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13,587 results for “specification”
Figure 1 from: Rakauskas R, Havelka J, Zaremba A, Bernotienė R (2014) Mitochondrial COI and morphological evidence for host specificity of the black cherry aphids Myzus cerasi (Fabricius, 1775) collected from different cherry tree species in Europe (Hemiptera, Aphididae). ZooKeys 388: 1-15. https://doi.org/10.3897/zookeys.388.7034
Figure 1 - Haplotype network (TCS 1.21 software: Clement et al. 2000) for COI fragment (616 positions in final set) haplotypes of Myzus cerasi and Myzus borealis. The haplotype with the highest outgroup probability is displayed as a square, while others are displayed as ovals. For sample information, see Table 2.
Figure 3 from: Rakauskas R, Havelka J, Zaremba A, Bernotienė R (2014) Mitochondrial COI and morphological evidence for host specificity of the black cherry aphids Myzus cerasi (Fabricius, 1775) collected from different cherry tree species in Europe (Hemiptera, Aphididae). ZooKeys 388: 1-15. https://doi.org/10.3897/zookeys.388.7034
Figure 3 - Plot of the mean scores of the first two canonical variates for 20 samples of Myzus cerasi (for specimen numbers per sample see Table 1). Samples cluster in accordance with winter host plant and COI haplotype (haplotype number is given in parentheses, see Table 2 for other haplotypes).
Figure 2 from: Rakauskas R, Havelka J, Zaremba A, Bernotienė R (2014) Mitochondrial COI and morphological evidence for host specificity of the black cherry aphids Myzus cerasi (Fabricius, 1775) collected from different cherry tree species in Europe (Hemiptera, Aphididae). ZooKeys 388: 1-15. https://doi.org/10.3897/zookeys.388.7034
Figure 2 - Maximum likelihood (ML) tree showing phylogenetic relationships among Myzus cerasi based on partial sequences of mitochondrial COI (616 positions in final set). Numbers above branches indicate support of NJ (left, > 50%) and MP (right, > 50%) bootstrap test with 1000 replicates, and numbers below branches indicate support of ML (left, > 50%) bootstrap test with 1000 replicates and posterior probabilities of BI analysis (right, > 0.50). Samples used for the discriminant analysis with a priori specified group membership followed by the construction of identification key are asterisked (*). The remaining samples were used for the post hoc classification. Sample numbers are the same as given in Table 1, together with the abbreviated symbol of respective country BG – Bulgaria, BY – Belarus, D – Germany, HU – Hungary, IT – Italy, LV – Latvia, LT – Lithuania, PL – Poland, RO – Romania, TR – Turkey, UA – Ukraine.
Figure 2 from: Bharti H, Guénard B, Bharti M, Economo EP (2016) An updated checklist of the ants of India with their specific distributions in Indian states (Hymenoptera, Formicidae). ZooKeys 551: 1-83. https://doi.org/10.3897/zookeys.551.6767
Figure 2 - Generic (A) and species (B) richness based on nominal species for the different states of India.
Figure 2 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646
Figure 2 - Classification of fungal OTUs by the RDP classifier to the different taxonomic levels as a percentage. Classification cutoff was a confidence level of 0.8.
Figure 5 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646
Figure 5 - Distribution of fungal orders in Lake Stechlin habitats based on the mean percentages as determined with SILVA NGS. Fungal phyla are highlighted with brackets. Habitat codes are taken from Table 1. (*) marks the false classified Neocallimastigales as clarified by phylogenetic inference (see discussion paragraph on sediments).
Figure 4 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646
Figure 4 - Habitat specificity of the fungal community in Lake Stechlin. NMDS plots based on the fungal OTU matrix (1027 OTUs). Ordination is based on Cao distances (Cao et al. 1997), which are insensitive to differences in sampling effort. Ellipses are based on standard deviations around habitat centroids (based on a confidence level of 0.95) and are coloured according to their POM type: FPOM (blue), MIX (magenta), CPOM (brown). Habitat codes and POM categories are taken from Table 1.
