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870 results for “boxing”
Data from: Associations between human non-motorized recreational activity on nest box occupation, exploratory behaviour, and breeding success in a passerine bird
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Do nest boxes breed the target species or its competitors? A case study of a critically endangered bird
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Efficacy of intervention to relieve nest box competition for Orange‐bellied Parrot Neophema chrysogaster
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What makes a good bat box? How box occupancy depends on box characteristics and landscape-level variables
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3D printing lifts the lid on black box instruments
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Unpacking the "black box": improving ecological interpretation of regression based models
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Reciprocal expression of MADS-box genes and DNA methylation reconfiguration initiate bisexual cones in spruce
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Data from: Thinking outside the box: problem-solving in free-living lizards
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Data for: Microclimate shifts in nest-boxes and natural cavities throughout reproduction
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Data from: Comparative assessment of a novel fan box trap for collecting Anopheles farauti and culicine mosquitoes alive in tropical north Queensland, Australia
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Nest-boxes alter the reproductive ecology of urban cavity-nesters in a species-dependent way
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Bounding-box detection data for delphinid whistles
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Box 4 in The species Severe acute respiratory syndromerelated coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2
Box 4 | Classifying SARS-CoV-2 The species demarcation threshold (also known as demarcation limit) in the family Coronaviridae is defined by viruses whose PPD(s) may cross the inter-species demarcation PPD threshold (threshold 'violators'). Due to their minute share of ~10–4 of the to- tal number of all intra- and inter-species PPDs, these violators may not even be visually recognized in a conventional diagonal plot clus- tering viruses on a species basis (panel a of the figure in Box 4). Furthermore, they do not involve any virus of the species Severe acute respiratory syndrome-related coronavirus, as is evident from the analysis of maximal intraspecies PPDs of 2,505 viruses of all 49 coronavirus species (of which 39 are established and 10 are pending or tentative) (panel b of the figure in Box 4) and PDs of 256 viruses of this species (panel c of the figure in Box 4). Thus, the genomic variation of the known viruses of the species Severe acute respiratory syndrome-related coronavirus is smaller compared to that of other comparably well-sampled species—for example, those prototyped by MERS-CoV, human coronavirus OC43 (HCoV-OC43) and in- fectious bronchitis virus (IBV) (panel b of the figure in Box 4)—and this species is well separated from other known coronavirus species in the sequence space. Both of these characteristics facilitate the un- ambiguous assignment of SARS-CoV-2 to this species. Intra-species PDs of SARS-CoV-2 belong to the top 25% of this species and also include the largest PD between SARS-CoV-2 and an African bat virus isolate (SARSr-CoV_BtKY72)56 (panel c of the figure in Box 4), representing two basal lineages within the species Severe acute respiratory syndrome-related coronavirus that constitute very few known viruses (Fig. 2b,c). These relationships stand in contrast to the shallow branching of the most populous lineage of this species, which includes all the human SARS-CoV isolates collected during the 2002–2003 outbreak and the closely related bat viruses of Asian origin identified in the search for the potential zoonotic source of that epidemic57. This clade structure is susceptible to homologous recombination, which is common in this species44,58,59; to formalize clade definition, it must be revisited after the sampling of viruses representing the deep branches has improved sufficiently. The current sampling defines a very small median PD for human SARS-CoVs, which is approximately 15 times smaller than the median PD determined for SARS-CoV-2 (0.16% versus 2.6%; panel c of the figure in Box 4). This small median PD of human SARS-CoVs also dominates the species- wide PD distribution (0.25%; panel c of the figure in Box 4). Pairwise distance demarcation of species in the family Coronaviridae. a, Diagonal matrix of PPDs of 2,505 viruses clustered according to 49 coronavirus species, 39 established and 10 pending or tentative, and ordered from the most to least populous species, from left to right; green and white, PPDs smaller and larger than the inter-species threshold, respectively. Areas of the green squares along the diagonal are proportional to the virus sampling of the respective species, and virus prototypes of the five most sampled species are specified to the left; asterisks indicate species that include viruses whose intra-species PPDs crossed the inter-species threshold (threshold 'violators'). b, Maximal intra-species PPDs (x axis, linear scale) plotted against virus sampling (y axis, log scale) for 49 species (green dots) of the Coronaviridae. Indicated are the acronyms of virus prototypes of the seven most sampled species. Green and blue plot sections represent intra-species and intra-subgenera PPD ranges. The vertical black line indicates the inter-species threshold. c, Shown are the PDs of non-identical residues (y axis) for four viruses representing three major phylogenetic lineages (clades) of the species Severe acute respiratorysyndrome-related coronavirus (panel b) and all pairs of the 256 viruses of this species ('all pairs'). The PD values were derived from pairwise distances in the MSA that were calculated using an identity matrix. Panels a and b were adopted from the DEmARC v.1.4 output.
