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4,107 results for “pointing”
ENMU_LA3324-25317 (Clovis Point)
<p>ENMU_LA3324-25317 is a Clovis point from the North Bank Mammoth Kill Area of the Blackwater Draw National Historic Landmark, and is culturally affiliated with the Clovis period. The point was discovered in 1963 in context with Mammoth IV by Agogino. </p>
ENMU_LA3324-25330 (Clovis Point)
<p>ENMU_LA3324-25330 is a Clovis point from the West Wall Area of the Blackwater Draw National Historic Landmark, and is affiliated with the Clovis period. It was recovered in 1962 in Spring No. 1, West of Hester Locality No. 4.</p>
ENMU_LA3324-32095 (Agate Basin Point)
<p>ENMU_LA3324-32095 is an Agate Basin point from the South Bank Area of the Blackwater Draw National Historic Landmark. The point was found in association with a bison kill in 2003 (Haynes Stratum D in bison bonebed) by O. J. Dickenson.</p>
ENMU_LA3324-24136 (Clovis Point)
<p>ENMU_LA3324-24136 is a Clovis point from the North Bank Mammoth Kill Area of the Blackwater Draw National Historic Landmark. It is culturally affiliated with the Clovis period, and was excavated from the Spring Conduit "Pothole 2" in 1963 by the F. E. Green excavation in Haynes Stratum C, and was heavily polished.</p>
ENMU_LA3324-EL-2-120 (Agate Basin Point)
<p>ENMU_LA3324-EL-2-120 is an Agate Basin point from the North Bank Spring Area of the Blackwater Draw National Historic Site. It was excavated in 1963 from stratigraphic unit D by the El Llano Archaeological Society under the direction of Dr. James Warnica.</p>
Figure 4. - Brightfield image showing the posterior mesosoma and anterior metasoma of Pteroceraphronmirabilipennis Dessart 1981. Arrows point to bifurcated anteromedian process of the propodeum-metanotum complex.
Figure 4. - Brightfield image showing the posterior mesosoma and anterior metasoma of Pteroceraphronmirabilipennis Dessart 1981. Arrows point to bifurcated anteromedian process of the propodeum-metanotum complex.
Figure 1. - Brightfield image showing the fore wing of Pteroceraphronmirabilipennis Dessart 1981. Arrows point to elongate marginal cilia.
Figure 1. - Brightfield image showing the fore wing of Pteroceraphronmirabilipennis Dessart 1981. Arrows point to elongate marginal cilia.
Development of low-cost instrumentation for single point autofluorescence lifetime measurements
<p>Dataset used for analysis in the paper. ABSTRACT: Autofluorescence lifetime measurements, which can provide label-free readouts in biological tissues, contrasting e.g. different types and states of tissue matrix components and different cellular metabolites, may have significant clinical potential for diagnosis and to provide surgical guidance. However, the cost of the instrumentation typically used currently presents a barrier to wider implementation. We describe a low-cost single point time-resolved autofluorescence instrument, exploiting modulated laser diodes for excitation and FPGA-based circuitry for detection, together with a custom constant fraction discriminator. Its temporal accuracy is compared against a “gold-standard” instrument incorporating commercial TCSPC circuitry by resolving the fluorescence decays of reference fluorophores presenting single and double exponential decay profiles. To illustrate the potential to read out intrinsic contrast in tissue, we present preliminary measurements of autofluorescence lifetime measurements of biological tissues <em>ex vivo.</em> We believe that the lower cost of this instrument could enhance the potential of autofluorescence lifetime metrology for clinical deployment and commercial development.</p>
CALLISTO-SPK: A Stochastic Point Kinetics Code for Performing Low Source Nuclear Power Plant Start-up and Power Ascension Calculations Data Repository
<p>This dataset provides data to accompany the submission named "CALLISTO-SPK: A Stochastic Point Kinetics Code for Performing Low Source Nuclear Power Plant Start-up and Power Ascension Calculations" which has been submitted to Annals of Nuclear Energy. Details of the file included may be found in the readme file.</p>
The dust source points from the west coast of South Africa from 2000 to 2021
<p>This data set describes the location and land use of the dust source points from 2000 and 2021 on the west coast of South Africa from succulent Karoo shrubland, bare areas, and dry pans. The data has been derived daily from MODIS images and the land cover was determined by the South African National Land Cover (SANLC) provided by the Department of Forestry, Fisheries and the Environment.</p>
Target-ligand binding affinity from single point enthalpy calculation and elemental composition
<p>This repository contains supporting files for the manuscript entitled: Target-ligand binding affinity from single point enthalpy calculation and elemental composition.</p>
Circum-Antarctic data used in "Tipping point behaviour of ice-sheet grounding-zone melting due to ocean water intrusion" by Bradley and Hewitt
