Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,855
datasets available to search
ShareScore release 0.9.0
Dataset results
1,855 results for “Framework”
FIGURE 13 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 13. Transverse histologic section of the H-MOS Stage 2 Diplodocus sp. MOR 790 7-23-95-122 femur at 4x. MOR 790 7-23-95-122 is HOS 7 out of 13. No LAGs are present.
FIGURE 2 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 2. Schematic of coring bit method used in this analysis. A two part Bosch™ core bit (1) with a coin placed on the bone surface prior to coring (2), the core bit separated post coring, with a bolt inserted to push on the coin (3) to extract the bone core (4).
FIGURE 7 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 7. CT scans of diplodocid anterior dorsal vertebrae. 1, Diplodocus sp. MOR 790 8-21-95-238; 2, Diplodocus sp. MOR 592 8-22-90-15. Colored planes in 1 and 2 correspond to CT scan sections for each respective vertebrae. pfs = Pneumatic Fossa, cmr = Camera, cml = Camella (Wedel, 2003). Red = frontal plane through the centrum, Blue = transverse plane through the pfs.
FIGURE 16 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 16. Calculated body masses for the Morrison diplodocids Apatosaurus (1) and Diplodocus (2) using the formula of Mazzetta et al. (2004) (log Body Mass = 2.955 x log Femur Circumference − 4.166); 3, Dorsal rib LAG count vs. femur circumference for Diplodocus; 4, Femur length vs. femur circumference for Diplodocus; 5, Dorsal rib LAG count vs. body mass for Diplodocus with posterior cervical vertebrae marking each size range to illustrate the correlation between mass and spine morphology. Data for all diplodocid specimens can be found in Appendix 3.
FIGURE 1. Elements histologically sampled for this analysis. 1 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 1. Elements histologically sampled for this analysis. 1, Digital reconstruction of Apatosaurus louisae (by K. Stevens) with sampled elements highlighted in red. Approximate location of sampling in dorsal ribs (2; from Gilmore, 1936), neural spines (3; from Hatcher, 1901), and femora (4; from Gilmore, 1936).
FIGURE 12 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 12. Transverse histologic section of the H-MOS Stage 4 Diplodocus CM 94 (Diplodocus carnegii paratype) dorsal rib at 4x. CM 94 records a minimum of 24 LAGs (blue lines). Red insert box highlights the episodic zones of large (LDC) and small (SDC) diameter longitudinal vascular canals with white arrows denoting some of the LAGs present. Green insert box highlights the outermost cortex which records the presence of an EFS. White arrows denote LAGS present, with the EFS bracketed.
FIGURE 11 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 11. Transverse histologic section of the H-MOS Stage 3 Diplodocus sp. MOR 592 dorsal rib at 4x. MOR 592 records a minimum of eight LAGs (blue lines). Red insert box highlights the organization of longitudinal vascular canals in radial rows (alternating rows highlighted in blue). Green insert box highlights the vascularity patterns with white arrows denoting four of the LAGs present.
FIGURE 15 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 15. Selection of the diplodocid femoral dataset used throughout this ontogenetic analysis. Top row diplodocines, from left to right: CM 33991 (Diplodocus longus), CM 21788 (D. longus), CM 30762 (D. longus), MOR 790 7-5-97-7 (Diplodocus sp.), MOR 790 7-23-95-122 (Diplodocus sp.), MOR 592-35 (Diplodocus sp.), CM 21752 (Diplodocus sp.), SMA 0013 (Diplodocus sp.), CM 84 (D. carnegii); Bottom row apatosaurines, from left to right: AMNH 613 (Apatosaurus sp.), OMNH 1279 (Apatosaurus sp.), AMNH 606 (Apatosaurus sp.), MWC 5439 (Apatosaurus sp.), CM 21784 (A. louisae), CM 33997 (A. louisae), MOR 700 7-24-91-31 (Apatosaurus sp.), AMNH 353 (Apatosaurus sp.), SMA 0014 (Apatosaurus sp.), CM 85 (Apatosaurus sp.), MOR 857 7-16-92-30 (Apatosaurus sp.), MWC "Moffit Co. Apato." (Apatosaurus sp.). Scale bar equals 1 m. Note the colored line on CM 84 and MWC "Moffit Co. Apato." illustrate how femoral positions and trends were examined. Colored lines to the far right of each row indicate the general allometric changes of each femur scaled to the same length (Black line = femoral length). Diplodocus row: Yellow lines = MOR 790 7-5-97-7, Blue lines = MOR 592-35, Red lines = CM 84. Apatosaurus row: Green lines = AMNH 613, Yellow lines = CM 33997, Blue lines = MOR 700 7-24-91-31, Red lines = MWC "Moffit Co. Apato."
