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Fig. 49 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 49. Distribution map of Iniforis pseudothomae Rolán & Fernández-Garcés, 1993; red circle = type locality.
Fig. 52 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 52. Distribution map of Isotriphora sp. 1 (gray circle) and Isotriphora leo sp. nov. (red circle).
Fig. 57 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 57. Distribution map of Monophorus caracca (Dall, 1927) comb. nov. (red circle = type locality; black circle = additional locality) and Monophorus verecundus sp. nov. (brown circle = type locality; gray circles = additional localities).
Fig. 54 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 54. Distribution map of Marshallora ostenta Rolán & Fernández-Garcés, 2008; red circle = type locality.
Fig. 48 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 48. Distribution map of Iniforis carmelae Rolán & Fernández-Garcés, 1993; red circle = type locality.
Fig. 77 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 77. Distribution map of Triphora charybdis Fernandes & Pimenta, 2015; red circle = type locality.
Fig. 43 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 43. Distribution map of "Inella" vanilla Fernandes & Pimenta, 2019; red circle = type locality.
Fig. 39 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 39. Distribution map of "Inella" faceta Fernandes & Pimenta, 2019; red circle = type locality.
Fig. 33 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 33. Distribution map of Eutriphora auffenbergi Rolán & Lee, 2008; red circle = type locality.
Fig. 34 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 34. Distribution map of Eutriphora costai Fernandes & Pimenta, 2015; red circle = type locality.
Fig. 5 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 5. Isotriphora leo sp. nov. A. MNRJ 29392*, holotype, 2.39 mm. B. MORG 25615*, 2.00 mm. C–D. MORG 25645*, 1.76 mm and 1.79 mm, respectively. E–I. HolotypE. Scale bars: A–E = 1 mm; F–G = 100 µm; H–I = 500 µm.
Fig. 1 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 1. Cheirodonta dupliniana (Olsson, 1916). A–C. PRI 1376, 5.75 mm (original description) or 6.31 mm (scale bar provided), lectotype, illustrated in Olsson (1916). D–E. PRI 11016, 5.57 mm, paralectotype, not illustrated in Olsson (1916). F–G. MCZ 34426, 6.75 mm and 6.35 mm, respectively. H. FLMNH 160564, 6.00 mm. I–J. FLMNH 507930, 4.60 mm. Scale bars: B–I = 1 mm; J = 500 µm. Photo credits B–E: Leslie Skibinski (Cornell University).
Fig. 10 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 10. Monophorus caracca (Dall, 1927) comb. nov. A. USNM 108343, lectotype, 7.1 mm. B–E. MNHN*, 4.42 mm, 6.84 mm, 4.50 mm and 5.74 mm, respectively. F–J. Same shell as E. Scale bars: A–F = 1 mm; G = 100 µm; H = 20 µm; I = 250 µm; J = 500 µm.
Fig. 6 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 6. Isotriphora sp. 1. A–B. MORG 52611*, 2.08 mm and 1.58 mm, respectively. C–D. Same shell as A. E–F. ZUEC-GAS 7489, 1.44 mm. G. ZUEC-GAS 7489, same shell as E. Scale bars: A–C, E–F = 1 mm; D, G = 100 µm. Photo credits E–G: Aramys Cesar (UNICAMP).
Fig. 3 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 3. Isotriphora tricingulata Rolán & Fernández-Garcés, 2015. A, C. MNRJ 32558*, 2.75 mm and 3.04 mm, respectively. B. MNRJ 17929*, 4.62 mm. D. MNRJ 32574*, 3.29 mm. E–I, K. Same shell as A. J. Same shell as D. Scale bars: A–E = 1 mm; F–H = 500 µm; I–K = 100 µm.
