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Fig. 22 in A revision and one new species of Begonia L. (Begoniaceae, Cucurbitales) in Northeast India
Fig. 22. Map showing the location of B. dioica Buch.-Ham. ex D.Don specimens.
Fig. 38 in A revision and one new species of Begonia L. (Begoniaceae, Cucurbitales) in Northeast India
Fig. 38. Map showing the location of B. lushaiensis C.E.C.Fisch. specimens.
Fig. 41 in A revision and one new species of Begonia L. (Begoniaceae, Cucurbitales) in Northeast India
Fig. 41. Map showing the location of B. obversa C.B.Clarke specimens.
Fig. 33 in A revision and one new species of Begonia L. (Begoniaceae, Cucurbitales) in Northeast India
Fig. 33. Map showing the location of B. koelzii R.Camfield sp. nov. specimens.
Fig. 25 in A revision and one new species of Begonia L. (Begoniaceae, Cucurbitales) in Northeast India
Fig. 25. Map showing the location of B. griffithiana (A.DC.) Warb. specimens.
Distal prong of MA longer than proximal one, curved (6c) in A revision of the African wolf spider genus Amblyothele Simon
Distal prong of MA longer than proximal one, curved (6c)
MA with one prong only; TA with back pointing tooth (4a) in A revision of the African wolf spider genus Amblyothele Simon
MA with one prong only; TA with back pointing tooth (4a)
Contemporary impression of oval intaglio engraved with a one-line brāhmī inscription
<p>Contemporary impression of oval intaglio engraved with a one-line brāhmī inscription.</p>
One-minute average horizontal wind velocity data (which has been corrected for air-flow distortion) from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4.
<p><strong>Dataset abstract</strong></p> <p>One-minute average horizontal wind velocity data from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4. The data has been filtered for spurious observations and the true wind correction has been redone using the quality checked one-minute ship track velocity data. The data has been corrected for air-flow distortion, which was caused by the ship's super structure.</p> <p><strong>Dataset contents</strong></p> <ul> <li>wind-observations-stbd-corrected-1min-legs0-4.csv, data file, comma-separated values</li> <li>wind-observations-port-corrected-1min-legs0-4.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This one-minute averaged wind velocity dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Data from: Can light-saturated photosynthesis in lowland tropical forests be estimated by one light level?
Leaf-level net photosynthesis (An) estimates and associated photosynthetic parameters are crucial for accurately parameterizing photosynthesis models. For tropical forests such data are poorly available and collected at variable light conditions. To avoid over- or underestimation of modelled photosynthesis, it is critical to know at which photosynthetic photon flux density (PPFD) photosynthesis becomes light saturated. We studied the dependence of An on PPFD in two tropical forests in French Guiana. We estimated the light saturation range, including the lowest PPFD level at which Asat (An at light saturation) is reached, as well as the PPFD range at which Asat remained unaltered. The light saturation range was derived from photosynthetic light-response curves, and within-canopy and interspecific differences were studied. We observed wide light saturation ranges of An. Light saturation ranges differed among canopy heights, but a PPFD level of 1000 µmol/m²/s was common across all heights, except for pioneer trees species that did not reach light saturation below 2000 µmol/m²/s. A light intensity of 1000 µmol/m²/s sufficed for measuring Asat of climax species at our study sites, independent of the species or the canopy height. Because of the wide light saturation ranges, results from studies measuring Asat at higher PPFD levels (for upper canopy leaves up to 1600 µmol/m²/s) are comparable with studies measuring at 1000 µmol/m²/s.
Sealing. Oval sealing in terracotta with a one line inscription; trident above
<p>Sealing. Oval sealing in terracotta with a one line inscription; trident above. British Museum 2005,0814.3.</p>
Sealing. Oval sealing in terracotta with a one line inscription.
<p>Sealing. Oval sealing in terracotta with a one line inscription. British Museum 2005,0814.14.</p>
Fig. 36 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 36. Distribution map of "Inella" differens Rolán & Lee, 2008; red circle = type locality.
Fig. 63 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 63. Distribution map of Sagenotriphora sp. 1.
Fig. 60 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 60. Distribution map of Nanaphora sp. 1.
Fig. 44 in Unraveling one of the 'Big Five': update of the taxonomy of Triphoridae (Gastropoda, Triphoroidea) from Brazil
Fig. 44. Distribution map of Inella sp. 1.
Data from: One panel to rule them all: DArTcap genotyping for population structure, historical demography, and kinship analyses, and its application to a threatened shark
With recent advances in sequencing technology, genomic data are changing how important conservation management decisions are made. Applications such as Close-Kin Mark-Recapture demand large amounts of data to estimate population size and structure, and their full potential can only be realised through ongoing improvements in genotyping strategies. Here we introduce DArTcap, a cost-efficient method that combines DArTseq and sequence capture, and illustrate its use in a high resolution population analysis of Glyphis garricki, a rare, poorly known and threatened euryhaline shark. Clustering analyses and spatial distribution of kin pairs from four different regions across northern Australia and one in Papua New Guinea, representing its entire known range, revealed that each region hosts at least one distinct population. Further structuring is likely within Van Diemen Gulf, the region that included the most rivers sampled, suggesting additional population structuring would be found if other rivers were sampled. Coalescent analyses and spatially explicit modelling suggest that G. garricki experienced a recent range expansion during the opening of the Gulf of Carpentaria following the conclusion of the Last Glacial Maximum. The low migration rates between neighbouring populations of a species that is found only in restricted coastal and riverine habitats show the importance of managing each population separately, including careful monitoring of local and remote anthropogenic activities that may affect their environments. Overall we demonstrated how a carefully chosen SNP panel combined with DArTcap can provide highly accurate kinship inference and also support population structure and historical demography analyses, therefore maximising cost-effectiveness.