Figure 1 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646
Figure 1 - Sampling sites in Lake Stechlin. Integrated water samples, above-sediment water, plankton (> 55 µm), and sediment were taken from pelagic locations. Surface water samples, reed plants (Phragmites australis), biofilm samples (from stone, wood and macrophytes) and benthic samples (detritus, macrozoobenthos) were taken from littoral locations.
Figure 3 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646
Figure 3 - Contribution of fungal phyla within each of the lakes habitat. Pie chart diameters are scaled by the contribution of fungal diversity to the total eukaryotic diversity in each habitat. Lower case letters group significantly different POM types in terms of OTU diversity and fungal reads (Tukey Post-Hoc tests, p < 0.01).
Figure 1 from: Riit T, Tedersoo L, Drenkhan R, Runno-Paurson E, Kokko H, Anslan S (2016) Oomycete-specific ITS primers for identification and metabarcoding. MycoKeys 14: 17-30. https://doi.org/10.3897/mycokeys.14.9244
Figure 1 - A Map of universal and oomycete-specific ITS region primers B Taxa with mismatches in the binding sites of primers ITS1oo and ITS3oo. Only taxa with 10% or more mismatching accessions are shown.
Figure 2 from: Riit T, Tedersoo L, Drenkhan R, Runno-Paurson E, Kokko H, Anslan S (2016) Oomycete-specific ITS primers for identification and metabarcoding. MycoKeys 14: 17-30. https://doi.org/10.3897/mycokeys.14.9244
Figure 2 - OTU and read distributions of ITS1 (A) and ITS2 (B) reads. Panels starting from outermost: 1 Oomycete read distribution between orders 2 Read distribution between classes, excluding reads of unknown origin 3 Read distribution between classes, including reads of unknown origin 4 OTU distribution between classes.
Bayesian estimation of the specific shear and bulk viscosity of the quark-gluon plasma
<p>This repository contains all data necessary to reproduce Bayesian parameter estimates of a computational model of relativistic heavy-ion collisions.</p> <p>The computational collision model which generated the raw data is available at <a href="https://github.com/Duke-QCD/hic-eventgen">https://github.com/Duke-QCD/hic-eventgen</a>. The analysis code which postprocessed the raw data and performed the parameter estimation is available at <a href="https://github.com/jbernhard/hic-param-est">https://github.com/jbernhard/hic-param-est</a>.</p> <p>For more information, see the author's dissertation, <a href="https://arxiv.org/abs/1804.06469">Bayesian parameter estimation for relativistic heavy-ion collisions (arXiv:1804.06469 [nucl-th])</a>. In particular, chapter 3 describes the computational collision model, chapter 4 describes the parameter estimation method, and section 5.3 presents the results based on this dataset.</p> <p><strong>Usage</strong></p> <p>hic-param-est-cache.tar.gz is designed to be used with the analysis code (<a href="https://github.com/jbernhard/hic-param-est">https://github.com/jbernhard/hic-param-est</a>).<br> See the documentation at <a href="http://qcd.phy.duke.edu/hic-param-est">http://qcd.phy.duke.edu/hic-param-est</a>. After downloading the code, extract the data archive in the hic-param-est folder. This will create the cache directory containing the parameter design files, model calculations, and experimental data. Note that this data archive includes Python pickle files created by <a href="https://joblib.readthedocs.io/en/latest/persistence.html">joblib</a>, which is included with <a href="https://scikit-learn.org">scikit-learn</a>, a dependency of the analysis code.</p> <p>alternate-format.hdf contains the same data in HDF5 format. This is not intended for use directly with the analysis code, but may be more convenient for other purposes.</p> <p>chain.hdf contains the posterior distribution sample (the "chain") generated by MCMC sampling in HDF5 format. It may be used with the analysis code by placing it in a subfolder "mcmc" in the hic-param-est folder. It can also be regenerated by the analysis code, although this can take a long time.</p>
FIGURE 4 in Reinstatement of the independent specific status of Chrysanthemum neo-oreastrum (Asteraceae, Anthemideae)
FIGURE 4. Distribution of Chrysanthemum neo-oreastrum (●).
