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Figure 2 from: Smith R (2019) The CLUZ plugin for QGIS: designing conservation area systems and other ecological networks. Research Ideas and Outcomes 5: e33510. https://doi.org/10.3897/rio.5.e33510
Figure 2 Screenshots of QGIS showing on the left, a CLUZ distribution map of one of the conservation features, and on the right a map of the number of conservation features found in each planning unit.
Figure 47 from: Sukhorukov AP, Liu P-L, Kushunina M (2019) Taxonomic revision of Chenopodiaceae in Himalaya and Tibet. PhytoKeys 116: 1-141. https://doi.org/10.3897/phytokeys.116.27301
Figure 47 Salsolajacquemontii plant at fruiting stage. Photograph by A. Sukhorukov (near Kagbeni vill., Dhaulagiri zone, Nepal, September 2009).
Figure 52 from: Sukhorukov AP, Liu P-L, Kushunina M (2019) Taxonomic revision of Chenopodiaceae in Himalaya and Tibet. PhytoKeys 116: 1-141. https://doi.org/10.3897/phytokeys.116.27301
Figure 52 Reproductive shoot of Haloxylonthomsonii at fruiting stage, with prominent perianth wings. Photograph by H. Hartmann (Jammu & Kashmir, India, 1995).
Figure 44 from: Sukhorukov AP, Liu P-L, Kushunina M (2019) Taxonomic revision of Chenopodiaceae in Himalaya and Tibet. PhytoKeys 116: 1-141. https://doi.org/10.3897/phytokeys.116.27301
Figure 44 Gruboviadasyphylla: A general view of the plant at blooming stage B close-up of the flowers. Photographs by Prashant Awale (near Khalsar village, Nubra valley, Jammu & Kashmir, India, September 2011).
Figure 19 from: Sukhorukov AP, Liu P-L, Kushunina M (2019) Taxonomic revision of Chenopodiaceae in Himalaya and Tibet. PhytoKeys 116: 1-141. https://doi.org/10.3897/phytokeys.116.27301
Figure 19 Dysphaniaambrosioides: A general view B close-up of the inflorescence branch. Photographs by A. Sukhorukov (Dehradun, Uttarakhand, India, February 2018).
Figure 17 from: Sukhorukov AP, Liu P-L, Kushunina M (2019) Taxonomic revision of Chenopodiaceae in Himalaya and Tibet. PhytoKeys 116: 1-141. https://doi.org/10.3897/phytokeys.116.27301
Figure 17 Distribution map of Atriplexpamirica (circles), A.hortensis (stars) and Microgynoeciumtibeticum (triangles).
Figure 12 from: Sukhorukov AP, Liu P-L, Kushunina M (2019) Taxonomic revision of Chenopodiaceae in Himalaya and Tibet. PhytoKeys 116: 1-141. https://doi.org/10.3897/phytokeys.116.27301
Figure 12 Chenopodiastrummurale plants at blooming stage. Photograph by A. Sukhorukov (Dead Sea area, Israel, February 2011).
Figure 8b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 8b "Point Pattern Edition" features. - Information that is displayed (marks of the point pattern, if available, as defined by the user) when an event is clicked
Figure 5a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 5a Example of use of the SimplifyLinearNetwork function. - A road network introduced as input in which there is an excess of road segments and vertex
Figure 1 from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 1 Workflow that describes all the steps that could be carried out in order to perform a spatial analysis on a point pattern that lies on a linear network. Some of these steps which lead to the final statistical analysis may be skipped but, at least, all of them should be considered. The blocks pointing the steps of the process include some of the R packages that would allow to successfully achieve each of them.
Figure 3b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 3b "Network Edition" example of use (I). - Network resulting from clicking on "Rebuild linear network" in the situation of a
Figure 2a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 2a "Network Edition" features. - Overview of the "Network Edition" section of the SpNetPrep application
Figure 6b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 6b "Network Direction" features. - Manual addition of traffic flow to the network by using the options "Add flow" and "Add long flow"
Figure 13 from: Sukhorukov AP, Liu P-L, Kushunina M (2019) Taxonomic revision of Chenopodiaceae in Himalaya and Tibet. PhytoKeys 116: 1-141. https://doi.org/10.3897/phytokeys.116.27301
Figure 13 SEM micrographs of Chenopodiastrummurale (A, B) and C.badachschanicum (C, D) seeds. Magnification: 50× (A, C), 200× (B, D).
Figure 3a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 3a "Network Edition" example of use (I). - Use of the "Join vertex" (in green), "Remove edge" (in red) and "Add point" options (in green) in the SpNetPrep application
Figure 8a from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 8a "Point Pattern Edition" features. - An example of a point pattern that lies on a road network as it can be visualized in SpNetPrep
Figure 10 from: Sukhorukov AP, Liu P-L, Kushunina M (2019) Taxonomic revision of Chenopodiaceae in Himalaya and Tibet. PhytoKeys 116: 1-141. https://doi.org/10.3897/phytokeys.116.27301
Figure 10 SEM micrographs of Chenopodium seeds. A, BC.novopokrovskyanumC, DC.atripliciformeE, FC.perttii. Magnification: 50× (A, C, E), 200× (B, D, F).
Figure 1 from: Sukhorukov AP, Liu P-L, Kushunina M (2019) Taxonomic revision of Chenopodiaceae in Himalaya and Tibet. PhytoKeys 116: 1-141. https://doi.org/10.3897/phytokeys.116.27301
Figure 1 The territory included in the present investigation (highlighted in green). Abbreviations: 1 – Sikkim.
Figure 4b from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 4b "Network Edition" example of use (II). - Network resulting from clicking on "Rebuild linear network" in the situation of a
Figure 7 from: Briz-Redón Á (2019) SpNetPrep: An R package using Shiny to facilitate spatial statistics on road networks. Research Ideas and Outcomes 5: e33521. https://doi.org/10.3897/rio.5.e33521
Figure 7 Example of a linear road network following usual notation for the edges (\documentclass[12pt]{standalone} \usepackage{varwidth} \usepackage[utf8x]{inputenc} \usepackage[T1]{fontenc} \usepackage{lmodern} \usepackage{amsmath, amssymb, graphics, setspace} \newcommand{\mathsym}[1]{{}} \newcommand{\unicode}[1]{{}} \newcounter{mathematicapage} \begin{document} \begin{varwidth}{50in} \begin{equation*} e_{i} \end{equation*} \end{varwidth} \end{document} ) and vertex (\documentclass[12pt]{standalone} \usepackage{varwidth} \usepackage[utf8x]{inputenc} \usepackage[T1]{fontenc} \usepackage{lmodern} \usepackage{amsmath, amssymb, graphics, setspace} \newcommand{\mathsym}[1]{{}} \newcommand{\unicode}[1]{{}} \newcounter{mathematicapage} \begin{document} \begin{varwidth}{50in} \begin{equation*} v_{i} \end{equation*} \end{varwidth} \end{document} ). Arrows represent the direction of traffic flow.
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.