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Fig. 3 in Methods for collecting large numbers of exuviae from Coptotermes (Blattodea: Rhinotermitidae) termite colonies
Fig. 3. Coptotermes gestroi workers (n = 1,000) on a media pad saturated with a 0.05% Nile Blue A and deionized water solution in a Petri dish wrapped with Parafilm.
Fig. 2 in Methods for collecting large numbers of exuviae from Coptotermes (Blattodea: Rhinotermitidae) termite colonies
Fig. 2. Overview of the methods. Coptotermes gestroi workers (n = 1,000) were placed on a Nile Blue A-dyed media pad for 2 d in a Petri dish. Dyed and non-dyed workers were separated. Non-dyed workers, potentially under pre-molt fast, were placed on a Nile Blue A-dyed filter paper and observed for 7 d in a Petri dish. Exuviae, newly molted workers, dyed workers (that acquired dye from the filter paper during the 7 d observation), and cadavers were collected.
Fig. 1 in Methods for collecting large numbers of exuviae from Coptotermes (Blattodea: Rhinotermitidae) termite colonies
Fig. 1. Laboratory colony rearing units. (A) Plastic cylindrical vial containing moistened organic soil, wood blocks, and agar used to house termite colonies from 0 to 1-yr-old; (B) larger cylindrical vial the colony was transferred to for colonies 1 to 2-yr-old; (C) plastic container in which the uncapped cylindrical vial (pictured in B) was placed into for colonies 2 to 4-yr-old; (D) plastic container in which the uncovered container (from C) was placed into for colonies aged 4+ yr. Red line points to vial within the box that usually contains the central nest (location of reproductives and brood).
Fig. 6 in Methods for collecting large numbers of exuviae from Coptotermes (Blattodea: Rhinotermitidae) termite colonies
Fig. 6. Mean ± standard error of (A) exuviae collected; (B) newly molted individuals observed; (C) workers that acquired Nile Blue A dye during the 7 d observation; and (D) cadavers collected during observation of 163.0 ± 48.2 Coptotermes gestroi workers (n = 3) that were potentially in pre-molt fast.
Datasets used in "Assesing the quality of random number generators through neural networks", Machine Learning: Science and Technology 5 (2024) 025072
<p>Datasets corresponding to the bits generated by different random number generators used in J. L. Crespo et al, Machine Learning: Science and Technology 5 (2024) 025072.</p> <p>VCSEL_QRNG_postprocessed_bits.txt: postprocessed bits from the random generator based on gain-switching of VCSELs </p> <p>EC_LCG_bits.txt: bits from the linear congruential generator on elliptic curves</p> <p>LCG_32_bits.txt:: bits from the linear congruential generator with 32 bits</p> <p>VCSEL_QRNG_raw_bits.txt: raw bits from the random generator based on gain-switching of VCSELs</p> <p> </p>
Generic residue numbering of the GAIN domain of adhesion GPCRs
<p>The dataset corresponding to the publication:</p> <ul> <li>Generic residue numbering of the GAIN domain of adhesion GPCRs <div> <div>Florian Seufert, Guillermo Pérez-Hernández, Gáspár Pándy-Szekeres, Ramon Guixà-González, Tobias Langenhan, David E. Gloriam, Peter W. Hildebrand</div> <div>ReasearchSquare</div> <div><a href="https://doi.org/10.21203/rs.3.rs-4761600/v1" rel="nofollow">https://doi.org/10.21203/rs.3.rs-4761600/v1</a></div> </div> </li> </ul> <p>The archive consists of three files:</p> <ul> <li>gaingrn_data.tgz</li> </ul> <p>Contains the underlying data and object structures for the GAIN-GRN creation process and the python package availabe in <a title="repo" href="https://github.com/FloSeu/GAIN-GRN" target="_blank" rel="noopener">https://github.com/FloSeu/GAIN-GRN</a>. This can be downloaded manually and extracted in the respective GAIN-GRN/ directory or automatically retrieved via a dedicated function</p> <ul> <li>agpcr_gains.tgz</li> </ul> <p>Contains the best (rank 1) PDB model of the ColabFold/AlphaFold2 workflow for each adhesion GPCR GAIN domain, named by its UniProt accession number.</p> <ul> <li>pkd_gains.tgz</li> </ul> <p>Contains the best (rank 1) PDB model of the ColabFold/AlphaFold2 workflow for each polycystic kidney disease (PKD1) / PKD1-like 1 protein (PKD1L1) GAIN domain, named by its UniProt accession number.</p>
Supporting data for RCANE: A Deep Learning Algorithm for Whole-genome Pan-Cancer Somatic Copy Number Aberration Prediction using RNA-seq Data.
