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9,882 results for “Scale”
Experimental characterization of a single-shot spectrometer for high-flux, GeV-scale gamma-ray beams -- associated data
<p>Supplementary experimental data for the results presented in the paper "Experimental characterization of a single-shot spectrometer for high-flux, GeV-scale gamma-ray beams", collected, processed and analysed by the research group within the School of Mathematics and Physics at Queen's University Belfast.</p> <p>Article located at DOI: 10.1103/PhysRevResearch.00.003000</p> <p>Electron and positron data over 8 nominal shots are provided as:</p> <ul> <li>background corrected spatial lineouts (in mm)</li> <li>derived energy spectra (in GeV)</li> </ul> <p>Also included are binned energy spectra for electrons and positrons, as well as the deconvolved photon spectra.</p> <p>Data is presented in the format of compressed Python numpy (.npz) files.</p>
Verifying Performance Guidelines for MPI Collectives at Scale - PMBS@SC23 Artifact
<p>ARTIFACT DESCRIPTION/ARTIFACT EVALUATION</p> <p> </p>
Do Agile Scaling Approaches Make A Difference? An Empirical Comparison of Team Effectiveness Across Popular Scaling Approaches
<p>This bundle contains supplementary materials for an upcoming academic publication <em>Do Agile Scaling Approaches Make A Difference? An Empirical Comparison of Team Effectiveness Across Popular Scaling Approaches?</em>, by Christiaan Verwijs and Daniel Russo. Included in the bundle are the dataset and SPSS syntaxes. This replication package is made available by C. Verwijs under a "Creative Commons Attribution Non-Commercial Share-Alike 4.0 International"-license (CC-BY-NC-SA 4.0).</p> <p><strong>About the dataset</strong></p> <p>The dataset (SPSS) contains anonymized response data from 15,078 team members aggregated into 4,013 Agile teams that participated from <a href="https://scrumteamsurvey.org">scrumteamsurvey.org</a>. Stakeholder evaluations of 1,841 stakeholders were also collected for 529 of those teams. Data was gathered between September 2021, and September 2023. We cleaned the individual response data from careless responses and removed all data that could potentially identify teams, individuals, or their parent organizations. Because we wanted to analyze our measures at the team level, we calculated a team-level mean for each item in the survey. Such aggregation is only justified when at least 10% of the variance exists at the team level (Hair, 2019), which was the case (ICC = 35-50%). No data was missing at the team level.</p> <p>Question labels and option labels are provided separately in Questions.csv. To conform to the privacy statement of <a href="https://scrumteamsurvey.org">scrumteamsurvey.org</a>, the bundle does not include response data from before the team-level aggregation.</p> <p><strong>About the SPSS syntaxes</strong></p> <p>The bundle includes the syntaxes we used to prepare the dataset from the raw import, as well as the syntax we used to generate descriptives. This is mostly there for other researchers to verify our procedure.</p>
Simulation data for "Impact of Dynamic Phytoplankton Stoichiometry on Global Scale Patterns of Nutrient Limitation, Nitrogen Fixation, and Carbon Export"
<p>Simulation data for our submission to GBC. Some of the files are compressed in order to minimize the size of the archive. Data files are stored as pickled python variables. The code for analysis of this data is in the github repository: https://github.com/georgehagstrom/BGCPaperFigureCode .</p>
Data for: Consistently heterogeneous structures observed at multiple spatial scales across fire-intact reference sites
<p>Geospatial polygons representing fire-suppressed control sites against which fire-intact reference sites were compared in Chamberlain et al. (2023). Control sites represent areas with 1) no record of fire history, 2) no record of late 20th century or early 21st century timber management, and 3) no "Fast Change" detected by the Landscape Change Monitoring System dataset. All sites are predominantly within the yellow pine and mixed-conifer zone of California's Sierra Nevada, USA. Polygon boundaries were defined using the NHDPlusV2 catchments, and were manually reshaped using aerial imagery to ensure that polygons were > 100 ha, represented primarily forested areas, and excluded major roads, infrastructure, and major rock outcrops.</p> <p>Detailed description of the methods used to produce this dataset provided in:<br> Chamberlain, C.P., Cova, G.R., Cansler, C.A., North, M.P., Meyer, M.D., Jeronimo, S.M.A., Kane, V.R., 2023. Consistently heterogeneous structures observed at multiple spatial scales across fire-intact reference sites. Forest Ecology and Management.</p>
Small scale spatial variability in diffusive erosion and deposition simulation data
<p>Small scale spatial variability in diffusive erosion and deposition simulation data</p>
FIGURE 4. Polystichum lionelii. A. Rhizome scale. B. Petiole scale with denticulate margins. C in Polystichum lionelii (Dryopteridaceae), a new Andean species from northwestern Argentina
