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Fig. 1 in Mastigotragus, a new generic name for Mastigoteuthis pyrodes Young, 1972 (Cephalopoda: Mastigoteuthidae)
Fig. 1. Longitudinal section through an integumental photophore of Mastigoteuthis agassizii Verrill, 1881 (modified from Chun 1910).
Fig. 2 in Mastigotragus, a new generic name for Mastigoteuthis pyrodes Young, 1972 (Cephalopoda: Mastigoteuthidae)
Fig. 2. Photomicrographs of the slightly damaged integument of the head (modified from Vecchione et al. 2004–2014). A. Mastigoteuthis agassizii. B. "Mastigoteuthis" pyrodes [= Mastigotragus pyrodes]. – Large, white arrows indicate photophores; only two photophores are visible in A but seven are visible in B. Small, white arrows indicate two of the many "white spherical structures." Black arrows indicate ringed chromatophores in A and typical chromatophores in B.
Data for Are Changes in Alcohol Use and Personality Traits associated? A Cohort Study among Young Swiss Men
<p>These are the data and metadata for the article </p> <p><strong>Are Changes in Alcohol Use and Personality Traits associated? A Cohort Study among Young Swiss Men</strong></p> <p>by </p> <p><strong>Gerhard Gmel, Simon Marmet, Joseph Studer, and Matthias Wicki</strong></p> <p><strong>to be published in Frontiers of Psychiatry</strong></p>
Mapped read data and files and scripts from: Vicariance followed by secondary gene flow in a young gazelle species complex
<p>Grant's gazelles have recently been proposed to be a species complex comprising three highly divergent mtDNA lineages (<em>Nanger granti</em>, <em>N. notata</em> and <em>N. petersii</em>). The three lineages have non-overlapping distributions in East Africa, but without any obvious geographical divisions, making them an interesting model for studying the early stage evolutionary dynamics of allopatric speciation in detail. Here we use genomic data obtained by restriction site-associated (RAD) sequencing of 106 gazelle individuals to shed light on the evolutionary processes underlying Grant's gazelle divergence, to characterize their genetic structure and to assess the presence of gene flow between the main lineages in the species complex. We date the species divergence to 134,000 years ago, which is recent in evolutionary terms. We find population subdivision within <em>N. granti</em>, which coincides with the previously suggested two subspecies, <em>N.g. granti</em> and <em>N.g. robertsii</em>. Moreover, these two lineages seem to have hybridized in Masai Mara. Perhaps more surprisingly given their extreme genetic differentiation, <em>N. granti</em> and <em>N. petersii</em> also show signs of prolonged admixture in Mkomazi, which we identified as a hybrid population most likely founded by allopatric lineages coming into secondary contact. Despite the admixed composition of this population, elevated X-chromosomal differentiation suggests that selection may be shaping the outcome of hybridization in this population. Our results therefore provide detailed insights into the processes of allopatric speciation and secondary contact in a recently radiated species complex.</p>
Mathematics Education for Young Children in Japan: An Ethnographic Study
<p>This research project examines mathematics education for young children aged 3 to 8 years old in contemporary Japan.</p>
Gene Regulatory Network inference in long lived C.elegans reveals modular properties that are predictive of novel ageing genes - Database of Physical gene-gene Interactions in young adult C.elegans.