<p>The file 'Antarctica-data.mat' contains the following fields:</p><p>'x' [units: m] x position of grid points</p><p>'y' [units m] y position of grid points</p><p>'tf_max' [units: C] maximum thermal forcing from Adusumilli et al. 2020 (doi: https://doi.org/10.1038/s41561-020-0616-z)</p><p>'H' [units: m] ice thickness from Bedmachine V3</p><p>'B' [units: m] bed elevation from Bedmachine V3</p><p>'mask' [units: n/a] Bedmachine V3 mask</p><p>'isedge' [units: n/a] Logical array with 1 corresponding to edges of ice shelves and 0 otherwise</p><p>'isgl' [units: n/a] Logical array with 1 corresponding to grounding line points and 0 otherwise</p><p>'isfront' [units: n/a] Logical array with 1 corresponding to ice fronts and 0 otherwise</p><p>'vx' [units: m/a] Ice velocity in the x-direction from ITS_LIVE 240m mosaic</p><p>'vy' [units: m/a] Ice velocity in the y-direction from ITS_LIVE 240m mosaic</p>
Hard Point Cloud Localization Dataset
<p>This is a dataset to evaluate the robustness of point-cloud-based localization algorithms in extremely severe situations including aggressive sensor motion, point cloud degeneration, and data interruptions.</p><p>The dataset contains five indoor sequences recorded with a Microsoft Azure Kinect and three outdoor sequences recorded with a Livox MID360. Each outdoor sequence is split into two consecutive rosbags.</p><p>indoor_easy_01 & 02 : "Easy" sequences without aggressive sensor motion and data interruptions.<br>indoor_hard_01 : "Hard" sequence involving quick sensor motion and point cloud degeneration.<br>indoor_kidnap_01 & 02 : Sequences that involve kidnapping situations (the sensor was moved to another room while its view was completely occluded several times)<br>outdoor_hard_01 & 02 : "Hard" outdoor sequence involving quick sensor motion and point cloud degeneration.<br>outdoor_kidnap : Outdoor sequence that involve kidnapping situations.<br><br>Each rosbag corresponds to an environmental map file as follows:<br>indoor_easy : map_indoor_easy.ply<br>indoor_kidnap : map_indoor_easy.ply<br>indoor_hard : map_indoor_hard.ply<br>outdoor_kidnap : map_outdoor_kidnap.ply<br>outdoor_hard : map_outdoor_hard.ply<br><br>Each indoor sequence contains the following ROS2 messages:<br>- /points2/decompressed : sensor_msgs/msg/PointCloud2 : Point cloud data<br>- /imu : sensor_msgs/msg/Imu : Imu data<br><br>Each outdoor sequence contains the following ROS2 messages:<br>- /livox/points : sensor_msgs/msg/PointCloud2 : Point cloud data<br>- /livox/lidar : livox_ros_driver2/msg/CustomMsg : Point cloud data in the Livox format<br>- /livox/imu : sensor_msgs/msg/Imu : Imu data<br><br>We used the follwoing LiDAR-IMU transformation parameters (T_lidar_imu : [tx, ty, tz, qx, qy, qz, qw]) for the indoor and outdoor sequences:<br>- indoor : [0.003, 0.004, -0.051, -0.476, 0.474, 0.524, 0.525]<br>- outdoor: [0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 1.000]<br><br>Groundtruth trajectories were obtained through batch optimization of point cloud registration residuals and IMU motion residuals. Each line in a GT trajectory file represents the LiDAR pose in the map frame [time, tx, ty, tz, qx, qy, qz, qw] (TUM format). We recommend evo toolkit (https://github.com/MichaelGrupp/evo) for quantitative evaluation.</p>
Stability (similarity) values of output maps generated using different background point sampling strategies
<p>These tables represent the model settings and similarity values of Species Distribution Models generated using different background pointssampling strategies. The similarity values are our own newly designed way to investigate model stability and were determined by comparing an output map of an SDM fitted using real data (original map) with an output map of an SDM fitted using virtual occurrences generated from the original map.</p>
Coordinates of jungle cat vehicle collision locations and background points
Open the record for dataset details and reuse information.
LiDAR and Photogrammetry Point Clouds and R code
<p>Some examples of point clouds from lidar and photogrammetry, from drone and from helicopter surveys.</p> <p>These data are used in the course "Remote Sensing" to forestry students at University of Padova, TESAF Department</p> <p> </p>
2005.002.007 Bag 5b Point 403
From the Connecticut State Museum of Natural History's Caldwell Collection of Neolithic Mali Points, Bag 5b, Point 403. Max height 44.89mm. Max width 19.72mm. GSD 0.0157 mm/pix, RMS reprojection error 0.430386 pix. Source: Objaverse 1.0 / Sketchfab
Newnan Point, SJ13_164
Newnan style biface, North Florida, Archaic (6200-5200 ya) Part of the Coontie Island Collection, SJ13_164 Model by Emily Jane Murray This model was made using RealityCapture software by Capturing Reality Source: Objaverse 1.0 / Sketchfab
Ethiopia Street - Point cloud to Mesh
This is a test to convert an iPad LIDAR point cloud into a PLY mesh using CloudCompare software. Source: Objaverse 1.0 / Sketchfab
Newnan Point, SJ13_118
Newnan style biface, North Florida, Archaic (6200-5200 ya) Part of the Coontie Island Collection, SJ13_118 Model by Emily Jane Murray This model was made using RealityCapture software by Capturing Reality Source: Objaverse 1.0 / Sketchfab
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.