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11,177 results for “identify”
FIG. 4 in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 4. — Phylogram generated from the best scoring MP tree based on combined LSU and SSU sequence data. Bootstrap support values for maximum parsimony (MP) equal or greater than 60 % are given above the nodes. The tree is rooted to Xylaria hypoxylon (OCS 100004) and Xylaria acuta (5089). Scale bar: 50 (expected number of nucleotide substitutions per site per branch).
FIG. 13. — Eutypella naqsii K.D in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 13. — Eutypella naqsii K.D.Hyde (BRIP 22588, holotype). A, herbarium material; B, horizontal section through ascostroma; C, D, vertical section through ascoma; E, peridium; F, paraphyses; G-I, asci; J-N, ascospores. Scale bars: B, 1000 μm; C, 500 μm; D,100 μm; E, F-I, 20 μm; J, 10 μm; K-N, 5 μm.
FIG. 3 in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 3. — Phylogram generated from the best scoring RAxML tree based on combined LSU and SSU sequence data. Bootstrap support values for maximum likelihood (ML, blue) equal or greater than 60 % are given above the nodes. Bayesian posterior probabilities (PP, green) equal or greater than 0.90 are shown above the branches. The tree is rooted to Xylaria hypoxylon (OCS 100004) and Xylaria acuta (5089). All sequences from ex-type strains are in bold. Scale bar: 0.02 (expected number of nucleotide substitutions per site per branch).
FIG. 17. — Pedumispora rhizophorae K.D.Hyde & E.B.G in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 17. — Pedumispora rhizophorae K.D.Hyde & E.B.G.Jones (BRIP 19201 – holotype): A, herbarium material; B, C, appearance of ascostromata on host; D, section through ascoma; E, section through neck region; F, peridium; G, paraphyses; H, I, asci; J, K, ascospores. Scale bars: B, 1000 μm; C, 500 μm; D, 50 μm; E-G, 20 μm; H-K, 100 μm.
FIG. 10 in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 10. — Cryptovalsa mangrovei Abdel-Wahab & Inderb (IMI 379746 – holotype): A, B, herbarium material; C, D, appearance of stromata on host; E, section through ascoma; F, neck region; G, peridium; H paraphyses; I-L, asci; M, ascospores. Scale bars: C, 500 μm; D, 200 μm; E, F, 100 μm; G, H, M, 20 μm; I-K, 50 μm.
FIG. 2 in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 2. — Phylogram generated from the best scoring RAxML tree based on ITS sequence data. Bootstrap support values for maximum likelihood (ML, black) and maximum parsimony (MP, blue) equal or greater than 60% are given above the nodes. Bayesian posterior probabilities (PP, green) equal or greater than 0.90 are shown above the branch. The tree is rooted to Xylaria hypoxylon (CBS 122620) and Kretzschmaria deusta (CBS 826.72). Scale bar: 0.09 (expected number of nucleotide substitutions per site per branch).
FIG. 16 in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 16. — Halodiatrype mangrovei (K.D.Hyde) Dayarathne & K.D.Hyde (BRIP 19869 – holotype); A, herbarium material; B, C, appearance of ascomata on host surface; D-F, vertical section through ascoma; G, vertical section through neck region; H, peridium; I, paraphyses; J-L, asci; M-P, ascospores. Scale bars: B, E, F, 500 μm; C, 1000 μm; D, 200 μm; G, 50 μm; H, K-L, 20 μm; M-P, 10 μm.
FIG. 1 in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 1. — Phylogram generated from the best scoring RAxML tree based on combined ITS and Btub sequence data. Bootstrap support values for maximum likelihood (ML, black) and maximum parsimony (MP, blue) equal or greater than 60 % are given above the nodes. Bayesian posterior probabilities (PP, green) equal or greater than 0.90 are shown above the branch. The tree is rooted to Xylaria hypoxylon (CBS 122620) and Kretzschmaria deusta (CBS 826.72). All sequences from ex-type strains are in bold. Symbols:, polysporous species;, octosporous species;, species with less than eight spores. Scale bar: 0.2 (expected number of nucleotide substitutions per site per branch).
FIG. 12 in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 12. — Diatrype mangrovei Dayarathne & K.D.Hyde, sp. nov. (MFLU 17-0412 – holotype): A, appearance of ascostromata on host (Bruguiera cylindrica); B, horizontal section through ascostroma; C, section through ascoma; D, peridium; E-G, asci; H, ascospores; I, germinating ascospore; J, K, culture on PDA (J-upper, K-lower). Scale bars: A, 500 µm; B, 500 μm; C, 100 μm; D-G, 50 μm; H, I, 10 μm.
FIG. 8 in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 8. — Cryptosphaeria halophila Dayarathne & K.D.Hyde, sp. nov. (MFLU 16-1199 – holotype): A, host (Avicennia sp.); B, horizontal section through conidioma; C-E, conidiophores and conidiogenous cells; F-I, conidia. Scale bars: A, 100 μm; B-E, 50 μm; F-I, 20 μm.
FIG. 6 in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 6. — Asexual morph of Cryptosphaeria avicenniae Devadatha & V.V.Sarma, sp. nov. (AMH-9952 – holotype): A, conidiomata on host (Avicennia marina); B, C, horizontal section through conidioma; D, peridium; E, F, conidiophores and conidiogenous cells; G-L, conidia. Scale bars: B-C, 100 μm; D, 50 μm; E-L, 10 μm.
Consensual videos of potentially re-identifiable individuals recorded at the Autonomous Driving Test Area Baden-Württemberg (raw images with location and IMU data).
