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865 results for “beds”
FIGURES 9–17. Specimen LAF 6956A, reproductive anatomy. FIG. 9 in Sporolithon sinusmexicanum sp. nov. (Sporolithales, Rhodophyta): a new rhodolith-forming species from deepwater rhodolith beds in the Gulf of Mexico
FIGURES 9–17. Specimen LAF 6956A, reproductive anatomy. FIG. 9. Dissecting microscope view of tetrasporangial sori (arrows). Scale bar 2 mm. FIGS. 10–11. Magnified views of sori. Scale bars 0.7 mm, 0.8 mm. FIG. 12. Surface view of tetrasporangial sorus undergoing sloughing off. Scale bar 400 μm. FIG. 13. Magnified view of sorus edge showing disintegrating pores (arrows) and rosette cells. Scale bar 110 μm. FIG. 14. Intact tetrasporangial pore (P) and rosette cells (R). Scale bar 24 μm. FIG. 15. Longitudinal section of protuberance showing tetrasporangial compartments at protuberance tip (arrow) and perithallium with no overgrown tetrasporangial compartments. Scale bar 400 μm. FIG. 16. Tetrasporangial compartments (arrows). Scale bar 70 μm. FIG. 17. Tetrasporangial stalk cell (arrow) and paraphyses surrounding tetrasporangial compartments with non-elongated cells at the base of the compartments (circle arrows). Scale bar 28.5 μm.
FIGURE 1 in Sporolithon sinusmexicanum sp. nov. (Sporolithales, Rhodophyta): a new rhodolith-forming species from deepwater rhodolith beds in the Gulf of Mexico
FIGURE 1. Phylogeny based on ML analyses of rbcL sequences. Branch numbers indicate bootstrap values out of 1,000 replicates. Sporolithon sinusmexicanum sp. nov. shown in boldface. Stars indicate species that slough off their tetrasporangial sori after spore release.
Raw data from Fast generation of a metamodel for conduction mode melt pool dimensions in Laser Powder Bed Fusion
<p>This is the raw data repository for the submission of the Manuscript <span>"Fast generation of a metamodel for conduction mode melt pool dimensions in Laser Powder Bed Fusion"</span></p>
Data for "Creep enhancement and sliding in a temperate, hard-bedded alpine glacier"
<p>This folder contains the data and ice flow simulation output used in:</p> <p>Creep enhancement and sliding in a temperate, hard-bedded alpine glacier which is submited to "The Cryosphere".</p> <p>The python script "Generate_dudz_and_ud.py" processes raw tiltometer data to generate .csv files containing deformation velocity and deformation rate time series. The timescale over which the data are averaged is specified by the DX parameter, and the time window of interest can be selected. The script also calculates the average profile as a function of depth.</p> <p>Python scripts to create the manuscript figures are also provided (if Python was used).</p>
FIGURE 2 in A new species of Sinoalidae from the (Hemiptera, Cicadomorpha) topmost Late Jurassic Daohugou Bed
FIGURE 2. Enlargements of Juroala pulchra sp. nov. moistened with 70% ethanol. A, Showing details of head structures, pronotum and mesonotum in ventral view. B, pronotum and mesonotum in dorsal view. C, Antenna. D, Abdomen. Abbreviations: sc, scape; pe, pedicel; fl, flagellum. Scale bars = 1 mm in A, B, D and 500 μm in C.
FIGURE 1 in A new species of Sinoalidae from the (Hemiptera, Cicadomorpha) topmost Late Jurassic Daohugou Bed
FIGURE 1. Holotype of Juroala pulchra sp. nov., from the topmost Daohugou Bed. A, Part, showing general habitus (NIGP171749a). B, Counterpart (NIGP171749b). C, Right tegmen. D, Left tegmen. Scale bars = 2 mm
Wetting-Induced Volumetric Collapse of UO2 Powder Beds and the Consequence on Transient Nuclear Criticality Excursions
<p>Mathematical and computational models are proposed to simulate wetting-induced volumetric collapse of fissile powder beds. Slumping, nuclear thermal hydraulics, radiolytic gas and steam production models are coupled with point neutron kinetics to investigate transient nuclear criticality excursions in two 5-wt% enriched UO<sub>2</sub> fissile powder beds with varying levels of wetting-induced volumetric collapse. The two beds are distinguished by their mean powder particle size of 30 µm and 100 µm. For the UO<sub>2</sub> powder beds modelled, the re-distribution of UO<sub>2</sub> powder and moderator due to slumping introduced a negative reactivity into the system. This increased the amount of time taken for a delayed critical state to be reached once infiltration began, and also reduced the total fission energy generated over the course of the simulated transient. The total fission energy generated ranged from 42 MJ to 48 MJ 100 seconds after the initial nuclear criticality excursion was observed for the 30 µm sized UO<sub>2</sub> powder bed. The fission energy of the larger sized powder bed (100 µm), varied from 42 MJ to 57 MJ. Larger discrepancies between the slumped and un-slumped initial peak power are predicted. Peak powers varied from 29.2 MW to 106 MW for the smaller-sized powder particles, whereas for larger particles, the peak powers varied from 255 MW to 501 MW.</p>
