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1,032 results for “vertical”
Quantifying vertical fluxes near the sediment water interface
<p>Field and laboratory observations used in GRL article "<a href="http://onlinelibrary.wiley.com/doi/10.1002/2017GL076789/abstract?campaign=wolacceptedarticle">Determining near-bottom fluxes of passive tracers in aquatic environments</a>" DOI: 10.1002/2017GL076789.</p>
Fine vertical structures at the cloud heights of Venus revealed by radio holographic analysis of Venus Express and Akatsuki radio occultation data -- dataset
<p>The data used in the figures in the paper "Fine vertical structures at the cloud heights of Venus revealed by radio holographic analysis of Venus Express and Akatsuki radio occultation data" by Imamura et al. (J. Geophys. Res)</p> <p>The description of the columns in the files are given in the header section.</p>
dataset for Biases in the Visual and Haptic Subjective Vertical Reveal the Role of Proprioceptive/Vestibular Priors in Child Development
<p>dataset for "Biases in the Visual and Haptic Subjective Vertical Reveal the Role of Proprioceptive/Vestibular Priors in Child Development" publication. </p>
Vertical variation in epiphytic cryptogam species richness and composition in a primeval Fagus sylvatica forest
<p>"Data description.docx " contains the description of the data-file " Data_JVS_Vertical variation.xlsx" used for analyses.<br> </p>
Dataset: Occupancy Detection, Tracking, and Estimation Using a Vertically Mounted Depth Sensor
<p>Occupancy detection, tracking, and estimation has a wide range of applications including improving building energy efficiency, safety, and security of the occupants. As depth sensors are getting cheaper, they offer a viable solution to estimate occupancy accurately in a non-privacy invasive manner. Even though there are publicly available depth datasets, they do not consider placing the sensor in the ceiling looking downwards to estimate occupancy. We deployed four Kinect for XBOX One in four CMU classrooms and conference rooms for a period of four weeks in 2017 and collected over 6 TB of depth data. We annotate this huge dataset by labelling bounding boxes around occupants and release the annotated dataset. </p> <p>A sample of the dataset can be found here: <a href="https://doi.org/10.5281/zenodo.3457385">https://doi.org/10.5281/zenodo.3457385</a></p>
Figure 1 in Diurnal vertical distribution of zooplankton in a newly formed reservoir (Tahtalı Reservoir, Kocaeli): the role of abiotic factors and chlorophyll a
Figure 1. Study area and sampling station.
Investigation of satellite vertical sensitivity on long-term retrieved lower tropospheric ozone trends
<p>Regional time-series (monthly mean) of lower tropospheric column ozone (LTCO3; 0-6 km or surface to 450 hPa) between 2008 and 2017 from three satellite products and an Earth System Model (UKESM1.0 - https://ukesm.ac.uk/). The regions of focus are North America, Europe and East Asia based on the HTAP-2 land mask (https://htap.org/). The three satellite products are from the Ozone Monitoring Instrument (OMI) (RAL Space - https://www.ralspace.stfc.ac.uk/Pages/Remote-Sensing.aspx), the Infrared Atmospheric Sounding Interferometer (IASI) FORLI (Fast Optimal Retrievals on Layers for IASI) scheme (https://iasi.aeris-data.fr/cos_iasi_b_arch/) and the IASI SOFRID (SOftware for Fast Retrievals of IASI Data) scheme (https://iasi-sofrid.sedoo.fr/). These data have been used to investigate long-term trends and investigation of satellite long-term discrepancies in retrieved LTCO3. The pre-print of the relevant manuscript can be found at https://doi.org/10.5194/egusphere-2023-3109. </p>
