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1,007 results for “three dimensional”
Dataset: A three-dimensional approach to general plant fire syndromes
<p>1. Plant fire syndromes are usually defined as combinations of fire response traits, the most common being resprouting (R) and seeding (S). Plant flammability (F), on the other hand, refers to a plant's effects on communities and ecosystems. Despite its important ecological and evolutionary implications, F has rarely been considered to define plant fire syndromes and, if so, usually separated from response syndromes.</p> <p>2. We propose a three-dimensional model that combines R, S and F, encapsulating both plant response to fire regimes and the capacity to promote them. Each axis is divided into three possible standardized categories, reflecting low, medium and high values of each variable, with a total of 27 possible combinations of R, S and F.</p> <p>3. We hypothesized that different fire histories should be reflected in the position of species within the three-dimensional space and that this should help assess the importance of fire as an evolutionary force in determining R-S-F syndromes.</p> <p>4. To illustrate our approach we compiled information on the fire syndromes of 24 dominant species of different growth forms from the Chaco seasonally-dry forest of central Argentina, and we compared them to 33 species from different Mediterranean-type climate ecosystems (MTCEs) of the world.</p> <p>5. Chaco and MTCEs species differed in the range (seven syndromes vs. thirteen syndromes, respectively) and proportion of extreme syndromes (i.e. species with extreme values of R, S and/or F) representing 29% of species in the Chaco vs. 45% in the MTCEs.</p> <p>6. Additionally, we explored the patterns of R, S and F of 4032 species from seven regions with contrasting fire histories, and found significantly higher frequencies of extreme values (predominantly high) of all three variables in MTCEs compared to the other regions, where intermediate and low values predominated, broadly supporting our general hypothesis.</p> <p>7. The proposed three-dimensional approach should help standardize comparisons of fire syndromes across taxa, growth forms and regions with different fire histories. This will contribute to the understanding of the role of fire in the evolution of plant traits and assist vegetation modelling in the face of changes in fire regimes.</p>
Dataset for the manuscript: "Three-dimensional species distribution modeling reveals the realized spatial niche for coral recruitment on contemporary Caribbean reefs"
<p>Whether the three-dimensional (3D) structure of habitats influences and partition recruitment niches of corals is unknown. We developed a new method that combined Species Distribution Modeling and Structure from Motion to characterize and map the three-dimensional recruitment niches of two ecosystem engineers on Caribbean coral reefs, scleractinian corals and octocorals. </p> <p>In this repository, we include 48 3D models of small areas of the reef (i.e., within ~ 0.25 m<sup>2</sup> quadrats) reconstructed with Structure-from-Motion, as well as the geospatial data used to characterize and map the realized recruitment niche for scleractinian corals and octocorals on Caribbean coral reefs. We conducted the study at two shallow, fringing reefs off the south shore of St. John, US Virgin Islands, named Grootpan and Europa Bays (18° 18.360’N, 64° 43.140’W, and 18° 19.016’N, 64° 43.798’W, respectively). Within each 0.25 m<sup>2</sup> quadrat, we counted and marked all recruits (octocorals ≤ 5 cm height, and scleractinians ≤ 4 cm wide).</p> <p><em>DATASET DESCRIPTIONS:</em></p> <ul> <li><strong>"Quadname_data.zip":</strong> In each of this folders we included all the data calculated within a quadrat: <ul> <li>ASCII files (.txt).</li> <li>The annotated dense point cloud (.las) for each quadrat.</li> <li>The quadrat 3D model texture (.jpg).</li> <li>The quadrat 3D polygon mesh (.ply).</li> <li>The quadrat 2.5D Digital Elevation Model (i.e., DEM; .tif).</li> <li>Shape files with recruits local coordinates within each quadrat (.dbf, .prj, .shp, .shx).