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Рис. 2. Варианты преΑсказанной Αоменной структуры патогенраспознающих моΛекуΛ гемоцитов моΛΛюсков Planorbarius corneus. a — фибриногенпоΑобные беΛки, b — гаΛектины, c — F-Λектины. УсΛовные обозначения и сокращения, зΑесь и ΑаΛее: горизонтаΛьные красные поΛоски — сигнаΛьный пептиΑ, горизонтаΛьные розовые — обΛасть низкой сΛожности, вертикаΛьные синие поΛоски — трансмембранная обΛасть, FBG — фибриногеновый Αомен, FTP — Αомен фукоΛектина, EGF — Αомен эпиΑермаΛьного фактора роста, EGF_CA — каΛьцийсвязывающий EGF-поΑобный Αомен, PAN_AP — APPLE-поΑобный Αомен, SCAN — обΛасть, богатая Λейцином, GLECT — гаΛактозосвязывающий Λектин, CLECT — Λектин C-типа, Gal-bind — гаΛактозиΑ–связывающий Λектин, ML — MD-2- поΑробный Αомен распознавания ΛипиΑов Fig. 2. Variants of the predicted domain structure of pattern recognition molecules from hemocytes of Planorbarius corneus molluscs. a — fibrinogen-related proteins, b — galectins, c — F-lectins. Symbols and abbreviations (here and further): horizontal red stripes — signal peptide, horizontal pink stripes — a low complexity region, vertical blue stripes — transmembrane region, FBG — fibrinogen-related domain, FTP — fucolectin domain, EGF — epidermal growth factor-like domain, EGF_CA — calcium-binding EGF-like domain, PAN_AP — APPLE-like domain, SCAN — leucine rich region, Apple — APPLE domain, GLECT — galactose-binding lectin, CLECT — C-type lectin, Gal-bind — galactoside-binding lectin, ML — MD-2-related lipid-recognition domain in Pathogen recognition molecules from hemocytes of Planorbarius corneus molluscs (Planorbidae, Pulmonata)
Рис. 2. Варианты преΑсказанной Αоменной структуры патогенраспознающих моΛекуΛ гемоцитов моΛΛюсков Planorbarius corneus. a — фибриногенпоΑобные беΛки, b — гаΛектины, c — F-Λектины. УсΛовные обозначения и сокращения, зΑесь и ΑаΛее: горизонтаΛьные красные поΛоски — сигнаΛьный пептиΑ, горизонтаΛьные розовые — обΛасть низкой сΛожности, вертикаΛьные синие поΛоски — трансмембранная обΛасть, FBG — фибриногеновый Αомен, FTP — Αомен фукоΛектина, EGF — Αомен эпиΑермаΛьного фактора роста, EGF_CA — каΛьцийсвязывающий EGF-поΑобный Αомен, PAN_AP — APPLE-поΑобный Αомен, SCAN — обΛасть, богатая Λейцином, GLECT — гаΛактозосвязывающий Λектин, CLECT — Λектин C-типа, Gal-bind — гаΛактозиΑ–связывающий Λектин, ML — MD-2- поΑробный Αомен распознавания ΛипиΑов Fig. 2. Variants of the predicted domain structure of pattern recognition molecules from hemocytes of Planorbarius corneus molluscs. a — fibrinogen-related proteins, b — galectins, c — F-lectins. Symbols and abbreviations (here and further): horizontal red stripes — signal peptide, horizontal pink stripes — a low complexity region, vertical blue stripes — transmembrane region, FBG — fibrinogen-related domain, FTP — fucolectin domain, EGF — epidermal growth factor-like domain, EGF_CA — calcium-binding EGF-like domain, PAN_AP — APPLE-like domain, SCAN — leucine rich region, Apple — APPLE domain, GLECT — galactose-binding lectin, CLECT — C-type lectin, Gal-bind — galactoside-binding lectin, ML — MD-2-related lipid-recognition domain
Fig. 8. Scanning micrographs about Camisiidae from Korea. a in Contribution to the mite (Acari) fauna of the Korean Peninsula
Fig. 8. Scanning micrographs about Camisiidae from Korea. a. Camisia biurus (C.L. Koch, 1839). b. Camisia biverrucata (C.L. Koch, 1839).
