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9,882 results for “Scale”
FIGURE 9 in Reassessment of the phylogenetic position of the spiny-scale pricklefish Hispidoberyx ambagiosus (Teleostei: Hispidoberycidae) based on comparative morphology
FIGURE 9. Lateral aspects of upper jaw and anterior part of suspensorium in Rondeletia loricata, HUMZ 130180, 76.8 mm. LPR, ligamentum primordium; M, maxilla; MPL, median palato-maxillary ligament; PAL, palatine. Scale indicates 5 mm.
FIGURE 16 in Reassessment of the phylogenetic position of the spiny-scale pricklefish Hispidoberyx ambagiosus (Teleostei: Hispidoberycidae) based on comparative morphology
FIGURE 16. Lateral aspect of urohyal in (A) Hispidoberyx ambagiosus, HUMZ 194634, 180.7 mm SL, (B) Stephanoberyx monae, HUMZ 230037, 88.8 mm SL, (C) Melamphaes typhlops, USNM 248477, 70.8 mm SL, (D) Neoniphon sammara, HUMZ 40434, 151.8 mm SL, (E) Beryx decadactylus, HUMZ 47735, 219.6 mm SL, and (F) Hoplostethus mediterraneus, NSMT-P 43389, 140.7 mm SL. C shown as mirror image. Scales indicate 5 mm.
Temporal Focus Scale
<p><span><span> </span><span>The dataset includes responses from 200 retirees in Chelyabinsk, Russia, assessed using the Temporal Focus Scale (Shipp et al., 2009) and the “Age-of–Me” technique (Barak, 2009). Data can be accessed through the journal's database, and all data have been anonymized to protect participant privacy</span></span></p>
zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation
<p>Data and code used to generate the analyses and figures in paper "zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation" are provided here.</p>
Data and code for figures of "Scale-tailored localization and its observation in non-Hermitian electrical circuits"
<p>The main data and code for figures of "Scale-tailored localization and its observation in non-Hermitian electrical circuits" are provided here.</p>
Example dataset and expected outcomes of Spatially resolved in situ profiling of mRNA life cycle at transcriptome scale in intact cells and tissues
<p>Here are the example datasets and expected outcomes included in "<strong>Spatially resolved in situ profiling of mRNA life cycle at transcriptome scale in intact cells and tissues</strong>" from Ren et al. Please refer to the README.txt file for more detailed information. Corresponding computational tools are available at <a href="https://github.com/wanglab-broad/starfinder">https://github.com/wanglab-broad/starfinder.</a></p>
Feldman et al. 2024 "Large global scale vegetation sensitivity to daily rainfall variability"
<p>These data and scripts are a part of the Feldman et al. manuscript accepted in principle titled "Large global scale vegetation sensitivity to daily rainfall variability".</p> <p>The data and scripts here can be used to generate all steps of the analysis. It includes:</p> <p>(1) The final generated outputs of the analysis and the python script to generate the figures in the main text, extended data, and supplemental information. This figure generation script is: "MainScript_GenerateFigures_V4.py"</p> <p>(2) The python script to conduct the main analysis in an example region in Africa, which is named: "MainScript_SatelliteVegetationProcessing_Example.py". </p> <p>(3) The python script to conduct the main analysis across the globe (to generate figure 1), which is named: "MainScript_SatelliteVegetationProcessing_V2.py". Input data for this script are available at a separate Zenodo account here: https://zenodo.org/records/10947071.</p> <p>(4) Scripts and input data to conduct rainfall trend analyses and mechanism analyses.</p> <p>(5) Scripts to show how the gridded datasets were processed into their one degree gridding to be input into other components of the analysis.</p> <p>Due to their size, the full global datasets to conduct the global analysis are available on a separate Zenodo account here: https://zenodo.org/records/10947071.</p> <p>Please consult the README.txt file for more information about python and names of files and scripts being used. </p> <p>For any use of the datasets and scripts, please cite (1) the Feldman et al "Large global scale vegetation sensitivity to daily rainfall variability" publication. Additionally, (2) please acknowledge the use of the scripts and/or datasets in the acknowledgements section of your publication. The use of any scripts or data are not allowed unless the paper is in print. For questions, please contact Andrew Feldman at andrew.feldman@nasa.gov. </p>
Amateur Radio Spot Data for "First Observations Linking Large-Scale Traveling Ionospheric Disturbances to Polar Vortex Strength"