</li> </ul> </li> <li><strong>"datawide.rds": </strong>This is the file needed to run the analyses performed in Martínez-Quintana et al., 2023. This file is obtained after processing all the raw data calculated within each quadrat. All code associated with the workflow used to obtain the datawide.rds file and run the analyses performed in Martínez-Quintana et al., 2023 is available at <a href="https://github.com/AdamWilsonLab/meshSDM">github.com/AdamWilsonLab/meshSDM</a>.</li> </ul> <p><strong>IMPORTANT NOTES: </strong></p> <ul> <li>Quadrat names starting with the letters “eu” indicate the data were collected at Europa Bay, whereas those starting with the letters “ec” indicate that data were collected at Grootpan Bay (commonly named East Cabritte).</li> <li>Each ASCII file (quadname_ASCII_subsampled_X.txt) contains the slope and roughness of the quadrat calculated on the point cloud at 5, 10, 20, and 100 mm scales, and the smooth point cloud used to calculate the topographic exposure index (TEI) described in Martínez-Quintana et al., 2023. Calculations were performed and ASCII files were created with CloudCompare.</li> <li>Each dense point cloud, mesh, texture, and DEM were calculated with Agisoft Metashape.</li> <li>Agisoft Metashape allows the user to classify and annotate groups of points in the dense point cloud. However, the list of classes provided by the software corresponds to the standard list used for terrestrial LiDAR data; these classes cannot be renamed within the software. Thus, for the present study, we coded the automatic semantic classifications available in Metashape as follows: <ul> <li>Ground = Calcareous rock.</li> <li>Building = Igneous rock.</li> <li>High noise = Sand.</li> <li>Low vegetation = Adult Scleractinian corals.</li> <li>Medium vegetation = Adult Octocoral base.</li> <li>High vegetation = Sponge.</li> <li>Water = Octocoral recruit (named also ocr).</li> <li>Road Surface = Scleractinian recruit (named also scr).</li> <li>Unclassified = created points but never classified (excluded from the analyses).</li> <li>Low Point = noise (unreliable points).</li> <li>Transmission tower and Rail = Points outside the quadrat and excluded from the analysis.</li> </ul> </li> </ul>
Three dimensional reconstruction of an existing age-old wooden shingle roof
<p>This dataset provides a complete and thorough three-dimensional reconstruction of an age-old shingled roof located in Rossinière, Switzerland (<a href="https://www.google.com/maps/dir//46.468247,7.059739/@46.4670828,7.012801,12z/data=!4m2!4m1!3e0">46.46837286488975, 7.059749511857417</a>), which provides reliable documentation to archive this valuable type of architecture.</p> <p>This dataset was obtained using a 3D Farco Focus scanner and the point clouds were processed using FaroScene software.</p> <p>This research was funded by the National Centres of Competence in Research (<a href="https://www.snf.ch/en/FJBJ8XGQ1tjG8J8w/funding/programmes/national-centres-of-competence-in-research-nccr">NCCRs</a>) and EPFL.</p>
Three-dimensional morphology of the biramous appendages in Isoxys from the early Cambrian of South China, and its implications for early euarthropod evolution
<p>Early euarthropod evolution involved a major transition from lobopodian-like taxa to organisms featuring a segmented, well-sclerotized trunk (arthrodization) and limbs (arthropodization). However, the precise origin of a completely arthrodized trunk and arthropodized ventral biramous appendages remain controversial, as well as the early onset of anterior-posterior limb differentiation in stem-group euarthropods. New fossil material and micro-computed tomography inform the detailed morphology of the arthropodized biramous appendages in the carapace-bearing euarthropod <em>Isoxys curvirostratus </em>from the early Cambrian Chengjiang biota. In addition to well-developed grasping frontal appendages. <em>I. curvirostratus</em> possesses two batches of morphologically and functionally distinct biramous limbs. The first batch consists of four pairs of short cephalic appendages with robust endites with a feeding function, whereas the second batch has more elongate trunk appendages for locomotion. Critically, our new material shows that the trunk of <em>I. curvirostratus</em> was not arthrodized. The results of our phylogenetic analyses recover isoxyids as some of the earliest branching sclerotized euarthropods, and strenghens the hypothesis that arthropodized biramous appendage evolved before full body arthrodization.</p>
