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Datasets and Codes for "Relative Moment Tensor Inversion for Microseismicity: Application to Clustered Earthquakes in the Cascadia Forearc"
<p>This Zenodo record contains the supplementary datasets and code for the paper titled "Relative Moment Tensor Inversion for Microseismicity: Application to Clustered Earthquakes in the Cascadia Forearc."<br><br></p> <p><strong>Datasets</strong></p> <ul> <li>phases.txt<br> Contains phases used for the event location and moment tensor inversion.<br> Format: ID, station, phase, year, month, day, secday<br> ID: Event identifier (same for all files)<br> station: Station name<br> phase: 1 for P-wave or 2 for S-wave<br> secday: Seconds in the day</li> <li>polarity.txt<br> Contains first motion P polarity used in the study.<br> Format: ID, station, polarity, trust, type<br> polarity: 1 for up or -1 for down<br> trust: Value between 0 and 1, indicating confidence level.<br> type: E for emergent or I for impulsive<br> Note that the arrival type has been automatically assigned and not double-checked.</li> <li>relocation.txt<br> HypoDD relocation file (see hypoDD manual for full description).<br> Format: ID, LAT, LON, DEPTH, X, Y, Z, EX, EY, EZ, YR, MO, DY, HR, MI, SC, MAG, NCCP, NCCS, NCTP, NCTS, RCC, RCT, CID</li> <li>MT_soluton.txt<br> Contains all double-couple moment tensor solutions.<br> Format: ID, strike, dip, rake, mag, kagan_std<br> mag: Moment magnitude (Mw); "None" if the event is not considered stable<br> kagan_std: Quality interpretation of the moment tensors using Kagan angle standard deviation, as described in the main paper.</li> </ul> <p> </p> <p><strong>Codes</strong></p> <p>Future development of the relative moment tensor algorithm will be conducted on GitHub as part of the Marie-Sklodowska-Curie Action relMT funded by the European Union (https://github.com/wasjabloch/relMT)</p> <p>Here are the files in Codes.zip:</p> <ul> <li>synthetics.zip<br> Contains codes for performing and testing synthetic moment tensor inversion.</li> <li>relMT.zip<br> Contains the code for performing moment tensor inversion on real data.</li> <li>intrustion.txt<br> Contains instructions for setting up and running the codes.</li> <li>environment_MAC.yml<br> File to create the python environment on a MAC or LINUX machine.</li> <li>environment_WINDOWS.yml<br> File to create the python environment on a WINDOWS machine.</li> </ul>
Integrated Omics-Based Discovery of Novel Genes, Secondary Metabolites Clusters, and Small Molecules in Penicillium spp. with Disparate Fungal Isolates
<p><em><span>Penicillium expansum</span></em><span> is a ubiquitous postharvest pathogen of pome fruit that causes blue mold decay of apple fruit while another member of the genus, <em>P. chrysogenum</em><span>,</span><em> </em>is a well-studied saprophyte used for antibiotic and small molecule production. While these two fungi have been investigated individually, the recent discovery of <em>P. chrysogenum </em>hindering <em>P. expansum</em> apple fruit infection has not been well studied. To shed light on this interaction between the two species, we conducted a comparative transcriptomic, metabolomic, and genomic study. Global transcriptional and metabolomic outputs were disparate between the species, nearly identical for the <em>P. chrysogenum </em>isolates, and different between <em>P. expansum </em>isolates. Further, the two <em>P. chrysogenum</em> genomes revealed secondary metabolite gene clusters that differed from <em>P. expansum</em>. This included the absence of an intact patulin gene cluster in <em>P. chrysogenum</em>, which corroborates the metabolomic data regarding the species’ inability to produce patulin. Additionally, <em>P. expansum </em>virulence gene homologues were identified in <em>P. chrysogenum </em>and were similarly transcriptionally regulated <em>in vitro</em>. Molecules with potential antimicrobial activity, and phytohormones like indole-3-acetic acid (IAA), were detected for the first time in <em>P. expansum</em> while pharmacological compounds like the well-studied antibiotic penicillin G were identified in <em>P. chrysogenum</em> culture supernatants. Our findings provide new omics-based resources that enable the study of small molecule production of interest, the potential of <em>Penicillium</em>-derived antimicrobials for postharvest decay control, and <em>P.</em> <em>expansum’s</em> metabolites roles in host-pathogen interactions. </span></p>
Extended data tables to Haering and Habermann, F1000Res, RNfuzzyApp: an R shiny RNA-seq data analysis app for visualisation, differential expression analysis, time-series clustering and enrichment analysis