Box 2 in Assessing dinosaur growth patterns: a microscopic revolution
Box 2. Assessing dinosaur longevity using the principle of Amprino's rule A less commonly utilized aging technique for dinosaurs and basal birds uses a principle called 'Amprino's rule' (sensu [11,22]). The formative rate of tissue types from living animals is used to estimate lengths of time for bone development and thus determine longevity. This aging technique is the only tested means to age animals in cases where growth lines were not deposited throughout life. The method has seen limited application in assessing dinosaur [11,22,31] and basal bird [11,36] longevity. In Figure Ia, the bones of an ostrich (Struthio camelus) were labeled by periodically administering fluorochromic chemical labels to establish the formative rate of the bone tissue (marked yellow and red; photo courtesy of Kristina Curry Rogers). Note that the values shown here are hypothetical and intended only to illustrate the methodology. The formation rate is divided into the amount of bone that formed during development (measured radially; Figure Ib) to reveal longevity.
Box 1 in Assessing dinosaur growth patterns: a microscopic revolution
Box 1. Assessing dinosaur longevity from growth-line counts Making growth curves for dinosaurs requires estimations of longevity for various individuals throughout development. To do this, osteohistologists sample bones from specimens spanning juvenile through adult developmental stages. The bones that are utilized show minimal remodeling (i.e. replacement or loss of the original bone during life because of metabolic, reproductive, biomechanical, or skeletal repair considerations [9]) and therefore provide a nearly complete record of development. Traditionally, dinosaur researchers have used the femur, but other bones have been shown to be equally or more efficacious in some taxa. For example, multi-element sampling in tyrannosaurs has shown (Figure Ia) that the bones shown in blue [pubis, fibula, ribs, gastralia (i.e. belly ribs) and some post-orbital skull bones] work better than the femur in these animals [12,24]. The bones are sectioned transversely at mid-shaft using a slow-speed saw fitted with a diamond-tipped blade (Figure Ib). The sections (Figure Ic) are then affixed to glass petrographic slides and sanded/polished for viewing with polarized and/or reflected microscopy. On very large specimens for which making entire cross-sectional slides is difficult, researchers polish the cut faces of the bones to reveal 'polished lines' that reflect hardness differences between individual growth lines [20,23,31]. Alternatively, Sanders has developed a method whereby a diamond-tipped drill coring-bit is used to extract a cylinder of bone from which polished-line preparations or petrographic slides can be made [23]. Aging is conducted by making total growth line counts within elements [28]. Here (Figure Ic), a thin-sectioned, dorsal rib from TYrannosaurus rex (Field Museum of Natural History, Chicago, FMNH PR 2081) shows growth lines (arrows) that were counted to age this specimen. Each line represents a period of slowed and/or potential stoppage in tissue deposition [9]. The highly vascularized regions between the rings are known as zones and represent periods of active growth [8,9]. The inset box denotes a region late in development composed of tightly stacked growth rings known as an external fundamental system that indicates when growth slowed precipitously [22,27]. At this point in development, somatic maturity and full-adult size was reached. (Figure I redrawn and reproduced with permission from [12]. Scale bar=10 mm.)