The Impact of the Three-Dimensional Structure of a Subduction Zone on Time-dependent Crustal Deformation Measured by HR-GNSS
<p>Companion data set to the paper "<strong>The Impact of the </strong><strong>Three-Dimensional Structure of a Subduction Zone on Time-dependent Crustal Deformation Measured by HR-GNSS.</strong>" The 'GNSS_Stations' folder contains the GNSS stations used for 2011 <strong>M</strong>7.9 Ibaraki, 2011 <strong>M</strong>7.4 Iwate, 2011A <strong>M</strong>7.3 Miyagi and 2003 <strong>M</strong>8.3 Tokachi 2003 earthquakes. The 'Mesh' folder contains the fault geometry mesh files for the Japan Trench, including the GMSH files. The '3D_velocity_model' folder contains the 3D velocity model for the combined West and East domains of the 3D Japan Integrated Velocity Structure Model in a rfile format and the corresponding ifile format. The 'Ruptures' folder contains the projected rupture models for each earthquake on the Japan Trench mesh and the corresponding 100 realizations of the mean rupture models generated using FakeQuakes. If you use these data, please cite the associated publication:</p> <p>Fadugba, ­O. I., Sahakian, V. J., Diego Melgar, D., Rodgers, A. & Shimony, R. (2023). The Impact of the Three-Dimensional Structure of a Subduction Zone on Time-dependent Crustal Deformation Measured by HR-GNSS.</p>
Data from: Three-dimensional nanoimaging of fuel cell catalyst layers
<p>The folders contain data and code source files associated with the article "Three-dimensional nanoimaging of fuel cell catalyst layers" published in Nature Catalysis, 6 (2023) 383-391</p> <p>Content:<br> - Data.zip: contains raw and processed data (reconstructed, denoised, segmented, thickness distributions) for samples LSC7 and HSC7. Data is organized to enable the reproduction of training models for denoising and segmentation using the notebooks in "Code and Scripts.zip".<br> - Code and Scripts.zip: contains jupyter notebooks for training and application of the segmentation models and for analysis of the segmented reconstructions; FIJI/imageJ script for semi-manual alignment of tilt-series</p>
Datasets for "Scalable, flexible carbon fiber electrode thread arrays for three-dimensional spatial profiling of neurochemical activity in deep brain structures of rodents"
<p>Datasets used in the manuscript titled, "<strong>Scalable, flexible carbon fiber electrode thread arrays for three-dimensional spatial profiling of neurochemical activity in deep brain structures of rodents</strong>" are uploaded here. </p> <p><strong>Brightfield and fluorescent stained images of brain tissue used for Fig. 5(a):</strong></p> <p>Malt3-20190624_Region 009_DAPI.png</p> <p>Malt3-20190624_Region 009_qCy5.png</p> <p>Malt3-20190624_Region 009_qFITC.png</p> <p>Malt3-20190624_Region 009_qTexasRed.png</p> <p>Malt3_BF20190628_Region 001.png</p> <p><strong>Fluorescent image of brain with embedded CFETs:</strong></p> <p>MALT2_Rat_100um_MOR1_x500_TSA_AF488.jpg</p> <p>Rat_100um_MOR1_x500_TSA.czi</p> <p><strong>In vivo dopamine recording data for Fig. 3:</strong></p> <p>ratarrays822_163.mat</p> <p>ratarrays822_57.mat</p>
Quantitative three-dimensional local order analysis of nanomaterials through electron diffraction
<p>Diffraction data for Yttrium Stabilized Zirconia Zr<sub>0.82</sub>Y<sub>0.18</sub>O<sub>1.91</sub></p> <p><strong>Electron diffraction data:</strong></p> <ul> <li>FEI Tecnai G2 microscope</li> <li>200 keV electrons</li> <li>Cheetah detector (ASI, 512 x 512 pixel)</li> <li>Condenser Aperature 10 micrometer, spot size 9</li> <li>Exposure 1.512 s / frame, rotation 0.4 deg/frame</li> <li>raw data was processed with PETS2 (http://pets.fzu.cz/)</li> </ul> <p><strong>X-ray diffraction data:</strong></p> <ul> <li>Rigaku Syneergy S diffractometer</li> <li>Eiger 1M Detector, energy discriminating threshold 17.4 keV</li> <li>Mo K-alpha radiation</li> <li>120 s exposure