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3,225 results for “Case studies”
NIMROD growth rates (1/s) by finite element poly_degree (columns) and case from "The Impact of Collisionality, FLR and Parallel Closure Effects on Instabilities in the Tomakak Pedestal: Numerical Studies with the NIMROD code”
<p>NIMROD growth rates (1/s) by finite element poly_degree (columns) and case from "The Impact of Collisionality, FLR and Parallel Closure Effects on Instabilities in the Tomakak Pedestal: Numerical Studies with the NIMROD code” as submitted to Physics of Plasmas</p>
Data for "Open Access impact on citations: a case study"
<p>This dataset is a list of 347 papers published in 2010 and retrieved from the Web of Science, Scopus and Google Scholar. For each paper, the number of citations and the citation date(s) have been collected. If the full-text is available online, the date of "liberation" and the URL of the file have been retrieved as well. The objective was to assess the impact of Open access on citation rate and more particularly the impact before and after full-text "liberation".</p> <p> </p>
FIGURE 3 in Phloeocharis subtilissima Mannerheim (Staphylinidae: Phloeo charinae) and Cephennium gallicum Ganglbauer (Scydmaenidae) new to North America: a case study in the introduction of exotic Coleoptera to the port of Halifax, with new records of other species
FIGURE 3: Cephennium gallicum Ganglbauer, Point Pleasant Park, Halifax, Nova Scotia, Canada. Dorsal habitus.
FIGURE 2 in Phloeocharis subtilissima Mannerheim (Staphylinidae: Phloeo charinae) and Cephennium gallicum Ganglbauer (Scydmaenidae) new to North America: a case study in the introduction of exotic Coleoptera to the port of Halifax, with new records of other species
FIGURE 2: Phloeocharis subtilissima Mannerheim, Point Pleasant Park, Halifax, Nova Scotia, Canada. Living specimen in bark of red maple (Acer rubrum).
FIGURE 1 in Phloeocharis subtilissima Mannerheim (Staphylinidae: Phloeo charinae) and Cephennium gallicum Ganglbauer (Scydmaenidae) new to North America: a case study in the introduction of exotic Coleoptera to the port of Halifax, with new records of other species
FIGURE 1: Phloeocharis subtilissima Mannerheim, Point Pleasant Park, Halifax, Nova Scotia, Canada. Dorsal habitus.
FIGURE 4 in Phloeocharis subtilissima Mannerheim (Staphylinidae: Phloeo charinae) and Cephennium gallicum Ganglbauer (Scydmaenidae) new to North America: a case study in the introduction of exotic Coleoptera to the port of Halifax, with new records of other species
FIGURE 4: Cephennium gallicum Ganglbauer, Point Pleasant Park, Halifax, Nova Scotia, Canada. Lateral habitus.
HUMANE internal case study: eVACUATE #1
<p>This case study was conducted on 14 December 2015. The purpose was to evaluate the usefulness of the HUMANE approach as perceived by relevant developers (software engineers), and additionally ask if the HUMANE typology facilitates cross-disciplinary understanding.</p> <p>The files included here provide a summary of the analysis and the transcript from a semi-structured focus group.</p>
HUMANE external case study: eVACUATE #2
<p>This case study was conducted in September to October 2016 with the purpose of providing an external validation of the HUMANE typology and method. This eVACUATE case-study comprises four different engagements in order to ensure a comprehensive evaluation: a quantitative online survey on the HUMANE design patterns; a quantitative survey on the HUMANE typology used for characterising Human-Machine Networks (HMNs); and two focus groups evaluating the HUMANE method (covering the profiling process, network diagramming, implication analysis, and design pattern approach).</p> <p>A summary of results, along with focus group transcripts, surveys and survey results are included here.</p>
10 eADAGE models used for the PAO1 KEGG pathways case study in PathCORE
