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1,855 results for “Framework”
Data from: A framework for the identification of long-term social avoidance in longitudinal datasets
Animal sociality is of significant interest to evolutionary and behavioural ecologists, with efforts focused on the patterns, causes and fitness outcomes of social preference. However, individual social patterns are the consequence of both attraction to (preference for) and avoidance of conspecifics. Despite this, social avoidance has received far less attention than social preference. Here, we detail the necessary steps to generate a spatially explicit, iterative null model which can be used to identify non-random social avoidance in longitudinal studies of social animals. We specifically identify and detail parameters which will influence the validity of the model. To test the usability of this model, we applied it to two longitudinal studies of social animals (Eastern water dragons (Intellegama leseurii) and bottlenose dolphins (Tursiops aduncus) to identify the presence of social avoidances. Using this model allowed us to identify the presence of social avoidances in both species. We hope that the framework presented here inspires interest in addressing this critical gap in our understanding of animal sociality, in turn allowing for a more holistic understanding of social interactions, relationships and structure.
Structural modulation of π-conjugated linkers in D-π-A dyes based on Triphenylamine dicyanovinylene framework to explore the NLO properties
<p>A donor-π-acceptor type series of Triphenylamine-dicyanovinylene based chromophores (<b>DPMN1-DPMN11</b>) was designed theoretically by the structural tailoring of π-linkers to exploit changes in the optical properties and their NLO behaviour. Density functional theory (DFT) computations were employed to understand the electronic structures, absorption spectra, charge transfer phenomena and the influence of these structural modifications on NLO properties. Interestingly, all investigated chromophores exhibited lower band gap (2.22-2.60 <i>eV</i>) with broad absorption spectra in the visible region, reflecting the remarkable NLO response. Furthermore, natural Bond Orbital (NBO) findings revealed a strong push-pull mechanism in <b>DPMN1-DPMN11 </b>as donor and π-conjugates exhibited positive, while all acceptors showed negative values. Examination of electronic transitions from donor to acceptor moieties via π-conjugated linkers revealed greater linear (<<i>α</i>>=526.536-641.756 <i>a.u</i>) and non-linear (<i>β</i><sub>tot</sub> =51313.8-314412.661 <i>a.u</i>) response. It was noted that the chromophores containing imidazole in 2<sup>nd</sup> p-linker expressed greater hyperpolarizability when compared with the ones containing pyrrole. This study reveals that by controlling the type of π-spacers, interesting metal-free NLO materials can be designed, which can be valuable for the hi-tech NLO applications.</p>
Comparison and assessment of different object-based classifications using machine learning algorithms and UAVs multispectral imagery in the framework of precision agriculture
<p>Supplementary material of the paper</p>
Inclusion and Exclusion Criteria in Software Engineering Tertiary Studies: A Systematic Mapping and Emerging Framework - Replication Package
<p>Replication Package for the paper:</p> <p>D. Costal, C. Farré, X. Franch, C. Quer. 2021. Inclusion and Exclusion Criteria in Software Engineering Tertiary<br> Studies: A Systematic Mapping and Emerging Framework. ESEM '21, <a href="https://doi.org/10.1145/3475716.3484190">https://doi.org/10.1145/3475716.3484190</a></p> <p>Please refer to the above paper if you want to cite/use this data.</p>
A classification framework for Bacillus anthracis defined by global genomic structure
<p><i>Bacillus anthracis</i>, the causative agent of anthrax, is a considerable global health threat affecting wildlife, livestock, and the general public. In this study whole-genome sequence analysis of over 350 <i>B. anthracis</i> isolates was used to establish a new high-resolution global genotyping framework that is both biogeographically informative, and compatible with multiple genomic assays. The data presented in this study shed new light on the diverse global dissemination of this species and indicate that many lineages may be uniquely suited to the geographic regions in which they are found. In addition, we demonstrate that plasmid genomic structure for this species is largely consistent with chromosomal population structure, suggesting vertical inheritance in this bacterium has contributed to its evolutionary persistence. This classification methodology is the first based on population genomic structure for this species and has potential use for local and broader institutions seeking to understand both disease outbreak origins and recent introductions. In addition, we provide access to a newly developed genotyping script as well as the full whole genome sequence analyses output for this study, allowing future studies to rapidly employ and append their data in the context of this global collection. This framework may act as a powerful tool for public health agencies, wildlife disease laboratories, and researchers seeking to utilize and expand this classification scheme for further investigations into <i>B. anthracis</i> evolution.</p>
Supplementary data for "Beyond radical-rebound: Methane oxidation to methanol catalyzed by iron species in metal–organic framework nodes"
<p>Cartesian coordinates in the *.XYZ format for all the structures optimized at the M06-L/def2-TZVP in the reactivity study as part of the article "Beyond radical-rebound: Methane oxidation to methanol catalyzed by iron species in metal-organic framework nodes" (<a href="https://doi.org/10.1021/jacs.1c04766">https://doi.org/10.1021/jacs.1c04766</a>)</p>
Assessment of the data assimilation framework for the prototype Rapid Refresh Forecast System and impacts on forecasts of convective storms
<p>The compressed file contains the data and scripts necessary for the numerical experiments conducted in this research and the processing and visualization of the results. It includes the namelist files used for the model when using cold and warm start, the analyses in each experiment, and the grid, topography and surface climatology along with the model configuration file, the file used in the analyses to read the horizontal and vertical scales from an external file, all scripts used to execute every task of the workflow, all scripts used to process model outputs with MET, as well as all scripts and data used to create all figures of the paper.</p>
FIGURE 3. A in A standardized and statistically defensible framework for quantitative morphological analyses in taxonomic studies
FIGURE 3. A visual description of a boxplot to illustrate how outliers are detected. Using this method, values above the maximum range or below the minimum range are considered outliers. The maximum range is defined as the upper quartile (Q3) plus 1.5 times the interquartile range (IQR), while the minimum range is defined as the lower quartile (Q1) minus 1.5 times the IQR.