Organochemical Characterization of Peat Reveals Decomposition of Specific Hemicellulose Structures as the Main Cause of Organic Matter Loss in the Acrotelm
<p>Peatlands store carbon in the form of dead organic residues. Climate change and human impact impose risks on the sustainability of the peatlands carbon balance due to increased peat decomposition. Here, we investigated molecular changes in the upper peat layers (0–40 cm), inferred from high-resolution vertical depth profiles, from a boreal peatland using two-dimensional <sup>1</sup>H–<sup>13</sup>C nuclear magnetic resonance (NMR) spectroscopy, and comparison to δ<sup>13</sup>C, δ<sup>15</sup>N, and carbon and nitrogen content. Effects of hydrological conditions were investigated at respective sites: natural moist, drainage ditch, and natural dry. The molecular characterization revealed preferential degradation of specific side-chain linkages of xylan-type hemicelluloses within 0–14 cm at all sites, indicating organic matter losses up to 25%. In contrast, the xylan backbone, galactomannan-type hemicelluloses, and cellulose were more resistant to degradation and accumulated at the natural moist and drainage site. δ<sup>13</sup>C, δ<sup>15</sup>N, and carbon and nitrogen content did not correlate with specific hemicellulose structures but reflected changes in total carbohydrates. Our analysis provides novel insights into peat carbohydrate decomposition and indicates substantial organic matter losses in the acrotelm due to the degradation of specific hemicellulose structures. This suggests that variations in hemicellulose content and structure influence peat stability, which may have important implications with respect to climate change.</p>
Sex-specific microglial responses to glucocerebrosidase inhibition
<p>Morpho-dynamic analysis occurring in primary cells derived from female and male mice in response to proinflammatory stimulations and glucocerebrosidase inhibition. The work was supported by the EU Joint Programme - Neurodegenerative Disease Research (JPND) project GBA-PaCTS.</p> <p>Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).</p>
CN-P (version 1): a crop-specific, 1 km-resolution phosphorus rate data product in China over 2004–2016
<p>CN-P harmonizes provincial and county-level phosphorus and component fertilizer statistics and crop distribution data to generate 1km gridded maps of phosphorus rate for rice, wheat and maize in the years of 2004-2016. </p>
Research and Evaluation of Allosteric Protein Specific Force Field Based on Deep Learning
<p>All trajectories for evaluating APSF force field</p>
Artifact for ICSE'23 paper: Triggers for Reactive Synthesis Specifications
<p>Artifact for ICSE'23 paper: Triggers for Reactive Synthesis Specifications</p>
Supplementary material 3 from: Xu M, Liu Y, Möller E, LaGreca S, Moya P, Wang X, Timdal E, de Boer H, Barreno E, Wang L, Thüs H, Andrésson Ó, Magnússon KP, Ólafsdóttir ES, Heiðmarsson S (2023) Mycobiont-specific primers facilitate the amplification of mitochondrial small subunit ribosomal DNA: a focus on the lichenized fungal genus Melanelia (Ascomycota, Parmeliaceae) in Iceland. MycoKeys 96: 57-75. https://doi.org/10.3897/mycokeys.96.100037
Multiple sequence alignment for fungal mtSSU primer design of the genus Usnea
Supplementary material 2 from: Xu M, Liu Y, Möller E, LaGreca S, Moya P, Wang X, Timdal E, de Boer H, Barreno E, Wang L, Thüs H, Andrésson Ó, Magnússon KP, Ólafsdóttir ES, Heiðmarsson S (2023) Mycobiont-specific primers facilitate the amplification of mitochondrial small subunit ribosomal DNA: a focus on the lichenized fungal genus Melanelia (Ascomycota, Parmeliaceae) in Iceland. MycoKeys 96: 57-75. https://doi.org/10.3897/mycokeys.96.100037
Priming sites for alternative mtSSU primers, Nanodrop results and in silico PCR amplicons
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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.
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.