Using White-Box Test Generation During Development: A Replicated Study
<p>This package contains the artifacts for our external, differentiated replication of an empirical study on using white-box test generation.</p> <p>The original experiment is described in the following paper.</p> <blockquote> <p>José Miguel Rojas, Gordon Fraser, and Andrea Arcuri. 2015. Automated unit test generation during software development: a controlled experiment and think-aloud observations. In Proceedings of the 2015 International Symposium on Software Testing and Analysis (ISSTA 2015), 338–349. DOI: 10.1145/2771783.2771801</p> </blockquote> <p>30 developers and students participated in the experiment in January 2016.</p> <p>The main difference in the replication was using the IntelliTest test generator tool instead of EvoSuite.</p> <p>The contents of the package are the followings.</p> <ul> <li>/assignments <ul> <li>session_starts_endings.csv - Timestamps when each session was started</li> <li>assignments_with_projects.csv - Assigments of participants to projects, classes and sessions</li> </ul> </li> <li>/projects <ul> <li>/golden - Contains the golden implementation and test suites of all 4 classes</li> <li>/user - Contains the user implementation and test method stubs of all 4 classs</li> </ul> </li> <li>/results <ul> <li>time_merged.csv - File of timing analysis containing each test run of subjects</li> <li>results.csv - Contains the coverage and other required data of each participant tasks</li> <li>exit.csv - Answers of the exit survey</li> <li>background.csv - Answers of the background questionnaire</li> </ul> </li> <li>/scripts <ul> <li>/ps <ul> <li>Get-Results.ps1 - Gets the results of both tasks for one specified participant (invokes MSBuild, MSTest, VisualMutator, OpenCover)</li> <li>Get-Failures-Errors.ps1 - Gets failures and errors of both tasks for one specified participant (invokes MSBuild, MSTest)</li> <li>Get-TimeData.ps1 - Iterates over all test runs for each participant</li> </ul> </li> <li>/r <ul> <li>likert.R - Generates the Likert chart</li> <li>si_st.R - Generates table of subject implementation executed with subject test suites</li> <li>gi_st.R - Generates table of results where subject test suites was run on golden implementation</li> <li>time_spent_tests.R - Generates a table of time and activity of testing</li> <li>errors_failures.R - Generates table of errors and failures obtained using the golden test suite</li> <li>correlation_analysis.R - Generates table containing correlation between lack of correctness and IntelliTest usage</li> </ul> </li> </ul> </li> </ul>
From smart apes to human brain boxes. A uniquely derived brain shape in late hominins clade: supplementary material
<p>DATA.rda: an RData file containing the phylogenetic tree, the landmark and semilandmark sets used in the analyses of the endocast shape (123 specimens), the semilandmark sets used in the asymmetry analyses (120 specimens), the vector of the corresponding ECV values and a mesh containing the triangulated semilandmark configuration.</p> <p>script.R: the annotated script used to replicate the analyses reported in this study.</p>
Object bounding box annotations for the GTEA Gaze+ dataset
<p>Object bounding box annotations for the GTEA Gaze+ dataset of the works <em>Learning to recognize daily actions using gaze</em> (Fathi et al., 2012) and <em>Delving into Egocentric Actions </em>(Li et al., 2015). The dataset contains folders for each of the subjects, within each of them folders for actions, and, within each action folder, a folder for each video. The video folder has a name composed of <name of the original video>_<start frame>_<end frame>. Within this folder, a json file for some frames can be found.</p> <p>The json contains two keys: <em>filename</em> and <em>objects</em>. <em>filename</em> refers to the path to the image and <em>objects</em> to a dictionary of objects. The keys of the dictionary are the objects present in the image. Each of the objects values is a list containing bounding box coordinates. Each coordinate list is composed of the ymin, xmin, ymax and ymax values.</p>
Contrasting signatures of introgression in North American box turtle (Terrapene spp.) contact zones
