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1,855 results for “Framework”

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zenodo32/100

FIGURE 1 in A review of growth form and plant duration (life cycle) in Kalanchoe (Crassulaceae subfam. Kalanchooideae) in an evolutionary and classificatory framework

FIGURE 1. Kalanchoes are variously annual or perennial succulents that survive the dry season and droughts predominantly through accumulating water in their leaves. The small-shrubby Kalanchoe pumila is shown here. Photograph: Gideon F. Smith.

opennotspecifiedApr 2023View details →
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FIGURE 2. Only a in A review of growth form and plant duration (life cycle) in Kalanchoe (Crassulaceae subfam. Kalanchooideae) in an evolutionary and classificatory framework

FIGURE 2. Only a few species of Kalanchoe, such as the multiannual K. crouchii, develop thickened roots. Photograph: Gideon F. Smith.

opennotspecifiedApr 2023View details →
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FIGURE 9. A in A review of growth form and plant duration (life cycle) in Kalanchoe (Crassulaceae subfam. Kalanchooideae) in an evolutionary and classificatory framework

FIGURE 9. A very dense stand of Kalanchoe lanceolata here constituting a virtual monoculture in the deep shade under the nearly closed canopy of bushveld (savanna) trees in western North West province, South Africa. Here the veld has been disturbed by heavy grazing by large game. Photograph: Gideon F. Smith.

opennotspecifiedApr 2023View details →
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FIGURE 15 in A review of growth form and plant duration (life cycle) in Kalanchoe (Crassulaceae subfam. Kalanchooideae) in an evolutionary and classificatory framework

FIGURE 15. Plants of Kalanchoe crenata are herbaceous-stemmed and develop into shrubby, multi-branched plants. Photograph: Gideon F. Smith.

opennotspecifiedApr 2023View details →
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FIGURE 21 in A review of growth form and plant duration (life cycle) in Kalanchoe (Crassulaceae subfam. Kalanchooideae) in an evolutionary and classificatory framework

FIGURE 21. Virtually all plant parts of Kalanchoe tomentosa are densely tomentose. Photograph: Gideon F. Smith.

opennotspecifiedApr 2023View details →
zenodo32/100

Dataset for the paper "Oxygen reduction reaction activity in non-precious single atom (M-N/C) catalysts – contribution of metal and carbon/nitrogen framework-based sites", 2023, ACS Catalysis, DOI:10.1021/acscatal.3c00356

<p>The data in this spreadsheet was used to produce the figures in the paper</p> <p>Authors:Mengjun Gong, Asad Mehmood, Basit Ali, Kyung-Wan Nam and Anthony Kucernak</p> <p>Title:Oxygen reduction reaction activity in non-precious single atom (M-N/C) catalysts &ndash; contribution of metal and carbon/nitrogen framework-based sites</p> <p>Journal:ACS Catalysis</p> <p>DOI:10.1021/acscatal.3c00356</p> <p>Please cite the above reference if you wish to use this data</p> <p>DOI of data:10.5281/zenodo.7879881</p>

opencc-by-4.0Apr 2023View details →
zenodo32/100

Information Management Standards and Frameworks

<p>List of&nbsp;Information Management Standards and Frameworks.</p>

opencc-by-4.0May 2023View details →
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Dataset from: A lightweight framework for chromatin loop detection at the single-cell level

<p>This dataset includes the following components:</p> <ul> <li>Loops identified by scGSLoop at the single-cell level on the mES dataset and the hPFC dataset</li> <li>Consensus loops of each cell type.&nbsp;These consensus loops are derived from the single-cell results and represent the common loops shared across the cells of a particular cell type.</li> </ul> <p>&nbsp;</p>

opencc-by-4.0May 2023View details →
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Supplementary data as part of the article "Comparing the reaction profiles of single-iron catalytic sites in enzymes and in reticular frameworks for methane-to-methanol oxidation" (https://doi.org/10.1016/j.xcrp.2023.101422)

<p>Cartesian coordinates in the *.XYZ format for all the structures optimized at the M06-L/def2-TZVP&nbsp;in the reactivity study as part of the article &quot;Comparing the reaction profiles of single-iron catalytic sites in enzymes and in reticular frameworks for methane-to-methanol oxidation&quot; (<a href="https://doi.org/10.1016/j.xcrp.2023.101422">https://doi.org/10.1016/j.xcrp.2023.101422</a>)</p>

opencc-by-4.0Jun 2023View details →
zenodo32/100

MHD/PSD data: Simulation of Radiation Belt Wave-Particle Interactions in an MHD-particle Framework

