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Fig. 34. Callistocythere laevis Okubo, 1979. A in Unrecorded species of Korean invertebrates discovered through the project of 'Discovery of Korean Indigenous Species' II
Fig. 34. Callistocythere laevis Okubo, 1979. A. left valve; B. right valve; C. hemipenis.
Fig. 31 in Unrecorded species of Korean invertebrates discovered through the project of 'Discovery of Korean Indigenous Species' II
Fig. 31. Hemicytherura okuboi Tanaka, Yusaku and Noriyuki, 2011. Right valve with labelled fossae.
Fig. 20 in Unrecorded species of Korean invertebrates discovered through the project of 'Discovery of Korean Indigenous Species' II
Fig. 20. Lepadella rhomboides (Gosse, 1886). A. dorsal view, B. cross section. Scale bars = 50 μm.
AMP – Adrian Miles Project (ongoing)
<p>Korsakow film</p>
Fig. 18 in Unrecorded species of Korean invertebrates discovered through the project of 'Discovery of Korean Indigenous Species' II
Fig. 18. Lecane clara (Bryce, 1892). Scale bar = 50 μm.
Fig. 32 in Unrecorded species of Korean invertebrates discovered through the project of 'Discovery of Korean Indigenous Species' II
Fig. 32. Robustaurila assimilis (Kayiyama, 1913). Right valve.
Codes for Slowness-Enhanced Back-Projection (SEBP)
<p>Slowness-Enhanced MUSIC back-projection (SEBP) of teleseismic P waves implemented in Matlab. The Matlab Signal processing, Mapping and Imaging tool boxes are required.</p> <p>The objective of this package is to perform the Back-Projection Imaging on the seismograms of large earthquakes recorded by large-scale dense arrays and calibrate the spatial errors by aftershock. The instruction is performed on the 2021 Mw 7.4 Maduo Earthquake, and you can also practise Back-Projection Imaging on the 2011 Mw 9.0 Tohoku Earthquake on your own.</p> <p>Back-Projection is an earthquake-rupture imaging technique utilizing the coherent teleseismic P wavefield based on seismic array processing. Back-tracking of seismic waves recorded by dense arrays allows Back-Projection to determine the spatio-temporal properties of the rupture (length, direction, speed, and segmentation). Over recent decades, the development of large-scale dense seismic networks has enabled the Back-Projection imaging of the rupture process of major large earthquakes.</p> <p>This code package is developed based on MUSIC BP. Please see the "MUSICBP" branch for more details about MUSIC BP.</p> <p>Meng, L., A. Inbal, and J.-P. Ampuero. 2011. “A window into the complexity of the dynamic rupture of the 2011 Mw 9 Tohoku-Oki earthquake”, Geophys. Res. Lett., 38, L00G07, doi:10.1029/2011GL048118.</p> <p>Bao, H., Ampuero, J. P., Meng, L., Fielding, E. J., Liang, C., Milliner, C. W., ... & Huang, H. (2019). Early and persistent supershear rupture of the 2018 magnitude 7.5 Palu earthquake. Nature Geoscience, 12(3), 200-205.</p> <p>Kiser, E., & Ishii, M. (2017). Back-projection imaging of earthquakes. Annual Review of Earth and Planetary Sciences, 45, 271-299.</p> <p>Backprojection imaging is also performed routinely by IRIS for all new large earthquakes: <a href="https://ds.iris.edu/ds/products/backprojection/" rel="nofollow">https://ds.iris.edu/ds/products/backprojection/</a></p> <p>The MUSICBP code is contributed and maintained by Liuwei Xu (<a href="mailto:xuliuw1997@ucla.edu">xuliuw1997@ucla.edu</a>), Han Bao (<a href="mailto:hbrandon@ucla.edu">hbrandon@ucla.edu</a>), and Lingsen Meng (<a href="mailto:meng@epss.ucla.edu">meng@epss.ucla.edu</a>).</p> <ul> <li> <p> Instruction: SEBP.pdf</p> </li> <li> <p> Code and Data: AU*.m</p> </li> <li> <p> Related Paper: BaoNG_2019.pdf</p> </li> </ul>
Source data supporting the Article " Malaria transmission risk is projected to increase in the highlands of Western and Northern Rwanda"
<p>Average T<sub>min</sub>, T<sub>max</sub>, rainfall, malaria incedence in 30 districts were retrieved from the Rwanda Meteorological Agency and Rwanda’s Health Management Information System (HMIS) during 2010–2015. We applied an ensemble learning method, namely, Random Forest Model (RFM), to comprehensively estimate the effect of a changing climate on malaria incidence according to historical observations in Rwanda. Based on this forecasting model, we predict future malaria risk and its spatiotemporal changes under two distinct Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5). </p>
Fig. 12 in Unrecorded species of Korean invertebrates discovered through the project of 'Discovery of Korean Indigenous Species' III
Fig. 12. photo-microscopic presentation of deutonymph stage of Parasitus wangdungqingi Ma, 1995.