FIGURE 2. The 5 in A standardized and statistically defensible framework for quantitative morphological analyses in taxonomic studies
FIGURE 2. The 5-step workflow for statistical hypothesis testing of morphological characters. Note that mensural and meristic data should be analyzed separately and that Step 4 should only be performed on mensural data. * = parametric tests; ** = nonparametric tests. The non-parametric tests shown here only serve as examples—the appropriate test should be selected based on which assumptions are violated. A companion R script that implements this workflow is provided in the Supplementary Material.
FIGURE 1 in A standardized and statistically defensible framework for quantitative morphological analyses in taxonomic studies
FIGURE 1. Results of the meta-analysis on taxonomic papers focused on amphibians (top) and reptiles (bottom) published in the journal ZooKeys from 2008–2020. The analysis evaluated whether body size corrections or statistical analyses were performed on morphological data.
Figure 8 in A morphometric and genetic framework for the genus Gazella de Blainville, 1816 (Ruminantia: Bovidae) with special focus on Arabian and Levantine mountain gazelles
Figure 8. Phylogeny of the genus Gazella. Consensus tree of 5000 post burn-in trees from Bayesian analysis of mitochondrial control region, cytochrome b and 12S rRNA gene sequences. Branch labels are posterior probabilities. Museum specimens labelled 'G. arabica' are highlighted with grey background. For GenBank accession numbers see Appendix S2. Photographs of living animals courtesy of S. Hammer (http://awwp.alwabra.com, photo gallery).
Figure 5 in A morphometric and genetic framework for the genus Gazella de Blainville, 1816 (Ruminantia: Bovidae) with special focus on Arabian and Levantine mountain gazelles
Figure 5. Bi-variate plots of specimen scores for discriminant functions. A, males, DA 2; B, females, DA 6.
Figure 6 in A morphometric and genetic framework for the genus Gazella de Blainville, 1816 (Ruminantia: Bovidae) with special focus on Arabian and Levantine mountain gazelles
Figure 6. Classification of the male Gazella arabica type skull ZMB_MAM_2115. A, B, bi-variate plots of specimen scores for main components in PCA 8; C, D, bi-variate plots of specimen scores for discriminant functions in DA 4.
Figure 1 in A morphometric and genetic framework for the genus Gazella de Blainville, 1816 (Ruminantia: Bovidae) with special focus on Arabian and Levantine mountain gazelles
Figure 1. Geographical origin of gazelle specimens included in this study. Black icons, specimens sampled for morphometrical data; white icons, specimens sampled for DNA data; grey icons, specimens sampled for morphometrical and DNA data. The geographical origins of specimens sampled for DNA data were taken from the original publications of the sequences (Hammond et al., 2001; Wronski et al., 2010; Zachos et al., 2010; Lerp et al., 2011; Wacher et al., 2011) or the specimen information on GenBank. The geographical range of G. subgutturosa extends further to the east into China and Mongolia.
Figure 2 in A morphometric and genetic framework for the genus Gazella de Blainville, 1816 (Ruminantia: Bovidae) with special focus on Arabian and Levantine mountain gazelles
Figure 2. Skull measurements used in this study. Abbreviations correlate with descriptions in Table 3.
