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Figure 7 in Three new species of the genus Mononchus (Nematoda: Mononchida), and the "real" Mononchus truncatus Bastian, 1865
Figure 7. Mononchus medius sp. nov. (A–C) anterior end; (D) cardial region; (E) mid-body region; (F) vulval region; (G–I) female posterior region.
Figure 3 in Three new species of the genus Mononchus (Nematoda: Mononchida), and the "real" Mononchus truncatus Bastian, 1865
Figure 3. Mononchus altiplanicus sp. nov. (A, B) Anterior end; (C) cervical region; (D) cardial region; (E) vulval region; (F–J) female posterior body region.
Figure 4 in Three new species of the genus Mononchus (Nematoda: Mononchida), and the "real" Mononchus truncatus Bastian, 1865
Figure 4. Mononchus oblongus sp. nov. (A) Anterior end; (B) cardial region; (C) vulval region; (D, E) female posterior end; (F) tail tip. Scale bars 20 µm.
Figure 6 in Three new species of the genus Mononchus (Nematoda: Mononchida), and the "real" Mononchus truncatus Bastian, 1865
Figure 6. Mononchus medius sp. nov. (A) Anterior end; (B) cardial region; (C) vulval region; (D, E) female posterior end. Scale bars 20 µm each.
Figure 2 in Three new species of the genus Mononchus (Nematoda: Mononchida), and the "real" Mononchus truncatus Bastian, 1865
Figure 2. Mononchus altiplanicus sp. nov. (A) Anterior end; (B) cardial region; (C) vulval region; (D, E) female posterior end. Scale bars 20 µm.
Figure 5 in Three new species of the genus Mononchus (Nematoda: Mononchida), and the "real" Mononchus truncatus Bastian, 1865
Figure 5. Mononchus oblongus sp. nov. (A–C) Anterior end; (D) cardial region; (E) vulval region; (F–H) female posterior region; (I) tail end with setiform papillae.
Figure 1 in Three new species of the genus Mononchus (Nematoda: Mononchida), and the "real" Mononchus truncatus Bastian, 1865
Figure 1. How to measure the buccal region of a Mononchus: a, width of the lip region; b, length of the buccal capsule; c, width of the buccal capsule at its widest part (inclusive of walls); d, width of the buccal capsule at its posterior third (inclusive of walls); e, distance of the tooth apex from the anterior end of buccal capsule; given either in µm or in % of the buccal length (in the present case about 30%); f, length (size) of the dorsal tooth.
Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat
<p>Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 < AUC < 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration. --</p>
The moisture plasticizing effect on enzyme-catalyzed reactions in model and real systems in view of legume ageing and their hard to cook development
<p>Data used for the figures in the article</p>
IQRM: real-time adaptive RFI masking for radio transient and pulsar searches
<p>This is repository of the data that were used for the analysis and results presented in "IQRM: real-time adaptive RFI masking for radio transient and pulsar searches" submitted to the Monthly Notices for the Royal Astronomical Society for publication. The readme file along with the data contains all the necessary information one would need to process the data. The data will be made available to everyone once the paper has been accepted for publication. If you are using data from this repository, please do not forget to cite the following paper:</p> <p>"IQRM: real-time adaptive RFI masking for radio transient and pulsar searches", V M Morello, K M Rajwade and B W Stappers, 2021, Monthly Notices of the Royal Astronomical Society, in press.</p>
GIR Dataset: A Geometry and real Impulse Response Dataset
<p>The GIR dataset is an open source dataset composed of more than 900k Impulse Responses (IRs). To foster the research in computational acoustics and in particular on the relationship between geometry and acoustic parameters, the measurements include acoustic responses acquired in 2952 positions and 312 surfaces. To maximize consistency, surfaces were 3D printed and the measurement process was automated using two robots. Detailed explanation of the dataset creation methods and possible applications are discussed in Rust <em>et al.</em> 2021 (<a href="https://doi.org/10.1177/1351010X20986901">https://doi.org/10.1177/1351010X20986901</a>) and Xydis <em>et al.</em> 2021 (in prep).</p> <p>The provenance and metadata tracked on Renku is enriched with the additional attributes recommended in the framework <a href="https://arxiv.org/abs/1805.03677">dataset nutrition labels</a> and Schema.org note on <a href="https://schema.org/docs/data-and-datasets.html">Data and Datasets</a>. This enriched metadata is provided in a standard JSON-LD format on Renku: <a href="https://renkulab.io/projects/ddad/gir-dataset/files/blob/dataset.json">dataset.json</a>.</p> <p>Dataset is released under <a href="https://renkulab.io/projects/ddad/gir-dataset/files/blob/LICENSE">the GNU General Public License v3.0</a></p>
FIGURE 7 in The real identity of the Malagasy Kalanchoe rosei (Crassulaceae subfam. Kalanchooideae) finally resolved, and the description of a new species, K. perrieri
FIGURE 7. Occurrences of specimens historically associated with the name K. rosei. Kalanchoe perrieri is of unknown provenance. © OpenStreetMap contributors.
