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250 results for “3D analysis”
Figures 18-24 from: Schmidt J, Scholz S, Will K (2022) Character analysis and descriptions of Eocene sphodrine fossils (Coleoptera, Carabidae) using light microscopy, micro-CT scanning, and 3D imaging. Deutsche Entomologische Zeitschrift 69(1): 19-44. https://doi.org/10.3897/dez.69.79931
Figures 18-24 Quasicalathus, light microscopic images of Q. elpis Ortuño & Arillo, 2009 (18–20.) and Q. agonicollis sp. nov. (21–24.). 18. General view of the amber piece "MAIG 76" (only that part of the large amber piece bearing the Quasicalathus fossil is shown; the fossil is widely covered by milky coating); 19. General view of the two fragments of specimen "GZG 16185"; the left one bears only the negative imprint of the left elytra on the inclusion wall; 20. Right anterior part of body of specimen "GZG 16185" showing part of head, pronotum and humerus; 21, 22. General view of the amber piece "GZG 16188" (21. With fossil in dorsal view; 22. In ventral view); 23. Anterior part of specimen "GZG 16188"; 24. Head of specimen "GZG 16188". Abbreviations: a1–a6 – antennomeres 1–6; as – anterior supraorbital seta; bs – pronotal laterobasal seta; ms – pronotal lateral seta; ps – posterior supraorbital seta.
Figures 58-60 from: Schmidt J, Scholz S, Will K (2022) Character analysis and descriptions of Eocene sphodrine fossils (Coleoptera, Carabidae) using light microscopy, micro-CT scanning, and 3D imaging. Deutsche Entomologische Zeitschrift 69(1): 19-44. https://doi.org/10.3897/dez.69.79931
Figures 58-60 Quasicalathus elpis (Ortuño and Arillo 2009), volume rendering of the dorsal aspects of specimens "Groehn 7962" (58.), "CCHH 952" (59.), and "OSAC 265" (60.).
Figures 65-72 from: Schmidt J, Scholz S, Will K (2022) Character analysis and descriptions of Eocene sphodrine fossils (Coleoptera, Carabidae) using light microscopy, micro-CT scanning, and 3D imaging. Deutsche Entomologische Zeitschrift 69(1): 19-44. https://doi.org/10.3897/dez.69.79931
Figures 65-72 Quasicalathus agonicollis sp. nov., volume rendering of the holotype using different grey scales of the Amira software. 65. Dorsal aspect (the negative imprint of the fossil on the inclusion wall is shown); 66. Basal portion of pronotum and anterior part of elytra (positive of the fossilized beetle is shown; the arrows point to the insertions of the pronotal basolateral setae and the parascutellar setae); 67. Metacoxa (the arrows point to the insertions of the three coxal setae each side); 68–71. Aedeagus in dorsal aspect (68.), Right lateral aspect (69.), Ventral aspect (70.), Left lateral aspect (71.); The remains of the parameres are coloured (red: left paramere; green: right paramere); 72. left lateral aspect of beetle body; the aedeagus (highlighted by red colour) was separated by the segmentation function of Amira software. Abbreviations: bb – basal bulb of aedeagal median lobe; hm – humerus; os – distal ostium of median lobe; sc – scutellum; tl – terminal lamella of median lobe.
Figures 1-5 from: Schmidt J, Scholz S, Will K (2022) Character analysis and descriptions of Eocene sphodrine fossils (Coleoptera, Carabidae) using light microscopy, micro-CT scanning, and 3D imaging. Deutsche Entomologische Zeitschrift 69(1): 19-44. https://doi.org/10.3897/dez.69.79931
Figures 1-5 Quasicalathus elpis (Ortuño and Arillo 2009), light microscopic images of specimens "Groehn 4879" (1–3.) and "Groehn 7814" (4, 5.). 1, 5. General view of the amber pieces; 2. Ventral side of head (the white arrow points to the mentum tooth; note that the mentum is somewhat detached from the head capsule); 3. Pronotum and anterior part of elytra showing the markedly concave basal margin and projected humeri; 4. Right lateral view of body.
