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6,861 results for “Animals”
Testing novel climate accounting identifies animal agriculture as the leading emissions sector
<p>Data and spreadsheet supporting the paper <span>"Testing novel climate accounting identifies animal agriculture as the leading emissions sector" G Wedderburn-Bisshop, 2024</span></p>
Figure 3 in Animal diversity in the mangrove forest at Bichitrapur of Balasore district, Odisha, India- A case study
Figure 3. Sea anemone Diadumene lineata on the mangrove trunk.
Figure 8 in Animal diversity in the mangrove forest at Bichitrapur of Balasore district, Odisha, India- A case study
Figure 8. Sphaeroma terebrans and its juveniles colonize in wooden holes.
Data from: Data for habitat quality or quantity? Niche marginality across 21 plants and animals suggests differential responses between highland and lowland species to past climatic changes
<p>Climatic changes can affect species distributions, population abundance, and evolution. Such organismal responses could be determined by the amount and quality of available habitats, which can vary independently. In this study, we assessed changes in habitat quantity and quality independently to generate explicit predictions of the species' responses to climatic changes between Last Glacial Maximum (LGM) and present day. We built ecological niche models and distribution models for 21 reptile, mammal, and plant taxa from the Baja California peninsula inhabiting lowland or highland environments. Geological data suggests the CCSM global circulation model is a better representation of LGM climate for the Baja California peninsula. Significant niche divergence was detected for all clades within species, along with significant differences in the niche breadth and area of distribution between northern and southern clades. Most clades showed a reduction in distribution area towards LGM. Further, niche marginality (used as a measure of habitat quality) was higher during LGM for most clades, except for northern highland species. Our results suggest that changes in habitat quantity and quality can affect organismal response independently. This allows the prediction of genomic signatures associated with changes in effective population size and selection pressure that could be explicitly tested to support our models.</p>
Human SAN model 2024 supplementary animations.
<p>This repository is associated with the manuscript: "<em>Computational investigation of structural (fibrosis) and functional (I<sub>CaL</sub> and I<sub>Na</sub>) causes of arrhythmogenesis in the human 3D sino-atrial node", </em>by Sanjay R Kharche<sup>*</sup>, Galina Yu Mironova, Andrew Atkinson, and Donald G Welsh<sup>*</sup>. This repository contains the animations referred to in the above manuscript. A description of the file names, figure labels, and draft figure legends is provided below.</p> <p>1) File name in repository: S1_supplementVideo1Control3D.gif</p> <p>Figure label: Figure S1.</p> <p>Draft figure legend: Animation of 3D SAN control activation sequence in the border (left) and no border (right) cases.</p> <p> </p> <p>2) File name in repository: S3_pacingInducedMacro2D_Supplement.gif</p> <p>Figure label: Figure S3.</p> <p>Draft figure legend: Animation of pacing induced macro re-entry, SEP block, and altered activation sequence in the 2D model under s<sub>Na</sub> = 0.6 and s<sub>Ca</sub> = 0.8 conditions. See Figure 7 and main manuscript for details.</p> <p> </p> <p>3) File name in repository: S4_supplementToFig6_sna0.8_sca0.8.gif</p> <p>Figure label: Figure S4.</p> <p>Draft figure legend: In relation to main manuscript Figure 6, animation of complex wave propagation under s<sub>Na</sub> = s<sub>Ca</sub> = 0.8 conditions. SEP block, macro-re-entry, as well as 2:1 propagation can be observed.</p> <p> </p> <p>4) File name in repository: S6_run1dir1_9_1_1_2DmacroAndAtrialSupplement.gif</p> <p>Figure label: Figure S6.</p> <p>Draft figure legend: Animation of pacing induced macro-reentry, SEP block, and altered activation sequence in the 2D model under s<sub>Na</sub> = s<sub>Ca</sub> = 1 and 10% fibrosis conditions. See Figure 11 and main manuscript for details.