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FIG. 3. — A-C in Vertical Gradient of Epiphytic Bryophytes in the Amazon: the Rule and its Exception
FIG. 3. — A-C, Overview of the number of species and shared species per vegetation type. Horizontal bars represent the total richness per zone; vertical bars represent the number of species found per each zone (points) and the number of species shared between zones (points connected by lines); D, mean and standard error of species richness per guild in the zones; E-G, association between zones and guilds based on the absolute frequency of taxa. Abbrevations: Sun, Sun specialist epiphytes; Sha, Shade specialist epiphytes, Gen, Generalist epiphytes; Z, Zone.
FIG. 1 in Vertical Gradient of Epiphytic Bryophytes in the Amazon: the Rule and its Exception
FIG. 1. — Sampling methods and study area. TABLE 2. — Similarity (Sørensen) and dissimilarity (Bray-Curtis) indices between height zones and vegetation types. Species richness and diversity per height zone are highlighted in gray.
BRAIN Journal-Right-Linear Languages Generated in Systems of Knowledge Representation based on LSG-Right-Figure 2. The representation of the rule
<p>In order to model these derivations in the stratified graph G, each production of the grammar will be represented in the labeled graph G0 by a direct arc of the form given in Figure 2.</p> <p> </p>
Data from Figures in "Selection rules for cavity-enhanced Brillouin light scattering from magnetostatic modes"
<p>Data from figures in our paper "Selection rules for cavity-enhanced Brillouin light scattering from magnetostatic modes" in Physical Review B. The figures are in an Origin file (OriginPro 2016). Matlab code (R2016b) that can be used to generate plots of the magneto-static modes is also included.</p>
CVL Ruling Database
<p>The CVL ruling dataset was synthetically generated to allow for comparing different ruling removal methods. It is based on the ICDAR 2013 Handwriting Segmentation database [1]. It was generated by synthetically adding four different ruling images resulting in a total of 600 test images. The pixel values are:</p> <ul> <li>255 background</li> <li>155 ruling</li> <li>100 text</li> <li>0 ruling and text (overlaping)</li> </ul> <p>For processing, a binary image must be generated which sets all pixels to 0 that are not 255. When evaluating, the line GT image can be found by setting all pixel having value 155 to one (e.g. linImg = img == 155). The text GT image can be extracted by setting all values below 155 to zero (e.g. txtImg = img < 155). Then, true positives (tp), false positives (fp) and false negatives (fn) are defined as:</p> <ul> <li>tp = result & linImg & !txtImg</li> <li>fp = result & !txtImg</li> <li>fn = !result & linImg & !txtImg</li> </ul> <p>The database ships with a Matlab that gives evaluation results if all images are already processed.</p>
Mining Rule Violations in JavaScript Code Snippets
<p><strong>Content of this repository</strong><br> This is the repository that contains the scripts and dataset for the MSR 2019 mining challenge</p> <p>Github Repository with the software used : <a href="https://github.com/urielfcampos/linting-js-codesnippets">here</a>.<br> =======</p> <p><strong>DATASET</strong><br> The dataset was retrived utilizing google bigquery and dumped to a csv<br> file for further processing, this original file with no treatment is called jsanswers.csv, here we can find the following information :<br> 1. The Id of the question (PostId)<br> 2. The Content (in this case the code block)<br> 3. the lenght of the code block<br> 4. the line count of the code block<br> 5. The score of the post<br> 6. The title</p> <p>A quick look at this files, one can notice that a postID can have multiple rows related to it, that's how multiple codeblocks are saved in the database.</p> <p><strong>Filtered Dataset:</strong></p> <p><strong>Extracting code from CSV</strong><br> We used a python script called "ExtractCodeFromCSV.py" to extract the code from the original csv and merge all the codeblocks in their respective javascript file with the postID as name, this resulted in 336 thousand files.</p> <p><strong>Running ESlint</strong><br> Due to the single threaded nature of ESlint, we needed to create a script to run ESlint because it took a huge toll on the machine to run it on 336 thousand files, this script is named "ESlintRunnerScript.py", it splits the files in 20 evenly distributed parts and runs 20 processes of esLinter to generate the reports, as such it generates 20 json files.</p> <p><strong>Number of Violations per Rule</strong><br> This information was extracted using the script named "parser.py", it generated the file named "NumberofViolationsPerRule.csv" which contains the number of violations per rule used in the linter configuration in the dataset.</p> <p><strong>Number of violations per Category</strong><br> As a way to make relevant statistics of the dataset, we generated the number of violations per rule category as defined in the eslinter website, this information was extracted using the same "parser.py" script.</p> <p><strong>Individual Reports</strong><br> This information was extracted from the json reports, it's a csv file with PostID and violations per rule.</p> <p><strong>Rules</strong><br> The file Rules with categories contains all the rules used and their categories.</p> <p> </p>
Fig. 2. a in Not playing by the rules: Unusual patterns in the epidemiology of parasites in a natural population of feral horses (Equus caballus) on Sable Island, Canada
Fig. 2. a) Dictyocaulus arnfieldi first-stage larvae showing typical granular appearance and beginning of cuticular separation b) closer view of tail showing stylet, or spear.