<p>MHD and phase space density simulation results.</p>

opencc-by-4.0Jun 2023View details →
zenodo32/100

Material Suplementar - Identifying Requirements for a Multimodal User Experience Evaluation Framework for Interactive Web Systems

<p>Esta planilha cont&eacute;m o detalhamento do processo de codifica&ccedil;&atilde;o realizado&nbsp;para a identifica&ccedil;&atilde;o dos requisitos apresentado no artigo &quot;<em>Identifying Requirements for a Multimodal User Experience Evaluation Framework for Interactive Web Systems</em>&quot;.&nbsp;Este artigo est&aacute; submetido no&nbsp;XXIX Simp&oacute;sio Brasileiro de Sistemas Multim&iacute;dia e Web (WebMedia).</p> <p>A primeira aba da planilha&nbsp;cont&eacute;m os trechos dos artigos&nbsp;que geraram os c&oacute;digos e os respectivos requisitos. A segunda aba mostra&nbsp;o agrupamento dos c&oacute;digos similares para definir o conjunto de requisitos.</p>

opencc-by-4.0Jun 2023View details →
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Inputs, output and animation files related to the article titled "A computational framework for crack propagation along contact interfaces and surfaces under load" submitted to CMAME.

<p>Here you can find input mesh files, parameter files, output files and animations for numerical examples considered in the paper entitled &quot;A computational framework for crack propagation along contact interfaces and surfaces under load&quot; submitted to Computer Methods in Applied Mechanics and Engineering.</p>

opencc-by-4.0Feb 2023View details →
zenodo32/100

Data set for Chemical bond analysis for the entire periodic table: Energy Decomposition and Natural Orbitals for Chemical Valence in the Four-Component Relativistic Framework

<p>Data related with the publication :Chemical bond analysis for the entire periodic table:<br> Energy Decomposition and Natural Orbitals for Chemical Valence in the Four-Component Relativistic Framework by&nbsp;Diego Sorbelli, Paola Belanzoni,&nbsp;Loriano Storchi, Olivia Bizzarri, Beatrice Bizzarri, Edoardo Mosconi&nbsp;and Leonardo Belpassi</p> <p>Input and data for:</p> <p>Tab.1 --&gt; data in dir &quot;w_dimer_AVDZ&quot; and in dir &quot;ADF/w_dimer&quot;.</p> <p>Tab.2 --&gt; data in dir &quot;Agalkyne&quot; and in dir &quot;ADF/Agalkyne&quot;</p> <p>Tab.3 --&gt; data in dir &quot;TMC05ethene&quot;<br> &nbsp;</p>

opencc-by-4.0Jun 2023View details →
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A federated learning framework based on transfer learning and knowledge distillation for targeted advertising-Click-Through Rate Prediction Dataset

<p>https://www.kaggle.com/c/avazu-ctr-prediction</p>

opencc-by-4.0Jun 2023View details →
zenodo32/100

Data and codes for Landslide hazard spatiotemporal modelling: a unified and data-driven framework

<p>Data and codes for Landslide hazard spatiotemporal modelling: a unified and data-driven framework</p>

opencc-by-4.0Jul 2023View details →
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Data used in "A novel response priority framework for an urban coastal catchment using global weather forecasts-based improved flood risk estimates"

<p>The datasets used in&nbsp;&quot;A novel response priority framework for an urban coastal catchment using global weather forecasts-based improved flood risk estimates&quot; have been provided as rar files. Further details and instructions are provided in readme.txt in each folder of the rar file.</p>

opencc-by-4.0Jul 2023View details →
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Human Phenotype Ontology: Standardized Framework Cataloging Comprehensive Phenotypic Information