</p> <p> </p> <p>5) File name in repository: S7_run3dir1_9_1_1_2DmicroAndComplexSupplement.gif</p> <p>Figure label: Figure S7.</p> <p>Draft figure legend: Animation of pacing induced micro re-entry, SEP block, and altered activation sequence in the 2D model under s<sub>Na</sub> = s<sub>Ca</sub> = 1 and 10% fibrosis conditions. See Figure 12 and main manuscript for details.</p> <p> </p> <p>6) File name in repository: S8_nopacingMacroreentryCedar0.80.8HSANb1.gif</p> <p>Figure label: Figure S8.</p> <p>Draft figure legend: Macro re-entry in the 3D non pacing with border model. s<sub>Na</sub> = s<sub>Ca</sub> = 0.8. See <strong>Figure 14</strong> in main manuscript.</p> <p> </p> <p>7) File name in repository: S9_HumanSAN_0.8_0.8_nonPacingCedar_Border1.gif</p> <p>Figure label: Figure S9.</p> <p>Draft figure legend: Atrial (complex) re-entry in the 3D model with s<sub>Na</sub> = s<sub>Ca</sub> = 0.8, no pacing and 10% fibrosis. See Figure 14 in main MS.</p>
ARCHIMEDES Project's Animated Video 'ARCHIMEDES: Pioneering a Sustainable Future'
<div> <p><span>The ARCHIMEDES project, a leading initiative in sustainable innovation, has launched an animated video titled "ARCHIMEDES: Pioneering a Sustainable Future." This video offers a detailed look into the project’s groundbreaking efforts to integrate sustainability with advanced technology across various sectors.</span></p> </div> <div> </div> <div> </div> <div> <p><span>ARCHIMEDES stands at the intersection of innovation and sustainability, aiming to revolutionize the future of mobility, energy, and safety within the framework of Society 5.0. The project focuses on developing state-of-the-art components, models, and methodologies to significantly improve the efficiency and lifespan of propulsion systems, power components, and energy storage devices.</span></p> </div> <div> </div> <div> </div> <div> <p><span>The video highlights how the ARCHIMEDES project spans multiple key industries:</span></p> </div> <div> <ul> <li> <p><span><strong>Automotive:</strong> Pioneering new propulsion systems to make vehicles more efficient and environmentally friendly.</span></p> </li> <li> <p><span><strong>Aviation:</strong> Enhancing energy efficiency and sustainability in the aerospace sector.</span></p> </li> <li> <p><span><strong>Industry:</strong> Transforming industrial processes to be more sustainable and cost-effective.</span></p> </li> </ul> </div> <div> </div> <div> </div> <div> <p><span>The ARCHIMEDES project is committed to creating a sustainable future by leveraging the latest innovations and technologies. By adopting an interdisciplinary approach, the project aims to be at the forefront of advancements in mobility, energy, and industrial processes. The vision is to not only meet current demands but also to anticipate and address future challenges.</span></p> </div> <div> </div> <div> </div> <div> <p><span>The newly released animated video provides a comprehensive overview of how ARCHIMEDES is leading the way toward a more sustainable future. The project invites viewers to join in this transformative journey.</span></p> </div>
Molecular markers for taxonomic validation of 7 deep water invertebrate animals
<p>File 1: MolecularBarcodeSeqs_forValidation.fasta</p> <p>Molecular markers extracted from transcriptome assemblies for validation of animal taxonomic identification.</p> <p>Files 2-4: 2022-03-29-01_JAB_FALKOR_RNA_1, 2022-03-29-01_JAB_FALKOR_RNA_2, 2022-03-29-01_JAB_FALKOR_RNA_2.</p> <p>TapeStation data for total RNA quality assessment. Identifiers in the Sample Description column are linked to identifiers in the published table, <span>Table 2. RNA and sequence statistics for each specimen, from the manuscript: </span><em><span>Transcriptome sequencing of seven deep marine invertebrates</span></em></p>
Figure 1 in Genetic structure of Trypanosoma congolense "forest type" circulating in domestic animals and tsetse flies in the South-West region of Cameroon
Figure 1. Allelic frequency at each locus by host.