Fig. 10 in Unrecorded species of Korean invertebrates discovered through the project of 'Discovery of Korean Indigenous Species' III
Fig. 10. Sexual organism and habitus of Tyrophagus fanetzhangorum Klimov and OConnor, 2009.
Fig. 21 in Unrecorded species of Korean invertebrates discovered through the project of 'Discovery of Korean Indigenous Species' III
Fig. 21. SEM image of Loxoconcha taiwanensis Zhao, 1988. Scale bar = 150 μm.
Fig. 9 in Unrecorded species of Korean invertebrates discovered through the project of 'Discovery of Korean Indigenous Species' III
Fig. 9. Pseudopolydora gigeriosa Radashevsky and Hsieh, 2000. Scale bar = 2 mm.
Figure 10 from: Tandberg AHS, Vader W (2018) On a new species of Amphilochus from deep and cold Atlantic waters, with a note on the genus Amphilochopsis (Amphipoda, Gammaridea, Amphilochidae). In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 103–134. https://doi.org/10.3897/zookeys.731.19899
Figure 10 Amphilochus hamatus. Mouthparts. IINH37894. Scale bars: 0.1 mm.
Figure 6 from: Brix S, Lorz A-N, Jazdzewska AM, Hughes L, Tandberg AHS, Pabis K, Stransky B, Krapp-Schickel T, Sorbe JC, Hendrycks E, Vader W, Frutos I, Horton T, Jazdzewski K, Peart R, Beermann J, Coleman CO, Buhl-Mortensen L, Corbari L, Havermans C, Tato R, Campean AJ (2018) Amphipod family distributions around Iceland. In: Brix S, Lorz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 1-53. https://doi.org/10.3897/zookeys.731.19854
Figure 6 - Distribution map for a Synopiidae b Urothoidae, in sorted IceAGE EBS samples.
Figure 7 from: Tandberg AHS, Vader W (2018) On a new species of Amphilochus from deep and cold Atlantic waters, with a note on the genus Amphilochopsis (Amphipoda, Gammaridea, Amphilochidae). In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 103–134. https://doi.org/10.3897/zookeys.731.19899
Figure 7 Amphilochus manudens. Pereopods. IINH37885. Scale bars: 0.1 mm.
Figure 6 from: Tandberg AHS, Vader W (2018) On a new species of Amphilochus from deep and cold Atlantic waters, with a note on the genus Amphilochopsis (Amphipoda, Gammaridea, Amphilochidae). In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 103–134. https://doi.org/10.3897/zookeys.731.19899
Figure 6 Amphilochus manudens. Mouthparts. IINH37887. Scale bars: 0.1 mm.
Figure 2 from: Tandberg AHS, Vader W (2018) On a new species of Amphilochus from deep and cold Atlantic waters, with a note on the genus Amphilochopsis (Amphipoda, Gammaridea, Amphilochidae). In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 103–134. https://doi.org/10.3897/zookeys.731.19899
Figure 2 Amphilochus anoculus sp. n. Head and mouthparts. ZMBN121952. Scale bars: 0.1 mm.
Figure 9 from: Tandberg AHS, Vader W (2018) On a new species of Amphilochus from deep and cold Atlantic waters, with a note on the genus Amphilochopsis (Amphipoda, Gammaridea, Amphilochidae). In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 103–134. https://doi.org/10.3897/zookeys.731.19899
Figure 9 Amphilochus hamatus. Habitus. IINH37900. Scale bar: 0.5 mm.
Figure 14 from: Tandberg AHS, Vader W (2018) On a new species of Amphilochus from deep and cold Atlantic waters, with a note on the genus Amphilochopsis (Amphipoda, Gammaridea, Amphilochidae). In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 103–134. https://doi.org/10.3897/zookeys.731.19899
Figure 14 Pictorial key to Amphilochidae in the NE Atlantic.
Figure 8 from: Tandberg AHS, Vader W (2018) On a new species of Amphilochus from deep and cold Atlantic waters, with a note on the genus Amphilochopsis (Amphipoda, Gammaridea, Amphilochidae). In: Brix S, Lörz A-N, Stransky B, Svavarsson J (Eds) Amphipoda from the IceAGE-project (Icelandic marine Animals: Genetics and Ecology). ZooKeys 731: 103–134. https://doi.org/10.3897/zookeys.731.19899
Figure 8 Amphilochus manudens. Appendages from pleon and urosome. IINH37885. Scale bars: 0.1 mm.
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.