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6 results for “feature points”
Text-fig. 2. Nymphaea sp. from the Miocene Clarkia Lake flora, Locality P-33. a: Photograph of the fossil leaf. b: Sketch of leaf showing the salient features of shape, basal lobes and margin, eccentric insertion point of the abaxial petiole, and primary actinodromous venation. Dashed lines represent torn edge of lamina; dotted line is outline of right basal lobe. Line drawing by P. Martin Sander. Scale bar applies to both photo and drawing. in First Water Lily, A Leaf Of Nymphaea Sp., From The Miocene Clarkia Flora, Northern Idaho, Usa: Occurrence, Taphonomic Observations, Floristic Implications
Text-fig. 2. Nymphaea sp. from the Miocene Clarkia Lake flora, Locality P-33. a: Photograph of the fossil leaf. b: Sketch of leaf showing the salient features of shape, basal lobes and margin, eccentric insertion point of the abaxial petiole, and primary actinodromous venation. Dashed lines represent torn edge of lamina; dotted line is outline of right basal lobe. Line drawing by P. Martin Sander. Scale bar applies to both photo and drawing.
DEM, rock point clouds, and 3D morphological features of Martian rocks in the landing region of Zhurong rover
<p>Rocks on the Martian surface and their three-dimensional (3D) morphology record the geological evolution of Mars and its interaction history with outer space. China's Zhurong Mars rover has traveled on Mars for nearly 2 kilometers and obtained a wealth of data, enabling the fine-scale measurement and morphological analysis of 3D Martian rocks. With 178 high-resolution Zhurong NaTeCams stereo images acquired in rings covering large circular areas, we extracted 6,185 3D rocks from centimeter-scale to meter-scale distributed along the traverse of the Zhurong rover using an automatic approach. This dataset includes the digital elevation model (DEM), extracted rocks in point clouds, and the 3D morphological features of rocks derived from the Zhurong NaTeCams images, obtained in six areas along the traverse of the Zhurong rover.</p> <p>To use this dataset, please cite "Li, Y., Xiao, Z., Ma, C., Zeng, L., Zhang, W., Peng, M., & Li, A. (2023). Extraction and Analysis of Three‐dimensional Morphological Features of Centimeter‐scale Rocks in Zhurong Landing Region. <em>Journal of Geophysical Research: Planets</em>, e2022JE007656."</p>
Data for "Estimation of Return Stroke Velocity by Time Reversal Reconstruction of Channel Feature Points"
<p>In the manuscript entitled “Estimation of Return Stroke Velocity by Time Reversal Reconstruction of Channel Feature Points”, station coordinates of the location system, simulation data, and experimental data can be obtained through the following attachment. These files can be opened by Matlab 2018(or later). The data supports the aforementioned manuscript and can be used freely for scientific purposes with appropriate citations.</p> <p> </p> <p>'IniationParameters_center.mat' is the coordinates of LFLLS stations and strike point (simulation).</p> <p>a) simulation_strike_point: coordinates of the return point (simulation).</p> <p>b) x0, y0, and z0: coordinates of LFLLS stations in x, y, and z directions.</p> <p> </p> <p>1. Simulation data (EE_zd: E-field waveforms (Unit V/m); Ee_zd: Electrostatic component of the E-field waveforms (Unit V/m); Ei_zd: Induction component of the E-field waveforms (Unit V/m); Er_zd: Radiation component of the E-field waveforms (Unit V/m); T: times corresponding to the E-field waveforms; vv: RS velocity condition; tort_x, tort_y, and tort_z: Coordinates of segmented channels).</p> <p>'Simulation_Vertical_channel_Ez_V1.mat' is the vertical channel E-field waveforms calculated under the RS velocity condition V1.</p> <p>'Simulation_Vertical_channel_Ez_V2.mat' is the vertical channel E-field waveforms calculated under the RS velocity condition V2.</p> <p>'Simulation_Vertical_channel_Ez_V3.mat' is the vertical channel E-field waveforms calculated under the RS velocity condition V3.</p> <p>'Simulation_Inclined_channel_Ez.mat' is the inclined channel E-field waveforms calculated under the RS velocity condition V1.</p> <p>'Simulation_Tortuous(randomly)_channel_Ez.mat' is the tortuous channel (randomly) E-field waveforms calculated under the condition of RS velocity constant.</p> <p>'Simulation_Tortuous_channel_Ez.mat' is the tortuous channel E-field waveforms calculated under the RS velocity condition V1.</p> <p> </p> <p>2. Experimental data</p> <p>'2020-08-09-002418-905.5ms(0.4)-siteidx(12346).mat' is the E-field original waveforms of -CG002418.RS2.</p> <p>a) wave: E-field original waveforms of -CG002418.RS2 (D.U.).</p> <p>b) time: times corresponding to the E-field waveforms.</p> <p> </p> <p>3. Figure data</p> <p>This folder contains the .fig format files of Figure 3 ~ 10 in the paper.</p>
BES bird survey habitat features. This is a collection of the habitat features for the BES bird sampling points. Features include number of houses, proximity to trees, shrubs, grass, annuals, and other vegetation and physical features.
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The data consists of four major elements, Sites, Surveys, Taxalist, and Birds. Sites records the sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: Here are the fields Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class
An Improved QEM Algorithm Based on Salient Feature Sampling Points
Open the record for dataset details and reuse information.
3D-MSNet: A point cloud based deep learning model for untargeted feature detection and quantification in profile LC-HRMS data
<p>Supplementary data of 3D-MSNet</p>
ScienceDex guides
Understand access before you commit
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)
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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.