<p>This is the data repository for <em>RCANE: A Deep Learning Algorithm for Whole-genome Pan-Cancer Somatic Copy Number Aberration Prediction using RNA-seq Data</em>. To use this dataset, please refer to <a href="https://github.com/HowardGech/RCANE" target="_blank" rel="noopener">https://github.com/HowardGech/RCANE</a>.</p>
Linked collectors and determiners for: Sea-ice meiofauna biodiversity from the Nansen Legacy cruise Q4 (cruise number: 2019711).
Natural history specimen data linked to collectors and determiners held within, "Sea-ice meiofauna biodiversity from the Nansen Legacy cruise Q4 (cruise number: 2019711)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/4579d9f1-f913-4d71-8581-e1dd2b812501">https://bionomia.net/dataset/4579d9f1-f913-4d71-8581-e1dd2b812501</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/4579d9f1-f913-4d71-8581-e1dd2b812501">https://gbif.org/dataset/4579d9f1-f913-4d71-8581-e1dd2b812501</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Sea-ice meiofauna biodiversity from the Nansen Legacy joint cruise JC1-2 (cruise number: 2018707).
Natural history specimen data linked to collectors and determiners held within, "Sea-ice meiofauna biodiversity from the Nansen Legacy joint cruise JC1-2 (cruise number: 2018707)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/727aa4d6-2436-4536-be48-d40963f9d352">https://bionomia.net/dataset/727aa4d6-2436-4536-be48-d40963f9d352</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/727aa4d6-2436-4536-be48-d40963f9d352">https://gbif.org/dataset/727aa4d6-2436-4536-be48-d40963f9d352</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Sea-ice meiofauna biodiversity from the Nansen Legacy joint cruise JC2-1 (cruise number: 2021708).
Natural history specimen data linked to collectors and determiners held within, "Sea-ice meiofauna biodiversity from the Nansen Legacy joint cruise JC2-1 (cruise number: 2021708)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/7b9ee529-aa5f-41b7-bbe8-8d8afb0a148c">https://bionomia.net/dataset/7b9ee529-aa5f-41b7-bbe8-8d8afb0a148c</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/7b9ee529-aa5f-41b7-bbe8-8d8afb0a148c">https://gbif.org/dataset/7b9ee529-aa5f-41b7-bbe8-8d8afb0a148c</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Sea-ice meiofauna biodiversity from the Nansen Legacy cruise Q3 (cruise number: 2019706).
Natural history specimen data linked to collectors and determiners held within, "Sea-ice meiofauna biodiversity from the Nansen Legacy cruise Q3 (cruise number: 2019706)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/ea261345-4e83-4f12-aa5f-f4b119d5a4ce">https://bionomia.net/dataset/ea261345-4e83-4f12-aa5f-f4b119d5a4ce</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/ea261345-4e83-4f12-aa5f-f4b119d5a4ce">https://gbif.org/dataset/ea261345-4e83-4f12-aa5f-f4b119d5a4ce</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Sea-ice meiofauna biodiversity from the Nansen Legacy joint cruise JC3 (cruise number: 2022702).
Natural history specimen data linked to collectors and determiners held within, "Sea-ice meiofauna biodiversity from the Nansen Legacy joint cruise JC3 (cruise number: 2022702)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/7181ab6e-32de-4928-b152-a60025cd1e21">https://bionomia.net/dataset/7181ab6e-32de-4928-b152-a60025cd1e21</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/7181ab6e-32de-4928-b152-a60025cd1e21">https://gbif.org/dataset/7181ab6e-32de-4928-b152-a60025cd1e21</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Sea-ice meiofauna biodiversity from the Nansen Legacy joint cruise JC2-2 (cruise number: 2021710).