Fig. 1 in Not playing by the rules: Unusual patterns in the epidemiology of parasites in a natural population of feral horses (Equus caballus) on Sable Island, Canada
Fig. 1. Map of Sable Island, Canada, which is about 50 km long, 1 km wide at its widest point, and in total, 34 km2 (from Gold et al., 2019).
Fig. 3 in Not playing by the rules: Unusual patterns in the epidemiology of parasites in a natural population of feral horses (Equus caballus) on Sable Island, Canada
Fig. 3. Proportions of third-stage larvae of large and small strongyle species cultured from feces of 81 Sable Island horses in summer 2014, showing an unusual dominance of S. equinus in adult horses. Larvae with a rhabditiform pharynx were rare in young (1–3 years) and adult horses (≥3 years), but common in foals, which could represent larvae of Strongyloides westeri.
Fig. 17.4 in Chapter 17: Gigantism, Dwarfism, and Cope's Rule: "Nothing in Evolution Makes Sense without a Phylogeny"
Fig. 17.4. Left, phylogeny of the Equidae, with emphasis on the North American record. Right, temporal distribution of the Equidae, with relative size indicated by skull length derived from toothlength dimensions (see appendix 17.2 and methodology discussion in text). Branches indicated by A, B, and C represent bodysize increase (giantism); D, E, F, and G represent bodysize decrease (nanism).
Fig. 17.2 in Chapter 17: Gigantism, Dwarfism, and Cope's Rule: "Nothing in Evolution Makes Sense without a Phylogeny"
Fig. 17.2. (a) The most recent phylogenetic hypothesis of varanid relationships based on mtDNA (Ast, 2001) compared to (b) a compilation of the hypotheses of bodysize evolution of varanids (taken from Pianka, 1995). The maximum total lengths for the species were retrieved from King and Green, 1999, and Mertens, 1942; these are listed in appendix 17.1. Note the following terminal clades were collapsed for the sake of brevity: Varanus salvator togianus, V. salvator bivittatus, V. indicus, and V. panoptes (horni).
Fig. 17.3 in Chapter 17: Gigantism, Dwarfism, and Cope's Rule: "Nothing in Evolution Makes Sense without a Phylogeny"
Fig. 17.3. Patterns of bodysize evolution in fossil horses from North America, based on MacFadden (1987; modified figure reproduced in MacFadden, 1992). Reproduced with permission of Cambridge University Press.
Fig. 17.1 in Chapter 17: Gigantism, Dwarfism, and Cope's Rule: "Nothing in Evolution Makes Sense without a Phylogeny"
Fig. 17.1. Threetaxon statements illustrating the four kinds of bodysize change discussed in the text.
Fig. 5. Majority rule tree from the 87 in A new freshwater basal eucryptodiran turtle from the Early Cretaceous of Spain
Fig. 5. Majority rule tree from the 87 maximum parsimonious trees produced by the cladistic analysis of Hoyasemys jimenezi in the modified data set of Joyce (2007). Retention index (RI) = 0.863 and consistency index (CI) = 0.569. Values refer percentages under 100% obtained in the majority rule analysis. Branchs with percentage under 50% are collapsed. Letters refer to the nodes mentioned in the text.
Fig. 2. Majority rule tree from the 73 in The European Early Cretaceous cryptodiran turtle Chitracephalus dumonii and the diversity of a poorly known lineage of turtles
Fig. 2. Majority rule tree from the 73 most parsimonious trees produced by the cladistic analysis of Chitracephalus dumonii using the modified data set of Joyce (2007) proposed in Pérez−García et al. (2012). Retention index (RI) = 0.872 and consistency index (CI) = 0.567. Values refer to percentages under 100% obtained in the majority rule analysis; those with values below 50% are collapsed. Letters refer to the nodes mentioned in the text.
