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8,537 results for “Openness”
Open cardiac sub-structure atlas
<p>A publicly shareable open atlas for use in cardiac substructure segmentation tools of the PlatiPy project.</p> <p>https://github.com/pyplati/platipy</p>
Linked Pipe: Linked Open Samian Ware
<p>A Linked Pipe for Linked Open Samian Ware</p> <p> </p>
Dataset - Templates Recommendation in the Open Research Knowledge Graph
<p>This dataset has been created for implementing a content-based recommender system in the context of the Open Research Knowledge Graph (ORKG). The recommender system accepts research paper's title and abstracts as input and recommends existing templates in the ORKG semantically relevant to the given paper.</p> <p> </p> <p>Two approaches have been trained on this dataset in the context of <a href="https://doi.org/10.15488/11834">this master's thesis</a>, namely a Natural Language Inference (NLI) approach based on SciBERT embeddings and an unsupervised approach based on ElasticSearch.</p> <p> </p> <p>This publication consists therefore of one general dataset, two training sets for each approach, validation set for the supervised approach and a test set for both approaches.</p> <p> </p> <p><strong>dataset.json</strong></p> <p>The main JSON object consists of a list of templates and a list of neutral papers.</p> <p>Each template object has an ID, label, list of research fields, list of properties and list of papers using that template, whereas each paper object has ID, label, DOI, research field and abstract.</p> <p>Each neutral paper object has the same schema of a paper object using that template.</p> <p>See an example instance below.</p> <p> </p> <pre><code class="language-json">{ "templates": [ { "id": "R138668", "label": "Psychiatric Disorders AI Overview", "research_fields": [ { "id": "http://orkg.org/orkg/resource/R133", "label": "Artificial Intelligence" } ... ], "properties": [ "Study cohort", ... ], "papers": [ { "id": "R138698", "label": "Application of Autoencoder in Depression Diagnosis", "doi": "10.12783/dtcse/csma2017/17335", "research_field": { "id": "R104", "label": "Bioinformatics" }, "abstract": "Major depressive disorder (MDD) is a mental disorder characterized by at least two weeks of low mood which is present across most situations. Diagnosis of MDD using rest-state functional magnetic resonance imaging (fMRI) data faces many challenges due to the high dimensionality, small samples, noisy and individual variability. No method can automatically extract discriminative features from the origin time series in fMRI images for MDD diagnosis. In this study, we proposed a new method for feature extraction and a workflow which can make an automatic feature extraction and classification without a prior knowledge. An autoencoder was used to learn pre-training parameters of a dimensionality reduction process using 3-D convolution network. Through comparison with the other three feature extraction methods, our method achieved the best classification performance. This method can be used not only in MDD diagnosis, but also other similar disorders." }, ... }, ... ] "neutral_papers": [ { "id": "R109377", "label": "Structural basis of SARS-CoV-2 3CLpro and anti-COVID-19 drug discovery from medicinal plants", "doi": "10.1016/j.jpha.2020.03.009", "research_field": { "id": "R104", "label": "Bioinformatics" }, "abstract": "Abstract The recent outbreak of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 in December 2019 raised global health concerns. The viral 3-chymotrypsin-like cysteine protease (3CLpro) enzyme controls coronavirus replication and is essential for its life cycle. 3CLpro is a proven drug discovery target in the case of severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV). Recent studies revealed that the genome sequence of SARS-CoV-2 is very similar to that of SARS-CoV. Therefore, herein, we analysed the 3CLpro sequence, constructed its 3D homology model, and screened it against a medicinal plant library containing 32,297 potential anti-viral phytochemicals/traditional Chinese medicinal compounds. Our analyses revealed that the top nine hits might serve as potential anti- SARS-CoV-2 lead molecules for further optimisation and drug development process to combat COVID-19." }, ... ] }</code></pre> <p> </p> <p><strong>All other files</strong></p> <p>The main JSON object consists of a list of entailments, a list of contradiction and a list of neutrals.</p> <p>Each object of the above mentioned lists has the same schema. An instance_id created by concatenating the template_id (when exists) with the paper_id, a template_id, a paper_id, premise (representing the paper's title), hypthesis (representing the paper's abstract), their concatenation in sequence and the target class.