FIGURE 3 in The real identity of the Malagasy Kalanchoe rosei (Crassulaceae subfam. Kalanchooideae) finally resolved, and the description of a new species, K. perrieri
FIGURE 3. Comparison of leaves and flowers (inserts) of selected specimens of K. variifolia and some sympatric nothospecies, all elements to scale. A. Isolectotype of K. variifolia var. seyrigii (B 10 0153778). B. Lectotype of K. variifolia var. variifolia (P-P00443996). C. A further specimen of K. variifolia var. variifolia (P-P00443995). D. A further specimen of K. variifolia var. seyrigii (B 10 1068977). E. K. ×lokarana (B 10 0171499), a nothospecies sympatric with K. variifolia var. seyrigii and K. variifolia var. variifolia. F–G. Material informally referred to in the horticultural trade as K. 'Rauhii', an entity that occurs sympatrically with K. variifolia var. variifolia: F. B 10 1186342; G. B 10 0120287. Photographs of material held by Herb. B (Botanischer Garten und Botanisches Museum Berlin-Dahlem Herbarium, Berlin) (A, D–G); and Herb. P (Vascular plants collection, Muséum national d'Histoire naturelle, Paris) (B–C).
FIGURE 6 in The real identity of the Malagasy Kalanchoe rosei (Crassulaceae subfam. Kalanchooideae) finally resolved, and the description of a new species, K. perrieri
FIGURE 6. Joseph Marie Henri Perrier de la Bâthie (11 August 1873–2 October 1958). Reproduced with the permission of Sheik Safdar, Sales Specialist—Permissions, Global Sales Partnerships, John Wiley & Sons Limited. The image, copyright of Taxon, appeared in Leandri (1962: 2) in Taxon 11(1).
FIGURE 4. A in The real identity of the Malagasy Kalanchoe rosei (Crassulaceae subfam. Kalanchooideae) finally resolved, and the description of a new species, K. perrieri
FIGURE 4. A. Flower (insert) and leaves and habit of horticultural material of K. daigremontiana; cultivated in South Africa (insert) and in Israel. B. Flowers and leaves of K. peltigera; a clone of the material deposited as the holotype, cultivated in Israel. C. General morphology of K. rosei [var. rosei] with trilobate leaves; cultivated in South Africa. D. Flowers and leaves of K. perrieri (R. Shtein 909); cultivated in Israel. Photograph credits: A, B, and D. Ronen Shtein; A (insert). Gideon F. Smith; C. Maddy Ogden. Elements are not to scale.
FIGURE 2 in The real identity of the Malagasy Kalanchoe rosei (Crassulaceae subfam. Kalanchooideae) finally resolved, and the description of a new species, K. perrieri
FIGURE 2. Comparison of leaves and flowers (inserts) of selected specimens of Kalanchoe rosei, all elements to scale. A. Lectotype of K. rosei (P-P00444019). B. Isolectotype of K. rosei (US00603536). C. Lectotype of K. bouvieri (P-P00444020), an abnormal form of K. rosei. D–E. Two further specimens of K. rosei [var. rosei] from the Onilahy region: D. P-P00444008; E. P-P00444018. F–G. Two specimens of K. peltigera from the Tsivory region: F. P-P00444012; G. P-P00374207, previously associated with "K. rosei var. seyrigii". H–I. Two specimens of K. rosei [var. rosei] from between Tsivory and Behara: H. P-P00444003; I. P-P00444006. Photographs of material held in the Vascular plants collection, Muséum national d'Histoire naturelle, Paris (P) (A–H); and United States National Herbarium, Smithsonian Institution (US) (I).