<p>ensemble Analysis using Denoising Autoencoders for Gene Expression<strong> </strong>(<strong>eADAGE</strong>) is an unsupervised feature construction algorithm developed by Tan et al. that uses an ensemble of neural networks (an ensemble of ADAGE models) to capture biological signatures embedded in the expression compendium. By initializing eADAGE with different random seeds, Tan et al. produced 10 eADAGE models that each extracted k=300 features from the compendium of genome-scale <em>P. aeruginosa</em> data.</p> <p>eADAGE is described in Tan et al.'s "System-wide automatic extraction of functional signatures in <em>Pseudomonas aeruginosa</em> with eADAGE" (https://doi.org/10.1101/078659). The code to construct these 10 models is available in this repository: https://bitbucket.org/greenelab/eadage (see eADAGE_construction.sh). </p>
Derived-ECVs for Case Studies (maps)
<p>Climate maps (raster layers .tif) of derived-ecvs with a spatial resolution of 5.5 km (1 km for Azores) obtained by statistically downscaling a set of CMIP6 simulations for different IPCC climate scenarios (historical, SSP1-2.6, SSP2-4.5, SSP5-8.5) and time horizons (reference, short time-horizon, medium time-horizon, long time-horizon). Data are representative of specific climate normals (yearly averaged values) and created by RethinkAction.</p> <p>We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.</p> <p>Moreover, we acknowledge the Copernicus Climate Change Service (C3S) Climate Data Store (CDS) to provide access to CMIP6, CERRA, ERA5 and ERA5-Land data:</p> <ul> <li>Copernicus Climate Change Service, Climate Data Store, (2021): CMIP6 climate projections. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.c866074c.</li> <li>Schimanke S., Ridal M., Le Moigne P., Berggren L., Undén P., Randriamampianina R., Andrea U., Bazile E., Bertelsen A., Brousseau P., Dahlgren P., Edvinsson L., El Said A., Glinton M., Hopsch S., Isaksson L., Mladek R., Olsson E., Verrelle A., Wang Z.Q., (2021): CERRA sub-daily regional reanalysis data for Europe on single levels from 1984 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.622a565a</li> <li>Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D.,Thépaut, J-N. (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.adbb2d47</li> <li>Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac</li> </ul> <p>Acknowledgement also to:</p> <ul> <li>DRAAC, 2023, Regional climate data provided by the Regional Ditectorate for the Environment and Climate Change of the Regional Autonomous Government of Azores (<a href="https://urldefense.com/v3/__https:/portal.azores.gov.pt/en/web/draac__;!!D9dNQwwGXtA!TAB9_FXZEEA4K_6AkmoIqX-krFMSiGcKRY--rOpV9psI98vjxa-sLAZQYR1s0G1fFmBrENoHHpZCdvP0s67vzss$" target="_blank" rel="noopener">https://portal.azores.gov.pt/en/web/draac</a>)</li> <li>SRAA\CCIAM, 2017. Programa Regional de Alterações Climáticas (PRAC), Secretaria Regional do Ambiente e Ação Climática (SRAA) of the Governo dos Açores, Climate Change Impacts, Adaptation and Modelling (CCIAM) of the Faculdade de Ciências da Universidade de Lisboa (FCUL), <a href="https://urldefense.com/v3/__https://snig.dgterritorio.gov.pt/rndg/srv/por/catalog.search*/metadata/8804acd9-9d0f-40fb-bc2e-e4dff8c2b4b1__;Iw!!D9dNQwwGXtA!SmILhnS0zICNt1ZcxuQ0VPP7VxtFeSEdLt4chAw8y5tsdlWqsgkyt9kESGhRu-00ZQqakzH36tvV-_DcQI7jGo-lOg$" target="_blank" rel="noopener">https://snig.dgterritorio.gov.pt/rndg/srv/por/catalog.search#/metadata/8804acd9-9d0f-40fb-bc2e-e4dff8c2b4b1</a></li> </ul> <p>This v2 includes metadata.</p>
Basic-ECVs for Case Studies (maps)