</p> <p>See an example instance below.</p> <p> </p> <pre><code class="language-json">{ "entailments": [ { "instance_id": "R138668xR138698", "template_id": "R138668", "paper_id": "R138698", "premise": "psychiatric disorders ai overview study cohort outcome assessment aims performance findings used models data", "hypothesis": "application of autoencoder in depression diagnosis major depressive disorder (mdd) is a mental disorder characterized by at least two weeks of low mood which is present across most situations diagnosis of mdd using rest state functional magnetic resonance imaging (fmri) data faces many challenges due to the high dimensionality, small samples, noisy and individual variability no method can automatically extract discriminative features from the origin time series in fmri images for mdd diagnosis in this study, we proposed a new method for feature extraction and a workflow which can make an automatic feature extraction and classification without a prior knowledge an autoencoder was used to learn pre training parameters of a dimensionality reduction process using 3 d convolution network through comparison with the other three feature extraction methods, our method achieved the best classification performance this method can be used not only in mdd diagnosis, but also other similar disorders", "sequence": "[CLS] psychiatric disorders ai overview study cohort outcome assessment aims performance findings used models data [SEP] application of autoencoder in depression diagnosis major depressive disorder (mdd) is a mental disorder characterized by at least two weeks of low mood which is present across most situations diagnosis of mdd using rest state functional magnetic resonance imaging (fmri) data faces many challenges due to the high dimensionality, small samples, noisy and individual variability no method can automatically extract discriminative features from the origin time series in fmri images for mdd diagnosis in this study, we proposed a new method for feature extraction and a workflow which can make an automatic feature extraction and classification without a prior knowledge an autoencoder was used to learn pre training parameters of a dimensionality reduction process using 3 d convolution network through comparison with the other three feature extraction methods, our method achieved the best classification performance this method can be used not only in mdd diagnosis, but also other similar disorders [SEP]", "target": "entailment" }, ... ], "contradictions": [ ... ], "neutrals": [ ... ] } </code></pre> <p> </p> <p><strong>Statistics</strong></p> <table align="center"> <tbody> <tr> <td>-</td> <td><strong>Training (supervised)</strong></td> <td><strong>Validation (supervised)</strong></td> <td><strong>Training (unsupervised)</strong></td> <td><strong>Test</strong></td> </tr> <tr> <td>Entailment</td> <td>180</td> <td>20</td> <td>200</td> <td>52</td> </tr> <tr> <td>Neutral</td> <td>180</td> <td>20</td> <td>200</td> <td>64</td> </tr> <tr> <td>Contradictrion</td> <td>736</td> <td>84</td> <td>0</td> <td>0</td> </tr> <tr> <td>Total</td> <td>1096</td> <td>124</td> <td>400</td> <td>116</td> </tr> </tbody> </table> <p> </p>
Resiloc-Open-Data-Sep-2021
Resiloc Open Data Entires for Sep 2021 For more info see https://www.resilocproject.eu/
Resiloc-Open-Data-Nov-2021
Resiloc Open Data Entires for Nov 2021 For more info see https://www.resilocproject.eu/
FIGURES –8. Cocconeis coronatoides Riaux-Gobin & Romero forma 1. SEM (New Caledonia, Melanesia). SVVC partially attached (2, arrowhead), SV areolae domed hymenes with radial slits arranged by sectors (external view 3, arrowhead), marginal RV hyaline area (external view 4, arrowhead), uniseriate striae up to margin (4), open RVVC (5, ellipse), RVVC with irregularly spread fimbriae (6, arrowhead), SVVC still attached, small marginal chambers (internal view 7, arrowhead), SV margin (external view 8). Scale bars = 3 µm (8), 2 µm (2, 4, 7), 1 µm (6), 700 nm (5), 200 nm (3). in Marine Achnanthales (Bacillariophyceae) from New Caledonia (Melanesia): assemblage specificities, ultramafic environment
FIGURES –8. Cocconeis coronatoides Riaux-Gobin & Romero forma 1. SEM (New Caledonia, Melanesia). SVVC partially attached (2, arrowhead), SV areolae domed hymenes with radial slits arranged by sectors (external view 3, arrowhead), marginal RV hyaline area (external view 4, arrowhead), uniseriate striae up to margin (4), open RVVC (5, ellipse), RVVC with irregularly spread fimbriae (6, arrowhead), SVVC still attached, small marginal chambers (internal view 7, arrowhead), SV margin (external view 8). Scale bars = 3 µm (8), 2 µm (2, 4, 7), 1 µm (6), 700 nm (5), 200 nm (3).