<p>This repository contains the raw data amateur radio data used to compute the Large Scale Traveling Ionosphic Disturbance activity presented the<br>Geophysical Research Letters manuscript<br>"First Observations Linking Large-Scale Traveling Ionospheric Disturbances to Polar Vortex Strength".</p> <p>This dataset has monthy *.tar files containing daily bzip2 Comma Separated Value (CSV) files of data from the following amateur radio spotting networks for the time period November 2018 - May 2019:</p> <ol> <li><a href="https://pskreporter.info/" target="_blank" rel="noopener">PSKReporter (https://pskreporter.info/)</a></li> <li><a href="https://www.wsprnet.org/" target="_blank" rel="noopener">Weak Signal Propagation Reporter Network (WSPRNet, https://www.wsprnet.org/)</a></li> <li><a href="https://reversebeacon.net/" target="_blank" rel="noopener">Reverse Beacon Network (https://reversebeacon.net/)</a></li> </ol> <p>Where necessary, spots have been geolocated using latitudes and longitudes from <a href="https://www.qrz.com/">https://www.qrz.com/</a>.</p> <p>We are grateful to the operators of PSKReporter, WSPRNet, and the Reverse Beacon Network for the use of their data.</p> <p>The columns of each CSV file correspond to the following values:</p> <p># [0] UTC Datetime <br># [1] Transmitter Call Sign<br># [2] Transmitter Maidenhead Grid Square<br># [3] Transmitter Geographic Latitude<br># [4] Transmitter Geographic Longitude<br># [5] Source of Transmitter Gride Information<br>#<br># [6] Receiver Maidenhead Grid Square<br># [7] Receiver Geographic Latitude<br># [8] Receiver Geographic Longitude<br># [9] Source of Receiver Gride Information<br>#<br># [11] Frequency (Hz)<br># [12] Signal to Noise Ration (SNR) [dB]<br># [13] Mode<br>#<br># [14] Source<br># [15] Sender Status<br># [16] Inter-Modulation Distortion (IMD)<br># [17] ipOriginID<br># [18] sendeMobileLocator<br># [19] c1<br># [10] c2<br># [21] mode2</p> <p># Computed Fields<br># [22] Great Circle Short Path [km]<br># [23] Great Circle Short Path Midpoint Geographic Latitude<br># [24] Great Circle Short Path Midpoint Geographic Longitude</p> <p>This dataset is designed to be used with the LSTID autodetection software available at <a href="https://doi.org/10.5281/zenodo.13630867" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13630867</a>.</p>
FIGURE 4. A–C. Blechnum laevigatum. A. Habit. B. Lamina apex showing indument. C. Rhizome scale. D–F in The Blechnum occidentale (Blechnaceae, Polypodiopsida) species group in southern and southeastern Brazil
FIGURE 4. A–C. Blechnum laevigatum. A. Habit. B. Lamina apex showing indument. C. Rhizome scale. D–F. Blechnum lanceola: D. Habit. E. Part of a pinna showing venation and sori. F. Rhizome scale. (A–C from L. Krieger s.n., CES 11193; D–F from A.C. Brade 3365 (CESJ).
FIGURE 1. A–C. Blechnum asplenioides. A. Habit. B. Basal pinnae. C. Rhizome scale. D–F. Blechnum auriculatum. D. Habit. E in The Blechnum occidentale (Blechnaceae, Polypodiopsida) species group in southern and southeastern Brazil
FIGURE 1. A–C. Blechnum asplenioides. A. Habit. B. Basal pinnae. C. Rhizome scale. D–F. Blechnum auriculatum. D. Habit. E. Part of a pinna showing venation. F. Rhizome scale. (A–C from A.C. Brade s.n., CESJ3366; D–F from A. Salino et al. 14733, CESJ).
Improved cross-scale snow cover simulations by developing a scale-aware parameterization in the Noah-MP land surface model
<p>Noah-MP data used to support the analyses conducted by Abolafia-Rosenzweig et al.: <strong>Improved </strong><strong>cross-scale </strong><strong>snow cover simulations by developing a scale-aware parameterization in the Noah-MP land surface model</strong></p>
FIGURE 1. Serpocaulon tayronae. A. Habit. B. Rhizome scale. C in Serpocaulon tayronae (Polypodiaceae), a new species from the Sierra Nevada de Santa Marta, Colombia
FIGURE 1. Serpocaulon tayronae. A. Habit. B. Rhizome scale. C. Basiscopic sterile part of the segment. D. Acroscopic fertile part of the segment. E. Lamina trichome. All from Smith 1025 (BR).
FIGURE 1. Carex concava, A. Inflorescence. B. Habit. C. Lateral pistillate spike. D. Terminal staminate spike. E. Perigynium with stigmas. F. Pistillate glume. G. Staminate glume. Scale A, B, D in Carex concava (Carex sect. Rhomboidales, Cyperaceae), a new species from Hainan, China
FIGURE 1. Carex concava, A. Inflorescence. B. Habit. C. Lateral pistillate spike. D. Terminal staminate spike. E. Perigynium with stigmas. F. Pistillate glume. G. Staminate glume. Scale A, B, D bars=1 cm; E, F, G bars=1 mm. Photographs by Hu-Biao YANG (Apr. 15th, 2014).