Fig. 8 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 8. Marshallora ostenta Rolán & Fernández-Garcés, 2008 from Brazil. A–C, E. IBUFRJ 19532, same shell as Fig. 7N. D. MNRJ 18623*. F. MNRJ 31017*, same shell as Fig. 7K. G. MNRJ 33801*, same shell as Fig. 7F. H–I. MNRJ 30750*, same shell as Fig. 7J. Scale bars: A–C = 500 µm; D–H = 100 µm; I = 50 µm.
Data, materials, methods and codes for publication Reis et al., "Understanding the stickiness of commodity supply chains is key to improving their sustainability", 2020, One Earth.
<p>Explanation of the data and code used for the article: "Understanding the stickiness of commodity supply chains is key to improving their sustainability", 2020, One Earth.</p> <p> The file: "StickinessAnalysisCompleteGeneric_CleanUpdate18-5-2020.R" is the R code/ script containing all the data preparation and the stickiness analysis.</p> <p>The file: "BRAZIL_SOY_V2.3_WITH_DOMESTIC_TRADERS.csv" contains the raw data of Brazil's soy exports and domestic consumption from trase.earth. This dataset can also be obtained from trase.earth in the latest version.</p> <p>The file: "NodesCiS.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: A. logistics hubs supplying traders, and D. traders supplying countries. They are put together in the same table because they are all "sending" relationships.</p> <p>The file: "NodesCiR.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: C. traders sourcing from logistics hubs, and E. countries sourcing from traders. They are put together in the same table because they are all "receiving" relationships.</p> <p>The file "NodesCiSMunCountry.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: B. logistics hubs supplying countries (directly not passing through traders). This is separate in another table because it is a direct sending relationship from LHs to countries.</p> <p>The file "NodesCiRMunCountry.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: F. countries sourcing from logistics hubs (directly not passing through traders). This is separate in another table because it is a direct receiving relationship from LHs to countries.</p> <p>The file: "NodesWPiS.csv" is a table with the WPi (stickiness on flows) measured for the types of supply chain relationships: A. logistics hubs supplying traders, and D. traders supplying countries. They are put together in the same table because they are all "sending" relationships.</p> <p>The file: "NodesWPiR.csv" is a table with the Ci (stickiness on flows) measured for the types of supply chain relationships: C. traders sourcing from logistics hubs, and E. countries sourcing from traders. They are put together in the same table because they are all "receiving" relationships.</p> <p>The file "NodesWPiSMunCountry.csv" is a table with the Ci (stickiness on flows) measured for the types of supply chain relationships: B. logistics hubs supplying countries (directly not passing through traders). This is separate in another table because it is a direct sending relationship from LHs to countries.</p> <p>The file "NodesWPiRMunCountry.csv" is a table with the Ci (stickiness on flows) measured for the types of supply chain relationships: F. countries sourcing from logistics hubs (directly not passing through traders). This is separate in another table because it is a direct receiving relationship from LHs to countries.</p>
Fig. 55. One ofthreetreesfromtotalevidenceanalysiswith POYof 92-taxondatasetusing 2 in Phylogenetic relationships of family groups in Pentatomoidea based on morphology and DNA sequences (Insecta: Heteroptera)
Fig. 55. One ofthreetreesfromtotalevidenceanalysiswith POYof 92-taxondatasetusing 2: 2 indel ⁄ transition–transversioncostratio, whichhad the lowest MRI value. Bremer support values are shown.
Figure 3 in New records of Nuuanuidae (Crustacea: Amphipoda: Senticaudata) from Korean waters, with descriptions of one new genus and two new species
Figure 3. Parvipalpus holocaudatus sp. nov., holotype, male. (A) Pereopod 3; (B) right pereopod 4; (C) left pereopod 4; (D) pereopod 5; (E) pereopod 6; (F) pereopod 7.
Figure 2 in A taxonomic review of the genus Gibbotettix with description of one new species (Orthoptera: Tetrigidae)
Figure 2. Gibbotettix vallis sp. nov.: (a–c) dorsal, oblique-lateral and lateral views of female body; (d) lateral view of male body. Scale bars = 1 mm.
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.