<p>This repository contains Supplementary Information for manuscript Suriyalaksh et al Gene Regulatory Network inference in long lived C.elegans reveals modular properties that are predictive of novel ageing genes corresponding to the curation of physical gene-gene interactions for young adult C elegans worms </p> <p>We manually curated 239,001 regulatory interactions from 289 young adult wild-type (WT) C.elegans datasets, consisting of 126 genes and 495 unique transcription factors (see TableS1_datasets_for_prior.csv for references). </p> <p>This repository contains 3 different files:</p> <p>TableS1_datasets_for_prior.csv - contains datasets used as sources for physical gene-gene or TF-gene interactions</p> <p>TableS2_physical_priors.xlsx - contains three tabs:<br> ChIPATAC - contains physical TF-gene interactions from 115 L4 or young-adult ChIP-seq datasets from modERN (Kudron et al., 2018) + ChIP-seq datasets (GSE28350, GSE81521) from (Hochbaum et. al, 2011, Li et. al, 2016).</p> <p>eY1HATAC- contains 3,501 TF-gene interactions from eY1H assay by Fuxman Bass et al. (2016).</p> <p>motifATAC - contains 202 unique TF DNA recognition motifs using “direct evidence” option from CiS-BP motif database (Weirauch et al., 2014), obtained through RTFBSDB R package (Wang et al., 2016) - see TableS1</p> <p>TableS3_WT_functional_priors.csv - contains functional knockdown data that we use as gold standard to validate inferred networks in Suriyalaksh et al. (see TableS1_datasets_for_prior.csv for sources)</p> <p>---</p> <p>Description of methodology to obtain regulatory interactions in TableS2:</p> <p>Regulatory sequences for each gene were acquired from ENSEMBL (Aken et al., 2017), obtained using biomaRt R package (accessed on 31st Oct 2017). This study used WBcel235/ce11 version of the C. elegans genome, and WormBase WS260 genome annotations.</p> <p>For motifs, TFs whose motifs overlapped with an open ATAC-seq region by at least one base pair were kept. For ChIP-seq, TF binding sites that overlapped with an open ATAC-seq region by at least one base pair were kept using bedtools intersect and bedtools merge commands.</p> <p>An interaction from a TF to a gene was inferred by aligning transcription start sites (TSS) using bedtools window commands with 1000 bp window size to the TF-binding locations from ChIP-seq and motifs.</p> <p>For eY1H data, an interaction is included if the TSS site of the target gene overlaps with an open ATAC-seq region by at least one base pair.</p> <p>For gene-gene interactions, of the 298 studies compiled in WormExp v1.0 database (Yang et al, 2016, updated 27/07/16), 98 studies were included in the database spanning 126 different genes (see Table S1 in this repository).</p>
A QUESTIONNAIRE FOR THE ASSESSMENT OF VIOLENT BEHAVIORS IN YOUNG COUPLES: THE ITALIAN VERSION OF DATING VIOLENCE QUESTIONNAIRE (DVQ)
<p> In the last years, intimate partner violence (IPV) became a relevant problem for community and for social life, particularly in young people. Its correct assessment and evaluation in the population is mandatory. Our objectives were: Confirm factor structure of Dating Violence Questionnaire (DVQ) and investigate its convergent and divergent validity. The DVQ along with other personality measures were filled by a sample of 418 university students (Females = 310) of average age of 23 y.o. (SD = 4.71). A subsample of participants (223 students) consented in being involved also in retest and filled also the Revised Eysenck Personality Questionnaire (short form) and a brief scale for describing the behavior of the (past) partner after the breaking of the relationship (BRS). The 8-factor structure, with respect to the two other competing models, reported better fit indexes and showed significant correlations with other personality measures. Personality traits, both Neuroticism and Psychoticism, correlated with Sexual Violence, while Detachment correlated only with Neuroticism and Coercion, Humiliation and Physical Violence correlated with only Psychoticism. Extraversion did not report significant relationships with any of the 8 DVQ factors. Also the predictive validity of DVQ was satisfactory with the partner violent reaction to the break of relationship predicted positively predicted by Coercion (b = 0.22) and by Humiliation (b = 0.20) and negatively by Emotional Punishment (b = -0.18). The present results indicate a good factor structure of the questionnaire, and interesting correlations with personality traits, allowing to identify psychological aspects with a predisposing role for anti-social aggressive behaviors. Further studies will be aimed at ascertaining other possible determinants of intimate partner violence and the weight of cultural aspects.</p>
ariedel/young_catalog: The Catalog of Suspected Nearby Young Stars (2016.1118)