FIGURE 10 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 10. Transverse histologic sections of the H-MOS Stage 2 Diplodocus sp. 1, MOR 790 7-24-96-95 (10x) and 2, MOR 790 7-27-8-96 dorsal ribs (4x). 1, MOR 790 7-24-96-95 records a minimum of two annuli (blue lines). Red insert box highlights bone microstructure differences between the anterior intercostal ridge and lateral margins with longitudinal vascular canals. Green insert box highlights a sample of the segments that comprise one of the growth markers (an annulus, highlighted in blue). 2, MOR 790 7-27-8-96 records a minimum of six LAGs (blue lines; note some of these LAGs do extend past the demarcated blue lines). Red insert box highlights the microstructure and shows the vascularity patterns while the white arrows denote two of the LAGs present.
FIGURE 9 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 9. Coronal histologic sections of diplodocid posterior cervical and anterior dorsal vertebrae neural spines. 1, Posterior cervical Diplodocus sp. MOR 790 (un-numbered 1); 2, Anterior dorsal Diplodocus sp. MOR 790 8-21-95-238; 3, Posterior cervical Diplodocus sp. MOR 592 8-24-90-91; 4, Anterior dorsal Diplodocus sp. MOR 592 8-22-90-15. R.L. (right lateral), L.L (left lateral), M. (medial), L (lateral). Not to scale. Scale bar equals 1 cm.
FIGURE 8 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 8. CT scans of diplodocid posterior dorsal vertebrae. 1, Diplodocus sp. MOR 790 7-8-95-17; 2, Diplodocus sp. MOR 592 8-22-90-77; 3, Apatosaurus sp. MOR 957 6-29-92#1. Colored planes in 1, 2, and 3 correspond to CT scan sections for each respective vertebrae. pfs = Pneumatic Fossa, cmr = Camera, cml = Camella (Wedel, 2003). Red = frontal plane through the centrum, Blue = transverse plane through the pfs.
FIGURE 4 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 4. Presence of the Postparietal Aperture within Diplodocidea (indicated by red arrows). 1-4, Diplodocid specimens with the Postparietal Aperture: 1, Suuwassea (ANS 21122); 2, Galeamopus (SMA 0011); 3, Apatosaurus sp. (BYU 17096) (Balanoff, et al., 2010); 4, Kaatedocus (SMA 0004). Note 1 and 3 are dorsal views while 2 and 4 are posterior views. 5-6, Diplodocid skulls illustrating the presence of the Postparietal Aperture in immature individuals (5- image courtesy of the Science Museum of Minnesota), and its absence in mature individuals (6). For 5, from left to right: Kaatedocus (SMA 0004), Diplodocus sp. (SMM P. 84.15.3), Apatosaurus sp. (MOR 700), Galeamopus (SMA 0011; this skull is partially damaged, so the morphology of the foramen may be distorted), Suuwassea (ANS 21122), and Diplodocus sp. (MOR 592). For 6, note that the Diplodocus and Apatosaurus skulls are stylized renderings based on multiple specimens (from Whitlock [2011b]; Diplodocus sp. to scale of USNM 2672, and Apatosaurus louisae to CM 11162). Skulls in 5 and 6 to scale.
FIGURE 5 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 5. Macroscopic pneumatic architecture in diplodocid cervical vertebrae. 1, diplodocid indeterminate MOR 714 7-22-3-53; 2, Diplodocus sp. MOR 790 8-10-96-204; 3, D. carnegii CM 84 (from Hatcher, 1901). Increasing pneumatic complexity from 1 to 3. pfs = Pneumatic Fossa, acl = Accessory Lamina, pfm = Pneumatic Foramen (Wedel, 2003). Not to scale. Scale bar equals 10 cm.
