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51 results for “research computing”
Data from: The appropriateness of language found in research consent form templates: a computational linguistic analysis
Background: To facilitate informed consent, consent forms should use language below the grade eight level. Research Ethics Boards (REBs) provide consent form templates to facilitate this goal. Templates with inappropriate language could promote consent forms that participants find difficult to understand. However, a linguistic analysis of templates is lacking. Methods: We reviewed the websites of 124 REBs for their templates. These included English language medical school REBs in Australia/New Zealand (n=23), Canada (n=14), South Africa (n=8), the United Kingdom (n=34), and a geographically-stratified sample from the United States (n=45). Template language was analyzed using Coh-Metrix linguistic software (v.3.0, Memphis, USA). We evaluated the proportion of REBs with five key linguistic outcomes at or below grade eight. Additionally, we compared quantitative readability to the REBs' own readability standards. To determine if the template's country of origin or the presence of a local REB readability standard influenced the linguistic variables, we used a MANOVA model. Results: Of the REBs who provided templates, 0/94 (0%, 95% CI=0-3.9%) provided templates with all linguistic variables at or below the grade eight level. Relaxing the standard to a grade 12 level did not increase this proportion. Further, only 2/22 (9.1%, 95% CI= 2.5-27.8) REBs met their own readability standard. The country of origin (DF= 20, 177.5, F=1.97, p=0.01), but not the presence of an REB-specific standard (DF=5, 84, F=0.73, p=0.60), influenced the linguistic variables. Conclusions: Inappropriate language in templates is an international problem. Templates use words that are long, abstract, and unfamiliar. This could undermine the validity of participant informed consent. REBs should set a policy of screening templates with linguistic software.
Experimental signals and processed data used in the research work "On-chip phonon-magnon reservoir for neuromorphic computing"
<p>The data set includes the raw experimental data, processed experimental data, and numerically modeled dependencies in the respective folders:</p><p>The raw experimental data (magnon readout, as measured) are given for all processed signals presented in the respective figures (folders 'Figure2', 'Figure3' and 'Sup Figure1') and used for the ANN training (folder '3x3Sets & AugmentedVisualShapes'). </p><p>The signals presented in the folders '\3x3Sets & AugmentedVisualShapes\3x3SET##' are named following the scheme shown in Fig. 3a. The signals in the folder \3x3Sets & AugmentedVisualShapes\RandomizedShapes' are simulated using the procedure described in the Methods section as "Drawing of randomized visual shapes". The sets of calculated statistical parameters used for the shapes' recognition are in the folder ''\3x3Sets & AugmentedVisualShapes\Parameters'</p><p>The waveforms for the trajectories formed by randomly selected 4, 5, 6, and 7 discrete positions and their statistical parameters are presented in the corresponding folder. </p>
Data from Wilson et al.: Applying computer vision to digitised natural history collections for climate change research: temperature-size responses in British butterflies
<p>This dataset supports the publication: Wilson et al. "Applying computer vision to digitised natural history collections for climate change research: temperature-size responses in British butterflies". These are the data used for the data figures (Fig 3-6, SI Figs 1-2) and the supplementary information tables.</p>
Kaisa Helminen is CEO of Fimmic Oy, a Finnish company that created the first commercial tool integrating deep learning and computer vision for pathology research. Photograph: Sebastian Mardones / Health Capital Helsinki. in Deep learning brings speed, accuracy to the life sciences.
Kaisa Helminen is CEO of Fimmic Oy, a Finnish company that created the first commercial tool integrating deep learning and computer vision for pathology research. Photograph: Sebastian Mardones / Health Capital Helsinki.
Data from: Computational research on mobile pastoralism using agent-based modeling and satellite imagery
Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level.
Experimental and Computational data related to research on ``Investigating the Electronic Structure of Prospective Water-splitting Oxide BaCe0.25Mn0.75O3−δ Before and After Thermal Reduction''
<p>Data files and gnuplot scripts for the figures included in the submission titled ``<strong>Investigating the Electronic Structure of Prospective Water-splitting Oxide BaCe<sub>0.25</sub>Mn<sub>0.75</sub>O<sub>3−δ </sub>Before and After Thermal Reduction''</strong></p>
A Research Study to Understand and Predict the Failure of Shoulder Fracture Fixations Using Computer Simulations
ClinicalTrials.gov study NCT04056351. IPD Sharing: NO. Countries: 2. Publications: 2.
Data from: The appropriateness of language found in research consent form templates: a computational linguistic analysis
Open the record for dataset details and reuse information.
Data from: X-ray computed tomography and its potential in ecological research: a review of studies and optimization of specimen preparation
Open the record for dataset details and reuse information.
Data from: Computational research on mobile pastoralism using agent-based modeling and satellite imagery
Open the record for dataset details and reuse information.
Figure 1 from: Conte M, Flynn AJ, Barrison P, Boisvert P, Landis-Lewis Z, Friedman C (2023) Digital objects to make computable biomedical knowledge FAIR: an infrastructural approach to knowledge representation, dissemination and implementation. Research Ideas and Outcomes 9: e109307. https://doi.org/10.3897/rio.9.e109307
Figure 1 Conceptual model of a Knowledge Object (KO) containing a payload, machine-actionable service and deployment specifications, metadata and a unique persistent identifier. We are exploring aligning our conceptual model with emerging best practices for FAIR Digital Objects. Derived from Wittenburg et al's Digital Objects as Drivers towards Convergence in Data Infrastructures (Wittenburg et al. 2019).