<p><strong>ABSTRACT:</strong></p> <p>The Human Phenotype Ontology (HPO) is a standardized and comprehensive framework that catalogs and organizes phenotypic information related to human diseases and genetic disorders. It provides a structured vocabulary of terms to describe observable traits and abnormalities associated with various medical conditions. This dataset showcases the Human Phenotype Ontology (HPO) by including HPO IDs, names, descriptions, and additional references. The HPO IDs serve as unique identifiers for specific phenotypes. The names provide concise labels for the phenotypic traits, while the descriptions offer detailed explanations of their characteristics. In addition to the essential information, the dataset includes references that further describe and support the understanding of diverse phenotypes. These references can be used to explore the scientific literature, studies, or clinical resources associated with each phenotype. By combining HPO IDs, names, descriptions, and references, the dataset offers a comprehensive overview of different phenotypes, facilitating research, diagnostics, and the exploration of genotype-phenotype relationships.</p> <p><strong>Instructions</strong>:</p> <p>The data was downloaded as an .obo file then converted to a .csv file. Unrelated columns were removed and a references column was added.&nbsp;</p> <p><strong>Acknowledgements</strong>:</p> <p><a>Sebastian K&ouml;hler</a>,&nbsp;<a>Michael Gargano</a>,&nbsp;<a>Nicolas Matentzoglu</a>,&nbsp;<a>Leigh C Carmody</a>,&nbsp;<a>David Lewis-Smith</a>,&nbsp;<a>Nicole A Vasilevsky</a>,&nbsp;<a>Daniel Danis</a>,&nbsp;<a>Ganna Balagura</a>,&nbsp;<a>Gareth Baynam</a>,&nbsp;<a>Amy M Brower</a>,&nbsp;</p> <p><a>Tiffany J Callahan</a>,&nbsp;<a>Christopher G Chute</a>,&nbsp;<a>Johanna L Est</a>,&nbsp;<a>Peter D Galer</a>,&nbsp;<a>Shiva Ganesan</a>,&nbsp;<a>Matthias Griese</a>,&nbsp;<a>Matthias Haimel</a>,&nbsp;<a>Julia Pazmandi</a>,&nbsp;<a>Marc Hanauer</a>,&nbsp;<a>Nomi L Harris</a>,&nbsp;<a>Michael&nbsp;J Hartnett</a>,&nbsp;<a>Maximilian Hastreiter</a>,&nbsp;<a>Fabian Hauck</a>,&nbsp;<a>Yongqun He</a>,&nbsp;<a>Tim Jeske</a>,&nbsp;<a>Hugh Kearney</a>,&nbsp;<a>Gerhard Kindle</a>,&nbsp;<a>Christoph Klein</a>,&nbsp;<a>Katrin Knoflach</a>,&nbsp;<a>Roland Krause</a>,&nbsp;<a>David Lagorce</a>,&nbsp;<a>Julie A McMurry</a>,&nbsp;<a>Jillian A Miller</a>,&nbsp;<a>Monica&nbsp;C Munoz-Torres</a>,&nbsp;<a>Rebecca L Peters</a>,&nbsp;<a>Christina K Rapp</a>,&nbsp;<a>Ana M Rath</a>,&nbsp;<a>Shahmir A Rind</a>,&nbsp;<a>Avi&nbsp;Z Rosenberg</a>,&nbsp;<a>Michael M Segal</a>,&nbsp;<a>Markus G Seidel</a>,&nbsp;<a>Damian Smedley</a>,&nbsp;<a>Tomer Talmy</a>,&nbsp;<a>Yarlalu Thomas</a>,&nbsp;<a>Samuel A Wiafe</a>,&nbsp;<a>Julie Xian</a>,&nbsp;<a>Zafer Y&uuml;ksel</a>,&nbsp;<a>Ingo Helbig</a>,&nbsp;<a>Christopher J Mungall</a>,&nbsp;<a>Melissa A Haendel</a>,&nbsp;<a>Peter N Robinson</a></p> <p><em>Nucleic Acids Research</em>, Volume 49, Issue D1, 8 January 2021, Pages D1207&ndash;D1217,&nbsp;<a href="https://doi.org/10.1093/nar/gkaa1043">https://doi.org/10.1093/nar/gkaa1043</a></p> <p><strong>Human Phenotype Ontology downloads</strong> <strong>page:</strong>&nbsp;https://hpo.jax.org/app/data/ontology</p> <p><strong>U-BRITE last update:&nbsp;</strong>7/6/23</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2023View details →
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Experienced Challenges of Adopting Agile Scaling Frameworks: Dataset

<p>Dataset for the paper &quot;Experienced Challenges of Adopting Agile Scaling Frameworks&quot;</p> <p>The data is in one SPSS file, with variable descriptions.</p> <p>&nbsp;</p>

opencc-by-4.0Oct 2023View details →
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A deep learning framework combining molecular image and protein structural representation identifies candidate drugs for chronic pain

<p>Official dataset for&nbsp;<i>A deep learning framework combining molecular image and protein structural representation identifies candidate drugs for chronic pain</i>.&nbsp;</p><p>The related code can be found at <a href="https://github.com/yuxin212/GPCR-public">here</a> and <a href="https://github.com/ChengF-Lab/LISA-CPI">here</a>.&nbsp;</p><p>The dataset is now public.&nbsp;</p>

openJul 2023View details →
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A first high-quality vector data of buildings in East Asian countries based on a comprehensive large-scale mapping framework

<p>We generate a high-quality and complete&nbsp;vector data of buildings in East Asian regions, including China, Japan, North Korea, South Korea and Mongolia, filling the gaps in the existing public buildings data.</p>

opencc-by-4.0Jul 2023View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

ScienceDex for faculty

Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.