FIGURE 19 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 19. An ontogenetic trajectory in consideration of morphologic and histologic attributes for the Morrison diplodocid Diplodocus. Note diplodocids, and possibly all other sauropods, did not skeletally develop along an isometric trajectory. Human scale bar is Dante Alighieri from Domenico di Michelino's "La commedia illumina Firenze", depicting Dante as 1.63 m tall. Modified silhouette of Diplodocus carnegii CM 84 by S. Hartman and available via PhyloPic under the Creative Commons Attribution-ShareAlike 3.0 Unported License.
FIGURE 3 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 3. Ontogenetic development of neural spine bifurcation in Morrison Formation sauropods. Apatosaurinae – represented by the immature individuals CM 555 (Apatosaurus excelsus or Brontosaurus excelsus) and CM 3390 (Apatosaurus sp.) compared to the mature 3018. Diplodocus – represented by the immature MOR 592 (Diplodocus sp.) compared to the mature CM 84 (Diplodocus carnegii). Camarasaurus – represented by the immature CM 11338 (Camarasaurus lentus) compared to the mature AMNH 5761 (Camarasaurus supremus). Barosaurus – represented by the immature AMNH 7535 compared to the mature AMNH 6341. Images not to scale. Scale bars equal 10 cm.
FIGURE 6 in A new multi-faceted framework for deciphering diplodocid ontogeny
FIGURE 6. CT scans of diplodocid anterior cervical vertebrae. 1, diplodocid indeterminate MOR 714 7-22-3-53; 2, Diplodocus sp. MOR 790 8-10-96-204. Colored planes in 1 and 2 correspond to CT scan sections for each respective vertebrae. pfs = Pneumatic Fossa, cmr = Camera (Wedel, 2003). Red = frontal plane through the centrum, Blue = transverse plane through the anterior portion of the pfs, Green = transverse plane through the posterior portion of the pfs. Ant = anterior; Pos = posterior.
Model intercomparison of medicane Ianos using ten mesoscale numerical frameworks
<p>The dataset provides numerical simulations of the high-impact medicane Ianos of September 2020. It is based on a collective effort with five mesoscale models to look for a robust response among ten numerical frameworks used in the community involved in the networking activity of the EU COST Action "MedCyclones" <a href="https://medcyclones.eu/">https://medcyclones.eu/</a></p> <p>The five mesoscale models are:</p> <ul> <li>The BOLAM hydrostatic model and the MOLOCH non-hydrostatic, fully compressible model developed at CNR-ISAC available upon request to <a href="mailto:dinamica@isac.cnr.it">dinamica@isac.cnr.it</a></li> <li>The Met Office Unified Model (MetUM) available for use under a closed licence agreement, further information at <a href="http://www.metoffice.gov.uk/research/modelling-systems/unified-model">http://www.metoffice.gov.uk/research/modelling-systems/unified-model</a></li> <li>The Meso-NH mesoscale non-hydrostatic model of the French research community freely available under CeCILL-C license agreement on <a href="http://mesonh.aero.obs-mip.fr">http://mesonh.aero.obs-mip.fr</a> with two variants included: <ul> <li>one run at Centre National de Recherches Météorologiques (MESONH-CNRM)</li> <li>one run at Laboratoire d’Aérologie (MESONH-LAERO)</li> </ul> </li> <li>The WRF (Weather Research and Forecasting) non-hydrostatic, fully compressible model freely available at <a href="https://github.com/wrf-model/WRF/releases">https://github.com/wrf-model/WRF/releases</a> with five variants included: <ul> <li>one run at the Aristotle University of Thessaloniki (WRF-AUTH)</li> <li>two run at CNR-ISAC (WRF-ISAC and WRF-ISAC-2)</li> <li>one run at the National Observatory of Athens (WRF-NOA)</li> <li>one run at the University of the Balearic Islands (WRF-UIB)</li> </ul> </li> </ul> <p>Four sets of simulations are provided:</p> <ul> <li>Control simulations obtained by initialising the models at 00 UTC on 15 September 2020 and using 6-h operational analyses from the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) as initial and lateral boundary conditions. The horizontal grid spacing is set to 10 km, which approximately matches the resolution of IFS analyses and requires parameterization of deep convection.</li> <li>A first sensitivity test obtained by initialising the models 12 h earlier at 12 UTC on 14 September 2020.</li> <li>A second sensitivity test obtained by using ECMWF Reanalysis v5 (ERA5), which provides higher frequency (hourly) but lower spatial resolution (about 30 km), as initial and lateral boundary conditions.