Accounting for viewshed area and animal availability when estimating density and recruitment of unmarked white-tailed deer
<p>Quantifying demography of wildlife is vital to population monitoring; however, studies using physical capture methods can prove challenging. Camera traps have gained popularity as a density estimator tool in recent decades due to noninvasive data collection, reduced labor, cost efficiency, and large-scale monitoring capabilities. Many wildlife populations are comprised of individuals with no unique natural markers for individual identification, resulting in the need for unmarked abundance models. The recently developed Space-to-Event (STE) model offers a method for density estimation of unmarked populations using timelapse photography. STE relates detections of animals to camera sampling area (i.e., viewshed), resulting in density estimates that can be extrapolated to abundance over large areas. Consequently, this makes STE sensitive to estimates of viewshed area as small changes in viewshed could significantly affect density estimation. Using STE, we estimated density and recruitment of white-tailed deer (<em>Odocoileus virginianus</em>) in a densely forested landscape using measurements of viewshed per camera. We compared estimates of abundance derived from uniquely measured viewshed to estimates of abundance derived from an assumed viewshed area held constant across all cameras. When using a constant viewshed across all cameras, our point estimates of abundance shifted away from uniquely measured viewshed estimates in predictable ways, depending upon how much area was sampled. Additionally, we demonstrated the need for further exploration of animal availability at fine temporal scales by comparing estimates of density derived from sampling the full diel period to estimates derived from periods of peak activity (i.e., crepuscular periods). Finally, we extended the usefulness of the STE model by using densities of fawns and adult females to derive estimates of fawn recruitment.</p>
Figure 3 in Cytotoxicity of extracts and compounds isolated from Croton echioides in animal tumor cell (HTC)
Figure 3. Clerodan diterpenes tested.
Data accompanying "Identification of capsid-like proteins in venomous and parasitic animals"
<p>This data accompanies the pub "Identification of capsid-like proteins in venomous and parasitic animals". The DOI for this pub is <a href="https://doi.org/10.57844/arcadia-14b2-6f27" target="_blank" rel="noopener noreferrer">https://doi.org/10.57844/arcadia-14b2-6f27</a></p> <p> </p> <p><strong>Files and folders included: </strong></p> <p> </p> <p><strong>1.</strong> Manually annotated results of searching VOG HMMs against venom transcriptomes: Annotated_capsid_no_cutoffs_summary_with_seqs_05092024.xlsx</p> <p><strong>2.</strong> Manually annotated results of running preHGT on the genomes of venomous species: Annotated_hgt_results_venom_050924.xlsx</p> <p><strong>3. </strong>The genomes we input into preHGT: preHGT_input_genomes.csv</p> <p><strong>4.</strong> Genbank files of the genomic neighborhood of putatively horizontally transferred viral genes in the tick genome. There are seven GenBank files, one for each contig. Named with protein name.</p> <p><strong>5.</strong> BLAST results from searching putatively endogenized viral proteins against tick salivary transcriptomes: TSA_blast_results.csv</p> <p><strong>6.</strong> Results from searching the putatively endogenized viral capsid proteins against AlphaFold/UniProt50 version 4, AlphaFold/Swiss-Prot version 4, and AlphaFold/Proteome version 4 using the Foldseek webserver: Foldseek_capsid_followup_05092024.xlsx</p> <p><strong>7.</strong> Newick files of the three trees displayed in Figure 3 and Figure 5 . </p>
ProteinCartograhpy data accompanying "Identification of capsid-like proteins in venomous and parasitic animals"