<p><b>Background</b> </p> <p>RNA-seq is a widely adopted affordable method for large scale gene expression profiling. However, user-friendly and versatile tools for wet-lab biologists to analyse RNA-seq data beyond standard analyses such as differential expression, are rare. Especially, the analysis of time-series data is difficult for wet-lab biologists lacking advanced computational training. Furthermore, most meta-analysis tools are tailored for model organisms and not easily adaptable to other species.</p> <p><b>Results</b></p> <p>With RNfuzzyApp, we provide a user-friendly, web-based R-shiny app for differential expression analysis, as well as time-series analysis of RNA-seq data. RNfuzzyApp offers several methods for normalization and differential expression analysis of RNA-seq data, providing easy-to-use toolboxes, interactive plots and downloadable results. For time-series analysis, RNfuzzyApp presents the first web-based, automated pipeline for soft clustering with the Mfuzz R package, including methods to aid in cluster number selection, Mfuzz loop computations, cluster overlap analysis, as well as cluster enrichments.</p> <p><b>Conclusion</b></p> <p>RNfuzzyApp is an intuitive, easy to use and interactive R shiny app for RNA-seq differential expression and time-series analysis, offering a rich selection of interactive plots, providing a quick overview of raw data and generating rapid analysis results. Furthermore, its orthology assignment, enrichment analysis, as well as ID conversion functions are accessible to non-model organisms.</p>
Supplement to "Rotation and Lithium Confirmation of a 500 Parsec Halo for the Open Cluster NGC2516"
<p>This repository contains supplementary data to the paper "Rotation and Lithium Confirmation of a 500 Parsec Halo for the Open Cluster NGC2516", which will be published in the Astronomical Journal in 2021 (https://arxiv.org/abs/2107.08050). Please see README.txt for a detailed description of the contents. To unzip and decompress the gzipped tarball file, <em>tar -xvzf ngc2516supplementary.tar.gz</em> should work on most computers.</p>
Clusters of cause specific neonatal mortality and its association with per capita gross domestic product: a structured spatial analytical approach
<p>Database used for the analysis of the manuscript entitled: Clusters of cause specific neonatal mortality and its association with per capita gross domestic product: a structured spatial analytical approach. The aim of the study was to investigate the cluster areas of asphyxia-associated neonatal mortality and to explore the per capita gross domestic product (GDP) as an associated risk factor in São Paulo State (SP), Brazil.</p>
FIGURE 8 in A trilobite cluster from the Silurian Rochester Shale of New York: predation patterns and possible defensive behavior
FIGURE 8. Plot of regressed PC coordinates against log-centroid size and histogram of maximum specimen length, coded for injured and noninjured specimens. A, Regressed PC coordinates against log-centroid size that shows no obvious pattern in injured and noninjured specimens, although many of the larger specimens are injured. B, Histogram of specimen length has an approximately normal distribution with the two largest specimens showing an injury.
FIGURE 1. Slab preserving a in A trilobite cluster from the Silurian Rochester Shale of New York: predation patterns and possible defensive behavior
FIGURE 1. Slab preserving a cluster of 18 fully articulated individuals of Arctinurus boltoni (AMNH- FI-101514–101531) from the mid-Silurian (Wenlock) Rochester Shale, New York state. Stars indicate injured specimens. Scale bar = 10 cm.
FIGURE 5 in A trilobite cluster from the Silurian Rochester Shale of New York: predation patterns and possible defensive behavior
FIGURE 5. Specimens of Arctinurus boltoni with injuries to the thorax (A, B) and with reconstruction that mimics an injury (C, D), under plain and UV light. Arrows point to injuries described in the text. Scale bar = 1 mm. A–B, AMNH-FI-101518. C–D, AMNH-FI-101516.
FIGURE 4 in A trilobite cluster from the Silurian Rochester Shale of New York: predation patterns and possible defensive behavior
FIGURE 4. Further specimens of Arctinurus boltoni with injuries to the pygidium, under plain and UV light. Arrows point to injuries described in the text. Scale bar = 1 mm. A–B, AMNH-FI-101529. C–D, AMNH- FI-101530. E–F, AMNH-FI-101531.
FIGURE 3 in A trilobite cluster from the Silurian Rochester Shale of New York: predation patterns and possible defensive behavior
FIGURE 3. Specimens of Arctinurus boltoni with injuries to the pygidium, under plain and UV light (with brighter areas indicating parts of reconstructed exoskeleton). Arrows point to injuries described in the text. Scale bar = 1 mm. A–B, AMNH-FI-101521. C–D, AMNH-FI-101527.
FIGURE 2 in A trilobite cluster from the Silurian Rochester Shale of New York: predation patterns and possible defensive behavior
FIGURE 2. Diagram of 12 landmarks selected to describe the overall shape of the exoskeleton of Arctinurus boltoni.