Figure 3 from: Conte M, Flynn AJ, Barrison P, Boisvert P, Landis-Lewis Z, Friedman C (2023) Digital objects to make computable biomedical knowledge FAIR: an infrastructural approach to knowledge representation, dissemination and implementation. Research Ideas and Outcomes 9: e109307. https://doi.org/10.3897/rio.9.e109307
Figure 3 This figure illustrates the dual nature of Knowledge Objects: knowledge-as-resource and knowledge-as-service. A KO can be curated and maintained in a repository, pass metadata to a knowledge graph or deployed into applications. Different to other digital objects, the methods to deploy the KO to applications via custom or generic runtimes called by microservices are built into the KO.
Figure 2 from: Conte M, Flynn AJ, Barrison P, Boisvert P, Landis-Lewis Z, Friedman C (2023) Digital objects to make computable biomedical knowledge FAIR: an infrastructural approach to knowledge representation, dissemination and implementation. Research Ideas and Outcomes 9: e109307. https://doi.org/10.3897/rio.9.e109307
Figure 2 (L) Sample KO as viewed from the KGrid Library, from which the KO can be implemented in a hosted runtime environment or downloaded. (R) Sample output results from deploying the KO.
Appendix to the paper titled: Which teamwork challenges do computing students face in a project-based learning course in research methods?
<p>Instructions on reflection reports, interview guide, and example student projects.</p>
Figure 5 from: Schmitt M, Uhl G (2015) Functional morphology of the copulatory organs of a reed beetle and a shining leaf beetle (Coleoptera: Chrysomelidae: Donaciinae, Criocerinae) using X-ray micro-computed tomography. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 5. ZooKeys 547: 193–203. https://doi.org/10.3897/zookeys.547.7143
Figure 5 - Donacia semicuprea. Volume rendering of the virtual sections – sagittal, right to the median – through the abdomina of a mating pair. The opening of the bursa copulatrix (circle) is armed with a conspicuous ring muscle. C: the compound muscle inserting at the manubrium and extending to the lateral rims of the basal orifice of the median lobe; M: median lobe; P: paramere.
Figure 1 from: Schmitt M, Uhl G (2015) Functional morphology of the copulatory organs of a reed beetle and a shining leaf beetle (Coleoptera: Chrysomelidae: Donaciinae, Criocerinae) using X-ray micro-computed tomography. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 5. ZooKeys 547: 193–203. https://doi.org/10.3897/zookeys.547.7143
Figure 1 - Schematic drawing of the sclerotised part of a Donaciinae aedeagus. The given terms of orientation do not refer to the position within the male abdomen nor within the female during copulation since these structures are rotated during mating. The median lobe is shaded grey. Paramere, tegminal ring and manubrium compose the tegmen.
Figure 6 from: Schmitt M, Uhl G (2015) Functional morphology of the copulatory organs of a reed beetle and a shining leaf beetle (Coleoptera: Chrysomelidae: Donaciinae, Criocerinae) using X-ray micro-computed tomography. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 5. ZooKeys 547: 193–203. https://doi.org/10.3897/zookeys.547.7143
Figure 6 - Donacia semicuprea, Volume rendering of ca. 390 virtual sections – sagittal, paramedian, tilted to the right – through the abdomina of a mating pair. The bursa is elongate, as seen from the proximal wall (arrow). The yellow shining areas inside the female abdomen are parts of the left ovary. P: paramere.
Figure 3 from: Schmitt M, Uhl G (2015) Functional morphology of the copulatory organs of a reed beetle and a shining leaf beetle (Coleoptera: Chrysomelidae: Donaciinae, Criocerinae) using X-ray micro-computed tomography. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 5. ZooKeys 547: 193–203. https://doi.org/10.3897/zookeys.547.7143
Figure 3 - Lilioceris lilii, copulating pair. Volume rendering of the virtual sections right to the median, digitally stained. The terminal part of the spermathecal duct can be seen immediately left to the bursa wall. The shape of the bursa is nearly globular. B: bursa copulatrix; C: the compound muscle inserting at the manubrium and extending to the lateral rims of the basal orifice of the median lobe; E: endophallus; M: median lobe.
Figure 2 from: Schmitt M, Uhl G (2015) Functional morphology of the copulatory organs of a reed beetle and a shining leaf beetle (Coleoptera: Chrysomelidae: Donaciinae, Criocerinae) using X-ray micro-computed tomography. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 5. ZooKeys 547: 193–203. https://doi.org/10.3897/zookeys.547.7143
Figure 2 - Lilioceris lilii. Virtual section – sagittal, median - through the abdomina of a mating pair. The endophallus is fully inflated (2a), the flagellum is positioned over the opening of the spermathecal duct (2b).
Figure 4 from: Schmitt M, Uhl G (2015) Functional morphology of the copulatory organs of a reed beetle and a shining leaf beetle (Coleoptera: Chrysomelidae: Donaciinae, Criocerinae) using X-ray micro-computed tomography. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 5. ZooKeys 547: 193–203. https://doi.org/10.3897/zookeys.547.7143
Figure 4 - Lilioceris lilii, as Fig. 3, the opening of the bursa copulatrix and the adjacent part of the bursa wall (circle) do not show significant muscle layers but are mere membranes. B: bursa copulatrix; M: median lobe.
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.