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52 results for “Scientific Reports”
Fig. 2 in Scientific Note Does the association of young fishes with jellyfishes protect from predation? A report on a failure case due to damage to the jellyfish
Fig. 2. Juvenile carangids and other fishes tend to stay close to a jellyfish's umbrella or among its tentacles while frightened.
MCR LTER: Coral Reef: Data for figures in Doo, et al., Ocean acidification effects on in situ coral reef metabolism, Scientific Reports, 2019
These data result from a Free Ocean CO2 Enrichment (FOCE). Data include net community calcification (NCC), net community production (NCP), and net ecosystem calcification (NEC) for the figures in Doo, Edmunds and Cparpenter, Ocean acidification effects on in situ coral reef metabolism, Scientific Reports, 2019, https://doi.org/10.1038/s41598-019-48407-7. Data for Figure 2A describe the 24-h NCC collected in the in situ SCoRe-FOCE. Data for Figures 2B and 2C describe the offset of NCC of the high CO2 treatment from ambient collected in the in situ SCoRe-FOCE. Data for Figure 3 describe the correlation of NCP to NCC collected in the in situ SCoRe-FOCE. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2018). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
Annexes to the EFSA external scientific report on the standard regulatory action for retrospective cumulative risk assessment of pesticides in MCRA
<p>Annexes to the EFSA external scientific report on the standard regulatory action for retrospective cumulative risk assessment of pesticides in MCRA.</p> <p>Harmonized methodology for retrospective dietary cumulative risk assessment (CRA) of pesticides was established by the European Commission (EC) and the European Food Safety Authority (EFSA) in 2018, in close collaboration with the Dutch National Institute for Public Health and the Environment (RIVM). An update of this regulatory methodology (RM) was proposed and adopted by EFSA in 2022 in a CRA on craniofacial alterations. This updated RM was implemented in version 10 of the MCRA software and validated as part of the first action defined in the third framework partnership agreements between EFSA and RIVM. This report describes the implementation of this updated methodology in the MCRA software for risk assessment. This is done from a proposed framework of standard regulatory actions (SRAs). SRAs offer a user-friendly and simple to use option for regulators to perform retrospective and prospective CRAs in MCRA according to agreed-upon RMs. In particular, this report provides guidance on the use of an SRA for a retrospective dietary CRA for craniofacial alterations according to the updated RM in MCRA version 10.</p> <p>Detailed results of the comparison between reported by MCRA and EFSA’s SAS® software and MCRA formatted input files for the catalogues and secondary data are presented in the following annexes:</p> <ul> <li>Annex A – Comparison of the MOET at different percentiles reported by MCRA and EFSA’s SAS® software for retrospective dietary CRA of craniofacial alterations. </li> <li> <p>Annex B – Comparison of risk-driver contributions reported by MCRA and EFSA’s SAS® software for retrospective dietary CRA of craniofacial alterations. </p> </li> </ul> <ul> <li> <p>Annex C – MCRA formatted input data file containing the primary entity catalogues for the SRA on retrospective dietary CRA of craniofacial alterations. </p> </li> <li> <p>Annex D – MCRA formatted input data file containing the secondary data for the SRA on retrospective dietary CRA of craniofacial alterations. </p> </li> <li> <p>Annex E – MCRA formatted input data file containing the unit- variability factors for the Tier II calculations of the SRA on retrospective dietary CRA of craniofacial alterations. </p> </li> <li> <p>Annex F – MCRA formatted input data file containing the unit- variability factors for the Tier I calculations of the SRA on retrospective dietary CRA of craniofacial alterations. </p> </li> </ul> <p> </p>
Dataset from 'Klever, L., Mamassian, P., & Billino, J. (2022). Age-related differences in visual confidence are driven by individual differences in cognitive control capacities. Scientific Reports, 12, 1-13. doi: 10.1038/s41598-022-09939-7