<p>Climate maps (raster layers .tif) of basic-ecvs with a spatial resolution of 5.5 km (1 km for Azores) obtained by statistically downscaling a set of CMIP6 simulations for different IPCC climate scenarios (historical, SSP1-2.6, SSP2-4.5, SSP5-8.5) and time horizons (reference, short time-horizon, medium time-horizon, long time-horizon). Data are representative of specific climate normals (yearly averaged values) and created by RethinkAction project.</p> <p>We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.</p> <p>Moreover, we acknowledge the Copernicus Climate Change Service (C3S) Climate Data Store (CDS) to provide access to CMIP6, CERRA, ERA5 and ERA5-Land data:</p> <ul> <li>Copernicus Climate Change Service, Climate Data Store, (2021): CMIP6 climate projections. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.c866074c.</li> <li>Schimanke S., Ridal M., Le Moigne P., Berggren L., Undén P., Randriamampianina R., Andrea U., Bazile E., Bertelsen A., Brousseau P., Dahlgren P., Edvinsson L., El Said A., Glinton M., Hopsch S., Isaksson L., Mladek R., Olsson E., Verrelle A., Wang Z.Q., (2021): CERRA sub-daily regional reanalysis data for Europe on single levels from 1984 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.622a565a</li> <li>Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D.,Thépaut, J-N. (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.adbb2d47 </li> <li>Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac </li> </ul> <p>Acknowledgement also to: </p> <ul> <li>DRAAC, 2023, Regional climate data provided by the Regional Ditectorate for the Environment and Climate Change of the Regional Autonomous Government of Azores (<a href="https://urldefense.com/v3/__https:/portal.azores.gov.pt/en/web/draac__;!!D9dNQwwGXtA!TAB9_FXZEEA4K_6AkmoIqX-krFMSiGcKRY--rOpV9psI98vjxa-sLAZQYR1s0G1fFmBrENoHHpZCdvP0s67vzss$" target="_blank" rel="noopener">https://portal.azores.gov.pt/en/web/draac</a>)</li> <li>SRAA\CCIAM, 2017. Programa Regional de Alterações Climáticas (PRAC), Secretaria Regional do Ambiente e Ação Climática (SRAA) of the Governo dos Açores, Climate Change Impacts, Adaptation and Modelling (CCIAM) of the Faculdade de Ciências da Universidade de Lisboa (FCUL), <a href="https://urldefense.com/v3/__https://snig.dgterritorio.gov.pt/rndg/srv/por/catalog.search*/metadata/8804acd9-9d0f-40fb-bc2e-e4dff8c2b4b1__;Iw!!D9dNQwwGXtA!SmILhnS0zICNt1ZcxuQ0VPP7VxtFeSEdLt4chAw8y5tsdlWqsgkyt9kESGhRu-00ZQqakzH36tvV-_DcQI7jGo-lOg$" target="_blank" rel="noopener">https://snig.dgterritorio.gov.pt/rndg/srv/por/catalog.search#/metadata/8804acd9-9d0f-40fb-bc2e-e4dff8c2b4b1</a></li> </ul> <p> </p> <p>This v2 includes metadata.</p>
W4RES Case studies of women leading RHC market uptake
<p>23 interviews were conducted with women (co-)leading or initiating RHC concepts in 8 different countries (IT, DK, EL, SK, AT, DE, BE, BG) that served as the background material for this dataset. Before conducting the interviews, the W4RES partners were asked to identify case studies based on: </p><p>• Structure of the organization</p><p>• Geographical outreach</p><p>• Visibility and interaction on social media</p><p>• Financial power</p><p>• Source of Renewable Energy</p><p>• Renewable Heating and Cooling concepts</p><p>It moreover entailed a scoring section in which the case studies were ranked according to:</p><p>• Technical innovation</p><p>• Social innovation</p><p>• Transferability</p><p>• Societal impact</p><p>• Political impact</p><p>• Market potential</p><p>• External communication</p><p>• Female leadership and influence</p><p>• Internal support measures for women</p><p>W4RES partners interviewed the female leaders and stakeholders in the organizations that ranked highest in the case study identification tables. These women were asked to reflect on the impact of their RHC solutions, the role of women in the organization, the support measures targeting women, as well as potential barriers and needs. The interview material was coded manually and collected in a synthesis matrix. This overview facilitates cross-case comparison and allows to see patterns for barriers and success factors.</p>
Is there a latitudinal diversity gradient for symbiotic microbes? A case study with sensitive partridge peas