A tectonic-rules-based mantle reference frame since 1 billion years ago – implications for supercontinent cycles and plate–mantle system evolution
<p>The archive <strong>Muller_etal_2022_SE_1Ga_Opt_PlateMotionModel.zip</strong> contains the files for the plate model in an optimised mantle reference frame. GPlates or pyGPlates software (<a href="https://www.gplates.org/">www.gplates.org</a>) is needed to read these files. </p> <p>The archive <strong>Muller_etal_2022_SE_mantle-ref-frame-oceanic-crustal-agegrids.zip</strong> contains the oceanic crustal age grids in netCDF-4 format for the optimised mantle reference frame plate model, while the archive <strong>Muller_etal_2022_SE_PMAG_oceanic-crustal-agegrids.zip</strong> contains the oceanic crustal age grids in netCDF-4 format for the paleomagnetic reference frame plate model from Merdith et al. (2021).</p> <p> </p> <p>The agegrids associated with this model can be accessed at: <a href="https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Muller_etal_2022_SE/" target="_blank" rel="noopener">https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Muller_etal_2022_SE/</a></p>
Conservation of animal genome structure is the exception not the rule
<p>Species from diverse animal lineages, including molluscs, annelids, echinoderms, hemichordates, and cephalochordates, have retained groups of orthologous genes on the same chromosomes for over half a billion years since the last common ancestor of bilaterians. Though there are notable exceptions, it has been proposed that the conservation of chromosome-scale gene linkages is the norm among animals. Here, by examining interchromosomal rearrangements in 64 chromosome-level genomes across 15 bilaterian phyla and at least 52 classes, we show that, though striking, cases of genome structure conservation are exceptionally rare. The ubiquity of massive genome rearrangements suggests that, in general, chromosome-scale gene linkages are of minimal importance to animal genome function.</p> <p>This project includes gene models for 14 genome assemblies annotated in this study, with files available for coding sequences (*.fasta), protein sequences (*.faa), and gene annotations in GTF format (*.gtf), as detailed below. Additionally, a spreadsheet containing all accession numbers and genome metadata for 64 bilaterian genomes and 3 cnidarian genomes is provided as a Supplemental Dataset.</p> <p>- Amphiscolops sp. MND2022 (acoel worm; phylum Xenacoelomorpha)<br>- Antedon bifida (crinoid; phylum Echinodermata)<br>- Carcinoscorpius rotundicauda (horseshoe crab; phylum Arthropoda)<br>- Convolutriloba macropyga (acoel worm; phylum Xenacoelomorpha)<br>- Emplectonema gracile (ribbon worm; phylum Nemertea)<br>- Gordius sp. MW1 (horsehair worm; phylum Nematomorpha)<br>- Hypsibius dujardini (water bear; phylum Tardigrada)<br>- Ophiura sarsii (brittle star; phylum Echinodermata)<br>- Schizocardium californicum (acorn worm, phylum Hemichordata)<br>- Schmidtea mediterranea (planarian; phylum Platyhelminthes)<br>- Strigamia acuminata (centipede; phylum Arthropoda)<br>- Styela plicata (tunicate; phylum Chordata)<br>- Trichinella spiralis (nematode; phylum Nematoda)<br>- Trididemnum miniatum (tunicate; phylum Chordata)</p> <p>Custom R scripts are available at our GitHub repository (https://github.com/symgenoevolab/animal_genome_structure) under the MIT License.</p>
MUTUAL RECOGNITION IN PRISON RULES AND PRE -TRIAL DETENTION AND DETENTION IN EU
<p><span>The purpose of this study is to highlight the important aspects on the creation of a criminal justice section inside prisons, as well as the creation of minimum requirements for jail and detention settings and a uniform set of rights for all EU inmates. The Council of Europe believes that efforts should be taken to improve mutual trust and to more effectively implement the concept of mutual recognition in custody, as stated in the Stockholm Program, which calls for the Council to address detention and related concerns. Among the instruments of mutual recognition of terms of incarceration that may be affected we mention the European Arrest Warrant issued by the Council, the transfer of prisoners, the mutual recognition of alternative sanctions and judicial proceedings, and the European supervision order. Following the analysis and empirical research, the paper summarizes that without mutual trust in detention, the European Union's mutual recognition instruments affecting detention will not work properly, as one Member State is unwilling to recognize and implement a decision taken by the authorities of another Member State. Without greater efforts to improve detention conditions and promote alternatives to detention, it may be difficult to develop closer judicial cooperation between Member States.</span></p>
Data for: Semiclassical approach to photophysics beyond Kasha's rule and vibronic spectroscopy beyond the Condon approximation. The case of azulene
<p>Data for publication: A. Prlj, T. Begušić, Z. T. Zhang, G. C. Fish, M. Wehrle, T. Zimmermann, S. Choi, J. Roulet, J.-E. Moser, and J. Vaníček, <em>J. Chem. Theory Comput.</em> <strong>16</strong> (4), 2617–2626 (2020).</p> <p>Contains simulated linear absorption and emission spectra of azulene, excited-state and ground-state ab initio trajectories and single-point calculations, and results of nonadiabatic mixed quantum-classical simulations.</p>
Text to Rule Conversion Full Results for Anirudh Prabhu's PhD Dissertation
<p>Part of Anirudh Prabhu PhD Dissertation. Contains the results of running the text to rule conversion workflow described in chapter 5 of the dissertation. The dataset preview and its description can be found in Appendix E of the dissertation document. </p>
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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.