Figure 4 in Form and function within a phylogenetic framework: locomotory habits of extant predators and some Miocene Sparassodonta (Metatheria)
Figure 4. Morphospaces defined by the first two shape axes for the ulna. A, B, relative warps (RWs); C, D, relative warps residuals (RRWs) after phylogenetic autocorrelation analysis; E, F, RRWs after phylogenetic eigenvector regression analysis. In A, C, and E, taxonomic groups are indicated by the symbols. In B, D, and F, locomotory groups are indicated by the symbols. Taxonomic group symbols: Ailuridae, Canidae, Dasyuridae, Didelphidae, Felidae, Herpestidae, Hyaenidae, Nandiniidae, Mephitidae, Mustelidae, Myrmecobiidae, Procyonidae, Thylacinidae, Ursidae, Viverridae, Sparassodonta species. Locomotory groups symbols: cursorial eutherians, cursorial metatherians, terrestrial eutherians, terrestrial metatherians, scansorial eutherians, scansorial metatherians,
Figure 2 in Form and function within a phylogenetic framework: locomotory habits of extant predators and some Miocene Sparassodonta (Metatheria)
Figure 2. Morphospaces defined by the first two shape axes for the humerus. A, B, relative warps (RWs); C, D, relative warps residuals (RRWs) after phylogenetic autocorrelation analysis; E, F, RRWs after phylogenetic eigenvector regression analysis. In A, C, and E, taxonomic groups are indicated by the symbols. In B, D, and F, locomotory groups are indicated by the symbols. Taxonomic group symbols: Ailuridae, Caenolestidae, Canidae, Dasyuridae, Didelphidae, Felidae, Herpestidae, Hyaenidae, Nandiniidae, Mephitidae, Mustelidae, Myrmecobiidae, Procyonidae, Thylacinidae, Ursidae, Viverridae, Sparassodonta species. Locomotory groups symbols: cursorial eutherians,
Figure 1 in Form and function within a phylogenetic framework: locomotory habits of extant predators and some Miocene Sparassodonta (Metatheria)
Figure 1. Analysed elements showing the position of landmarks (squares) and semilandmarks (circles). A, anterior view of distal humerus: 1, proximolateral extreme of articular surface, 2 to 6, proximal margin of articular surface, 7, proximomedial extreme of articular surface, 8, proximal end of lateral epicondylar crest, 9 to 11, lateral margin of lateral epicondylar crest, 12 to 14, medial margin of lateral epicondylar crest, 15, lateral extreme of lateral epicondyle, 16, distolateral corner of articular surface, 17 to 20, distal margin of articular surface, 21, distomedial corner of articular surface, 22, distomedial extreme of medial epicondyle, 23, medial extreme of medial epicondyle, 24 to 26, medial margin of supraepicondylar bridge, 27, medial projection of proximal end of lateral epicondylar crest. B, lateral view of proximal ulna: 1, posteroproximal extreme of olecranon, 2 to 6, posterior margin of proximal ulnar shaft, 7, posterior projection of distal tip of coronoid process, 8, posterior margin of radial notch at level of distal tip of coronoid process, 9, distal tip of coronoid process, 10, anterior end of coronoid process, 11, distal end of trochlear notch, 12 to 16, trochlear notch margin, 17, proximal end of trochlear notch, 18, anterior projection of anconeus process, 19, anterior margin of olecranon, 20, anteroproximal olecranon extreme (on olecranon lateral surface), 21, proximal olecranon margin. C, proximal view of tibia: 1, anterior end of medial condyle, 2 to 6, medial margin of medial condyle, 7, posterior end of medial condyle, 8 to 10, lateral margin of medial condyle, 11, anterior end of lateral condyle, 12 to 15, lateral margin of lateral condyle, 16, posterior end of lateral condyle, 17 to 20, medial margin of lateral condyle, 21, posterior end of intercondyloid area, 22, medial extreme of tibial tuberosity base, 23, lateral extreme of tibial tuberosity base, 24, maximum projection in anterior-lateral margin of non-articular surface, 25, lateral end of cranial intercondylar area. Modified from Ercoli (2010) and Ercoli & Prevosti (in press).
Figure 6 in Relationships of the haematophagous marine snail Colubraria (Rachiglossa: Colubrariidae), within the neogastropod phylogenetic framework
Figure 6. Phylogenetic relationships among the species in the BUC data set (see text). Topology derived after a Bayesian inference. Numbers above the branches are the Bayesian posterior support values; numbers below the branches are the bootstrap support values from a maximum-likelihood (ML) analysis.
Figure 5 in Relationships of the haematophagous marine snail Colubraria (Rachiglossa: Colubrariidae), within the neogastropod phylogenetic framework
Figure 5. Phylogenetic relationships among the species in the NEO data set (see text). Topology derived after a Bayesian inference. Numbers above the branches are the Bayesian posterior support values; numbers below the branches are the bootstrap support values from a maximum-likelihood (ML) analysis.
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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.