FIGURE 5 in The real identity of the Malagasy Kalanchoe rosei (Crassulaceae subfam. Kalanchooideae) finally resolved, and the description of a new species, K. perrieri
FIGURE 5. Comparison of leaves and flowers of living material historically associated with Kalanchoe rosei, to scale. A. K. ×richaudii. B. Two forms of what has been informally referred to as K. 'Rauhii'. C. K. variifolia var. variifolia (R. Shtein 426). D. Three forms of K. variifolia var. seyrigii (D2 illustrates material erroneously referred to as "K. rosei cv. Seyrigi"). E. Material variously referred to "K. rosei var. variifolia" and K. rosei [var. rosei]. F. Two forms of K. perrieri (R. Shtein 909 & 877). G. Clone of the holotype of K. peltigera. Photograph credits: Ronen Shtein.
FIGURE 1 in The real identity of the Malagasy Kalanchoe rosei (Crassulaceae subfam. Kalanchooideae) finally resolved, and the description of a new species, K. perrieri
FIGURE 1. Kalanchoe perrieri (R. Shtein 909). A. Inflorescences with acute-tipped, basally somewhat flattened buds. B. A specimen of R. Shtein 909 preserved at TELA (isotype TELA912), showing the comparatively short inflorescence, pink flowers, as well as the basally decumbent and suffrutescent stem. C. A specimen branching above the base, an uncommon character. D. Minutely auriculate, almost cordate, mature leaves bearing a few apical bulbils. E. Basal branching, preceding flowering. F. The fine and dense abaxial leaf marking unique to K. perrieri, as well as a few apical bulbils, on a plant approaching flowering. G. Close up of the dense inflorescence, and pink flowers showing calyx fused for half of its length. Photographs: Ronen Shtein.
Are Palmer's elm-leaf goldenrod and the smooth elm-leaf goldenrod real? The Angiosperms353 kit provides within-species signal in Solidago ulmifolia s.l.
<p><b><i>Abstract </i>— </b>The genus <i>Solidago</i> represents a taxonomically challenging group due to its sheer number of species, putative hybridization, polyploidy, and shallow genetic divergence among species. Here we use a dataset obtained exclusively from herbarium specimens to evaluate the status of <i>Solidago ulmifolia</i> var. <i>palmeri</i>, a morphologically subtle taxon potentially confined to Alabama, Arkansas, Mississippi, and Missouri. A multivariate analysis of both discrete and continuous morphological data revealed no clear distinction between <i>S. ulmifolia</i> var. <i>palmeri</i> and <i>Solidago ulmifolia</i> var. <i>ulmifolia</i>. <i>Solidago ulmifolia</i> var. <i>palmeri</i>'s status was also assessed with a phylogenomic and SNP clustering analysis of data generated with the "Angiosperms353" probe kit. Neither analysis supported <i>Solidago ulmifolia</i> var. <i>palmeri</i> as a distinct taxon, and we suggest that this name should be discarded. The status of <i>Solidago delicatula</i> (formerly known as <i>Solidago ulmifolia</i> var. <i>microphylla</i>) was also assessed. Both morphological and phylogenetic analyses supported the species status of <i>S. delicatula</i> and we suggest maintaining this species at its current rank. These results highlight the utility of the Angiosperms353 probe kit, both with herbarium tissue and at lower taxonomic levels. Indeed, this is the first study to utilize this kit to identify genetic groups within a species.</p>
Data for "Evaluating vertical velocity retrievals from vertical vorticity equation constrained dual-Doppler analysis of real, rapid-scan radar data"
<p>This archive contains data from the Rapid Scanning X-Band Polarimetric (RaXPol) radar, Atmospheric Imaging Radar (AIR), and Shared Mobile Atmospheric Research and Teaching radar (SMART-R) for 4 September 2018 in central Oklahoma. This is a rapid-scan dual-Doppler dataset of a convective storm. RaXPol and AIR were the two radars that can be used for dual-Doppler retrievals and the SMART-R data can be used for verification of vertical velocity.</p> <p>The AIR and RaXPol data have been quality controlled and are provided in cfRadial format. The SMART-R data has not been quality controlled and are available in its raw data format. All data can be read using the Python ARM Radar Toolkit.</p> <p>This dataset was used for the manuscript:</p> <p>Gebauer, J. G., A. Shapiro, C. K. Potvin, N. A. Dahl, M. I. Biggerstaff, and A. A. Alford, 2021: Evaluating vertical velocity retrievals from vertical vorticity equation constrained dual-Doppler analysis of rapid-scan radar data. <em>J. Atmos. Meas. Tech., </em>in review.</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.