Gummern - Horizontal (2D) vertical (1D) displacements from low cost GNSS
<h2>Abstract</h2> <p>Horizontal (2D) and vertical(1D) displacements, estimated for two locations in Gummern, AUT.</p> <p>This depository contains data generated within the European S34 project.</p> <h2>Metadata Information</h2> <table> <tbody> <tr> <td> <p><strong>Identification</strong></p> </td> </tr> <tr> <td> <p>Full Title</p> </td> <td> <p>Gummern (horizontal-2D and vertical-1D displacements)</p> </td> </tr> <tr> <td> <p>Abstract</p> </td> <td> <p>Horizontal (2D) and vertical(1D) displacements, estimated for two locations in Gummern, AUT.</p> </td> </tr> <tr> <td> <p>Keywords</p> </td> <td> <p>GNSS, displacements, coordinate time series</p> </td> </tr> <tr> <td> <p>Pilot area</p> </td> <td> <p>Gummern</p> </td> </tr> <tr> <td> <p>Associated resources</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Language</p> </td> <td> <p>English</p> </td> </tr> <tr> <td> <p>URL</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Categories</p> </td> <td> <p>GNSS</p> </td> </tr> <tr> <td> <p><strong>Temporal reference</strong></p> </td> </tr> <tr> <td> <p>Creation date (dd.mm.yyyy)</p> </td> <td> <p>14.06.2024</p> </td> </tr> <tr> <td> <p>Revision date (dd.mm.yyyy)</p> </td> <td> <p>14.06.2024</p> </td> </tr> <tr> <td> <p><strong>Quality and validity</strong></p> </td> </tr> <tr> <td> <p>Representation type</p> </td> <td> <p>Other</p> </td> </tr> <tr> <td> <p>Format</p> </td> <td> <p>Other</p> </td> </tr> <tr> <td> <p>Lineage</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Spatial resolution</p> </td> <td> <p>None</p> </td> </tr> <tr> <td> <p>Positional accuracy</p> </td> <td> <p>5 mm</p> </td> </tr> <tr> <td> <p>Maintenance information</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Coordinate system</p> </td> <td> <p>EPSG 4883</p> </td> </tr> <tr> <td> <p><strong>Constranits related to access and use</strong></p> </td> </tr> <tr> <td> <p>Use limitation</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Access constraint</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Public/Private</p> </td> <td> <p>Public</p> </td> </tr> <tr> <td> <p><strong>Responsible organisation</strong></p> </td> </tr> <tr> <td> <p>Responsible Contact</p> </td> <td> <p>Veton Hamza (<a href="mailto:veton.hamza@fgg.uni-lj.si">veton.hamza@fgg.uni-lj.si</a>)</p> <p>Polona Pavlovcic Preseren (<a href="mailto:polona.pavlovcic-preseren@fgg.uni-lj.si">polona.pavlovcic-preseren@fgg.uni-lj.si</a> )</p> </td> </tr> <tr> <td> <p>Responsible Party</p> </td> <td> <p>UL</p> </td> </tr> <tr> <td> <p><strong>Metadata on metadata</strong></p> </td> </tr> <tr> <td> <p>Contact</p> </td> <td> <p>Veton Hamza (<a href="mailto:veton.hamza@fgg.uni-lj.si">veton.hamza@fgg.uni-lj.si</a>)</p> <p>Polona Pavlovcic Preseren (<a href="mailto:polona.pavlovcic-preseren@fgg.uni-lj.si">polona.pavlovcic-preseren@fgg.uni-lj.si</a> )</p> </td> </tr> <tr> <td> <p>Metadata language</p> </td> <td> <p>English</p> </td> </tr> </tbody> </table>
Table 2 in Circulating dengue virus serotypes and vertical transmission in AEdES larvae during outbreak and inter-outbreak seasons in a high dengue risk area of Sri Lanka
