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15,519 results for “r”
Supplementary material 7 from: Reshetnikov AN, Zibrova MG, Ayaz D, Bhattarai S, Borodin OV, Borzée A, Brejcha J, Çiçek K, Dimaki M, Doronin IV, Drobenkov SM, Gichikhanova UA, Gladkova AY, Gordeev DA, Ioannidis Y, Ilyukh MP, Interesova EA, Jadhav TD, Karabanov DP, Khabibullin VF, Khabilov TK, Khan MMH, Kidov AA, Klimov AS, Kochetkov DN, Kolbintsev VG, Kuzmin SL, Lotiev KY, Louppova NE, Lvov VD, Lyapkov SM, Martynenko IM, Maslova IV, Masroor R, Mazanaeva LF, Milko DA, Milto KD, Mozaffari O, Nguyen TQ, Novitsky RV, Petrovskiy AB, Prelovskiy VA, Serbin VV, Shi H-t, Skalon NV, Struijk RPJH, Taniguchi M, Tarkhnishvili D, Tsurkan VF, Tyutenkov OY, Ushakov MV, Vekhov DA, Xiao F, Yakimov AV, Yakovleva TI, Yang P, Zeleev DF, Petrosyan VG (2023) Rarely naturalized, but widespread and even invasive: the paradox of a popular pet terrapin expansion in Eurasia. NeoBiota 81: 91-127. https://doi.org/10.3897/neobiota.81.90473
Evaluation metrics for MaxEnt models made across a range of feature-class combinations and regularization multipliers
Supplementary material 1 from: Liu R, Li D, Zhang Z, Liu S, Liu X, Wang Y, Zhao H, Liu X, Zhang X, Xia J, Wang Y (2023) Morphological and phylogenetic analyses reveal two new species and a new record of Apiospora (Amphisphaeriales, Apiosporaceae) in China. MycoKeys 95: 27-45. https://doi.org/10.3897/mycokeys.95.96400
Morphological and phylogenetic analyses reveal two new species and a new record of Apiospora (Amphisphaeriales, Apiosporaceae) in China
AptaShape dataset and R analysis files, oDIN oLIVER project, Laborotory of Jørgen Kjems, Aarhus University
<p>.Aarhus University, February 2023. </p> <p>The attached dataset consists of a test and validation dataset obtained during the oDIN oLIVER project (https://projects.au.dk/odin/oliver). </p> <p>The datasets contain two cohorts of patients suffering from liver diseases. The metadata files present common clinically relevant parameters. The focus is on identifying patterns and protein markers for Non-Alcoholic Fatty Liver Disease (NAFLD) and Non-Alcoholic SteatoHepatitis (NASH). </p> <p>The uploaded folder also contains the R scripts used to generate the report presented here: https://doi.org/10.5281/zenodo.7629808</p> <p>Contact information</p> <p>Daniel Miotto Dupont</p> <p><a href="http://inano.au.dk/"><strong>Interdisciplinary Nanoscience Center - INANO-MBG, iNANO-huset</strong></a><br> Gustav Wieds Vej 14<br> <a href="https://www.au.dk/en/map/?b=1590">building 1590</a>, 316<br> 8000 Aarhus C<br> Denmark<br> <a href="mailto:dmd@inano.au.dk">dmd@inano.au.dk</a></p> <p> </p>
R Scripts - Replication Package
<p><strong>R Scripts - Replication Package:</strong> Contains R scripts for the complete quantitative analysis:</p> <ul> <li>One script for the preliminary question</li> <li>Three scripts, one for each research question</li> <li>One script for the classification of reactors based on their number of commits.</li> </ul>