FIGURE 7 in A trilobite cluster from the Silurian Rochester Shale of New York: predation patterns and possible defensive behavior
FIGURE 7. Principal components analysis of landmark data, with 49.5% variance in the data explained by the first two PCs (PC1=29.7%, PC2=19.8%). PC1 describes the variation in the intersection of the occipital furrow and anterior-posterior axis and junction points between posterior margin of the 11th tergite. PC2 mostly describes variation in cephalic width.
FIGURE 6 in A trilobite cluster from the Silurian Rochester Shale of New York: predation patterns and possible defensive behavior
FIGURE 6. Arctinurus boltoni specimen AMNH-FI-101520 with injuries to the thorax and pygidium, under A, plain and B, UV light. Arrows point to injuries described in the text. Scale bar = 1 mm.
Text-fig. 1. Scanning electron micrographs of Mugideiriflora portugallica gen. et sp. nov. from the Early Cretaceous Catefica locality, Portugal (holotype, S174254, Catefica sample 150). a) Flower in oblique lateral view showing numerous broad tepals, numerous inwardly curved stamens and the flat floral receptacle with a conical gynoecial region; b–c) Flower in two different oblique apical views showing numerous broad laminar tepals and inwardly curved stamens surrounding the carpels; note cellular differences between outer (op) and inner (in) perianth parts, as well as bases of anthers, apparently with laterally to slightly dorsally placed pollen sacs (arrow heads); d) Detail of flower showing a cluster of poorly differentiated carpels in the center surrounded by elongated stamens; note grooves in the dorsal surface of the stamens indicating the position of the pollen sacs; e) Detail of flower showing the broad bases of the laminar tepals, rhomboidal stamen bases and poorly differentiated carpels; f) Detail of flower showing inwardly arched stamens and poorly differentiated carpels. Scale bars = 1 mm (a–c), 200 µm (d–f). in Multiparted, Apocarpous Flowers From The Early Cretaceous Of Eastern North America And Portugal
Text-fig. 1. Scanning electron micrographs of Mugideiriflora portugallica gen. et sp. nov. from the Early Cretaceous Catefica locality, Portugal (holotype, S174254, Catefica sample 150). a) Flower in oblique lateral view showing numerous broad tepals, numerous inwardly curved stamens and the flat floral receptacle with a conical gynoecial region; b–c) Flower in two different oblique apical views showing numerous broad laminar tepals and inwardly curved stamens surrounding the carpels; note cellular differences between outer (op) and inner (in) perianth parts, as well as bases of anthers, apparently with laterally to slightly dorsally placed pollen sacs (arrow heads); d) Detail of flower showing a cluster of poorly differentiated carpels in the center surrounded by elongated stamens; note grooves in the dorsal surface of the stamens indicating the position of the pollen sacs; e) Detail of flower showing the broad bases of the laminar tepals, rhomboidal stamen bases and poorly differentiated carpels; f) Detail of flower showing inwardly arched stamens and poorly differentiated carpels. Scale bars = 1 mm (a–c), 200 µm (d–f).
Text-fig. 12. Scanning electron microscope (SEM) images of pollen of Sergipea sp. from a group of probable fragmentary pollen sacs; Torres Vedras locality, Portugal. a) Cluster of probable fragmentary pollen sacs that yielded the pollen in this Text-figure; b, c) Pollen grains showing the robust longitudinal ribs separated by prominent areas of granular exine; note the groove along the margins of the longitudinal ribs (arrowheads); d) Pollen grain showing the granular exine flanked by two robust ribs; note the groove along the margins of the longitudinal ribs (arrowheads). Specimen, TV44-S148012 (a–d). Scale bars 150 Μm (a), 12 Μm (c), 6 Μm (b, d). in The Early Cretaceous Mesofossil Flora Of Torres Vedras (Ne Of Forte Da Forca), Portugal: A Palaeofloristic Analysis Of An Early Angiosperm Community
Text-fig. 12. Scanning electron microscope (SEM) images of pollen of Sergipea sp. from a group of probable fragmentary pollen sacs; Torres Vedras locality, Portugal. a) Cluster of probable fragmentary pollen sacs that yielded the pollen in this Text-figure; b, c) Pollen grains showing the robust longitudinal ribs separated by prominent areas of granular exine; note the groove along the margins of the longitudinal ribs (arrowheads); d) Pollen grain showing the granular exine flanked by two robust ribs; note the groove along the margins of the longitudinal ribs (arrowheads). Specimen, TV44-S148012 (a–d). Scale bars 150 Μm (a), 12 Μm (c), 6 Μm (b, d).