Hybridization occurs differentially across the genome in a balancing act between selection and migration. With the unprecedented resolution of contemporary sequencing technologies, selection and migration can now be effectively quantified such that researchers can identify genetic elements involved in introgression. Furthermore, genomic patterns can now be associated with ecologically relevant phenotypes, given availability of annotated reference genomes. We do so in North American box turtles (<i>Terrapene</i>) by deciphering how selection affects hybrid zones at the interface of species-boundaries and identifying genetic regions potentially under selection that may relate to thermal adaptations. Such genes may impact physiological pathways involved in temperature-dependent sex determination, immune system functioning, and hypoxia tolerance. We contrasted these patterns across inter- and intra-specific hybrid zones that differ temporally and biogeographically. We demonstrate hybridization is broadly apparent in <i>Terrapene</i>, but with observed genomic cline patterns corresponding to species boundaries at loci potentially associated with thermal adaptation. These loci display signatures of directional introgression within intra-specific boundaries, despite a genome-wide selective trend against intergrades. In contrast, outlier loci for inter-specific comparisons exhibited evidence of being under selection against hybrids. Importantly, adaptations coinciding with species-boundaries in <i>Terrapene</i> overlap with climatic boundaries and highlight the vulnerability of these terrestrial ectotherms to anthropogenic pressures.
Simulated pollen microscope slides for segmentation/bounding box regression and classification
<p><strong>Pollen dataset</strong></p> <p>Sebastian Seurig, Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, TU Dresden<br> (<a href="https://orcid.org/0000-0001-6511-0102">https://orcid.org/0000-0001-6511-0102</a>)<br> Peter Steinbach, Helmholtz AI, Artificial Intelligence Cooperation Unit, Helmholtz-Zentrum Dresden-Rossendorf<br> (<a href="https://orcid.org/0000-0002-4974-230X">https://orcid.org/0000-0002-4974-230X</a>)<br> Nico Scherf, Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, TU Dresden and Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig<br> (<a href="https://orcid.org/0000-0003-4003-9121">https://orcid.org/0000-0003-4003-9121</a>)<br> Ingo Röder, Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, TU Dresden</p> <p>This artificial dataset was created for testing machine learning models on segmentation or bounding box regression and classification tasks.<br> It contains 80.000 (1280x1280 RGB) images of airborne pollen of different sizes within their natural range:</p> <ul> <li>2x10.000 images each Chenopodium bonus-henricus and Corylus colurna making up the medium-sized pollen</li> <li>10.000 images Urtica dioica making up the smaller pollen</li> <li>10.000 images Secale cereale making up the larger pollen</li> <li>4x10.000 images each containing artifacts such as dust or bursted pollen and a mix of pollen in the following ratios:<br> - 'equal_split' 25% each class<br> - 'smaller_pollen_split' 70% Urtica dioica, *<br> - 'middle_pollen_split' 40% Corylus colurna, 10% Chenopodium bonus-henricus, *<br> - 'bigger_pollen_split' 70% Secale cereale, *<br> - * the rest of the pollen split equally between the remaining classes<br> Labels consist of :</li> <li>monochrome masks of each pollen slide (ignoring artifacts) for segmentation</li> <li>x and y-coordinates of the bounding boxes containing all pixels of each of the pollen for regression</li> <li>class names for each labeled pollen.</li> </ul> <p>For further questions and suggestions, please do not hesitate to contact the authors.</p> <p>Extensive code and configuration settings for the generator used can be found at <a href="https://github.com/seurig/slide-generator">https://github.com/seurig/slide-generator</a>.<br> All raw images used to generate this dataset were taken from <a href="https://pollen.tstebler.ch/">https://pollen.tstebler.ch/</a>.</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.