Planning extra ICU beds for pandemics: an experimental study
<p>Dataset of paper "Planning extra ICU beds for pandemics: an experimental study".</p>
Planning extra ICU beds for pandemics: an experimental study
<p>Dataser of paper "Planning extra ICU beds for pandemics: an experimental study".</p>
CoRE-BED datasets
<p>This dataset contains pre-compiled reference sets for use with the CoRE-BED model that note genome-wide status of 19 genomic features (TSS proximity, H3K27ac, H3K27me3, H3K4me1, H3K4me2, H3K4me3, H3K36me3, H3K79me2, H3K9ac, H3K9me3, H4K20me1, ATAC-seq, DNase-seq, CTCF, EP300, H2AFZ, POL2RA, RAD21, and SMC3) across 816 biosamples encompassing 33 major cell and tissue types. Also included are the raw peak calls in UCSC BED format that were used to generate these reference files. </p> <p>Additionally, we include genome-wide sets of functional predictions generated using the CoRE-BED framework across all 816 biosamples, the discrete combinations of 19 genomic features found in each of the major cell and tissue types, and the datasets used to train the CoRE-BED model. Relevant data are made available with both hg19 and hg38 genome build alignments.</p> <p>Please cite:</p> <p>Betti, M.J., Aldrich, M.C., & Gamazon, E.R. (2023). <em>Maximum-entropy integrative epigenomic framework reveals regulatory mechanisms at human disease loci. </em>Preprint.</p> <p>Betti, M.J., Aldrich, M.C., & Gamazon, E.R. (2023). CoRE-BED datasets (Version 2). Zenodo. 10.5281/zenodo.7558115</p>
Dataset: Bed Stability of Step-Pool Channels with Macrorough Sidewalls
<p>The data set includes the cumulative sediment outflow data and the digital elevation model (DEM) data of flume experiments conducted at the Laboratory of Hydraulics, Hydrology, and Glaciology (VAW) at ETH Zurich.</p>
FIGURE 1 in A third species of Plesioblattogryllus Huang et al., 2008 discovered in the Middle- Upper Jurassic Daohugou Beds (Insecta: Plesioblattogryllidae)
FIGURE 1. Plesioblattogryllus aristovi sp. nov., holotype NIGP201823, Photographs. A, General habitus with vertical light. B, General habitus with lateral light. Scale bars = 5 mm (A, B), 2 mm (C, D).
FIGURE 3 in A third species of Plesioblattogryllus Huang et al., 2008 discovered in the Middle- Upper Jurassic Daohugou Beds (Insecta: Plesioblattogryllidae)
FIGURE 3. Plesioblattogryllus magnificus Huang, Nel & Petrulevičius, 2007, holotype NIGP 133701, Photographs. A, General habitus. B, Forewing apex; C, Median region of forewing showing the overlapping of the veins ScP, R, and M. Scale bars = 10 mm (A), 5 mm (B, C).
Dopamine in the Dorsal Bed Nucleus of Stria Terminalis signals Pavlovian sign-tracking and reward violations
<p>Raw data associated with Gyawali et al., 2022</p>
Dataset of the Austrian test bed until 2050
<p>This repository includes the data of the results presented in the paper "Designing a model for the cost-optimal decommissioning and refurbishment investment decision for gas networks: application on a real test bed in Austria until 2050". </p> <p>Further information can be found in the <a href="https://github.com/sebastianzwickl/GND_Mod">GitHub</a> repository of the work.</p> <p> </p>
DATASET - Automated grain sizing from UAV imagery of a gravel-bed river: benchmarking of three object-based methods and analysis of particle-size clustering
<p>Dataset used to compute the grain size distributions from in-field line sampling and digitally on orthoimages with automated methodologies and by manual labelling. It also contains the data used to produce spatial statistics.</p>
IC-BASAROTs: New Practice Method for More Accurate Bed-side Assessment of Individual Energy Expenditure
ClinicalTrials.gov study NCT02682537. IPD Sharing: YES. Countries: 1. Publications: 16.
Er,Cr:YSGG Laser For Recipient Bed Bio-modification And Connective Tissue Harvesting in Treatment of Gingival Recession
ClinicalTrials.gov study NCT03200392. IPD Sharing: NO. Countries: 1. Publications: 1.
The Effect of Foot Massage and Bed Bath on Individuals With Cancer
ClinicalTrials.gov study NCT06373614. IPD Sharing: NO. Countries: 1. Publications: 5.
Bed Rest, Alternate Daily Fasting and Incretin Effect
ClinicalTrials.gov study NCT02134860. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.