<p>For the purpose of research on data intermediaries and data anonymisation, it is necessary to test these processes with realistic video data containing personal data. For this purpose, the <a href="http://treumoda.de">Treumoda</a> project, funded by the German Federal Ministry of Education and Research (BMBF), has created a dataset of different traffic scenes containing identifiable persons.</p> <p>This video data was collected at the <a href="https://taf-bw.de/">Autonomous Driving Test Area Baden-Württemberg</a>. On the one hand, it should be possible to recognise people in traffic, including their line of sight. On the other hand, it should be usable for the demonstration and evaluation of anonymisation techniques.</p> <p><strong>The legal basis for the publication of this data set the consent given by the participants as documented in the file Consent.pdf (all purposes) in accordance with Art. 6 1 (a) and Art. 9 2 (a) GDPR. Any further processing is subject to the GDPR.</strong></p> <p>We make this dataset available for non-commercial purposes such as teaching, research and scientific communication. Please note that this licence is limited by the provisions of the GDPR. Anyone downloading this data will become an independent controller of the data. This data has been collected with the consent of the identifiable individuals depicted.</p> <p>Any consensual use must take into account the purposes mentioned in the uploaded consent forms and in the privacy terms and conditions provided to the participants (see Consent.pdf). All participants consented to all three purposes, and no consent was withdrawn at the time of publication. KIT is unable to provide you with contact details for any of the participants, as we have removed all links to personal data other than that contained in the published images.</p>
FIG. 15. — B, C, F, H, I, K, M-P, R, S in Modern taxonomic approaches to identifying diatrypaceous fungi from marine habitats, with a novel genus Halocryptovalsa Dayarathne & K.D.Hyde, gen. nov.
FIG. 15. — B, C, F, H, I, K, M-P, R, S, Halodiatrype salinicola Dayarathne & K.D.Hyde (MFLU 15-0179 – holotype); A, D, E, G, J, L, O, P, T, U, Halodiatrype avicenniae Dayarathne & K.D.Hyde (MFLU 16-1185 – holotype and MFLU – 16-1197):A, B, horizontal section of ascoma (MFLU 16-1185,MFLU 15-0179);C, D, vertical section through ascoma (MFLU 15-0179, MFLU 16-1185); E, F, peridium (MFLU 16-1185, MFLU 15-0179); G, H, section through neck (MFLU 16-1185, MFLU 15-0179); I, J, asci (MFLU 15-0179 (in Congo red), MFLU 16-1185); K, L, paraphyses (MFLU 15-0179, MFLU 16-1185); M-P, ascospores (MFLU 15-0179, MFLU 16-1185); Q, conidia from culture on PDA (MFLU 18-0150); R-U, culture on PDA (MFLU 15-0179, MFLU 16-1185) Scale bars: A, 1000 µm; B, 500 µm; C, D, I-L, 100 μm; E, F, Q, 20 μm; G-H, 50 μm; M-P, 10 μm
CoUDlabs_WP8_T812_UDC_001. Identifying sediment deposits from temperature signals
<p>This dataset contains the results of the experimental campaign and how data were collected on the research activity “Identifying sediment deposits from temperature signals” performed under Joint Research Activity “JRA 3- Improving Resilience and Sustainability in Urban Drainage solutions” of <a href="https://co-udlabs.eu">Co-UDlabs</a> project, funded under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101008626.</p> <p>The experiments introduce a new approach which uses high-resolution temperature data to identify sediment bed deposits by analysing time series. Water (wastewater or drainage water in UDS) and sediments show different thermal properties and heat transfer dynamics. Thus, the aim of the dataset is to estimate or at least evidenced the presence of sediments by analyzing the differences between the temperature timeseries measured in the water phase and at the bottom of bed deposits. Results from this experimental campaign will help to understand heat transfer processes between water and saturated sediment mixtures and, therefore, develop new methodologies to estimate accumulation in UDS.</p> <p>The data are described so that others can use them.</p>
Artifact for "Identifying Concepts in Software Projects"
<p>This artifact complements the manuscript "Identifying Concepts in Software Projects". It contains all data necessary to independently verify our findings.</p>
How do young identify plants? Using the drawing method to explore early ethnobotanical knowledge in Madagascar
<p>Database from the article "How do young identify plants? Using the drawing method to explore early ethnobotanical knowledge in Madagascar"</p> <p>Please contact the author before using it for more details.</p> <p> </p>
Identifying cost-effective decarbonisation pathways for South Africa's power sector (EMP-A 2023) - Dataset
<p>Dataset of the project "Identifying cost-effective decarbonisation pathways for South Africa's power sector (EMP-A 2023)".</p>
Summary statistics for: Phenome-wide analyses identify an association between the parent-of-origin effects dependent methylome and the rate of aging in humans
<p>Summary statistics of single POE-CpG based and POE-CpG co-methylation module based phenome-wide association analyses for the manuscript "Phenome-wide analyses identify an association between the parent-of-origin effects dependent methylome and the rate of aging in humans"</p>
BioNames persistent identifiers for taxonomic names and publications
<p>Linked data for taxonomic names in BioNames linked to publications of those names. Triples use terms from http://schema.org vocabulary, taxonomic names identified by Life Science Identifiers, publications identified with DOIs.</p>
Index Fungorum persistent identifiers for taxonomic names and publications
<p>Linked data for taxonomic names in Index Fungorum linked to publications of those names. Triples use terms from http://schema.org vocabulary, fungal names identified by Life Science Identifiers, publications identified with DOIs.</p>
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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.