<p>This is the data for the <a href="https://github.com/Arcadia-Science/ProteinCartography/releases/tag/v0.4.2">ProteinCartography</a> analysis in the pub "<a href="https://doi.org/10.57844/arcadia-14b2-6f27">Identification of capsid-like proteins in venomous and parastic animals.</a>" Note that ProteinCartography (v0.4.2) was run in "Cluster" mode or "From-folder" mode using the parameters set in the <code>config_ff.yml</code> and the <em>Ornithodoros turicata </em>proteins. Notebooks used to fetch data and prepare custom plots can be found in the capsids GitHub <a href="https://github.com/Arcadia-Science/capsids">repository</a>.</p> <p> </p> <p><strong>Files in this data repository include: </strong></p> <p><code>output.zip</code> is a folder containing all of the output files for the <em>Ornithodoros</em> ProteinCartography run, including the maps, aggregated features files, and the all-v-all similarity matrix.</p> <p><code>structures.zip</code> is a folder containing all the structures used in the ProteinCartography analysis. Structures beginning with "VOG" are viral capsid proteins folded using <a href="https://doi.org/10.1126/science.ade2574">ESMFold</a>.</p> <p><code>ornithodoros_aggregated_features.tsv</code> is a file containing all the metadata gathered for each protein in the analysis from either <a href="https://www.uniprot.org">UniProt</a> or the <a href="https://vogdb.org">VOG database</a>.</p> <p><code>ornithodoros_aggregated_features_pca_umap.html</code> is the final map of the capsid proteins with the <em>Ornithodoros</em> proteins with metadata overlays.</p> <p><code>ornithodoros_aggregated_features_pca_umap.tsv</code> is a file containing all of the metadata gathered for each protein in the analysis, as well as the coordinates for the map.</p> <p><code>ornithodoros_leiden_similarity.html</code> is a heatmap showing the average between-cluster and within-cluster similarity between every cluster in the analysis.</p> <p><code>tick_or_virus_umap.html</code> is a version of the final map that specifically highlights which proteins are from capsids and which proteins are from <em>Ornithodoros</em>. </p> <p><code>uniprot_features1.tsv</code> is a file containing all of the UniProt metadata fetched for the <em>Ornithodoros</em> proteins, as well as the viral capsid VOG identifiers. This file is used as an input for the ProteinCartography analysis.</p> <p><code>ornithodoros.txt</code> us a file containing all of the <em>Ornithodoros</em> proteins fetched from the <a href="https://doi.org/10.1038/s41586-021-03819-2">AlphaFold</a> <a href="https://doi.org/10.1093/nar/gkab1061">database.</a></p> <p><code>config_ff.yml</code> is the configuration file for the ProteinCartography run. </p>
Fig. 1. A in A few notes on the diet and the copulation of Theba pisana (Müller, 1774) snails: observations on terrarium kept animals
Fig. 1. A pair of copulating Theba pisana hanging from the glass cover of the terrarium.
Fig. 4 in Animal remains of the Late Antiquity settlement near Dyakovo Village (Kyustendil Region (SW Bulgaria)
Fig. 4. Domestic donkey (Equus asinus) – molar tooth P-4 sin. ad. (Photo: Z. Boev).
Fig. 1 in Animal remains of the Neolithic Ritual Burial Complex near Krum Village (Haskovo Region, SE Bulgaria)
Fig. 1. Eurasian beaver (Castor fiber) – molar tooth. (Photograph: Z. Boev).
Fig. 3 in Animal remains of the Late Antiquity settlement near Dyakovo Village (Kyustendil Region (SW Bulgaria)
Fig. 3. Domestic donkey (Equus asinus) – metatarsus sin. dist. ad. (Photo: Z. Boev).
Fig. 1 in Animal remains of the Late Antiquity settlement near Dyakovo Village (Kyustendil Region (SW Bulgaria)
Fig. 1. Wisent (Bison bonasus) – molar tooth ad. (Photo: Z. Boev).
Fig. 2 in Animal remains of the Neolithic Ritual Burial Complex near Krum Village (Haskovo Region, SE Bulgaria)
Fig. 2. Cattle (Bos taurus) – mandibular, processus coronoideus (Photograph: Z. Boev).
Fig. 2 in Animal remains of the Late Antiquity settlement near Dyakovo Village (Kyustendil Region (SW Bulgaria)
Fig. 2. Cattle (Bos taurus) – molar tooth M-3 sin. ad. (Photo: Z. Boev).
Fig. 5 in Animal remains of the Late Antiquity settlement near Dyakovo Village (Kyustendil Region (SW Bulgaria)
Fig. 5. Sheep (Ovis aries) - molar tooth M-3 ad. (Photo: Z. Boev).
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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.