High cooperativity coupling to nuclear spins on a circuit QED architecture - Open Access Data SAet
<p>Open data set supporting figures of the related publication.</p>
FIGURE. Drosera tomentosa (a–d): a, rosette; b, rosette and base of inflorescences of D. tomentosa var. glabrata (Serra do Cipó, MG); c, inflorescence of the "type morphotype" of D. tomentosa (Chapada Diamantina, BA); d, inflorescence with open flower of the "glabrate morphotype" of D. tomentosa, side view (Diamantina, MG). Drosera villosa (e, f): e, habit; f, flower (Parque Estadual da Serra Negra da Mantiqueira, MG). Drosera viridis (g–i): g, rosettes of D. viridis (bottom) and D. communis (single plant, top; Imbituva, PR); h, leaf, detail (Piraquara, PR); i, flower (Balsa Nova, PR). Photo credits: a, b, d–f by PMG; c by FR; g–i by Carlos Rohrbacher. in A synopsis of the genus Drosera (Droseraceae) in Brazil
FIGURE. Drosera tomentosa (a–d): a, rosette; b, rosette and base of inflorescences of D. tomentosa var. glabrata (Serra do Cipó, MG); c, inflorescence of the "type morphotype" of D. tomentosa (Chapada Diamantina, BA); d, inflorescence with open flower of the "glabrate morphotype" of D. tomentosa, side view (Diamantina, MG). Drosera villosa (e, f): e, habit; f, flower (Parque Estadual da Serra Negra da Mantiqueira, MG). Drosera viridis (g–i): g, rosettes of D. viridis (bottom) and D. communis (single plant, top; Imbituva, PR); h, leaf, detail (Piraquara, PR); i, flower (Balsa Nova, PR). Photo credits: a, b, d–f by PMG; c by FR; g–i by Carlos Rohrbacher.
FIGURE. Drosera montana (a–c): a, rosette (Diamantina, MG); b, rosette (Parque Nacional do Itatiaia, RJ); c, rosettes with flowers (Parque Estadual da Serra de Ibitipoca, MG). Drosera quartzicola (d–f): d, habit with flower; e, habit; f, flower (Parque Nacional da Serra do Cipó, MG). Drosera riparia (g–i): g, habit of plant exposed to full sun; h, detail of leaves; i, inflorescence apex with open flower (Parque Nacional da Chapada Diamantina, BA). Photo credits: a, d, f by PMG; b by FR; c by Rodrigo Freitas; e by AF; g–i by Gabriel Garcia. in A synopsis of the genus Drosera (Droseraceae) in Brazil
FIGURE. Drosera montana (a–c): a, rosette (Diamantina, MG); b, rosette (Parque Nacional do Itatiaia, RJ); c, rosettes with flowers (Parque Estadual da Serra de Ibitipoca, MG). Drosera quartzicola (d–f): d, habit with flower; e, habit; f, flower (Parque Nacional da Serra do Cipó, MG). Drosera riparia (g–i): g, habit of plant exposed to full sun; h, detail of leaves; i, inflorescence apex with open flower (Parque Nacional da Chapada Diamantina, BA). Photo credits: a, d, f by PMG; b by FR; c by Rodrigo Freitas; e by AF; g–i by Gabriel Garcia.