<p><span>Mutualism is thought to be more prevalent in the tropics than temperate zones and may therefore play an important role in generating and maintaining high species richness found at lower latitudes. However, results on the impact of mutualism on latitudinal diversity gradients are mixed, and few empirical studies sample both temperate and tropical regions. We investigated whether a latitudinal diversity gradient exists in the symbiotic microbial community associated with the legume <em>Chamaecrista</em> <em>nictitans</em>. We sampled bacteria DNA from nodules and the surrounding soil of plant roots across a latitudinal gradient (38.64 °N to 8.68 °N). Using 16S rRNA sequence data, we identified many non-rhizobial species within <em>C. nictitans </em>nodules that cannot form nodules or fix nitrogen. Species richness increased towards lower latitudes in the non-rhizobial portion of the nodule community but not in the rhizobial community. The microbe community in the soil did not effectively predict the non-rhizobia community inside nodules, indicating that host selection is important for structuring non-rhizobia communities in nodules. We next factorially manipulated the presence of three non-rhizobia strains in greenhouse experiments and found that co-inoculations of non-rhizobia strains with rhizobia had a marginal effect on nodule number and no effect on plant growth. Our results suggest that these non-rhizobia bacteria are likely commensals – species that benefit from associating with a host but are neutral for host fitness. Overall, our study suggests that temperate <em>C. nictitans</em> plants are more selective in their associations with the non-rhizobia community, potentially due to differences in soil nitrogen across latitude.</span></p>
Fig. 8 in Meiofaunal Biodiversity In A Marine Protected Area: A Case Study In The Rocky And Sedimentary Shores Of The Snake Island (North-Western Black Sea)
Fig. 8. Plot of the non-metric multidimensional scaling (nMDS) based on the by Bray–Curtis similarity index for logarithmic values of meiobenthos taxa density in the recognized habitats of the Snake Island MPA (Black Sea).
Fig. 7 in Meiofaunal Biodiversity In A Marine Protected Area: A Case Study In The Rocky And Sedimentary Shores Of The Snake Island (North-Western Black Sea)
Fig. 7. Cluster analysis dendrogram based on meiobenthos density on the different habitats in MPA of the Snake Island (Black Sea).
Fig. 4 in Meiofaunal Biodiversity In A Marine Protected Area: A Case Study In The Rocky And Sedimentary Shores Of The Snake Island (North-Western Black Sea)
Fig. 4. The average density (N, means ± SE ind.·m–2) and biomass (B, means ± SE mg·m–2) of the total meiobenthos with contribution permanent and temporary taxa in the different habitats of the Snake Island MPA (Black Sea).
Fig. 3 in Meiofaunal Biodiversity In A Marine Protected Area: A Case Study In The Rocky And Sedimentary Shores Of The Snake Island (North-Western Black Sea)
Fig. 3. Meiobenthic community structure of different substrate types in the MB143 habitat of the Snake Island MPA (Black Sea).
Fig. 2 in Meiofaunal Biodiversity In A Marine Protected Area: A Case Study In The Rocky And Sedimentary Shores Of The Snake Island (North-Western Black Sea)
Fig. 2. The average density (N, means ± SE ind.·m–2) and biomass (B, means ± SE mg·m–2) of the total meiobenthos of different substrate types in the MB143 habitat of the Snake Island MPA (Black Sea).
Fig. 1 in Meiofaunal Biodiversity In A Marine Protected Area: A Case Study In The Rocky And Sedimentary Shores Of The Snake Island (North-Western Black Sea)
Fig. 1. The map-scheme of the study area near the Snake Island (north-western Ukrainian shelf of the Black Sea).
Fig. 6 in Meiofaunal Biodiversity In A Marine Protected Area: A Case Study In The Rocky And Sedimentary Shores Of The Snake Island (North-Western Black Sea)
Fig. 6. The contribution (%) of each meiobenthic taxon to the average density and biomass in the different habitats of the Snake Island MPA (Black Sea).
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.