Retires, Russia, Temporal Focus Scale
<p>The dataset includes responses from 200 retirees in Chelyabinsk, Russia, assessed using the Temporal Focus Scale (Shipp et al., 2009) and the “Age-of–Me” technique (Barak, 2009). all data have been anonymized to protect participant privacy</p>
A multi-species benchmark for training and validating large scale mass spectrometry proteomics machine learning models
<p>This is a de novo sequencing benchmark dataset derived from nine<br>publicly available mass spectrometry datasets. There are two versions<br>of the benchmark: main and balanced. The balanced version randomly<br>eliminates some spectra associated with some species in order to<br>create a smaller, more evenly balanced dataset. Also provided are two<br>zip files containing the raw data as well as intermediate results.<br>Details about how the benchmark was created are provided in an<br><a href="../records/13653420">associated zenodo release</a>, which contains the source code as well as a<br>manuscript describing the benchmark.</p> <p>This release fixes a bug that incorrectly detected shared peptides <br>between different species. It also includes the annotated spectra in <br>mzSpecLib format.</p> <p> </p>
FIGURE 2. A–C. Austroblechnum lehmannii. A. Habit. B. Pinna and venation pattern. C. Rhizome scale. D–F. Austroblechnum organense. D. Habit. E. Pinna pair showing venation. F in The family Blechnaceae (Polypodiopsida) in Brazil: key to the genera and taxonomic treatment of Austroblechnum, Cranfillia, Lomaridium, Neoblechnum and Telmatoblechnum for southern and southeastern Brazil
FIGURE 2. A–C. Austroblechnum lehmannii. A. Habit. B. Pinna and venation pattern. C. Rhizome scale. D–F. Austroblechnum organense. D. Habit. E. Pinna pair showing venation. F. Rhizome scale. (A–C from A. Salino et al. 14054, BHCB; D–F from A.L. Gasper et al. 2658, BHCB).
FIGURE 1. A–C. Austroblechnum andinum. A. Habit. B. Pinna pair showing venation. C. Rhizome scale. D–G. Austroblechnum divergens. D. Habit. E in The family Blechnaceae (Polypodiopsida) in Brazil: key to the genera and taxonomic treatment of Austroblechnum, Cranfillia, Lomaridium, Neoblechnum and Telmatoblechnum for southern and southeastern Brazil
FIGURE 1. A–C. Austroblechnum andinum. A. Habit. B. Pinna pair showing venation. C. Rhizome scale. D–G. Austroblechnum divergens. D. Habit. E. Base of sterile blade showing vestigial pinnae. F. Pinna pair showing venation. G. Rhizome scale. (A–C from A.C. Brade s.n., CESJ0003368; D–G from V.A.O. Dittrich et al. 1807, CESJ).
FIGURE 5. A–C. Lomaridium plumieri. A. Habit. B. Basal pinnae showing venation pattern. C. Rhizome scale. D–F. Neoblechnum brasiliense. D. Habit. E in The family Blechnaceae (Polypodiopsida) in Brazil: key to the genera and taxonomic treatment of Austroblechnum, Cranfillia, Lomaridium, Neoblechnum and Telmatoblechnum for southern and southeastern Brazil
FIGURE 5. A–C. Lomaridium plumieri. A. Habit. B. Basal pinnae showing venation pattern. C. Rhizome scale. D–F. Neoblechnum brasiliense. D. Habit. E. Pair of basal pinnae showing venation. F. Rhizome scale. (A–C from F.S. Souza et al. 613, CESJ0052285; D–F from C. Kozera 3992, CESJ0062336, CESJ0062336_01).
FIGURE 4. A–C. Cranfillia mucronata. A. Habit. B. Pinna and venation pattern. C. Rhizome scale. D–F. Cranfillia caudata. D. Habit. E in The family Blechnaceae (Polypodiopsida) in Brazil: key to the genera and taxonomic treatment of Austroblechnum, Cranfillia, Lomaridium, Neoblechnum and Telmatoblechnum for southern and southeastern Brazil
FIGURE 4. A–C. Cranfillia mucronata. A. Habit. B. Pinna and venation pattern. C. Rhizome scale. D–F. Cranfillia caudata. D. Habit. E. Pair of basal pinnae showing venation. F. Rhizome scale. (A–C from F.S. Souza et al. 1482, BHCB; D–F from L.L. Giacomin et al. 1350, CESJ).
FIGURE 3. A–C. Austroblechnum penna-marina. A. Habit. B. Pinnae and venation pattern. C. Rhizome scale. D–F. Austroblechnum squamipes. D. Habit. E in The family Blechnaceae (Polypodiopsida) in Brazil: key to the genera and taxonomic treatment of Austroblechnum, Cranfillia, Lomaridium, Neoblechnum and Telmatoblechnum for southern and southeastern Brazil
FIGURE 3. A–C. Austroblechnum penna-marina. A. Habit. B. Pinnae and venation pattern. C. Rhizome scale. D–F. Austroblechnum squamipes. D. Habit. E. Base of blade showing pinnae and venation. F. Rhizome scale. (A–C from A. Salino et al. 14745, BHCB; D–F from A. Salino et al. 12036, CESJ).
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.