Fig. 9. Scanning micrographs about Camisiidae and Nothriidae from Korea. a in Contribution to the mite (Acari) fauna of the Korean Peninsula
Fig. 9. Scanning micrographs about Camisiidae and Nothriidae from Korea. a. Heminothtus peltifer (C.L. Koch, 1839). b. Nothrus palustris C.L. Koch, 1839. c. Camisia spinifer (C.L. Koch, 1836).
Ultrasound scans of wind turbine bearings with white etching crack damage
<p>A set of ultrasound images of wind turbine bearings with white etching crack subsurface damage. Attenuation levels above -10 dB indicate subsurface damage. Five tests were run under constant loading in a laboratory test rig, with two bearings in parallel. Tests were stopped at the indicated times (in hours) when vibration levels went above a certain threshold. This typically means that one of the two bearings has failed, although this is somewhat inconclusive for the fifth test where both bearings seem to be close to failure. For each bearing two sides were scanned (indicated by A and H).</p> <p>The experiment was performed in summer-autumn 2017 by DTU Wind Energy, as part of the FP7 Integrated Research Programme in the field of Wind Energy (IRPWIND), 2nd Round of Joint Experiments.</p> <p>For more information about this dataset please contact Dr Hilmar Danielsen at DTU Wind Energy.<br> </p> <p> </p>
A cone beam scan of a rat skull
<p>This upload contains a circular cone beam dataset of a rat skull with teeth still attached. This dataset is suitable for testing reconstruction and image segmentation algorithms. Additional renderings of the reconstructions are included in this submission as well as the projections at angles 0 and 90. </p> <p> </p> <p>The dataset is acquired using the custom built and highly flexible CT scanner, FlexRay Lab, developed by XRE NV and located at CWI. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1943-by-1535 pixels, 14-bit, flat detector panel. </p> <p> </p> <p>The dataset was collected over a 360 degrees in circular and continuous motion with 1200 projections distributed evenly over the full circle. The uploaded dataset is not normalized; a single dark and two (pre- and post-) flat fields are included for the scan. The dataset is binned by 2, meaning the size of each projection is 972-by-768 pixels. The dataset is packaged with the full list of data and scan settings files (in .txt format). These files contain the tube settings, scan geometry and full list of motor positions at the start of the scan.</p> <p> </p> <p>Sample is of a rat skull used for various scientific experiments. The sample was mounted in a sponge to allow mounting vertically, and to dampen any vibrations from rotation. The sample was provided by Udo van Hes from Technology Centre, University of Amsterdam. The teeth of the rat are still attached to the skull and can be segmented out. We include the projections at angles 0 and 90 for viewing purposes. </p> <p> </p> <p>These dataset are produced by the Computational Imaging members at Centrum Wiskunde & Informatica (CI-CWI). For any useful Python/MATLAB scripts for FlexRay dataset, we refer the reader to our group's <a href="http://github.com/cicwi">GitHub page</a>.</p> <ul> </ul> <p> </p> <p>For more information or guidance in using these dataset, please get in touch with </p> <ul> <li>s.b.coban [at] cwi.nl</li> </ul>
Underwater hyperspectral scan from India, scene 29
<p>Underwater hyperspectral scan from India, scene 29</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 24
<p>Underwater hyperspectral scan from India, scene 24</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 28
<p>Underwater hyperspectral scan from India, scene 28</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 17
<p>Underwater hyperspectral scan from India, scene 17</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 21
<p>Underwater hyperspectral scan from India, scene 21</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 20
<p>Underwater hyperspectral scan from India, scene 20</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 16
<p>Underwater hyperspectral scan from India, scene 16</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 13
<p>Underwater hyperspectral scan from India, scene 13</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 11
<p>Underwater hyperspectral scan from India, scene 11</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 7
<p>Underwater hyperspectral scan from India, scene 7</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 8
<p>Underwater hyperspectral scan from India, scene 8</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 10
<p>Underwater hyperspectral scan from India, scene 10</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 6
<p>Underwater hyperspectral scan from India, scene 6</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 4
<p>Underwater hyperspectral scan from India, scene 4</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</p>
Underwater hyperspectral scan from India, scene 5
<p>Underwater hyperspectral scan from India, scene 5</p> <p>Used previously in publication Zimmermann, Nevala, Yoshimatsu et al., 2018, Current Biology, in press.</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.