Text-fig. 18. Scanning electron microscope (SEM) images of a fruit of Canrightia sp. with associated pollen; Torres Vedras locality, Portugal. a) Fruit in lateral view showing prominent cavities in the fruit wall formed by the scattered oil bodies and the broad hypanthium fused to the base of the fruit (arrowhead); b) Fruit surface showing epidermal cells and the scattered oil cells embedded in the fruit wall (arrowheads); c) Cluster of monocolpate pollen grains in the probable stigmatic region of the fruit; d) Pollen grains showing the long colpus and semitectate-reticulate pollen wall; e) Pollen wall showing the reticulum with large and small lumina, and scattered, compressed columellae supporting the smooth muri. Specimen, TV142-S170213. Scale bars 300 Μm (a), 100 Μm (b), 30 Μm (c), 6 Μm (d), 1 Μm (e). in The Early Cretaceous Mesofossil Flora Of Torres Vedras (Ne Of Forte Da Forca), Portugal: A Palaeofloristic Analysis Of An Early Angiosperm Community
Text-fig. 18. Scanning electron microscope (SEM) images of a fruit of Canrightia sp. with associated pollen; Torres Vedras locality, Portugal. a) Fruit in lateral view showing prominent cavities in the fruit wall formed by the scattered oil bodies and the broad hypanthium fused to the base of the fruit (arrowhead); b) Fruit surface showing epidermal cells and the scattered oil cells embedded in the fruit wall (arrowheads); c) Cluster of monocolpate pollen grains in the probable stigmatic region of the fruit; d) Pollen grains showing the long colpus and semitectate-reticulate pollen wall; e) Pollen wall showing the reticulum with large and small lumina, and scattered, compressed columellae supporting the smooth muri. Specimen, TV142-S170213. Scale bars 300 Μm (a), 100 Μm (b), 30 Μm (c), 6 Μm (d), 1 Μm (e).
Figure 27 Apical sensorial setal cluster area and setaed3 and d4 in Review of Amblyseius Berlese (Acari: Phytoseiidae) in Western Siberia, Russia
Figure 27 Apical sensorial setal cluster area and setaed3 and d4 of tarsus I, female, right leg, dorsal aspect. A – Amblyseius rademacheri Dosse, 1958, B – Amblyseius obtusus (Koch, 1839), C – Amblyseius omaloensis Gomelauri, 1968, D – Amblyseius myrtilli Papadouliset al., 2009.
Reproduction package for "A Shock Near the Virial Radius of the Perseus Cluster"
<p>This is the reproduction package of the paper "A Shock Near the Virial Radius of the Perseus Cluster", published by Astronomy & Astrophysics (A&A) on Aug 25th, 2021.</p> <p>ADS link: https://ui.adsabs.harvard.edu/abs/2021A%26A...652A.147Z/abstract</p>
A niching particle swarm optimization strategy combined with cluster analysis for the multimodal inversion of surface waves
<p>The data include two study cases used for multimodal surface wave inversion.</p> <p>For case 1, the data present a combination of active and passive surface wave methods.</p> <p>For case 3, we use Rayleigh waves to detect a low-velocity soft interlayer underneath the road.</p> <p>Detailed description can be found in the data description document.</p>
Optimal sequence similarity thresholds for clustering of molecular operational taxonomic units in DNA metabarcoding studies
<p><span>Clustering approaches are pivotal to handle the many sequence variants obtained in DNA metabarcoding datasets, therefore they have become a key step of metabarcoding analysis pipelines. Clustering often relies on a sequence similarity threshold to gather sequences in Molecular Operational Taxonomic Units (MOTUs), each of which ideally representing a homogeneous taxonomic entity, e.g. a species or a genus. However, the choice of the clustering threshold is rarely justified, and its impact on MOTU over-splitting or over-merging even less tested. Here, we evaluated clustering threshold values for several metabarcoding markers under different criteria: limitation of MOTU over-merging, limitation of MOTU over-splitting, and trade-off between over-merging and over-splitting. We extracted sequences from a public database for nine markers, ranging from generalist markers targeting Bacteria or Eukaryota, to more specific markers targeting a class or a subclass (e.g. Insecta, Oligochaeta). Based on the distributions of pairwise sequence similarities within species and within genera, and on the rates of over-splitting and over-merging across different clustering thresholds, we were able to propose threshold values minimizing the risk of over-splitting, that of over-merging, or offering a trade-off between the two risks. For generalist markers, high similarity thresholds (0.96-0.99) are generally appropriate, while more specific markers require lower values (0.85-0.96). These results do not support the use of a fixed clustering threshold. Instead, we advocate a careful examination of the most appropriate threshold based on the research objectives, the potential costs of over-splitting and over-merging, and the features of the studied markers.</span></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.