Natural history specimen data linked to collectors and determiners held within, "Sea-ice meiofauna biodiversity from the Nansen Legacy joint cruise JC2-2 (cruise number: 2021710)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8daf75ea-e1c4-4231-9848-b3ba4928aa4a">https://bionomia.net/dataset/8daf75ea-e1c4-4231-9848-b3ba4928aa4a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8daf75ea-e1c4-4231-9848-b3ba4928aa4a">https://gbif.org/dataset/8daf75ea-e1c4-4231-9848-b3ba4928aa4a</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Correction of collecting number errors in the protologues of sixty-four taxon names from China.
Natural history specimen data linked to collectors and determiners held within, "Correction of collecting number errors in the protologues of sixty-four taxon names from China". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/057ddfc8-53dc-4dc3-89ce-058fcc84ff71">https://bionomia.net/dataset/057ddfc8-53dc-4dc3-89ce-058fcc84ff71</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/057ddfc8-53dc-4dc3-89ce-058fcc84ff71">https://gbif.org/dataset/057ddfc8-53dc-4dc3-89ce-058fcc84ff71</a>. Formatted as a Frictionless Data package.
Figures 34–37. Homaledra wings. MGCL slide number given. 34 in Two new species of palm-leaf skeletonizers (Lepidoptera: Pterolonchidae: Homaledra Busck)
Figures 34–37. Homaledra wings. MGCL slide number given. 34) H. sabalella (#3321). 35) H. howardi (#3335). 36) H. knudsoni (#5005). 37) H. heptathalama (#5029).
Figures 27–33. Homaledra female genitalia, MGCL slide number given. 27 in Two new species of palm-leaf skeletonizers (Lepidoptera: Pterolonchidae: Homaledra Busck)
Figures 27–33. Homaledra female genitalia, MGCL slide number given. 27) H. sabalella (#4566). 28) H. sabalella, detail of signum (#4566). 29) H. sabalella, detail of signum (#3303). 30) H. howardi (#4261). 31) H. howardi, detail of signum (#4261). 32) H. knudsoni (#4673). 33) H. knudsoni, detail of signum (#4673). Scale bars = 500 µm.
Opinions and data on short food supply chains related policy analysis in 9 EU countries generated in the H2020 SMARTCHAIN Project grant number: 773785
<p>Questionnaires: Opinions and data on short food supply chains related policy analysis in 9 EU countries generated in the H2020 SMARTCHAIN Project grant number: <strong>773785</strong></p>
Figure 20 in The European centipedes hitherto referred to Eurygeophilus, Mesogeophilus, and Chalandea (Chilopoda, Geophilomorpha): taxonomy, distribution, and geographical variation in segment number
Figure 20. Elongation of antennal article XIV in representative specimens of E. pinguis (Brölemann, 1898). The ratio between the length of article XIV and the total length of the previous two articles is plotted against head width as a measure of the body size. A black circle marks the only specimen putativily representative of the nominal species Chalandea scheerpeltzi.
Figure 19 in The European centipedes hitherto referred to Eurygeophilus, Mesogeophilus, and Chalandea (Chilopoda, Geophilomorpha): taxonomy, distribution, and geographical variation in segment number
Figure 19. Geographical occurrence of Eurygeophilus multistiliger (Verhoeff, 1899) (white symbols) and Eurygeophilus Europe generally; (b) the Pyrenees; and (c) the Alps. Type localities are indicated with diamonds, other published Localities of the specimens directly examined by us are indicated with dotted symbols. All published records of E.
Figures 14–18 in The European centipedes hitherto referred to Eurygeophilus, Mesogeophilus, and Chalandea (Chilopoda, Geophilomorpha): taxonomy, distribution, and geographical variation in segment number
Figures 14–18. Eurygeophilus pinguis (Brölemann, 1898), female, 27 mm long, M. La Marzola (Alps). (14) Head, dorsal (right antenna and setae not drawn). (15) Head, ventral (antennae not drawn). (16) Forcipular segment, ventral. (17) Sternum of leg-bearing segment V, ventral. (18) Last leg-bearing segment and terminal segments, ventral (right telopodite and setae on the relevant coxopleuron not drawn).
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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.