<p><b>Table 2</b> Distribution of DENV serotypes in patients with suspected dengue and in <i>Aedes</i> mosquito larvae</p><table><tbody><tr><th>Patient no.</th><th><i>Ae. aegypti</i></th><th><i>Ae. albopictus</i></th><th>DENV serotype identified in mosquito pools</th><th>DENV serotype identified in patients</th></tr></tbody><tbody><tr><th>1</th><td>Detected</td><td>ND</td><td>DENV-3</td><td>DENV-3</td></tr><tr><th>2</th><td>ND</td><td>Detected</td><td>DENV-1</td><td>DENV-1</td></tr><tr><th>3</th><td>ND</td><td>Detected</td><td>DENV-3</td><td>DENV-3</td></tr><tr><th>4</th><td>ND</td><td>Detected</td><td>DENV-4</td><td>ND</td></tr><tr><th>5</th><td>ND</td><td>Detected</td><td>DENV-3</td><td>ND</td></tr><tr><th>6</th><td>ND</td><td>Detected</td><td>DENV-1</td><td>ND</td></tr><tr><th>7</th><td>Detected</td><td>ND</td><td>DENV-2</td><td>ND</td></tr><tr><th>8</th><td>Detected</td><td>ND</td><td>DENV-1</td><td>ND</td></tr><tr><th>9</th><td>Detected</td><td>ND</td><td>DENV-1</td><td>ND</td></tr><tr><th>10</th><td>ND</td><td>Detected</td><td>DENV-3</td><td>ND</td></tr><tr><th>11</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>ND</td></tr><tr><th>12</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>DENV-1</td></tr><tr><th>13</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>ND</td></tr><tr><th>14</th><td>ND</td><td>Detected</td><td>DENV-4</td><td>ND</td></tr><tr><th>15</th><td>ND</td><td>Detected</td><td>DENV-1</td><td>ND</td></tr><tr><th>16</th><td>ND</td><td>Detected</td><td>DENV-2</td><td>DENV-2</td></tr></tbody></table><p><i>ND</i> Not detected</p>
Table 1 in Circulating dengue virus serotypes and vertical transmission in AEdES larvae during outbreak and inter-outbreak seasons in a high dengue risk area of Sri Lanka
<p><b>Table 1</b> Distribution of <i>Aedes</i> mosquito larvae in and around residences of patients with suspected dengue in Mawanella from December 2015 to March 2017</p><table><tbody><tr><th>Period</th><th>Month and year of sample collection</th><th>Total no. of vector pools collected in entomological survey</th><th>No. of <i>Aedes</i> mosquito pools identified</th></tr><tr><th><i>Ae. aegypti</i></th><th><i>Ae. albopictus</i></th></tr></tbody><tbody><tr><th>Epidemic</th><td>12/2015</td><td>18</td><td>3</td><td>15</td></tr><tr><th></th><td>1/2016</td><td>22</td><td>8</td><td>14</td></tr><tr><th>Inter-epidemic</th><td>2/2016</td><td>5</td><td>0</td><td>5</td></tr><tr><th></th><td>3/2016</td><td>3</td><td>1</td><td>2</td></tr><tr><th></th><td>4/2016</td><td>4</td><td>1</td><td>3</td></tr><tr><th></th><td>5/2016</td><td>12</td><td>1</td><td>11</td></tr><tr><th></th><td>6/2016</td><td>15</td><td>9</td><td>6</td></tr><tr><th>Epidemic</th><td>7/2016</td><td>7</td><td>1</td><td>6</td></tr><tr><th></th><td>8/2016</td><td>5</td><td>2</td><td>3</td></tr><tr><th></th><td>9/2016</td><td>5</td><td>2</td><td>3</td></tr><tr><th>Inter-epidemic</th><td>10/2016</td><td>6</td><td>1</td><td>5</td></tr><tr><th></th><td>11/2016</td><td>6</td><td>1</td><td>5</td></tr><tr><th>Epidemic</th><td>12/2016</td><td>14</td><td>3</td><td>11</td></tr><tr><th></th><td>1/2017</td><td>23</td><td>8</td><td>15</td></tr><tr><th>Inter-epidemic</th><td>2/2017</td><td>1</td><td>0</td><td>1</td></tr><tr><th></th><td>3/2017</td><td>25</td><td>8</td><td>17</td></tr><tr><th>Total</th><td></td><td>171</td><td>49</td><td>122</td></tr></tbody></table>
Vertical assemblage of the holoplanktonic mollusks (Pteropoda and Pterotracheoidea) in the Campeche Canyon, southern Gulf of Mexico, during a "Nortes" season
<p>Data: Vertical assemblage of the holoplanktonic mollusks (Pteropoda and<br>Pterotracheoidea) in the Campeche Canyon, southern Gulf of Mexico,<br>during a “Nortes” season</p>
Vertical temperature profiles obtained from Venus Express and Akatsuki radio occultation data using FSI
<p>Vertical temperature profiles of Venusian atmosphere obtained from selected radio occultation data taken in ESA's Venus Express and JAXA's Akatsuki missions. The temperatures were retrieved using a radio holographic method, Full Spectrum Inversion (FSI). The data list and format are given in two Excel files and the data are given in text files with an extension ".dat".</p>