Figures 25-30 from: Schmidt J, Scholz S, Will K (2022) Character analysis and descriptions of Eocene sphodrine fossils (Coleoptera, Carabidae) using light microscopy, micro-CT scanning, and 3D imaging. Deutsche Entomologische Zeitschrift 69(1): 19-44. https://doi.org/10.3897/dez.69.79931
Figures 25-30 Quasicalathus agonicollis sp. nov., light microscopic images of specimen "GZG 16188" (25–26.) and the holotype (28–30.). 25. Posterior part of pronotum and anterior part of elytra, right side; 26. Anterior part of fifth interval of left elytra showing microsculpture; 27. Posterior part of elytra (the arrows point to the insertions of the discal setae); 28. General view of the amber piece; 29. Right dorsal view of beetle body (the arrow points to the insertion of the discal seta on left elytron); 30. Left ventral view. Abbreviations: bs – insertion of the pronotal laterobasal seta; hm – humerus; m – mite (syninclusion).
Comparative analysis of mechanical properties of alumina and in-office 3D-printed zirconia ceramic brackets
<p>Dataset for all analyses</p>
Data from: Comparative analysis of 2D and 3D distance measurements to study spatial genome organization
The spatial organization of genomes is non-random, cell-type specific, and has been linked to cellular function. The investigation of spatial organization has traditionally relied extensively on fluorescence microscopy. The validity of the imaging methods used to probe spatial genome organization often depends on the accuracy and precision of distance measurements. Imaging-based measurements may either use 2 dimensional datasets or 3D datasets which include the z-axis information in image stacks. Here we compare the suitability of 2D vs 3D distance measurements in the analysis of various features of spatial genome organization. We find in general good agreement between 2D and 3D analysis with higher convergence of measurements as the interrogated distance increases, especially in flat cells. Overall, 3D distance measurements are more accurate than 2D distances, but are also more susceptible to noise. In particular, z-stacks are prone to error due to imaging properties such as limited resolution along the z-axis and optical aberrations, and we also find significant deviations from unimodal distance distributions caused by low sampling frequency in z. These deviations are ameliorated by significantly higher sampling frequency in the z-direction. We conclude that 2D distances are preferred for comparative analyses between cells, but 3D distances are preferred when comparing to theoretical models in large samples of cells. In general and for practical purposes, 2D distance measurements are preferable for many applications of analysis of spatial genome organization.
Data from: A 3D Analysis of Dendritic Solidification and Mosaicity in Ni-Based Single Crystal Superalloys
<p>Author: F. Scholz, M. Cevik, P. Hallensleben, P. Thome, G. Eggeler, J. Frenzel</p> <p>Affiliation: Ruhr University Bochum</p> <p>Date: 08/2021</p> <p>Material: Nickel-base superalloy ERBO/1 (more details: Parsa, A. B., et al. Advanced scale bridging microstructure analysis of single crystal Ni-base superalloys. Adv. Eng. Mater. 2015, 17 (2), 216-230, <a href="https://doi.org/10.1002/adem.201400136">https://doi.org/10.1002/adem.201400136</a>)</p> <p>Casting: Bridgman seed technique; Withdrawal rate: 180 mm/h, Thermal gradient 13.3 K/mm (more details: Hallensleben, P., et al. On the evolution of cast microstructures during processing of single crystal Ni-base superalloys using a Bridgman seed technique, Mat. Des. 2017, 128, 98–111, <a href="https://doi.org/10.1016/j.matdes.2017.05.001">https://doi.org/10.1016/j.matdes.2017.05.001</a>)</p> <p>Sample: Cross sectional slices extracted perpendicular to the growth direction of a single crystal superalloy cylinder (diameter 12mm, length 120 mm).