<p>We provide two files; one data file contains data on which analyses are based, the other one gives the column labels for the data file.</p> <p>___________________________________________<br> For further questions, please contact:<br> lena.klever[at]psychol.uni-giessen.de</p>
OTU sequences - Joli et al. Scientific Reports - Janus Gateway
<p>Fasta file representing the sequences of the representative OTUs from the paper Joli et al. published Scientific Reports as <strong>Need for focus on microbial species following ice melt and changing freshwater regimes in a Janus Arctic Gateway. </strong></p> <p>Those sequences have been selected based on 99% identity between reads.</p>
Coral growth data from Dongsha Atoll - published in DeCarlo et al. (2017) in Scientific Reports
<p>Coral growth data (annual extension, density, and calcification) for massive <em>Porites</em> corals from the eastern reef flat and lagoon of Dongsha Atoll, South China Sea. The data are derived from computed tomography (CT) scans of coral skeletons. Please cite the following paper when using these data:</p> <p>DeCarlo, T. M. <em>et al</em>. Mass coral mortality under local amplification of 2 °C ocean warming. <em>Sci. Rep</em> <strong>7</strong>, 44586 (2017).</p>
Data for publication 'Recreational vessels without Automatic Identification System (AIS) dominate anthropogenic noise contributions to a shallow water soundscape' (Scientific Reports 2019)
<p>Data on vessel tracks and underwater noise levels presented in the publication Hermannsen, L., Mikkelsen, L., Tougaard, J., Beedholm, K., Johnson, M. and P. T. Madsen, "Recreational vessels without Automatic Identification System (AIS) dominate anthropogenic noise contributions to a shallow water soundscape", Scientific Reports 9:15477 (<a href="https://doi.org/10.1038/s41598-019-51222-9">https://doi.org/10.1038/s41598-019-51222-9</a>).</p>
Data from the article "Short-interval wildfire and drought overwhelm boreal forest resilience" Whitman et al., Scientific Reports, 2019
<p>Field data collected in the Northwest Territories and Wood Buffalo National Park, as well as plot locations, for the study "Short-interval wildfire and drought overwhelm boreal forest resilience" by Whitman et al. in Scientific Reports, 2019.</p> <p>For metadata or assistance please contact the authors. If you intend to publish research using these data, please contact and inform the authors, and cite the source article.</p>
Repository of speech features from speakers with and without Parkinson's Disease. Neurovoz - Rasta PLP - V2 - Scientific Reports Publication: Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson's Disease
<p>This repository contains the Rasta-PLP features of six different speech recordings (sentences) from Neurovoz corpus (47 parkinsonian and 32 control speakers whose mother tongue is Spanish Castillian.)<br> Number of PLP coefficients: [6, 8, 10, 12, 14, 16, 18, 20].<br> Delta coefficients: Yes<br> Delta Delta coefficients: Yes<br> Sampling rate: 16 kHz<br> Frame size: 15 ms<br> Frame overlapping: 50%</p> <p>This subset of the Neurovoz corpus was recorded between 2015 and 2017 by Universidad Politécncia de Madrid and Hospital General Universitario Gregorio Marañón.</p> <p>This version includes the same files as the previous version and information about UPDRS, H&Y, years since diagnosis and age of each participant.</p> <p>The sentences were:</p> <p>BARBAS: "Cuando las barbas de tu vecino veas pelar, pon las tuyas a remojar"</p> <p>CALLE: "De la calle vendrá quien de tu casa te echará"</p> <p>DIABLO: " Cuando el diablo no sabe qué hacer, con el rabo mata moscas "</p> <p>PETACA BLANCA: " La petaca blanca es mía"</p> <p>PIDIO: "No pidas a quien pidió ni sirvas a quien sirvió"</p> <p>SOMBRA: " El que a buen árbol se arrima, buena sombra le cobija "</p> <p> </p> <p>How to cite:<br> [1] Moro-Velazquez, L., Gomez-Garcia, J. A., Godino-Llorente, J. I., Grandas-Perez, F., Shattuck-Hufnagel, S. Yagüe-Jimenez, V., and Dehak, N. (2019). Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson’s disease.Scientific reports 9, 19066.</p> <p><br> [2] Moro-Velazquez, L., Gomez-Garcia, J. A., Godino-Llorente, J. I., Villalba, J., Rusz, J., Shattuck-Hufnagel, S. and Dehak, N. (2019). A forced Gaussians based methodology for the differential evaluation of Parkinson's Disease by means of speech processing. Biomedical Signal Processing and Control, 48, 205-220.