Example data for: FIESTA: A Forest Inventory Estimation and Analysis R package
<p class="MsoNormal">This dataset is for examples in the Ecography Software Note, FIESTA: A Forest Inventory Estimation and Analysis R package, by Frescino, Tracey S.; Moisen, Gretchen G.; Patterson, Paul, L.; Toney, Chris; White, Grayson W. The examples demonstrate how to generate estimates of forest attributes using three different <em>FIESTA</em> modules: Green Book (GB), Model-Assisted (MA), and Small Area (SA). Included in the dataset are: a geospatial vector shapefile (.shp) of the Middle Bear-Logan Watershed area of interest (AOI); an R sf object (.rds) defining an ecological extent encompassing the AOI, Ecomap Section M331D (Cleland et al. 2007) ; a SQLite database (.db) including FIA plot data downloaded from FIA's publicly available DataMart (<a href="https://apps.fs.usda.gov/fia/datamart/datamart.html">https://apps.fs.usda.gov/fia/datamart/datamart.html</a>) and subset to the M331D boundary; and five auxiliary spatially-explicit raster layers (.img) clipped to the M331D boundary.</p>
Fi g ur e 1 5. B o x p l o t o f p a t r i s t i c d i s t a n c e a m o n g Typhlopinae (Amerotyphlops, Typhlops, Antilotyphlops and Cubatyphlops). in Revealing the cryptic diversity of the widespread and poorly known South American blind snake genus Amerotyphlops (Typhlopidae: Scolecophidia) through integrative taxonomy
Fi g ur e 1 5. B o x p l o t o f p a t r i s t i c d i s t a n c e a m o n g Typhlopinae (Amerotyphlops, Typhlops, Antilotyphlops and Cubatyphlops).
Supplementary material 3 from: Miranda-Gamboa R, Espinasa L, Verde-Ramírez MA, Hernández-Lozano J, Lacaille JL, Espinasa M, Ornelas-García CP (2023) A new cave population of Astyanax mexicanus from Northern Sierra de El Abra, Tamaulipas, Mexico. Subterranean Biology 45: 95-117. https://doi.org/10.3897/subtbiol.45.98434
Contrasting vertical isolation between Pachón and El Refugio caves and the fossil canyon between Pachón and El Refugio caves
Supplementary material 2 from: Miranda-Gamboa R, Espinasa L, Verde-Ramírez MA, Hernández-Lozano J, Lacaille JL, Espinasa M, Ornelas-García CP (2023) A new cave population of Astyanax mexicanus from Northern Sierra de El Abra, Tamaulipas, Mexico. Subterranean Biology 45: 95-117. https://doi.org/10.3897/subtbiol.45.98434
Geometric morphometric coordinates, PCA values obtained from the geometric morphometric data and orbit diameter values for the populations
FIG. 9. Echolocation callof R in A New Species of Horseshoe Bat (Chiroptera: Rhinolophidae) from Mount Namuli, Mozambique
FIG. 9. Echolocation callof R. namuli sp. nov. (X, MHNG 1971.067; recordedat Mount Namuli, Zambesia Province, Mozambique, -15.405933 / 37.067006, ca. 1,200 ma.s.l.)
