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124 results for “distributed sampling”
FIGURE 2 in Hypogean presumably sister species Quedius repentinus sp. n. from Altai and Q. roma from Sikhote-Alin (Coleoptera: Staphylinidae): a disjunct distribution or poorly sampled Siberia?
FIGURE 2. Quedius przewalskii, holotype: A, habitus; B, aedeagus (laterally); C, same (in parameral view); D, apex of paramere, underside (side facing median lobe); E, tergite X; F, sternite IX; G, sternite VIII; H, labels. Scale bars: A–C, E–G = 1 mm, D = 0.4 mm.
A Tale of Two Retinal Domains: Near-Optimal Sampling of Achromatic Contrasts in Natural Scenes through Asymmetric Photoreceptor Distribution
<p>Spectral image data of an early spring daytime forest scene recorded using a ‘‘hyperspectral scanner’’. For details, see<a href="https://www.ncbi.nlm.nih.gov/pubmed/24314730"> Baden, Schubert et al. (2013)</a> doi: 10.1016/j.neuron.2013.09.030. For a script to access the data, see <a href="https://github.com/eulerlab/published_data">github.com/eulerlab/published_data</a>.</p>
FIGURE 2. Bromeliad species sampled. A in Ciliate species from tank-less bromeliads in a dry tropical forest and their geographical distribution in the Neotropics
FIGURE 2. Bromeliad species sampled. A=Tillandsia dasyliriifolia, B=T. rothii, C=Bromelia pinguin, D=T. polystachia and E=B. karatas.
Fig. 4 in Distributional modeling of Mantophasmatodea (Insecta: Notoptera): a preliminary application and the need for future sampling
Fig. 4 Summed distribution maps for all modeled species of Mantophasmatodea considering both ENVSC (left column) and MAX (right column) algorithms
Fig. 3 in Distributional modeling of Mantophasmatodea (Insecta: Notoptera): a preliminary application and the need for future sampling
Fig. 3 Summed distribution for the Mantophasma genus for both ENVSC (a and b) and MAX (c and d) either considering the LPT (a and c) and ROC (b and d) thresholds
Fig. 1 in Distributional modeling of Mantophasmatodea (Insecta: Notoptera): a preliminary application and the need for future sampling
Fig. 1 Occurrences for all Mantophasmatodea (Notoptera) divided by a genera and b species. The inset map highlighted in a was increased in b
Figure 2 in Distribution of tiger salamanders in northern Sonora, Mexico: comparison of sampling methods and possible implications for an endangered subspecies
Figure 2. Relationship between mean volume filtered and mean DNA index (±95% confidence interval) for sites where we detected Western Tiger Salamanders (Ambystoma mavortium) with eDNA methods. For every 1% increase in volume of water filtered, DNA recovered decreased by 1.42% (DNA Index = e1.54 [95%CI = 4.14] × Volume (ml) −1.42 [95%CI = 0.80]; R2 = 0.25).
Figure 3 in Distribution of tiger salamanders in northern Sonora, Mexico: comparison of sampling methods and possible implications for an endangered subspecies
Figure 3. Effect of total aquatic vegetation (standardized) on detection of Western Tiger Salamanders (Ambystoma mavortium; ±95% confidence interval), based on all sampling methods. Total aquatic vegetation is the sum of percent cover of emergent vegetation, submerged vegetation, and algae.
Figure 1 in Distribution of tiger salamanders in northern Sonora, Mexico: comparison of sampling methods and possible implications for an endangered subspecies
Figure 1. Waterbodies sampled for Western Tiger Salamanders (Ambystoma mavortium) and sub-species in northern Sonora, Mexico, during 2015-2018. Yellow circles indicate locations where salamanders were estimated to be present, white circles indicate where salamanders were not detected, and turquoise triangles indicate sites where Jones et al. (1988) sampled in 1983 and did not detect A. mavortium. The red star indicates the approximate location of Cananea, Sonora.
Research data supporting: "Extended sampling of macromolecular conformations from uniformly distributed points on multidimensional normal mode hyperspheres"
<p>This repository contains protein structures generated by the approach "distributed points Molecular Dynamics using Normal Modes" (dpMDNM). dpMDNM is an enhanced-sampling approach that allows large protein conformational sampling based on normal mode (NM) vector combinations.</p> <p>Input parameter and equilibrated files for Lysozyme and CYP3A4 are provided, including their respective ensemble of structures after conformational exploration combining from 2 to 8 NMs.</p> <p>For more information, please visit the <a href="https://github.com/antonielgomes/dpMDNM">dpMDNM GitHub repository</a>.</p>
Figure 4. Regression lines between average length and sampling depth for the 19 in Bathymetric trends in distribution and size of demersal fish species in the north Aegean Sea
Figure 4. Regression lines between average length and sampling depth for the 19 species with significant size-depth relationships.
FIGURE1. Map showing the sampling localities and distribution of all valid Korean species identified and described so far. The black line between Stations 6a and 6b represents a man-made road with no gap for water entry from either side. Stations 1 to 15 refer to the study sites in Vakati et al. (2019), station 16 refers to the study site in Kim et al. (2017). in -On- two- new- species- of- Nannopus- Brady,- 1880- (Copepoda:- Harpacticoida Nannopodidae)-from-intertidal-mudflats-of-the-Korean-west-coast-(Yellow-Sea)
FIGURE1. Map showing the sampling localities and distribution of all valid Korean species identified and described so far. The black line between Stations 6a and 6b represents a man-made road with no gap for water entry from either side. Stations 1 to 15 refer to the study sites in Vakati et al. (2019), station 16 refers to the study site in Kim et al. (2017).
Molecular characterization of brown carbon chromophores in atmospherically-relevant samples and their gas-particle distribution and diurnal variation in the atmosphere
<p>This file include all data given in the figures in our manuscript submitted to JGR-Atmosphere</p>
Figure 1: Global distribution of ESKAPE pathogens sample size
<p><strong>Figure 1: Global distribution of ESKAPE pathogens sample size</strong></p>
Figure 1: Global distribution of ESKAPE pathogens sample size
<p><strong>Figure 1: Global distribution of ESKAPE pathogens sample size </strong></p>
Protocol for Collecting, Banking and Distributing Human Tissue Samples: St. Jude Children's Research Hospital Tissue Resources Core Facility
ClinicalTrials.gov study NCT01354002. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Collection and Distribution of Samples From Healthy Donors for In Vitro Research at the NCI-Frederick
ClinicalTrials.gov study NCT00339911. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Data from: Accounting for observation processes across multiple levels of uncertainty improves inference of species distributions and guides adaptive sampling of environmental DNA
Open the record for dataset details and reuse information.
Data from: The behavior of Metropolis-coupled Markov chains when sampling rugged phylogenetic distributions
Open the record for dataset details and reuse information.
Data from: Comparing the prediction of joint species distribution models with respect to characteristics of sampling data
Open the record for dataset details and reuse information.
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.