FIGURE 4. Polystichum lionelii. A. Rhizome scale. B. Petiole scale with denticulate margins. C. Linear-lanceolate scale of raquis with glandular-cell at the apex (detail). D. Filiform scales, twisted. E. Scale margin with 1–2-cellular glandular (arrowhead) and pluricellular hair. F. Detail of glandular hair on scale margin. G. Detail of surface scale with glandular hairs (arrowhead). H. Laminar tissue with filiform scales. I. Filiform scales. J. Spores. Polystichum pycnolepis. K. Laminar tissue with glandular hairs (adaxial side). L. laminar tissue with glandular hairs (abaxial side). A–J: Serapio 120 (holotype MCNS), K-L: Castillón 1496 (LIL 41248)
Physicochemical habitat data and multi-scale occupancy data for spring-associated fishes in Oklahoma streams
<p class="vC7TJ allowTextSelection">Spring-associated fishes occupy thermally unique habitats in groundwater-dominated streams that are often of high quality. However, outside of water temperature, little else is known about the physicochemical habitat requirements for many of these species. With human effects on streams increasing, it is important to conservation and management to characterize spring habitats and the species that occupy them. Our study objective was to determine the physicochemical factors related to occupancy of four spring-associated species in the Arbuckle Uplift and Ozark Highlands ecoregions, Oklahoma USA. We used a hierarchal approach to identify habitat relationships at multiple spatial scales. We collected detection and non-detection data using both snorkeling and seining methods. We examined the physicochemical relationships related to detection and occupancy for four spring-associated fishes. Data were analyzed using occupancy modeling in a Bayesian framework. Our results indicated water depth and water clarity were important factors affecting detection of spring-associated fishes. Occupancy of our target species differed by ecoregion, with least darter being less common in the Ozark Highlands ecoregion and subadult smallmouth bass being more common in the Ozark Highlands. Interestingly, we found water temperature occupancy relationship for only least darter and southern redbelly dace, whereas redspot chub and smallmouth bass were more likely to occur at sites with deeper pool habitats of larger streams. We documented both spatial and temporal differences in occurrence probabilities at ecoregion, reach, and riffle-run-pool complex scale. Furthermore, our results indicate snorkeling was a superior sampling method compared to seining for detecting most fishes in clear warmwater streams even at relatively low visibilities. Lastly, we demonstrate the importance of using multi-scale studies when developing conservation plans for warmwater fishes.</p>
Dataset for large-scale experiment of block-grain phase transition
<p>Dataset related to the manuscript “Block-grain phase transition in rock avalanches: insights from large-scale experiments”, submitted to the Journal of Geophysical Research: Solid Earth.</p> <p>The dataset provides the raw and processed data for the large-scale experiments of block-grain phase transition due to fragmentation, including parameters reflecting the dynamics, fragmentation, deposit.</p> <p><strong>S1_data_velocity</strong> provides the average velocity at the front, middle and tail of the moving mass determined by the laser ranging sensors under different experimental configurations.</p> <p><strong>S2_data_fragmentation</strong> provides the fragment size distribution and relative breakage ratio.</p> <p><strong>S3_data_deposit </strong>provides the parameters of deposit, including the runout distances, friction coefficients.</p> <p><strong>S4_data_seismic </strong>provides the parameters used to characterize the seismic signal excited by the moving mass, including the envelope curve, marginal spectrum and seismic energy.</p>
FIGURES 2–4 in Two new species of silica-scaled chrysophytes (Chrysophyceae, Synurales) Mallomonas kicherica and M. sibirica water bodies of Eastern Siberia, Russia
FIGURES 2–4. Mallomonas kicherica sp. nov. Figure 2. Tips of bristles with teeth and bristle's foot. Figures 3–4, scales with labyrinthlike reticulation on the dome and transverse ribs, except for the area between the first and second, are connected in random order by short ribs-jumpers. SEM Scale bars: 2 μm.
FIGURES 5–11 in Two new species of silica-scaled chrysophytes (Chrysophyceae, Synurales) Mallomonas kicherica and M. sibirica water bodies of Eastern Siberia, Russia
FIGURES 5–11. Scales of Mallomonas sibirica sp. nov. from different types of habitats. Figure 5. Body scales with subcircular and smooth dome, evenly spaced transverse ribs and rounded depressions between them. The posterior rim, wide and smooth, bears numerous internal struts. The posterior flange has struts and scattered rounded depressions in the base plate that are not evenly spaced, from Lake Baikal, TEM. Figure 6. Body scale from the type habitat, Lake Ulu, SEM. Figures 7. Body scale, the dome is subcircular, ornamented with struts, undersurface view of the scales, from Lake Labynkyr, SEM. Figures 8. Body scale, the dome is subcircular patterned with rounded depressions, from Lake Labynkyr, SEM. Figure 9. Body scale, from a mixing zone of the Yenisei River and the Kara Sea waters, SEM. Figures 10–11. Body scale, undersurface view of the scales, from Lake Labynkyr, SEM. Scale bars: 2 μm.