time, 0.5 deg/frame</li> <li>Raw data can be processed with CrysAlisPro (https://www.rigaku.com/products/crystallography/crysalis)</li> </ul> <p><strong>Neutron diffraction data:</strong></p> <ul> <li>D19 ILL, Grenoble</li> <li>0.95 A wavelength</li> <li>80 s exposure time, 0.1 deg/frame</li> <li>Raw data can be accessed at <a href="http://dx.doi.org/10.5291/ILL-DATA.5-13-277">doi:10.5291/ILL-DATA.5-13-277</a> and processed with the Instrument software Int3D (https://www.ill.eu/users/instruments/instruments-list/d19/software)</li> </ul> <p><strong>Reciprocal space reconstructions and 3D-DeltaPDF maps</strong></p> <p>Provided in .h5 format and can be vizualized e.g. with DISCUS (https://github.com/tproffen/DiffuseCode/releases) or DensityViewer (https://github.com/aglie/DensityViewer/releases/)</p>
Site-directed placement of three-dimensional DNA origami
<p><span>The combination of lithographic methods with 2D DNA origami self-assembly has led, among others, to the development of photonic crystal cavity arrays and the exploration of sensing nanoarrays where molecular devices are patterned on the sub-micron scale. Here we extend this concept to the third dimension by mounting 3D DNA origami onto nano-patterned substrates, followed by silicification to provide mechanical and chemical stability. We created fully addressable, three-dimensional nanopatterns of hybrid DNA-silica structures with heights up to 50 nm and feature size in the sub-10-nm regime. Our versatile and scalable method relying on self-assembly at ambient temperatures offers the potential to 3D-position any inorganic and organic components compatible with DNA origami nanoarchitecture, demonstrated with gold nanoparticles. This way of nanotexturing could provide a route for the low-cost production of complex and 3D-patterned surfaces and integrated devices designed on the molecular level while reaching macroscopic dimensions.</span></p>
Model Partition of Three-Dimensional Space
* Model Relating to the Regular Partition of Three-Dimensional Space. This white plaster model has faces that are rectangles, pentagons, hexagons, and septagons. Four line segments are indicated. * *(метка Р127.3)* Source: Objaverse 1.0 / Sketchfab
Two and Three Dimensional Contrast-enhanced Ultrasound for Screening of Renal Cell Carcinoma Recurrence Following Cryoablation
ClinicalTrials.gov study NCT02440334. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Three-Dimensional Evaluation of Pharyngeal Airway and Facial Dimension Changes in Skeletal Class II Patients Treated With Twin Block Versus Myobrace Appliances
ClinicalTrials.gov study NCT06976749. IPD Sharing: YES. Countries: 1. Publications: 1.
Three-Dimensional Printing and Three-Dimensional Miniplates in Treatment of Anterior Mandibular Fractures
ClinicalTrials.gov study NCT06898736. IPD Sharing: NO. Countries: 1. Publications: 3.
Interpreting morphological adaptations associated with viviparity in the Tsetse fly (Glossina morsitans) by three-dimensional analysis
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Three-dimensional time-resolved flash occurrences of swarming Photinus carolinus fireflies in their natural habitat
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Three dimensional localization refinement and motion model parameter estimation for confined single particle tracking under low-light conditions: Simulation datasets
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Effects of three-dimensional soil heterogeneity and species composition on plant biomass and biomass allocation of grass-mixtures
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Data from: Three-dimensional midwater camouflage from a novel two-component photonic structure in hatchetfish skin
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Data from: Human face-off: a new method for mapping evolutionary rates on three-dimensional digital models
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The three-dimensionally articulated oral apparatus of a Devonian heterostracan sheds light on feeding in Palaeozoic jawless fishes
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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.