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1,048 results for “interpreting”
FIGURE 2. A Neigbour Net constructed from uncorrected P in Taraxacum sect. Orientalia (Compositae-Crepidinae) and the West Himalayan dandelions: A new interpretation
FIGURE 2. A Neigbour Net constructed from uncorrected P-distances in SplitsTree based on nrDNA ITS sequences of sexual dandelions of 24 sections. The position of the new T. sect. Squamulosa is marked dark grey.
FIGURE 1. A in Taraxacum sect. Orientalia (Compositae-Crepidinae) and the West Himalayan dandelions: A new interpretation
FIGURE 1. A detail of the characteristic achene squamulosity in T. section Squamulosa. T. persquamulosum (G. Miehe & S. Miehe 2606, no. det. 28118). Structures that appear to be long spinules are in fact broad squamules in side view.
Data and code: Local hydroclimate alters interpretation of speleothem 𝛿18O records
<p>This repository contains PCP-corrected d18O records for stalagmite HH-1, rainfall isotope data from Phong Nha Ke Bang National Park, and code to conduct PCP correction analyses presented and used in E.W. Patterson et al., "Local hydroclimate alters interpretation of speleothem 𝛿18O records". The data can be used to replicate figures and analyses presented in the main text. The O'neil correction was primarily used for analyses in the publication.</p>
Rapid Flood Simulation and Source Area Identification in Urban Environments via Interpretable Deep Learning
<p>Here is the data and original code for the paper titled <em>Rapid Flood Simulation and Source Area Identification in Urban Environments via Interpretable Deep Learning</em>. If you have any questions, please contact <a rel="noopener">202331470015@mail.bnu.edu.cn</a>.</p>
Dataset for the paper 'Predicting mechanical properties of polycrystalline nanopillars by interpretable machine learning'
<div> <div>This dataset contains the data produced for the above paper. The dataset consists of:</div> <div> </div> <div>- input nanopillars before deformation (molecular_dynamics/nanopillars)</div> <div>- stress-strain curves acquired by deforming the nanopillars (molecular_dynamics/stress_strain_curves)</div> <div>- weights of the CNNs trained to predict mechanical properties of the nanopillars (machine_learning/train_CNN)</div> <div>- Grad-CAM fields of the predictions (machine_learning/train_CNN)</div> <br> <div>Codes used for creating and analyzing the dataset are available at https://github.com/tekoivisto/nanopillar-ML</div> </div>
Rapid Flood Simulation and Source Area Identification in Urban Environments via Interpretable Deep Learning
<p>Here are the relevant data and preliminary code for the paper titled 'Rapid Flood Simulation and Source Area Identification in Urban Environments via Interpretable Deep Learning' for your reference. If you have any questions, please contact <a rel="noopener">202331470015@mail.bnu.edu.cn</a>.</p>
Dataset from literature review of the paper "A Classification and Interpretation of Methodological Approaches to Pursue Natural Capital Valuation in Forest Research"
<p>This is a dataset of papers used for the analysis of the literature review of the paper "A Classification and Interpretation of Methodological Approaches to Pursue Natural Capital Valuation in Forest Research". The paper was acceped in the FORESTS Journal on 25th September 2024. </p> <p> The papers selected for the review were collated in a spreadsheet and coded using an inductive approach by considering the goals, methods, and typologies of natural capital (NC) approaches implemented in each case study. We have formulated a subjective classification of NC approaches that suits the reviewed case studies and builds on the knowledge summarised in the guidance suite “Enabling a Natural Capital Approach” (ENCA), produced by the UK Gov to help policy and decision makers when considering NC values.</p> <p>Codes used, as reported in the Excel file, are the following:</p> <ol> <li> Authors 2. Title of the publication 3. Journal/book 4. Goal<br>5. Methods 6. Details of the methods 7. NC approach classification 8. Provisioning services 9. Regulating services 10. Cultural services Location 11. Payment for ecosystem services 12. Country 13. Location 14. Policy goal 15. Theme </li> </ol> <p> </p> <p> </p> <p> </p>
Appendix A for the paper title : ArtInsight: A Multimodal AI Framework for Interpreting Children's Drawings and Enhancing Emotional Understanding
<p> Appendix A in this paper includes the specific prompt used for annotating the children's drawings with ChatGPT. This prompt was meticulously designed to ensure that the AI generated consistent and relevant descriptions and assessment reports for each image. The prompt guides the AI to focus on several key areas:</p> <ul> <li><strong>Description of the Artwork</strong>: Encouraging a detailed observation of the visual elements in the drawing, such as colors, shapes, figures, and any notable features.</li> <li><strong>Psychological Interpretation</strong>: Guiding the AI to interpret the possible emotional and psychological themes represented in the artwork based on the visual cues.</li> <li><strong>Possible Emotional Themes</strong>: Identifying underlying emotions or feelings that the child might be expressing through their drawing.</li> <li><strong>Recommended Interventions</strong>: Suggesting appropriate actions or conversations that therapists, educators, or parents could initiate to support the child's emotional well-being.</li> </ul>
Data associated with interpretable_gmms
<p>Data associated with the GitHub repo: <a href="https://github.com/arpit-omprakash/interpretable_gmms">https://github.com/arpit-omprakash/interpretable_gmms</a> for reproduction of analysis and figures from Omprakash et. al. (in prep.)</p> <p>Unzip the file provided here, and place the 'resources' folder in the base directory of the GitHub code.</p>
Data from: Interpreting and predicting the spread of invasive wild pigs
The eruption of invasive wild pigs (IWPs) Sus scrofa throughout the world exemplifies the need to understand the influences of exotic and non-native species expansions. In particular, the continental USA is precariously threatened by a rapid expansion of IWPs, and a better understanding of the rate and process of spread can inform strategies that will limit the expansion. We developed a spatially and temporally dynamic model to examine three decades (1982–2012) of IWP expansion, and predict the spread of IWPs throughout the continental USA, relative to where IWPs previously inhabited. We used the model to predict where IWPs are likely to invade next. The average rate of northward expansion increased from 6.5 to 12.6 km per year, suggesting most counties in the continental USA could be inhabited within the next 3–5 decades. The spread of IWPs was primarily associated with expansion into areas with similar environmental characteristics as their previous range, with the exception of spreading into colder regions. We identified that climate change may assist spread into northern regions by generating milder winters with less snow. Otherwise, the spread of IWPs was not dependent on agriculture, precipitation, or biodiversity at the county level. The model correctly predicted 86% of counties that were invaded during 2012, and those predictions indicate that large portions of the USA are in immediate danger of invasion. Synthesis and applications. Anti-invasion efforts should focus along the boundaries of current occupied range to stop natural expansion, and anti-invasion policies should focus on stopping anthropogenic transport and release of invasive wild pigs (IWPs). Our results demonstrate the utility of a spatio-temporal examination to inform strategies for limiting the spread of IWPs.