<p>This is the Catalog of Suspected Young Stars from Riedel et al. (2017) (at time of paper submission).</p> <p>The catalog is meant to contain astrometric, photometric, and basic spectroscopic information for all stars EVER reported as being young (and nearby, with a rough outer limit of 100 parsecs plus the Pleiades and stars in the Octans moving group (both extend beyond 100 parsecs) plus field stars included in papers presenting young stars, or considered and rejected in those papers. Basically, if the star's youth was ever under consideration, this catalog should have it.</p> <p>The catalog currently contains 5350 stars, in a one-line-per-star format, with 388 columns. Every quantity has an associated reference, nearly all quantities have uncertainties, and most quantities have upper limit/lower limit/joint/deblended flags. The master file is actually an OpenDocument (.ods) spreadsheet which has the following improvements over the .csv file:</p> <p>Color-coded sections In-sheet calculations for derived quantities like Mean RV, Mean Parallax, and most photometric colors. Properties of companions that were simply copied from the primary star are in bold. For instance, if all that's known is that the star is a binary, EVERYTHING should be bolded. The procedure upon discovering a companion is to copy the entire primary star's line and bold it, and then replace those values with the ones specific to the secondary. Note that the OpenDocument and Excel files have two extra header lines as compared to the CSV</p> <p>The .csv file is probably easier to read into a program. Code for using Python 2.7+ and Astropy 0.4+ to produce a Python table is below:</p> <p>from astropy.io import ascii</p> <p>catalog = ascii.read(infilename)</p> <p>Buyer beware: This is a work in progress. There is missing data (no lithium data for The Pleiades yet; I haven't added the papers; nearly no Hyades at all because I haven't added the papers yet). Multiplicity is incomplete. The Bold/Unbolded method of dealing with multiples is not consistently applied, and I intend to supplant it with flags on every data value.</p> <p>Earlier versions exist for the purposes of reproducing prior work but are far less complete and correct; versions prior to 2016.0704 have fewer objects; versions prior to 2016.0116 do not have headers that comply with AAS journal standards.</p> <p>Comments and suggestions are welcome.</p>
A modular set of synthetic spectral energy distributions for young stellar objects - Robitaille (2017) - v1.1 [Hyperion files]
<p>These are the input and output files for the radiative transfer code (Hyperion) for the model sets presented in</p> <p><em>A modular set of synthetic spectral energy distributions for young stellar objects</em>, Robitaille (2017)</p> <p>Each model set is provided as a single tar file. Each tar file expands to <strong>grids-1.1/<set name></strong>, so if you expand all tar files in the same folder, you will end up with a single <strong>grids-1.1</strong> folder with 18 sub-folders, one for each model set.</p> <p>For a given model set, the files are as follows:</p> <ul> <li>grids-1.1/<set name>/input - input Hyperion files</li> <li>grids-1.1/<set name>/log - log files from Hyperion</li> <li>grids-1.1/<set name>/output - output Hyperion files</li> <li>grids-1.1/<set name>/par - parameters for each model</li> <li>grids-1.1/<set name>/ranges.conf - ranges of parameters varied in the model set</li> <li>grids-1.1/<set name>/parameters.hdf5 - table of parameters for all models</li> <li>grids-1.1/<set name>/d03_5.5_3.0_A_sub.hdf5 - dust file used for the models</li> </ul> <p>Given the large number of models for some of the model sets, the models are not all stored directly inside the par, input, output or log directories - instead these directories contain folders formed from the first two characters (forced to lowercase) of the names of the models they contain. For example, a3 contains all models whose name starts with a3 or A3. This was done to avoid having too many files in a single folder which can cause issues on certain file systems.</p> <p>For the Hyperion input and output files, in some cases an _sed file is present. In these cases, the output SEDs (and polarization spectra) should be read from the _sed file, not the original output file. This is the case for all models that are in a set for which the ambient medium was present, as described in §4.2.3 of Robitaille (2017). Furthermore, in some cases the SED file is called _sed_noscat to indicate that scattering was not included, as described in §5.1 of Robitaille (2017).</p> <p>To avoid taking up too much disk space, the Hyperion HDF5 input/output files use external links to refer to each other and to the dust file. To make sure the links work, you should do all operations with the input/output files from the directory containing <strong>grids-1.1</strong>. For example, to open a Hyperion output file, you would need to do (in Python):</p> <p> In [1]: from hyperion.model import ModelOutput</p> <p> In [2]: mo = ModelOutput('grids-1.1/s---s-i/output/a3/A3kQmQtj.rtout')</p> <p>A notebook with examples of reading in the output files can be found here:</p> <p>https://github.com/hyperion-rt/paper-2017-sed-models/blob/master/notebook_raw/reading_raw_files.ipynb</p> <p>More information on using Hyperion, including reading input/output files, can also be found at http://docs.hyperion-rt.org</p> <p>For <strong>announcements</strong> of new versions of these models, you can subscribe to the following mailing list:</p> <p>https://groups.google.com/forum/#!forum/protostars</p> <p>For <strong>questions or issues</strong> using these models, you can open a GitHub issue in the companion repository:</p> <p>https://github.com/hyperion-rt/paper-2017-sed-models/issues/new</p>
Observational Bias and Young Massive Cluster Characterisation II. Can Gaia accurately observe young clusters and associations?