Replication data and R script for 'Anticipated administrative burdens: How proximity to upcoming compulsory meetings affect welfare recipients' experiences of administrative burden'
<p>Administrative burden research claims that target group members are likely to experience learning, compliance, and psychological costs when interacting with government programs. We argue that the mere anticipation of such interactions may translate into experiences of administrative burden. Utilizing a large-scale dataset with responses from 2,276 Danish social benefit recipients, we estimate how proximity to upcoming compulsory meetings with street-level bureaucrats – a common condition in means-tested benefit programs – affect the recipients’ experiences of burdens. We find that the shorter the time to future meetings, the more benefit recipients experience stress and stigma, but the less they experience learning costs. The findings suggest that welfare recipient experiences of burden are likely to fluctuate over time and that psychological costs increase as recipients have to make mental and practical preparations for complying with government demands.</p>
High confidence calls (BCL6-R FL and DLBCL)
<p>High confidence calls (BCL6-R FL and DLBCL)</p>
EGID Express R Data File
<p>Date file for EGID Epress</p>
Data for FUV to MIR R(V) relationship paper
<p>Extinction curves used for the analysis presented in the paper titled "One Relation for All Wavelengths: The Far-Ultraviolet to Mid-Infrared Milky Way Spectroscopic R(V) Dependent Dust Extinction Relationship" by Gordon et al. (2023, ApJ, in press).</p>
TA B L E 2 Identified R packages useful for taxonomic name harmonization. Square brackets indicate supplementary references in Harmonizing taxon names in biodiversity data: A review of tools, databases and best practices
TA B L E 2 Identified R packages useful for taxonomic name harmonization. Square brackets indicate supplementary references
R notebooks to reproduce all analyses from the manuscript "grandR: a comprehensive package for nucleotide conversion sequencing data analysis"
<p>This package contains all R notebooks to reproduce the analyses from our manuscript "grandR: a comprehensive package for nucleotide conversion sequencing data analysis".</p> <p>In the zip file you find</p> <ul> <li>several rds files in the data folder: They contain grandR objects of both simulated and real SLAM-seq data sets. You can delete them and create them again by either just "knitting" the notebooks (which will generate all data necessary for this notebook and save it into the data folder), or by executing the generateAllDataFiles.R script ("Rscript generateAllDataFiles.R"), which will generate all rds files that do not exist).</li> <li>several R notebooks (Rmd): "Knitting" them will generate all figures from the manuscript. Without the data files (rds), this will be slow!</li> <li>knit_all.bash: Execute to "knit" all notebooks</li> <li>clean.bash: Clear the output of "knitting" the notebooks</li> </ul> <p> </p>
Database of flow cytometric analyses from: Roxo, G., Brilhante, M., Moura, M., Menezes de Sequeira, M., Costa, J., Silva, L., Vasconcelos, R., Talhinhas, P., Romeiras, M. (2022) Genome size variation within Crithmum maritimum: clues on the colonization of insular environments.
<p>Raw data of the Genome size of <em>Crithmum maritimum</em> for the 114 populations across the Portuguese territory (Portugal Mainland, Azores and Madeira archipelago). The data was obtained through the flow cytometry technique. This dataset contains a total of 1565 analyzes. </p>
Supplementary material 4 from: Eusébio RP, Fonseca PE, Rebelo R, Mathias ML, Reboleira ASPS (2023) How to map potential mesovoid shallow substratum (MSS) habitats? A case study in colluvial MSS. Subterranean Biology 45: 141-156. https://doi.org/10.3897/subtbiol.45.96332
Abundance of invertebrates collected in colluvial Mesovoid Shallow Substratum (MSS) at the Arrábida National Park
Supplementary material 3 from: Eusébio RP, Fonseca PE, Rebelo R, Mathias ML, Reboleira ASPS (2023) How to map potential mesovoid shallow substratum (MSS) habitats? A case study in colluvial MSS. Subterranean Biology 45: 141-156. https://doi.org/10.3897/subtbiol.45.96332
Results of criteria met for each location pinpointed as potential colluvial Mesovoid Shallow Substratum (MSS)
Supplementary material 1 from: Eusébio RP, Fonseca PE, Rebelo R, Mathias ML, Reboleira ASPS (2023) How to map potential mesovoid shallow substratum (MSS) habitats? A case study in colluvial MSS. Subterranean Biology 45: 141-156. https://doi.org/10.3897/subtbiol.45.96332
Characterization of each of the locations found in situ as colluvial Mesovoid Shallow Substratum (MSS): latitude, longitude and estimated area (m2)
Supplementary material 5 from: Eusébio RP, Fonseca PE, Rebelo R, Mathias ML, Reboleira ASPS (2023) How to map potential mesovoid shallow substratum (MSS) habitats? A case study in colluvial MSS. Subterranean Biology 45: 141-156. https://doi.org/10.3897/subtbiol.45.96332
Total invertebrate abundance, collected in colluvial Mesovoid Shallow Substratum (MSS) at the Arrábida National Park
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.