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2,113 results for “High resolution”
Figs 24–27 in On the Nature of Tintinnid Loricae (Ciliophora: Spirotricha: Tintinnina): a Histochemical, Enzymatic, EDX, and High-resolution TEM Study
Figs 24–27. Transmission electron micrographs of a lorica surface in Eutintinnus angustatus at middle (24) and higher (25–27) resolution. 24 – crystal lattice; 25 – digitally enlarged detail of Fig. 24 (bottom part). The periodicity of the hexagonal structures amounts to ~ 23.7 nm with a resolution of ~ 3 nm for the smallest details; 26 – fast Fourier transform of Fig. 25; 27 – noise filtered bright field image after inverse Fourier transform of Fig. 26, using only the diffraction spots. Due to the enhanced contrast, the ultrastructure of the crystal lattice appears more distinct.
Figs 20–23 in On the Nature of Tintinnid Loricae (Ciliophora: Spirotricha: Tintinnina): a Histochemical, Enzymatic, EDX, and High-resolution TEM Study
Figs 20–23. Transmission electron micrographs of a lorica surface in Eutintinnus angustatus at middle resolution. 20 – a crystalline region ~ 1.5 µm in diameter is shown in the centre of the micrograph. An aggregate of bitter salt (MgSO 4) is attached to the wall (arrow); 21 – crystalline area at higher magnification showing dark spots of sodium and potassium chloride on the lorica wall; 22 – each black spot represents a NaCl or KCl nanocrystal (arrows), which has almost the same size as the unit cells of the crystal lattice (~ 20 nm); 23 – Fourier filtered high-resolution micrograph of a sodium chloride nanocrystal.
Fig. 15. Energy-dispersive X in On the Nature of Tintinnid Loricae (Ciliophora: Spirotricha: Tintinnina): a Histochemical, Enzymatic, EDX, and High-resolution TEM Study
Fig. 15. Energy-dispersive X-ray spectrometric (EDX) analysis in the scanning electron microscope, using uncoated material. The analysed area of the Eutintinnus angustatus lorica is marked by a white frame (~ 11 × 9 µm in size). Since this part of the lorica was freely suspended in the vacuum, elemental detection occurred without influence of the carbon substrate.
Figs 16–19 in On the Nature of Tintinnid Loricae (Ciliophora: Spirotricha: Tintinnina): a Histochemical, Enzymatic, EDX, and High-resolution TEM Study
Figs 16–19. Transmission electron micrographs of an uncoated lorica surface of Eutintinnus angustatus at different magnifications. 16 – overview of right lorica half. The lorica lies nearly horizontally on the electron transparent holey carbon substrate. The black rectangular structures are the copper bars of the TEM grid; 17 – anterior portion of right lorica half; 18 – apical lorica portion; 19 – lateral lorica portion. The dark crystalline dendritic structures consist of sodium chloride nanocrystals, which probably originate in the sea water.
Fig. 1 in Species-specific qPCR assays allow for high-resolution population assessment of four species avian schistosome that cause swimmer's itch in recreational lakes
Fig. 1. Abundance of cercariae by sampling site. Water samples were obtained in mid-June and cercariae abundance was determined using the pan-avian schistosomes qPCR.
Fig. 2 in Species-specific qPCR assays allow for high-resolution population assessment of four species avian schistosome that cause swimmer's itch in recreational lakes
Fig. 2. Percent contribution of T. stagnicolae, T. szidati, T. physellae and A. brantae species to each lake. Water samples from different locations and dates were tested using the species-specific qPCR assay and results were pooled by lake to understand the relative contribution overall of each species to each lake. The percent contribution (based on gene copy number) of each species was calculated.
Fig. 3 in Species-specific qPCR assays allow for high-resolution population assessment of four species avian schistosome that cause swimmer's itch in recreational lakes
Fig. 3. Lifecycles of T. stagnicolae, A. brantae, T. szidati, and T. physellae. life cycle summary of the avian schistosome species targeted for species-specific qPCR tests designed in this study.
Fig. 3 in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)
Fig. 3. Phylogenetic tree of seven Trypanosome species and subsequent genotypes constructed with sequences of the amplicons generated by the HRMqPCR primers.
Fig. 4 in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)
Fig. 4. Amplification plots, melt curves and standard curves of T. copemani, T. vegrandis G7 and T. noyesi G8 prepared from a plasmid containing trypanosome species.
Fig. 5. A-D in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)
Fig. 5. A-D: Derivative melt curves showing mock mixed infections generated from plasmid clones containing the following DNA: (A) T. noyesi G8 and T. copemani; (B) T. vegrandis G7 and T. copemani; (C) T. vegrandis G7 and T. noyesi G8; (D) T. vegrandis G7, T. noyesi G8 and T. copemani.
Fig. 1 in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)
Fig. 1. Multiple sequence alignment of a portion of the 18S rDNA of seven Trypanosome species and subsequent genotypes used to design the HRM-qPCR assays.