Data from: One and two year visual outcomes from the Moorfields age-related macular degeneration database: a retrospective cohort study and an open science resource
Objectives: To analyse treatment outcomes and share clinical data from a large, single-center, well-curated database (8174 eyes / 6664 patients with 120,756 single entries) of patients with neovascular age related macular degeneration (AMD) treated with anti-vascular endothelial growth factor (VEGF). By making our depersonalised raw data openly available, we aim to stimulate further research in AMD, as well as setting a precedent for future work in this area. Setting: Retrospective, comparative, non-randomised electronic medical record (EMR) database cohort study of the UK Moorfields AMD database with data extracted between 2008 and 2018. Participants: Including one eye per patient, 3357 eyes/patients (61% female). Extraction criteria were ≥ 1 ranibizumab or aflibercept injection, entry of "AMD" in the diagnosis field of the EMR, and a minimum of one year of follow-up. Exclusion criteria were unknown date of first injection and treatment outside of routine clinical care at Moorfields before the first recorded injection in the database. Main outcome measures: Primary outcome measure was change in VA at one and two years from baseline as measured in Early Treatment Diabetic Retinopathy Study (ETDRS) letters. Secondary outcomes were the number of injections and predictive factors for VA gain. Results: Mean VA gain at one-year and two years were +5.5 (95%CI:5.0,6.0) and +4.9 (95%CI:4.2,5.6) letters respectively. Fifty-four percent of eyes gained ≥5 letters at two years, 63% had stable VA (±≤14 letters), forty-four percent of eyes maintained good VA (≥70 letters). Patients received a mean of 7.7 (95%CI:7.6,7.8) injections during year one and 13.0 (95%CI:12.8,13.2) injections over two years. Younger age, lower baseline VA, and more injections were associated with higher VA gain at two years. Conclusion: This study benchmarks high quality EMR study results of real life AMD treatment and promotes open science in clinical AMD research by making the underlying data publicly available.
Dataset: Object condensation: one-stage grid-free multi-object reconstruction in physics detectors, graph, and image data
<p>This dataset is the dataset used to train and test the object condensation particle flow approach described in <a href="https://arxiv.org/abs/2002.03605">arxiv:2002.03605</a>.</p> <p>The data can be read with DeepJetCore 3.1 (https://github.com/DL4Jets/DeepJetCore)<br> The entries in the truth array are of dimension (batch, 200, N_truth). The truth inputs are:</p> <p>isElectron,<br> isGamma,<br> isPositron,<br> true_energy,<br> true_x,<br> true_y</p> <p>The entries in the feature array are of dimension (batch, 200, N_features), with the features being:</p> <p>rechit_energy,<br> rechit_x,<br> rechit_y,<br> rechit_z,<br> rechit_layer,<br> rechit_detid</p> <p>The "train.zip" file contains the training sample<br> The "test.zip" file the test sample</p> <p>The main test sample is identical to the training sample in composition, but statistically independent.<br> Other samples can be found in subfolders:</p> <p>test/flatNpart: sample with flat distribution of additional particles in the event w.r.t. each individual particle<br> Test/hiNPart: sample with up to 15 particles per event</p>
Description of the microbiota in epidermal mucus and skin of sharks (Ginglymostoma cirratum and Negaprion brevirostris) and one stingray (Hypanus americanus)
<p>Skin mucus in fish is the first barrier between the organism and the environment but the role of skin mucus in protecting fish against pathogens is not well understood. During copulation in sharks, the male bites the female generating wounds, which are then highly likely to become infected by opportunistic bacteria from the water or from the male shark's mouth. Describing the microbial component of epithelial mucus may allow future understanding of this first line of defense in sharks. In this study, we analyzed mucus and skin samples obtained from 19 individuals of two shark species and a stingray: the nurse shark (<i>Ginglymostoma cirratum</i>), the lemon shark (<i>Negaprion brevirostris</i>) and the southern stingray (<i>Hypanus americanus</i>). Total DNA was extracted from all samples, and the bacterial 16S rRNA gene (region V3-V4) was amplified and sequenced on the Ion Torrent Platform. Bacterial diversity (order) was higher in skin and mucus than in water. Order composition was more similar between the two shark species. Alpha-diversities (Shannon and Simpson) for OTUs (clusters of sequences defined by a 97% identity threshold for the16S rRNA gene) were high and there were non-significant differences between elasmobranch species or types of samples. We found orders of potentially pathogenic bacteria in water samples collected from the area where the animals were found, such as Pasteurellales (i.e. genus <i>Pasteurella</i> spp. and <i>Haemophilus</i> spp.) and Oceanospirillales (i.e. genus <i>Halomonas</i> spp.) but these were not found in the skin or mucus samples from any species. Some bacterial orders, such as Flavobacteriales, Vibrionales (i.e. genus <i>Pseudoalteromonas</i>), Lactobacillales and Bacillales were found only in mucus and skin samples. However, in a co-occurrence analyses, no significant relationship was found among these orders (strength less than 0.6, p-value > 0.01) but significant relationships were found among the order Trembayales, Fusobacteriales, and some previously described marine environmental Bacteria and Archaea, including Elusimicrobiales, Thermoproteales, Deinococcales and Desulfarculales. This is the first study focusing on elasmobranch microbial communities. The functional role and the benefits of these bacteria still needs understanding as well as the potential changes to microbial communities as a result of changing environmental conditions.</p>
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.