</p> <p>Image acquisition: Optical microscope of type Axio (Carl Zeiss GmbH) equipped with a high-resolution CCD-camera of type Leica DFC320 and stepper-motor driven sample stage of type Tango Desktop (Märzhäuser)</p> <p>Image pre-processing: Preparation of wide-field image collages using the stitching procedures implemented in software package Imagic ims (<a href="https://imagic.ch/en/imagic-ims">https://imagic.ch/en/imagic-ims</a>, 07/2021)</p> <p>Image post-processing: Image registration with CorelDraw X7 (: <a href="https://www.coreldraw.com/en/">https://www.coreldraw.com/en/</a>, 07/2021) using a contour reference mask</p> <p>Quantitate analysis: Dendrite positions were extracted using the software package ImageJ (<a href="https://imagej.de.softonic.com/">https://imagej.de.softonic.com/</a>, 07/2021).</p> <p>--------------------------------------</p> <p>The five optical micrographs cross sections represent image data which were obtained by tomographic characterization of as-cast single crystal nickel-base superalloy prepared by a seeded Bridgman technique. The material has been studied in the frame of the collaborative research center SFB/TR 103. All details on the applied Bridgman technique are described in the literature (Hallensleben, P., et al., Mat. Des. 2017, 128, 98–111, <a href="https://doi.org/10.1016/j.matdes.2017.05.001">https://doi.org/10.1016/j.matdes.2017.05.001</a> and Hallensleben, P., et al., Crystals 2019, 9 (3), 149, <a href="https://doi.org/10.3390/cryst9030149">https://doi.org/10.3390/cryst9030149</a>). The tomographic image slices were prepared by successive electro discharge machining using incremental steps of 1mm. The image series represents the evolution of dendritic microstructures during the early stages of crystal growth from the back melted seed. The five wide-field micrographs were used to retrieve dendrite positions (enclosed as CSV data for each cross section) to evaluate crystal mosaicity on the basis of dendrite growth directions. All information and a detailed interpretation of tomographic are available in (Scholz, F., PhD-thesis, Ruhr University Bochum, <a href="https://doi.org/10.13154/294-8079">https://doi.org/10.13154/294-8079</a>). We hope that our image data will be useful for other types of solidification research. Please provide a notification by personal mail on the re-use of our raw data. Thank you.</p> <p>All images and dendrite position data were evaluated in the following study concerning dendrite growth behavior, low angle misorientation defects, dendrite arrangements and spacings:</p> <p>Scholz, F.; Cevik, M.; Hallensleben, P.; Thome, P.; Eggeler, G.; Frenzel, J. A 3D Analysis of Dendritic Solidification and Mosaicity in Ni-based Single Crystal Superalloys, Materials 2021, 14 (17), 4904 (https://doi.org/10.3390/ma14174904).</p>
XYZ coordinates of middle lumbar vertebrae - 3D GM analysis for: A nearly complete lower back of Australopithecus sediba
<p>Adaptations of the lower back to bipedalism are frequently discussed but infrequently demonstrated in early fossil hominins. Newly discovered lumbar vertebrae contribute to a near-complete lower back of Malapa Hominin 2 (MH2), offering additional insights into posture and locomotion in <i>Australopithecus sediba</i>. We show that MH2 demonstrates a lower back consistent with lumbar lordosis and other adaptations to bipedalism, including an increase in the width of intervertebral articular facets from the upper to lower lumbar column ("pyramidal configuration"). These results contrast with some recent work on lordosis in fossil hominins, where MH2 was argued to demonstrate no appreciable lordosis ("hypolordosis") similar to Neandertals. Our three-dimensional geometric morphometric (3D GM) analyses show that MH2's nearly complete middle lumbar vertebra is human-like in overall shape but its vertebral body is somewhat intermediate in shape between modern humans and great apes. Additionally, it bears long, cranially and ventrally oriented costal (transverse) processes, implying powerful trunk musculature. We interpret this combination of features to indicate that <i>A. sediba</i> used its lower back in both bipedal and ape-like arboreal positional behaviors, as previously suggested based on multiple lines of evidence from other parts of the skeleton and reconstructed paleobiology of <i>A. sediba</i>.</p>
Fig. 4. Synchronized 3D in Metabolic fingerprinting of Ganoderma spp. using UHPLC-ESI-QTOF-MS and its chemometric analysis
Fig. 4. Synchronized 3D PCA plot of all 18 samples of Ganoderma mushroom.