Figure 2 in High-Resolution Functional Imaging of Native Proteins using Force Distance Curve Based Atomic Force Microscopy
Figure 2. - Juvenile Trachipterus arcticus, 129 mm SL, collected at Faial Island, Azores, 14 May 2014, on the surface. A: Portrait with anterior black facet visible; B: Oblique lateral view with first spines erected; note orange bulbous outgrowths on the prolonged spine; C: Lateral view showing proportions, markings and orientation of fins. Scale bars: A = 1 cm; B, C = 5 cm.
Figure 1 in High-Resolution Functional Imaging of Native Proteins using Force Distance Curve Based Atomic Force Microscopy
Figure 1. - Adult Trachipterus arcticus, about 1.8 m long, observed south of Pico Island, Azores, 18 Aug. 2013, 950 m deep.
High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data
<p>We developed Pan-European maps of timber volume (V), above-ground biomass (AGB), and deciduous-coniferous proportion (DCP) with a pixel size of 10 x 10 m<sup>2</sup> for the reference year 2020 using a combination of a Sentinel 2 mosaic, Copernicus layers, and National Forest Inventory (NFI) data.</p> <p>For mapping, we used the k-Nearest Neighbor (kNN, k=7) approach with a harmonized database of species-specific V and AGB from 14 NFIs across Europe. This database encompasses approximately 151,000 sample plots, which were intersected with the above-mentioned Earth observation data. The maps cover 40<a> European countries, </a>forming a continuous coverage of the western part of the European continent.</p> <p>A sample of 1/3 of NFI plots was left out for validation, whereas 2/3 of the plots were used for mapping. Maps were created independently for 13 multi-country processing areas. Root-mean-squared-errors (RMSEs) for AGB ranged from 53 % in the Nordic processing area to <a>73 % </a>the South-Eastern area.</p> <p>The created maps are the first of their kind as they are utilizing a huge amount of harmonized NFI observations and consistent remote sensing data for high-resolution forest attribute mapping. While the published maps can be useful for visualization and other purposes, they are primarily meant as auxiliary information in model-assisted estimation where model-related biases can be mitigated, and field-based estimates improved. Therefore, additional calibration procedures were not applied, and especially high V and AGB values tend to be underestimated. Summarizing map values (pixel counting) over large regions such as countries or whole Europe will consequently result in biased estimates that need to be interpreted with care.</p> <p>The author list is sorted by last name except for the first and last authors who also serve as corresponding authors.</p> <p>Corresponding authors: <a href="mailto:Jukka.Miettinen@vtt.fi">Jukka.Miettinen@vtt.fi</a>, <a href="mailto:Johannes.Breidenbach@nibio.no">Johannes.Breidenbach@nibio.no</a></p>
High spatiotemporal resolution free surface detection using cost-effective video equipment and computer vision techniques in nearly stationary flow along a transparent wall in the laboratory
<p>The identification of the air-water interface in free surface flows traditionally involves intrusive techniques or costly equipment. Non-intrusive alternatives, such as computer vision, are emerging as highly effective substitutes or supplements for more invasive techniques in laboratory measurements, thanks to their straightforward implementation and cost efficiency. This research specifically delves in the conjunction of various naive techniques, exploring their collective precision in detecting the air-water interface along transparent walls in laboratory. A detection technique based on the double gradient of the image is applied and thoroughly examined. The study progresses through multiple refinement stages, culminating in a method that is both cost effective and easy to implement. This methodology allows for large-scale, high resolution measurements (200 mm × 1800 frames per video at a 0.25 mm, 50 Hz resolution), offering both spatial and temporal measurements by adeptly detecting the free surface along transparent walls.</p>
T1234: A distortion-matched structural scan solution to misregistration of high resolution fMRI data, Part 1
<p>Raw and processed MRI data of the study entiled: T1234-Part 1</p> <p>Authors: Chung (Kenny) Kan1, Rüdiger Stirnberg2, Marcela Montequin1, Omer Faruk Gulban3,4, A Tyler Morgan1, Peter Bandettini1, Laurentius (Renzo) Huber1</p> <ol> <li>NIMH, NIH, Bethesda, United States,</li> <li>German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany,</li> <li>CN, FPN, University of Maastricht, The Netherlands,</li> <li>Brain Innovation, Maastricht, The Netherlands</li> </ol> <p><strong>Purpose</strong>: High-resolution fMRI at 7T is limited by limited registration quality between functional data with structural scans. We aim to provide a fast acquisition method that provides distortion-matched, artifact mitigated structural reference data.</p> <p><strong>Methods</strong>: We developed an efficient sequence approach with adjustable distortions, termed T1234: T1-weighted 2-inversion 3D-EPI with 4 directions for high-resolution fMRI. A forward Bloch model is implemented for T1 quantification and protocol optimization. 20 participants were scanned on 7T with structural and functional protocols to evaluate the utility of T1234.</p> <p><strong>Results</strong>: We find that a fast protocol provides reliable data for whole-brain segmentations in EPI-space in 3:00-3:40 min). It is robust across sessions, participants, and three 7T SIEMENS scanners. T1234 allows layer fMRI signal analysis with higher laminar precision.</p> <p><strong>Conclusion: </strong>This structural mapping approach allows precise registration with fMRI data. T1234 is implemented, validated, and tested to serve users of our sequence (locally and >50 centers worldwide). </p>
