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9,882 results for “Scale”
Data for: Epidemiological landscape of Batrachochytrium dendrobatidis and its impact on amphibian diversity at global scale
<p>Chytridiomycosis, caused by the fungal pathogen <em>Batrachochytrium dendrobatidis </em>(<em>Bd</em>), is a major driver of amphibian decline worldwide. The global presence of <em>Bd </em>is driven by a synergy of factors, such as climate, species life history, and amphibian host susceptibility. Here, using a Bayesian data-mining approach, we modeled the epidemiological landscape of <em>Bd </em>to evaluate how infection varies across several spatial, ecological, and phylogenetic scales. We compiled global information on <em>Bd </em>occurrence, climate, species ranges, and phylogenetic diversity to infer the potential distribution and prevalence of <em>Bd</em>. By calculating the degree of co-distribution between <em>Bd </em>and our set of environmental and biological variables (e.g. climate and species), we identified the factors that could potentially be related to <em>Bd </em>presence and prevalence using a geographic correlation metric, epsilon (ε). We fitted five ecological models based on 1) amphibian species identity, 2) phylogenetic species variability values for a given species assemblage, 3) temperature, 4) precipitation and 5) all variables together. Our results extend the findings of previous studies by identifying the epidemiological landscape features of <em>Bd</em>. This ecological modeling framework allowed us to generate explicit spatial predictions for <em>Bd </em>prevalence at the global scale and a ranked list of species with high/low probability of <em>Bd </em>presence. Our geographic model identified areas with high potential for <em>Bd </em>prevalence (potential <em>Bd</em>-risk areas) and areas with low potential <em>Bd </em>prevalence as potential refuges (free <em>Bd</em>). At the amphibian assemblage level, we found a non-relationship with amphibian phylogenetic signals, but a significantly negative correlation between observed species richness and <em>Bd </em>prevalence indicated a potential dilution effect at the landscape scale. Our model may identify species and areas potentially susceptible and at risk for <em>Bd </em>presence, which could be used to prioritize regions for amphibian conservation efforts and to assess species and assemblage at risk.</p>
Fig. 4. 2B in High and lowland dependent wing phenotypic variation of the dark blue tiger butterfly, Tirumala septentrionis (Butler, 1874) (Lepidoptera: Nymphalidae) with FE-SEM wing scales nanomorphology
Fig. 4. 2B-PLS analysis of T. septentrionis. (A) Forewing size; (B) Forewing shape; (C) Hindwing size; and (D) Hindwing shape.
Fig. 7 in High and lowland dependent wing phenotypic variation of the dark blue tiger butterfly, Tirumala septentrionis (Butler, 1874) (Lepidoptera: Nymphalidae) with FE-SEM wing scales nanomorphology
Fig. 7. Forewing shape analysis. Mlp female (A) % of variance, (B) PC1, (C) PC2, (D) PC3. Mlp male (E) % of variance, (F) PC1, (G) PC2, (H) PC3. Wyn female (I) % of variance, (J) PC1, (K) PC2, (L) PC3. Wyn male (M) % of variance, (N) PC1, (O) PC2, (P) PC3.
Fig. 10 in High and lowland dependent wing phenotypic variation of the dark blue tiger butterfly, Tirumala septentrionis (Butler, 1874) (Lepidoptera: Nymphalidae) with FE-SEM wing scales nanomorphology
Fig. 10. FE-SEM image analysis of T. septentrionis. Forewing brown regions (A–F), and bluish-white regions (G–J) of T. septentrionis. Hindwing brown regions (K–Q), and bluish-white regions (R–T). FE-SEM image of the male pouch scale of T. septentrionis (U–X). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1. T in High and lowland dependent wing phenotypic variation of the dark blue tiger butterfly, Tirumala septentrionis (Butler, 1874) (Lepidoptera: Nymphalidae) with FE-SEM wing scales nanomorphology
Fig. 1. T. septentrionis forewing (A) with 25 landmarks; hindwing (B) with 18 landmarks. male pouch represented in white circle.
Fig. 9 in High and lowland dependent wing phenotypic variation of the dark blue tiger butterfly, Tirumala septentrionis (Butler, 1874) (Lepidoptera: Nymphalidae) with FE-SEM wing scales nanomorphology
Fig. 9. Morphospace analysis. (A) forewing PCs morphospace analysis, PC1 vs. PC2; (B) forewing CVs morphospace analysis; (C) hindwing PCs morphospace analysis, PC1 vs. PC2; (D) hindwing CVs morphospace analysis. Alphabet code used in image – first three letter code indicated as the collection site and fourth letter for sex (male or female). For eg: MlpF – Malappuram female.
Fig. 6 in High and lowland dependent wing phenotypic variation of the dark blue tiger butterfly, Tirumala septentrionis (Butler, 1874) (Lepidoptera: Nymphalidae) with FE-SEM wing scales nanomorphology
Fig. 6. Sexual wing asymmetry (male vs. female) of T. septentrionis wings validated by Discriminant function analysis (DFA). Forewing of T. septentrionis (A–D) and hindwing of T. septentrionis (E–H). Alphabet code used in image – first three letter code indicated as the collection site and fourth letter for sex (male or female). For eg: MlpF – Malappuram female.