</p> <p>BibTeX:</p> <pre><code>@article{moro2019phonetic, title={Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson's Disease}, author={Moro-Velazquez, Laureano and Gomez-Garcia, Jorge A. and Godino-Llorente, Juan I. and Grandas-Perez, Francisco and Shattuck-Hufnagel, Stefanie and Yague-Jimenez, Virginia and Dehak, Najim}, journal={Scientific Reports}, volume={9}, pages={19066}, year={2019}, publisher={Nature Research Publishing} } @article{moro2019forced, title={A forced Gaussians based methodology for the differential evaluation of Parkinson's Disease by means of speech processing}, author={Moro-Velazquez, Laureano and Gomez-Garcia, Jorge Andres and Godino-Llorente, Juan Ignacio and Dehak, Najim}, journal={Biomedical Signal Processing and Control}, pages={205--220}, volume={48}, year={2019}, publisher={Elsevier} } </code></pre> <p> </p>
Data for Pelgrim et al. (2021) Scientific Reports
<p>Dataset for Pelgrim et al. (2021). Functional connectivity (FC) matrices were created by computing Pearson correlation coefficients between the mean time course of 105 regions of interest (ROIs) of the functional MRI images, then converted to normally distributed <em>Z</em>-scores using Fisher's r-to-<em>Z</em>-transformation.</p> <p>- 40 connectivity matrices of 22q11 deletion syndrome patients<br> - 76 connectivity matrices of healthy controls <br> - subject data<br> - names of 105 ROIs</p> <p> </p> <p>22q11 deletion syndrome, psychosis, functional MRI, network analysis, graph theory, functional connectivity</p>
FIGURE 2 in Dates of publication of the Zoology parts of the Report of the Scientific Results of the Voyage of H.M.S. Challenger During the Years 1873-76
FIGURE 2. The title-page of the fourth volume of the Zoology of the Report on the Scientific Results of the H.M.S. Challenger During the Years 1873–76. Image from a work no longer in copyright held by the library of the Woods Hole Oceanographic Institute and digitised under the Biodiversity Heritage Library initiative (see text for details). Note, the first line "(Provisional Title)" was removed from the title page of this and successive volumes (see Fig. 1).
FIGURE 1 in Dates of publication of the Zoology parts of the Report of the Scientific Results of the Voyage of H.M.S. Challenger During the Years 1873-76
FIGURE 1. The title-page of the first volume of the Zoology of the Report on the Scientific Results of the H.M.S. Challenger During the Years 1873–76. Image from a work no longer in copyright held by the library of the Woods Hole Oceanographic Institute and digitised under the Biodiversity Heritage Library initiative (see text for details). Note, the first line "(Provisional Title)" was removed from the title page for volume IV and successive volumes (see Fig. 2).
Translating Scientific Evidence Into Practice Using Digital Medicine and Electronic Patient Reported Outcomes
ClinicalTrials.gov study NCT04345393. IPD Sharing: YES. Countries: 1. Publications: 1.
Figure 5 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 5 Option C: GDP/cap and GERD. Vertical axis: annual monetary contribution per country. Horizontal axis: countries corresponding to Table (left).
Figure 3 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 3 Option A: GDP and GERD testing. Vertical axis: annual monetary contribution per country. Horizontal axis: countries corresponding to table (left).
Figure 4 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 4 Option B with GDP and GERD/cap. Vertical axis: annual monetary contribution per country. Horizontal axis: countries corresponding to Table (left).
Figure 10 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 10 Visualisation of annual membership fees distribution according to the two proposals selected.
Kunkhyen et al Scientific Reports 2024 dataset
<p>Source data for figures included in Kunkhyen et al. Scientific Reports 2024</p>
2024 07 26 Data for MS submitted to Scientific Reports
Open the record for dataset details and reuse information.
Figure 6 from: Landel S, Lymer G, Pasterk M, Guiraud M, Worley K (2024) A report on recommendations for the most suitable financial contribution model for the Distributed System of Scientific Collections Research Infrastructure (DiSSCo-RI). Research Ideas and Outcomes 10: e117217. https://doi.org/10.3897/rio.10.e117217
Figure 6 Simulating inflation, between 2024 and 2040 – Basic number: 2% inflation per year.
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.