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Fig 60 in A review of Afrotropical Trichardis Hermann, 1906, and the description of the first Oriental representative of the genus (Diptera: Asilidae: Laphriinae)
Fig 60. Distribution of Trichardis testacea (Macquart, 1838) in southern Africa.
Fig 57 in A review of Afrotropical Trichardis Hermann, 1906, and the description of the first Oriental representative of the genus (Diptera: Asilidae: Laphriinae)
Fig 57. The distribution of Afrotropical Trichardis species.
Figure S1. Spearman correlation matrix representing the relationships between phytoestrogens and biofluids.
<p>(A) Daidzein, (B) Genistein, (C) the sum of both phytoestrogens, (D) follicular fluid, (E) urine on the day of vaginal oocyte retrieval. Blue represents a positive correlation, while red represents a negative correlation. Color intensity is proportional to the correlation strength. Strikethrough values represent non-significant associations (p>0.05).</p>
Figure S2. Spearman correlation matrix representing the relationships between the essential trace elements within each biological matrix
<p>Blue represents a positive correlation, while red represents a negative correlation. Color intensity is proportional to the correlation strength. Strikethrough values represent insignificant/negligible associations (p>0.05). Cr, chromium; Cu, copper; Fe, iron; Li, lithium; Mn, manganese; Mo, molybdenum; Se, selenium; Zn, zinc</p>
Frontopolar cortex represents complex features and decision value during choice between environments
<p><span>Important decisions often involve choosing between complex environments that define future item encounters. Despite its importance for adaptive behaviour and distinct computational challenges</span><span>, decision-making</span><span> research primarily focuses on item choice ignoring environment choice altogether. Here we contrast previously studied item choice in ventromedial prefrontal cortex with lateral frontopolar cortex (FPl) linked to environment choice. Furthermore, we propose a mechanism for how FPl decomposes and represents complex environments during decision-making. Specifically, we trained a choice-optimized, brain-naive convolutional neural network (CNN) and compared predicted CNN activation with actual FPl activity. We showed the high dimensional FPl activity decomposes environment features to represent the complexity of an environment to make such choice possible. Moreover, FPl functionally connects with posterior cingulate cortex for guiding environment choice. Further probing FPl's computation revealed a parallel processing mechanism in extracting multiple environment features.</span></p>
Figure 1 in Amerizus (Tiruka) gaoligongensis sp. n. (Coleoptera: Carabidae): an endogean adapted representative of the genus
Figure 1.Amerizus gaoligongensis sp. n., habitus, paratype. Scale bar = 1.5 mm.
Data for validation and norming of the Danish KIDSCREEN-10 child/adolescent version in a national representative sample of school pupils in grades five through eight
<p>Data for for analyses in Measuring child and adolescent well-being in Denmark: validation and norming of the Danish KIDSCREEN-10 child/adolescent version in a national representative sample of school pupils in grades five through eight. Contains the following variables:</p> <p>Variables Kid1 to Kid10 are the KISDCREEN 10 items. Category labels are the orginal from the KIDSCREEN consortium (Danish version). Items Kid3 and Kid4 are reversed coded according to the KIDSCREEN coding manual. Valus have been recoded from 1-5 to 0-4 for the purpose of item analyses.</p> <p>Language (spoken in the home): 1 = Danish, 2 = other</p> <p>School: 1 = public, 2 = private</p> <p>Sex: 1 = boy, 2 = girl</p> <p>Grade (level): 1 = 5th grade, 2 = 6th grade, 3 = 7th grade, 4 = 8th grade</p> <p>Sample (random): 1 to 7</p>
MCMC chains representing stellar halo fits for Lane et al. (2023) paper published in MNRAS
<p>Results for the paper entitled "The stellar mass of the Gaia-Sausage/Enceladus accretion remnant" published in MNRAS by Lane, Bovy, & Mackereth. The results are in the form of MCMC posterior chains, which are used to generate the results recorded in Table 1 of the manuscript. The process used to generate these data is outlined in section 2 (data & sample preparation), section 3 (Density modelling framework), and section 4 (Presentation of results) of the manuscript.</p> <p>The data are contained within a single gzipped .tar file, organized in two directories: gse/ containing the results for fits to the GS/E kinematic samples, and all/ containing the results for the fits to the whole halo sample. In the gse/ directory, there are three directories: eLz/, AD/, and JRLz/, containing the results for the fits to each of the respective kinematically defined subsamples. Within these directories, as well as within all/, are a final set of directories for each of the eight density profiles considered in the work.</p> <p>Within each of these directories are a single file named "samples.npy" which is a binary file (see <a href="https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html#module-numpy.lib.format">this link</a> for format information) containing a numpy array of shape (# of parameters, # of posterior samples). The number of posterior samples is the number of walkers (100) times the number of samples per walker (10,000), minus the number of burn-in steps per walker (1,000) = 900,000. The number of parameters can be inferred from the density profiles definitions in section 3 of the manuscript, and the ordering of the parameters is the same as in Table 1. The units of the parameters are as in Table 1, except for the parameters theta and phi which are scaled such that they are defined on the interval (0,1), representing the intervals (0,2pi) and (0,pi) respectively.</p>
Is the USDA core collection of common bean representative of genetic diversity of the species, as assessed by SNP diversity?
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Data from: Unhatched eggs represent the invisible fraction in two wild bird populations
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Chemical properties of foliar metabolomes represent a key axis of functional trait variation in forests of the tropical Andes
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Current flow files mapped by Omniscape representing the dispersal of saltwater crocodiles
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Vertical structural complexity of plant communities represents the combined effects of resource acquisition and environmental stress on the Tibetan Plateau
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Data from: Prevalence and correlates of anemia among adolescents in Nepal: findings from a nationally representative cross-sectional survey
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Genome sequence and silkomics of the spindle ermine moth, Yponomeuta cagnagella, representing the early diverging lineage of the ditrysian Lepidoptera
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Representing the dynamics of natural marmoset vocal behaviors in frontal cortex
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Data from: The weight of the crust: biomass of crustose lichens in tropical dry forest represents more than half of foliar biomass
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Data from: Hyperspectral imaging predicts differences in carbon and nitrogen status among representative biocrust functional groups of the Colorado Plateau
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Data from: Altered spring phenology of North American freshwater turtles and the importance of representative populations
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Conceptualizing relationships among hyporheic exchange, storage, and water age: data represented in published figures
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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.