Atmospheric circulation sensitivity to changes in the vertical structure of polar warming
<p>This is the dataset used to make main figures of Atmospheric circulation sensitivity to changes in the vertical structure of polar warming (2021), GRL (<em>in preparation</em>).</p> <p>Please refer to the method section.</p> <p>1. The name of GRAM experiments, bot, mid1, mid2, and mid3 indicate L990, L850, L700, and L550 forcing respectively. Depending on the forcing amplitude, it varies 1X to 5.5X. The control run for GRAM is ctl_GRAM.nc.</p> <p>2. There are additional data for L990 and L650 for AM2 experiments. The control run for AM2 is ctl_AM2.nc.</p> <p>3. kernel_GRAM.mat = the radiative Kerel which is the OLR response to incremental increases in temperature of 1 K at each vertical level and the surface, based on GRaM (Lowest level is the surface kernel).</p> <p> </p> <p>Arctic domain averaged monthly temperature kernel data for figure 2d :</p> <p>1. ERA-Interim (Huang et al. 2017); the original data can be obtained from <a href="https://huanggroup.wordpress.com/research/">https://huanggroup.wordpress.com/research/</a>.</p> <p>2. GFDL-AM2 Aquaplanet (Feldl et al. 2017); the original data can be obtained from <a href="https://climate.rsmas.miami.edu/data/radiative-kernels">https://climate.rsmas.miami.edu/data/radiative-kernels</a>.</p>
The dataset of the manuscript: A Sub-Grid Parameterization Scheme for Topographic Vertical Motion in CAM5-SE
<p><a href="https://zenodo.org/api/files/1f1181b5-2418-40af-b0ee-d05da12eed37/figure_code.zip?versionId=83ff16db-ce42-4c35-80cc-f8f8cee2c7d5">figure_code.zip</a>: code of drawing figures.</p> <p><a href="https://zenodo.org/api/files/1f1181b5-2418-40af-b0ee-d05da12eed37/modification_code.zip?versionId=6f6e777a-8c5c-4134-b4e2-34985ff6c595">modification_code.zip</a>: add the code of topographic vertical montion and sub-grid topographic parameterization scheme in CAM5-SE.</p> <p><a href="https://zenodo.org/api/files/1f1181b5-2418-40af-b0ee-d05da12eed37/output_data.rar">output_data.rar</a>: the results of sensitivity experiments for CAM5-SE.</p> <p><a href="https://zenodo.org/api/files/1f1181b5-2418-40af-b0ee-d05da12eed37/draw_data.rar">draw_data.rar</a>: interpolated data according to output results and inputdata of drawing figures.</p> <p> </p>
CLAMPS2 Doppler Lidar Vertical Stare Data
<p>These files contain 24 hour periods of data collected from the CLAMPS2 Halo Streamline XR+ Doppler lidar. While not conducting other scans, the lidar directs the beam to zenith, allowing for the measurement of vertical velocity. These data were collected during the SPLASH project.</p>
Data for: Visual guidance of honeybees approaching a vertical landing surface
<p>Landing is a critical phase for flying animals, whereby many rely on visual cues to perform controlled touchdown. Foraging honeybees rely on regular landings on flowers to collect food, crucial for colony survival and reproduction. Here, we explore how honeybees utilize optical-expansion cues to regulate approach flight speed when landing on vertical surfaces. Three sensory-motor control models have been proposed for landings of natural flyers. Landing honeybees maintain a constant optical-expansion-rate set-point, resulting in a gradual decrease in approach velocity and gentile touchdown. Bumblebees exhibit a similar strategy, but they regularly switch to a new constant optic-expansion-rate set-point. Meanwhile, landing birds fly at a constant time-to-contact to achieve faster landings. Here, we re-examined the landing strategy of honeybee by fitting the three models to individual approach flights of honeybees landing on platforms with varying optic-expansion cues. Surprisingly, the