FIGURE. Drosera hirticalyx (a–c): a, habit; b, inflorescence; c, flower (Kukenán-tepui, Venezuela). Drosera intermedia (d–f): d, habit; e, rosette (Porto Seguro, BA); f, inflorescence with open flower (cultivated). Drosera latifolia (g–i): g, rosette (Parque Nacional das Sempre-Vivas, MG); h, rosettes (Mogi das Cruzes, SP); i, flowers (Diamantina, MG). Photo credits: a–c by AF; d, e by FR; f–i by PMG. in A synopsis of the genus Drosera (Droseraceae) in Brazil
FIGURE. Drosera hirticalyx (a–c): a, habit; b, inflorescence; c, flower (Kukenán-tepui, Venezuela). Drosera intermedia (d–f): d, habit; e, rosette (Porto Seguro, BA); f, inflorescence with open flower (cultivated). Drosera latifolia (g–i): g, rosette (Parque Nacional das Sempre-Vivas, MG); h, rosettes (Mogi das Cruzes, SP); i, flowers (Diamantina, MG). Photo credits: a–c by AF; d, e by FR; f–i by PMG.
FIGURES 42–46. SEM micrographs. 42–43. Planothidium frequentissimum. 42. Internal valve view showing the roundish cavum with the narrow opening. 43 in A new species of an unexplored diatom genus: Gomphosphenia minima sp. nov. (Cymbellales, Rhoicospheniaceae)
FIGURES 42–46. SEM micrographs. 42–43. Planothidium frequentissimum. 42. Internal valve view showing the roundish cavum with the narrow opening. 43. External view showing the striae composed of three rows of small rounded areolae, and straight raphe branches with expanded drop–like proximal raphe endings. 44–45. Sellaphora nigri. 44. External valve view showing the bow tie-shaped central area and the 'tear-drop' shaped proximal ends of the raphe. 45. External valve view showing the areoles closest to the raphe being larger and slightly angular, square or nearly rounded, while the marginal areoles become smaller and more circular. 46. Eunotia minor, girdle view. Scale bar = 3 µm.
Theoretical Design of Optimal Molecular Qudits for Quantum Error Correction. Open data set
<p>Data supporting the original figures 1, 2, 3 and 4 of the related publication.</p>
Results from CODATA-RDA Schools for Research Data Science "being open and responsible at home" exercise 2022
<p>This is an exercise in identifying potential influence of environmental factors on open and responsible research practices. Students were asked to write down concerns about conducting open and responsible research in their home environments (column 2), and to group these concerns around institutional/cultural issues, infrastructural issues and personal concerns (column 1). Through a facilitated discussion, the class identified tools, communities and resources to use to help overcome these concerns (column 3).</p>
Cultivation of the PHB-producing cyanobacterium Synechococcus leopoliensis in a pilot-scale open system using nitrogen from waste streams
<p class="MsoNormal"><span>The cultivation of PHB-producing cyanobacteria is a promising approach to obtain the raw material for bio-based and biodegradable plastics. To commercialise photoautotrophic PHB production, the cultivation needs to be scaled up in open cultivation systems and to improve sustainability of the process, nutrients must be obtained from waste streams. Different PHB-producing cyanobacteria were compared in laboratory-scale cultivations using either water from recirculating aquaculture systems or pre-processed liquid digestate as nutrient sources. The species <em>Synechococcus leopoliensis</em> was cultivated in an open thin-layer photobioreactor (18 m<sup>2</sup>, 200 L), were growth in mineral Z-medium was again compared to said waste streams. Cultivation in mineral medium resulted in both the highest final biomass yield (6 g L<sup>-1</sup>) and productivity (0.7 g L<sup>-1</sup> d<sup>-1</sup>). Both waste stream-based media showed lower biomass yields and productivities (2 g L<sup>-1 </sup>and 0.25–0.3 g L<sup>-1</sup> d<sup>-1</sup>). However, due to differences in the cultivation conditions (e.g., temperature, nutrient supply), final biomass yield and productivity do not represent the performance of the cultivations adequately. Relative parameters such as nitrogen and energy conversion ratios indicate that cultivation with aquaculture water suffered from insufficient nitrogen supply to the culture, whereas the use pre-processed liquid digestate resulted