A New Model of Interpretation and Communication for Ensemble Music-Making - Appendices
<p>Appendices for Music Ph.D</p>
FIGURE 5 in New interpretation of the Ranunculus cornutus-R. marginatus complex (Ranunculaceae)
FIGURE 5. Schematic drawing of Ranunculus achenes, side view: 1) R. marginatus var. trachycarpus from Turkey; 2) R. cornutus var. cornutus from Syria 3) R. cornutus var. scandicinus from Israel 4) R. cornutus var. leiocarpus from Azerbaijan. Author's illustration.
FIGURE 1 in New interpretation of the Ranunculus cornutus-R. marginatus complex (Ranunculaceae)
FIGURE 1. Ranunculus cornutus var. cornutus epitype specimen, showing dissected leaves and long-beaked, winged achenes (SYRIA, about Aleppo, M. Zohary, 3.V.1931 [HUJ])
FIGURE 2 in New interpretation of the Ranunculus cornutus-R. marginatus complex (Ranunculaceae)
FIGURE 2. Middle leaves of R. cornutus var. scandicinus. A—First degree dissection, leaf deeply divided into three lobes (ISRAEL (then Palestine), Wadi Musrara, Eig, Zohary and Feinbrun 2 May 1926 [HUJ]). B—Second degree dissection, leaf divided three lobes, each lobe deeply dissected into three trilobed lobules; plant from the same population as in A. C—Third degree dissection, leaf divided into three lobes, each lobe divided into three lobules and lobules are deeply dissected (ISRAEL, Hula Valley, Beldinger 19.May1953 [HUJ]). Drawings by Tom Fogel
FIGURE 4 in New interpretation of the Ranunculus cornutus-R. marginatus complex (Ranunculaceae)
FIGURE 4. Specimen of Ranunculus marginatus var. trachycarpus, demonstrating simple, trilobed but undissected leaves (TURKEY, Antalya Province, near site of Arlan Lake, 30 May 1988. Zearzty & Atkins [HUJ]).
FIGURE 3 in New interpretation of the Ranunculus cornutus-R. marginatus complex (Ranunculaceae)
FIGURE 3. Herbarium specimen of R. cornutus var. scandicinus, showing dissected leaves and short-beaked achenes (ISRAEL [then Palestine], Athlit, 2 May 1935, R. Aaronsohn and Laurent-Täckholm, [AAR])
FIGURE 3 in Holotypes for three Caspian gastropods of the family Hydrobiidae tracked down description and taxonomic interpretations
FIGURE 3. (a, b) Laevicaspia derzhavini (Logvinenko & Starobogatov, 1969), holotype, locality 21 (ZIN 1/534-2021). (c–f) L. derzhavini, three paratypes, locality 21 (ZIN 2/534-2021 (c, d) and ZIN 3/534-2021 (e, f)). Images of one specimen (e and f) reproduced after Anistratenko et al. 2021. Scale bar = 1 mm.
FIGURE 5 in A new species of Euprox (Cervidae, Artiodactyla) from the upper Miocene of the Linxia Basin, Gansu Province, China, with interpretation of its paleoenvironment
FIGURE 5. Antlers of Euprox grandis sp. nov. (V 20081.1-2) a, V 20081.1, left antler, anterior view; b, V 20081.2, right antler, posterior view; scale bar equals 5 cm.
FIGURE 8 in A new species of Euprox (Cervidae, Artiodactyla) from the upper Miocene of the Linxia Basin, Gansu Province, China, with interpretation of its paleoenvironment
FIGURE 8. Phylogenetic relationships of Euprox within Muntiacinae and relevant taxa (Lucentia excluded). Most parsimony tree (L = 47; CI = 0.787; RI = 0.767) with nodes numbers. Bootstrap value figure in brackets under the clade.
FIGURE 2 in A new species of Euprox (Cervidae, Artiodactyla) from the upper Miocene of the Linxia Basin, Gansu Province, China, with interpretation of its paleoenvironment
FIGURE 2. Skull of Euprox grandis sp. nov. (V 20080.1, holotype). a, dorsal view; b, lateral view; c, ventral view; scale bar equals 5 cm; the dash line shows the orientation of the pedicle ridge.
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.