</li> <li>A third sensitivity test obtained by setting the horizontal grid spacing to 2 km, which allows explicit representation of deep convection.</li> </ul> <p>The model output is stored every 3 h until 00 UTC 20 September 2020 and interpolated onto the same regular 0.1°×0.1° horizontal grid and pressure levels. The data files are formatted in Network Common Data Form (NetCDF) and named <strong>runs_ILBC_DDHH_RES.nc</strong> where</p> <ul> <li><strong>ILBC</strong> describes the initial and lateral boundary conditions (IFS or ERA5) </li> <li><strong>DDHH</strong> describes the initial day and hour (1500 or 1412) </li> <li><strong>RES</strong> describes the horizontal grid spacing (10 or 2 km)</li> <li>simulated infrared brightness temperatures are provided in extra files with <strong>RTTOV</strong> suffix for five of the models and variants</li> </ul>
A parametric life cycle framework to promote sustainable-by-design product development: Application to a hydrogen production technology
<p>The European Ecodesign Directive is an effective normative framework that has been extensively proven to support the energy transition of numerous European industrial sectors. From an analytical standpoint, it provides practitioners with the EcoReport tool, a simplified life cycle spreadsheet that is aimed at guiding the development of ecodesign measures of mandatory compliance in European countries. In this regard, several studies have highlighted the limitations of the EcoReport tool when addressing emerging technologies like those tied to the hydrogen sector. These works also propose to further integrate material criticality and social metrics in order to enlarge the scope of the European Directive and foster the shift from ecodesign to sustainable-by-design product development. In this situation, building upon the principles of the EcoReport tool and recognizing the outcomes of the aforementioned critical analyses, the conceptualization of a novel sustainable-by-design framework is presented and applied to a Solid Oxide Electrolysis Cell (SOEC) stack for hydrogen production. The operationalization of the framework is conducted, for the first time in the context of sustainable design, by combining the use of the <em>Brightway2</em> and <em>lca_algebraic</em> Python packages. Overall, the proposed approach succeeds in providing a complete sustainability perspective to the design of emerging technologies. Regarding the tangible lessons learned on the hydrogen-related case study, product concepts are proven to progressively improve the sustainability performance of the technology. It is noticeable that the enhancement of the economic competitivity is more limited than that achieved at the remaining sustainability indicators (i.e., environmental, social and material criticality metrics). In line with the outcomes of the life cycle contribution assessment, multi-criteria decision analysis ratings lead to concluding that a sustainable-by-design SOEC stack product concept should prioritize limiting its material intensity.</p>
Framework for the Supply-side Food self-sufficiency ratio (SSFSSR)
<p><span>The SSFSSR is<span> <strong> </strong></span><strong>a method of calculating Food self-sufficiency Ratio (FSSR) by considering food from the point it enters the supply chain after harvest until it is consumed.</strong> It thus incorporates the stages of post-harvest, storage, import, and export. Most food in these stages is in the form of primary products, with some being processed into secondary products, such as livestock products, edible oils, sugar products, and juices, which undergo compositional changes. The SSFSSR automatically accounts for the quantitative loss of food due to spoilage, waste, rodent damage, and attrition during processing after harvest. <strong>The conventional methods of the FSSR excludes the calories of primary products used as intermediate inputs, such as livestock feed and raw materials for edible oils, as well as losses</strong>, spoilage, waste, rodent damage, and attrition during processing from the post-harvest stage until human consumption.</span></p>
Data for The Design and Formalization of an Embodied Soundscape Sonification Framework
<p>This repository contains evaluation data ane experimental stimuli for the paper :The Design and Formalization of an Embodied Soundscape Sonification Framework.</p>
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.