in a substantial loss of nitrogen due to volatilization. All cultivations in the open system were continued in the laboratory, where cultures were starved for ten days under nutrient-depleted conditions (without nitrogen, phosphorus, or both). While PHB accumulation occurred, concentrations were comparatively low (< 1 %<sub>dw</sub>). The comparison of the results suggests that PHB yields were influenced more by the initial cultivation condition than by the specific type of nutrient depletion. Thus, while the cultivation with waste streams in an open system is feasible, environmental parameters seem to influence PHB yields considerably and must be considered for the optimisation of the complete process.</span></p>
What is Open Science Word Art
<p>On August 11th 2022, TOPS held a community forum during which Mentimeter was used to collect anonymous survey data from the participants. Using the responses to the question, "In your own words, how do you define open science?", NASA Transform to Open Science created a word art diagram to show key issues. </p>
FIGURE. Landscapes and vegetation types at Quiçama National Park. A. Wooded savannah with Adansonia digitata. B. Mosaic of wooded savannah and thicket. C. Grassy savannah. D. Slope with thicket. E. Grassy savanna with Setaria welwitschi. F. Wooded savannah. G. Cuanza River shores with herbaceous vegetation. H. Herbaceous vegetation on the banks of the Cuanza River and slope with open forest. I. Coastal sands. J. Mangrove at the Cuanza River estuary, with Rhizophora racemosa. (Photographs by the authors). in An annotated checklist of the vascular flora of Quiçama National Park, Angola
FIGURE. Landscapes and vegetation types at Quiçama National Park. A. Wooded savannah with Adansonia digitata. B. Mosaic of wooded savannah and thicket. C. Grassy savannah. D. Slope with thicket. E. Grassy savanna with Setaria welwitschi. F. Wooded savannah. G. Cuanza River shores with herbaceous vegetation. H. Herbaceous vegetation on the banks of the Cuanza River and slope with open forest. I. Coastal sands. J. Mangrove at the Cuanza River estuary, with Rhizophora racemosa. (Photographs by the authors).
OPENING SESSION: Shifting paradigms: Turning non-conventional to non-negotiable
<p><em>What are the global systems of industry, manufacture and education which label bamboo and adobe as ’non-conventional’ and concrete and steel as ‘conventional?</em> Are these systems designed for equity and social & environmental justice, or are they perpetuating systems of power which were established in colonial times? Are we encouraging the next generation of decision makers to think about choices of materials and technologies outside of the technical realm, so that they may be a part of the paradigm shift required for transformational change to occur? </p> <p>Search for a definition of non-conventional materials and technologies (NOCMAT), and you are more likely to find 'bamboo and adobe’ than 'concrete and steel’. But if over 90% of global dwellings fall into the NOCMAT category, then why are these materials still considered non-conventional? As we search for low-carbon alternatives for the built environment, NOCMAT is a most promising solution. Perhaps it is time we shift the paradigm and drop the 'non-conventional' label in favour of 'non-negotiable’; our lives on this planet could depend on it. </p> <p>These are the big issues which were explored by NOCMAT’s expert panel during the opening plenary session on 7 June 2022.</p>
CompactIE: Compact Facts in Open Information Extraction [Dataset]
<p>Dataset for the paper <a href="https://arxiv.org/abs/2205.02880">"CompactIE: Compact Facts in Open Information Extraction"</a>. </p>
Open access data for "Chip-Based Laser with 1 Hertz Integrated Linewidth"
<p>Open access data for "Chip-Based Laser with 1 Hertz Integrated Linewidth," by Guo, McLemore, et al.</p>
Double-lined spectroscopic binaries in the open cluster M 11 (NGC 6705)
<p>Figures with spectral fits for 265 Gaia-ESO spectra for open cluster M 11 (NGC 6705), analysed by single-star and binary spectroscopic models. </p> <p>Kovalev M., Straumit I., 2022, MNRAS, 510, 1515</p> <p>also used in arxiv 2207:06996</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.