-paper: OpenMICE: an open spatial and temporal data set of small mammals in south-central Italy based on owl pellet data by Paniccia, C., M. Di Febbraro, L. Delucchi, R. Oliveto, M. Marchetti, and A. Loy. 2018. Ecology. <a href="https://github.com/Envixlab/OpenMICE/files/2273658/OpenMICE.sqlite.zip">OpenMICE.sqlite.zip</a></p>
Data for: Temporal variation in intertidal habitat use by nekton at seasonal and diel scales
<p>A two-year dataset of nekton community structure, seagrass, temperature, and salinity for seagrass-vegetated and unvegetated habitats in Willapa Bay, Washington State, USA. </p>
The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing
<p>The OpenEar Dataset provides a library consisting of eight three-dimensional models of the human temporal bone to enable surgical training including color data. Each dataset is based on a combination of multimodal imaging including Cone Beam Computed Tomography (CBCT) and micro-slicing. 3D reconstruction of micro-slicing images and subsequent registration to CBCT images allowed for relatively efficient multimodal segmentation of inner ear compartments, middle ear bones, tympanic membrane, relevant nerve structures, blood vessels and the temporal bone. Raw data from the experiment as well as voxel data and triangulated models from the segmentation are provided in full for use in surgical simulators or any other application which relies on high quality models of the human temporal bone.</p>
Systematic spatio-temporal mapping reveals divergent cell death pathways in three mouse models of hereditary retinal degeneration
<p>Values for immuohistochemical analysis or enzymatic analysis of various markers theorised to have roles in retinal dystrophies in three models of mouse retinal degeneration with a control. Analysis has been broken down by marker, mouseline, age and region of the retina recorded from</p>
Data base for the paper "Inhibitory control and temporal perception in cerebral palsy" submitted to Child Neuropsychology
<p>Data base for the paper “Inhibitory control and temporal perception in cerebral palsy” submitted to “Child Neuropsychology” Review</p>
Data collection that describes the calibration of the temporal and displacement characteristics of an optical tweezers in buffered saline at room temperature.
<p><strong>Introduction</strong>. This data provides the calibration of an optical tweezers within the linear Hookian region. Once the laser was aligned, the power at the objective measured and a bead trapped the instrument was calibrated. <strong>Data Collection</strong>. Calibration was performed by moving a trapped bead by supplying a periodic square wave train input (amplitude: −800 to +800 nm, period: 80 ms) to an acousto-optical device, AOD and monitoring the trajectory of the bead in the 𝑋𝑌 plane with a quadrant photo diode, QPD for ~ one minute. Data was collected at 200 kHz from three (3) QPD channels: displacement in the 𝑋 (∆𝑋<sub>𝑀</sub>) (i) and 𝑌 directions (∆𝑌<sub>𝑀</sub>) (ii) and the sum of the fluorescent intensity (∑<sub>𝐿</sub>) (iii). Typically, each bead was stimulated with a train of square waves of constant amplitude in the 𝑋 direction. This stimulation was performed four (4) times at each of the different amplitudes i.e., −800, +800, −500, and +500 nm. The QPD signal in the dark, ∆𝑋<sub>𝐷</sub>, ∆𝑌<sub>𝐷</sub>, ∑<sub>𝐷</sub> was recorded and subtracted in real time, and the gain, 𝐺 of the QPD noted. The Stokes-Faxen coefficient, 𝛽 was calculated having recorded the height of the bead above the Petri dish, ℎ and the viscosity, 𝜂 of the saline solution. The detected fluorescent bead was excited either with a Xenon lamp or TLED transmitted light source. Some calibrations were performed with a TLED light that was borrowed from the manufacturer for testing, and the signal to noise of these measurements was significantly decreased.<strong> Data Transformation</strong>. For each of the two (2) channels the measured signal was normalized by the sum, and the ~750 waves were averaged for each pulse train stimulus. The reciprocal of the time constant (s<sup>-1</sup>) was determined from the exponential rise or decay of the back-ground subtracted averaged response. Spring constant (pN/nm) was determined from the product of this reciprocal time constant and the Stokes-Faxen coefficient (pNs/nm). The net displacement of the bead (nm) was calculated by determining the resultant vector of the 𝑋 and 𝑌 components of the QPD (V/V). For the four (4) stimuli determined for each bead the normalized displacement (V/V) was plotted as a function of net bead displacement and the slope (V/V/nm) calculated from best linear fit. For each calibration the mean spring constant, reciprocal time constant, and mean slope are provided. <strong>Data Format</strong>. The data was saved in LabView with the proprietary TDMS format (National Instruments, NI, Austin, TX). It was transformed to a text file and imported into MATLAB (The Mathworks, Natick, MA) and stored as struct and analyzed with a Python script. The collection contains raw and transformed results from 69 days for a total 153 beads. The data is provided with annotated descriptions in HDF5, a standard non-proprietary container storage format. Each file is about 1.1 GBs (HDF5).</p> <p> </p> <p>The package contains:</p> <p>1. Standard Container HDF5 with custom organization format of data with annotations.</p> <p>2. Python Script (calibrateopticaltweezers.py file) that describes how data is analyzed and written to HDF5 and .MAT formats. (1 file)<br> </p>
The Physics of Changing Tectonic Regimes: Implications for the Temporal Evolution of Mantle Convection and the Thermal History of Venus
<p>Input and relevant data files for "The Physics of Changing Tectonic Regimes: Implications for the Temporal Evolution of Mantle Convection and the Thermal History of Venus." Each data set was used to generate figures in text, and was used with, or obtained from, CitcomS (v3.3).</p> <p> </p> <p>diagnostic.dat contains internal metrics [#step time Mobility Tint T_asthen_avg D U Uc RMS_Velocity]<br> Where #step is iteration number, time is the non dimensional diffusion time scale for the step, Mobility is defined in text, Tint is the mid mantle temperature (average), T_asthen_avg is the upper mantle temperature (average), D U Uc not used, and RMS_Velocity is the root mean square velocity.</p> <p> </p> <p>Nusselt.dat contains heat flow information [time, surface nusselt number, basal nusselt number].</p> <p>Time is the non dimensional diffusion time scale for the step. nusselt numbers are nondimesional heatflow from the surface (lithosphere) and base (core).<br> </p> <p>Melt2.dat contains melting information. #step is iteration number, time is the non dimensional diffusion time scale for the step,</p> <p>non-dimensional melt</p> <p> </p> <p>the input.* file is the model input file used with CitcomS (v3.3) that includes all parameters used for the reference case. Variations from this file are described in text.</p>
Development of a global 30-m impervious surface map using multi-source and multi-temporal remote sensing datasets with the Google Earth Engine platform
<p>An accurate global impervious surface map at a resolution of 30-m for 2015 by combining Landsat-8 OLI optical images, Sentinel-1 SAR images and VIIRS NTL images based on the Google Earth Engine (GEE) platform.</p>
Figure 5 in Occurrence and temporal variation in the size-frequency distribution of 2 bloom-forming jellyfishes, Catostylus perezi (L. Agassiz, 1862) and Rhizostoma pulmo (Cuvier, 1800), in the Indus Delta along the coast of Sindh, Pakistan
Figure 5. Temporal variation of jellyfish medusae in zooplankton samples.
Figure 3 in Occurrence and temporal variation in the size-frequency distribution of 2 bloom-forming jellyfishes, Catostylus perezi (L. Agassiz, 1862) and Rhizostoma pulmo (Cuvier, 1800), in the Indus Delta along the coast of Sindh, Pakistan
Figure 3. Temporal variation in size distribution in 3 populations of C. perezi.
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.