Impact of Grid Resolution on Wave-mean Flow Interactions with High Resolution Mars Global Climate Model Simulations
<p>This dataset contains NetCDF files necessary to replicate results from the 2024 paper "<em>Impact of Grid Resolution on Wave-mean Flow Interactions with High Resolution Mars Global Climate Model Simulations</em>"</p> <p>The dataset contains NetCDF files with 1 year of zonally-averaged NASA Ames Mars Global Climate Model (MGCM) fields with 5-sol binning for each of the simulations presented in the paper: </p> <ul> <li>a "low-resolution" simulation with no parameterization for gravity waves</li> <li>a "high-resolution" simulation with no parameterization for gravity waves</li> <li>a "low-resolution" simulation with parameterizations for orographic and non-orographic gravity waves</li> </ul> <p>Also included are:</p> <ul> <li>a file describing the coordinates for the MGCM's vertical grids used in the study </li> <li> atmospheric fields not provided in the other NetCDF files and necessary to replicate figures 3 and supplemental figure FS2 from the paper.</li> <li>a README.txt detailing the content of each file in the dataset</li> </ul>
Dataset for the publication "Identification of plasticity-induced crack closure by using high-resolution digital image correlation"
<p>This repository publishes the data generated in the article "Identification of plasticity-induced crack closure by using high-resolution digital image correlation" (see arxiv preprint <a href="https://arxiv.org/html/2409.02560v1">Plasticity-induced crack closure identification during fatigue crack growth in AA2024-T3 by using high-resolution digital image correlation (arxiv.org)</a>)</p> <p>This repository is structured with the following subfolders:</p> <ul> <li><strong>0_fe_data: </strong>contains the displacement field of the free surface of the 3D finite element model that were used to determine the crack opening curves and, in the following, the crack opening value Kop</li> <li><strong>1_hrdic_data: </strong>contains the high-resolution DIC displacement field data at a crack length of 27.8 mm at different load levels, starting from minimum load 1.5 kN to maximum load 15 kN</li> </ul>
(Magnetic dataset) High-Resolution Magnetic Investigation of a Hydrothermal System in a Volcanic-Evaporitic Environment
<p>This is the ground magnetic dataset collected in hydrothermal vent field sites (called Yellow Lake Fissure and the surrounding area near Dallol Dome) in the Danakil Depression, Ethiopia.</p> <p>The dataset consists of 12 profiles and 2 grided data. and useful geological locations.</p> <p>The dataset is in Excel spreadsheet format and consists of 15 sheets (12 profiles, 2 grid data and other useful points).</p> <p>The format of each profile and grid consists of 8 columns and is formatted as below</p> <p>Latitude(dd°mm.mmmm'), Longitude(ddd°mm.mmmm'), Altitude(meter), Date(yyyy-mm-dd), UTC_time(hhmmss), MagneticField(nT), MagneticAnomaly(nT), Signal_Quality</p> <p> </p>
High-resolution DEMs and ortho images of Langtang village post-2015 Gorkha earthquake in Nepal
<p>Datasets related to the article "Quality Assessment of Multiple UAV-SfM DEMs Derived for Impact Assessment of a Co-seismic Avalanche in the Himalayas." The data were collected around Langtang village, which was destroyed by snow and ice avalanches triggered by the 2015 Gorkha earthquake. The datasets include digital elevation models (DEMs) and orthoimages, gathered using three types of UAVs equipped with different cameras in October 2015.<br><br>Description of files:<br>-a7_DEM_50cm.tif: 0.5 m resolution DEM derived from a quadcopter UAV equipped with a Sony α7R (36.3-megapixel sensor).<br>-a7_ortho_9cm.tif: 0.09 m resolution orthoimage derived from the same data as in a7_DEM_50cm.tif.<br>-ebee_DEM_50cm.tif: 0.5 m resolution DEM derived from a fixed-wing UAV equipped with a Canon IXUS 125HS (16-megapixel sensor).<br>-ebee_ortho_15cm.tif: 0.15 m resolution orthoimage derived from the same data as in ebee_DEM_50cm.tif.<br>-gr_DEM_50cm.tif: 0.5 m resolution DEM derived from a fixed-wing UAV equipped with a Ricoh GR (14.2-megapixel sensor).<br>-gr_ortho_12cm.tif: 0.12 m resolution orthoimage derived from the same data as in gr_DEM_50cm.tif.<br><br></p> <p>Please refer to the related journal article for more details on the datasets.</p> <p>Sunako S, Fujita K, Yamaguchi S, Inoue H, Immerzeel WW, Izumi T and Kayastha RB (2024) Quality Assessment of Multiple UAV-SfM DEMs Derived for Impact Assessment of a Co-Seismic Avalanche in the Himalayas. J. Disaster Res. 19(5), 865–873 (doi:10.20965/jdr.2024.p0865)</p>
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.