landing model identified in bumblebees proves to be the most suitable for these honeybees. This reveals that honeybees adjust their optic-expansion-rate in a stepwise manner. Bees flying at low optic-expansion-rates tended to stepwise increase their set-point, while those flying at high optic-expansion-rates tend to stepwise decrease it. This modular landing control system enables honeybees to land rapidly and reliably under a wide range of initial flight conditions and visual landing platform patterns. The remarkable similarity between the landing strategies of honeybees and bumblebees suggests that this may also be prevalent among other flying insects. Furthermore, these findings hold promising potential for bioinspired guidance systems in flying robots.</p>
Incorporating the effect of large-scale vertical motion on convection through convective mass flux adjustment in E3SMv2
<p>Simulation data for the manuscript entitled of "Incorporating the effect of large-scale vertical motion on convection through convective mass flux adjustment in E3SMv2". </p>
Figure 2 in Mammal diversity among vertical strata and the evaluation of a survey technique in a central Amazonian forest
Figure 2. Species accumulation curve for (A) sampling effort (camera trap days) and (B) completeness of vertical strata.
Figure 1 in Mammal diversity among vertical strata and the evaluation of a survey technique in a central Amazonian forest
Figure 1. Locations of the nine paired camera traps located in the Cuieiras Biological Reserve, Brazil. F represents the floor stratum and C represents the canopy stratum.
Metabarcoding data reveal vertical multitaxa variation in topsoil communities during the colonization of deglaciated forelands
<p>Ice-free areas are increasing worldwide due to the dramatic glacier shrinkage and are undergoing rapid colonization by multiple lifeforms, thus representing key environments to study ecosystem development. Soils have a complex vertical structure. However, we know little about how microbial and animal communities differ across soil depths and development stages during the colonization of deglaciated terrains, how these differences evolve through time, and whether patterns are consistent among different taxonomic groups. Here, we used environmental DNA metabarcoding to describe how community diversity and composition of six groups (Eukaryota, Bacteria, Mycota, Collembola, Insecta, Oligochaeta) differ between surface (0-5 cm) and relatively deep (7.5-20 cm) soils at different stages of development across five Alpine glaciers. Taxonomic diversity increased with time since glacier retreat and with soil evolution; the pattern was consistent across different groups and soil depths. For Eukaryota, and particularly Mycota, alpha-diversity was generally the highest in soils close to the surface. Time since glacier retreat was a more important driver of community composition compared to soil depth; for nearly all the taxa, differences in community composition between surface and deep soils decreased with time since glacier retreat, suggesting that the development of soil and/or of vegetation tends to homogenize the first 20 cm of soil through time. Within both Bacteria and Mycota, several molecular operational taxonomic units were significant indicators of specific depths and/or soil development stages, confirming the strong functional variation of microbial communities through time and depth. The complexity of community patterns highlights the importance of integrating information from multiple taxonomic groups to unravel community variation in response to ongoing global changes.</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.