3D X-ray Motion Analysis of Ankle-foot Motion After Total Ankle Arthroplasty
ClinicalTrials.gov study NCT03575975. IPD Sharing: NO. Countries: 1. Publications: 0.
Feasibility Analysis of LCD-SLA 3D Printing Technology for Overall Surgical Planning of Liver Malignant Tumors
ClinicalTrials.gov study NCT06526754. IPD Sharing: YES. Countries: 1. Publications: 0.
Analysis of Orthodontic Tooth Movement Using 3D Imaging
ClinicalTrials.gov study NCT03398798. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Comparative analysis of 2D and 3D distance measurements to study spatial genome organization
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Data from: Use of anisotropy, 3D segmented atlas, and computational analysis to identify gray matter subcortical lesions common to concussive injury from different sites on the cortex
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Soil images in DICOM format including Python programs for data transformation, 3D analysis, CNN traininig, CNN analysis
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XYZ coordinates of middle lumbar vertebrae - 3D GM analysis for: A nearly complete lower back of Australopithecus sediba
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Data from: A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture
Open the record for dataset details and reuse information.
MERRA-2 inst6_3d_ana_Np: 3d,6-Hourly,Instantaneous,Pressure-Level,Analysis,Analyzed Meteorological Fields 0.625 x 0.5 degree V5.12.4 (M2I6NPANA) at GES DISC
M2I6NPANA (or inst6_3d_ana_Np) is an instantaneous 3-dimensional 6-hourly data collection in Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2). This collection consists of analyzed meteorological fields at 42 pressure levels, such as temperature, wind components, specific humidity, ozone mixing ratio, and geopotential height. The data field is available every six hour starting from 00:00 UTC, e.g.: 00:00, 06:00, … , 18:00 UTC. The information on the pressure levels can be found in the section 4.2 of the MERRA-2 File Specification document. MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present with the latency of ~3 weeks after the end of a month. Data Reprocessing: Please check “Records of MERRA-2 Data Reprocessing and Service Changes” linked from the “Documentation” tab on this page. Note that a reprocessed data filename is different from the original file.MERRA-2 Mailing List: Sign up to receive information on reprocessing of data, changing of tools and services, as well as data announcements from GMAO. Contact the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov) to be added to the list.Questions: If you have a question, please read "MERRA-2 File Specification Document", “MERRA-2 Data Access – Quick Start Guide”, and FAQs linked from the ”Documentation” tab on this page. If that does not answer your question, you may post your question to the NASA Earthdata Forum (forum.earthdata.nasa.gov) or email the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov).
MERRA-2 instM_3d_ana_Np: 3d,Monthly mean,Instantaneous,Pressure-Level,Analysis,Analyzed Meteorological Fields 0.625 x 0.5 degree V5.12.4 (M2IMNPANA) at GES DISC
M2IMNPANA (or instM_3d_ana_Np) is an instantaneous 3-dimensional monthly mean data collection in Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2). This collection consists of analyzed meteorological fields at 42 pressure levels, such as temperature, wind components, specific humidity, ozone mixing ratio, and geopotential height. The information on the pressure levels can be found in the section 4.2 of the MERRA-2 File Specification document. The collection also includes certain quadratic information (such as the variance and covariance of certain parameters). MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present with the latency of ~3 weeks after the end of a month. Data Reprocessing: Please check “Records of MERRA-2 Data Reprocessing and Service Changes” linked from the “Documentation” tab on this page. Note that a reprocessed data filename is different from the original file.MERRA-2 Mailing List: Sign up to receive information on reprocessing of data, changing of tools and services, as well as data announcements from GMAO. Contact the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov) to be added to the list.Questions: If you have a question, please read "MERRA-2 File Specification Document", “MERRA-2 Data Access – Quick Start Guide”, and FAQs linked from the ”Documentation” tab on this page. If that does not answer your question, you may post your question to the NASA Earthdata Forum (forum.earthdata.nasa.gov) or email the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov).
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)
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.