Fig. 8 in High and lowland dependent wing phenotypic variation of the dark blue tiger butterfly, Tirumala septentrionis (Butler, 1874) (Lepidoptera: Nymphalidae) with FE-SEM wing scales nanomorphology
Fig. 8. Hindwing shape analysis. Mlp female (A) % of variance, (B) PC1, (C) PC2, (D) PC3. Mlp male (E) % of variance, (F) PC1, (G) PC2, (H) PC3. Wyn female (I) % of variance, (J) PC1, (K) PC2, (L) PC3. Wyn male (M) % of variance, (N) PC1, (O) PC2, (P) PC3.
Fig. 5 in High and lowland dependent wing phenotypic variation of the dark blue tiger butterfly, Tirumala septentrionis (Butler, 1874) (Lepidoptera: Nymphalidae) with FE-SEM wing scales nanomorphology
Fig. 5. Wing asymmetry (right or left) of T. septentrionis wings validated by Discriminant function analysis (DFA). Forewing of T. septentrionis (A–D) and hindwing of T. septentrionis (E–H). Alphabet code used in image – first three letter code indicated as the collection site and fourth letter for sex (male or female), fifth letter for wing side (right or left). For eg: MlpFR – Malappuram female right.
Fig. 2. 30 in High and lowland dependent wing phenotypic variation of the dark blue tiger butterfly, Tirumala septentrionis (Butler, 1874) (Lepidoptera: Nymphalidae) with FE-SEM wing scales nanomorphology
Fig. 2. 30 years mean climate data (A) Mlp region mean temperature, and precipitation; (B) Mean temperature of Mlp; (C) Wyn region mean temperature, and precipitation; (B) Mean temperature of Wyn.
Tactician's Web of Large-Scale Formal Knowledge
<p>This dataset contains machine-readable data extracted by <a href="https://coq-tactician.github.io">Tactician</a> from formal knowledge encoded in the <a href="https://coq.inria.fr">Coq Proof Assistant</a>. It includes definitions, theorems, proof terms and tactical proofs presented both as Coq's default textual format and a graph format. The entire known universe of formal knowledge in Coq is encoded as a single interconnected graph of mathematical concepts where all knowledge is faithfully and unambiguously encoded. The dataset is intended for machine learning, analysis and general proof engineering purposes. In addition to exploring this offline dataset, it is also possible to interact directly with Coq in the same data format through <a href="https://coq-tactician.github.io/api">Tactician's API</a>.</p><p>See the README.md file for more information.</p>
Data for the paper Large-Scale Tropical Circulation Intensification by Aerosol Effect on Clouds
<p>Data for the paper Large-Scale Tropical Circulation Intensification by Aerosol Effect on Clouds.</p> <p> </p> <p>Please see the README for more information. </p>
Supplementary material 1 from: Erdélyi A, Hartdégen J, Malatinszky Á, Vadász C (2023) Historical reconstruction of the invasions of four non-native tree species at local scale: a detective work on Ailanthus altissima, Celtis occidentalis, Prunus serotina and Acer negundo. One Ecosystem 8: e108683. https://doi.org/10.3897/oneeco.8.e108683
Derived data of Ailanthus altissima, Celtis occidentalis, Prunus serotina and Acer negundo from the National Forestry Database and its archives.
Pilot-Scale Continuous Foam Fractionation for the Removal of Per- and Polyfluoroalkyl Substances (PFAS) from Landfill Leachate
<p>This is the supplementary data for the publication '<span>Pilot-Scale Continuous Foam Fractionation for the Removal of Per- and Polyfluoroalkyl Substances (PFAS) from Landfill Leachate' (</span>https://pubs.acs.org/doi/full/10.1021/acsestwater.2c00032)</p>
Electrochemical Oxidation for Treatment of PFAS in Contaminated Water and Fractionated Foam─A Pilot-Scale Study
<p>This is the supplementary data to the publication '<span>Electrochemical Oxidation for Treatment of PFAS in Contaminated Water and Fractionated Foam─A Pilot-Scale Study' (<a title="DOI URL" href="https://doi.org/10.1021/acsestwater.2c00660">https://doi.org/10.1021/acsestwater.2c00660</a>). </span></p>
Patient-specific genome-scale metabolic models reconstructed for 8 TCGA tumor types
<p>TCGA_reconstructedGEMs: 3,599 cancer patient-specific GEMs for 8 different tumor types reconstructed using the TCGA (The Cancer Genome Atlas) RNA-seq data and generic human GEM 'Recon 2M.2'</p>
Vintage - Scales of Justice
Source: Objaverse 1.0 / Sketchfab
Temporal and Spatial Evolution of Pore Scale PDFs of Solute Concentrations to Study Incomplete Mixing in Porous Media
<p>C at M.I for Pe100 (sample): Sample (vector) of pore scale concentrations at Pe100 and five different times.</p> <p>C Chunk for All Pe (sample): Sample (3D block) of pore scale concentrations at the mixing interface for six Peclet number cases ( 10, 32, 100, 316, 1000, 3160) and at 11 different time steps extracted from the full size column. This is extracted using the semi-analytical appraoch to eliminate boundary effect.</p> <p>meanvelocities: Matlab Data of the pore scale longitudinally averaged velocity.</p> <p>MLE: Result of maximum likelihood estimation analysis for 18 different distribution functions (Excel file)</p> <p>SemiAnalytical: Matlab code for the implementation of the semi-analytical apporach.</p> <p>gamma_incomplete: Incomplete Gamma function required for the SemiAnalytical code.</p>
82 Block--63k or 50k scale Maps of South Asia
<p>6 maps of the Survey of India covering block 82.</p>
63 Block--63k or 50k scale Maps of South Asia--additional 1--20240105
<p>98 new map files to add to the set of 63k/50k Maps of South Asia, Block 63. </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.