<p>Field-of-View for synthetic Gaia observations of clusters Orion-type-3, Orion-type-5.5 and Wd2-type presented in Buckner et al. (2023).</p><p>Files contain both simulation and field stars along the Line-of-Sight (l = 270^o, b = 0^o) for the clusters when placed at 500pc, 2500pc and 4300pc distances.</p><p>The original simulation files are included for reference.</p><p>Included README files provide more detailed descriptions of the files.</p>
Figure 17 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 17. Selected dentaries of Thylacinus showing differences in the diastemata between the premolars as the effect of increasing age. A, subadult (in labial view) with m3 erupted, but not m4. Only slight suggestions of diastemata are evident between the premolars; B (lingual view) and C (labial view), showing later stages of m4 eruption and the increase of diastemata in adults.
Figure 16 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 16. Later stages of early eruption in Thylacinus showing the presence and early loss of dp3 in the dentary. A, Part of the dentary (CU A6 7/10), redrawn from Moeller (1968), showing the erupted dp3, the unerupted successor p3 in its alveolar crypt, immediately anterior to dp3, and the erupting m1. The erupting dp1 and dp2 are also labeled; B, A slightly later stage of eruption in the dentary (USNM 115365) shows that the dp3 has been lost, and successor p3 is in early eruption. The m1 is now almost completely erupted. c indicates lower successional canine in B.
Figure 13 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 13. Computed tomography images from the supplementary data of Newton et al. (2018). A, section of the skull and dentition from TMAG A931, a thylacine pouch young of 35 - 37 days old; B, Section of the skull and dentition from TMAG A930, a thylacine pouch young of 66 - 67 days old. Scale bars are 5 mm. C, canine; dP1, deciduous first premolar; dP2, deciduous second premolar; dP3, deciduous third premolar; M1, first molar; P3, successional third premolar.
Figure 12 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 12. Section through dp3 and its successor p3. Only a small fragment of the lingual successional lamina is evident. Compare this single section with the camera lucida drawings in Figure 11. dp3, deciduous third premolar; lsl, lingual successional lamina; p3, successional third premolar.
Figure 10 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 10. Section through the level of the metacone on M1, with thick enamel on its apex and disrupted dentin; d, dentin; e, enamel; me, metacone apex.
Figure 11 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 11. Camera lucida drawings of dp3 and p3 in the dentary, at different planes of section. A, The lingual successional lamina is fragmented, but still largely intact, between the small dp3 and its larger successional p3; B, The small dp3 is evident with its dentin and enamel, and its primary dental lamina connection to the oral epithelium is fragmented but still evident. The section through the successor p3 is not central, but it shows the fragmented lingual successional lamina between the two teeth. A, ameloblasts; AB, alveolar bone; D, dentin; dp3, deciduous third premolar; E, enamel; O, odontoblasts; OE, oral epithelium; P, dental papilla; p3, successor third premolar; PL, primary dental lamina; SL, lingual successional lamina; SR, stellate reticulum.
Figure 6 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 6. Longitudinal section through dP2, with disrupted dentin and well - developed enamel. d, dentin; e, enamel.
Figure 9 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 9. Section of M1, at level of paracone. A, paracone with overlying epithelial nodule; B, paracone at more central level, lacking the epithelial nodule; en, epithelial nodule; pa, paracone apex.
Figure 3 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 3. Histological section of I1 in Thylacinus, in middle bell stage. dp, dental papilla; en, epithelial nodule; o, oral epithelium; pdl, primary dental lamina.
Figure 1 in Microscopic analysis of the developing dentition in the pouch young of the extinct marsupial Thylacinus cynocephalus, with an assessment of other developmental stages and eruption
Figure 1. Thylacinus (71.1 mm Head Length) pouch young, with unerupted dentition; redrawn from Flower, 1867. C, upper and lower canine; dP3, upper and lower deciduous third premolar; M1, upper and lower first molar; P3, upper and lower successional third premolar.
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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.