Large-scale attributed hypergraph datasets: Amazon & MAG-PM
<p>Amazon and MAG-PM are two large-scale datasets of real-world attributed hypergraphs. The ScaNN indices for fast K-nearest neighbor searching are also included.</p><p>For further details, please refer to our publication "Efficient and Effective Attributed Hypergraph Clustering via K-Nearest Neighbor Augmentation" on SIGMOD 2023, and the <a href="https://github.com/CyanideCentral/AHCKA">GitHub repository</a>.</p>
MR-Eye atlas: a large-scale atlas of the eye based on T1-weighted MR imaging
<p>MR-Eye atlas is a novel digital atlas contructed from MR images (T1-weighted MRI acquired at 1.5T ) of large-scale population of healthy volonteers. It gathers a male and female structural atlas constructed from 594 males and 616 females, with their corresponding probability maps of the different labels projected onto the average respective male and female templates. The atlases include 9 regions of interest lens, globe, optic nerve, intraconal and extraconal fat, and four rectus muscles (lateral, medial, inferior and superior).</p> <p>The original dataset includes:</p> <ul> <li>sub_metadata.csv: dataset summary table</li> <li>template.nii.gz: atlas of the eye images (per sex)</li> <li>max_prob_map.npy and max_prob_map.nii.gz: maximum probability maps (per sex)</li> <li>prob_map.npy and prob_map.nii.gz: probability maps (per sex)</li> </ul> <p>The new version adds:</p> <ul> <li>a combined eye atlas (image + labels)</li> <li>labels projected onto Colin27 and MNI152 T1w spaces (along with the images and their cropped versions)</li> <li>2 more preview figures (labels onto the Colin27 and MNI152, and the scheme of the process)</li> <li>updates on release_notes.md and release_notes.txt (to track changes)</li> <li>modified readme.md and readme.txt</li> </ul> <p>Detailed information on the original large-scale cohort, automated segmentation method and unbiased atlas construction is detailed in the README file.</p> <p>MR-Eye atlas is presented and described in the following article: </p> <p><strong>"Eye-Opening Advances: Automated 3D Segmentation, Key Biomarkers Extraction, and the First Large-Scale MRI Eye Atlas"</strong>, J. Barranco, A. Luyken, H. Kebiri, P. Stachs, P. M. Gordaliza, O. Esteban, Y. Aleman, R. Sznitman, O. Stachs, S. Langner, B. Franceschiello<em>, </em>M. Bach Cuadra, https://doi.org/10.1101/2024.08.15.608051</p> <p><strong>Works using any of the provided ressources should cite the above-referred article.</strong></p> <p>Copyright (c) - All rights reserved. Medical Image Analysis Laboratory - Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne,Switzerland & CIBM Center for Biomedical Imaging. 2024.</p>
A Large-Scale In-the-wild Dataset for Plant Disease Segmentation
Open the record for dataset details and reuse information.
Development and Validation of the Saint Paul's Endoscopy Comfort Scale (SPECS) for Colonoscopy and Upper Endoscopy
ClinicalTrials.gov study NCT02443480. IPD Sharing: Not stated. Countries: 1. Publications: 11.
Online Emotional Response to Completing a Childhood Maltreatment Self-report Scale
ClinicalTrials.gov study NCT06152549. IPD Sharing: Not stated. Countries: 1. Publications: 21.
Pain Protocol: Nociception Coma Scale-Revised With Personalized Stimulus
ClinicalTrials.gov study NCT06012357. IPD Sharing: YES. Countries: 1. Publications: 1.
Validation of the French Translation of the Scale HSCL25 in the Diagnosis of Depression in Primary Care
ClinicalTrials.gov study NCT02414711. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Pain Comparison Whit Visual Analog Scale (EVA) Between Four Analgesic Methods During Trans Rectal Prostatic Biopsy
ClinicalTrials.gov study NCT03442075. IPD Sharing: NO. Countries: 1. Publications: 6.
Validation of Faces Thermometer Scale (FTS)
ClinicalTrials.gov study NCT05322018. IPD Sharing: NO. Countries: 1. Publications: 11.
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.