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5,371 results for “Flow”
Data for "Fluctuation-induced quantum friction in nanoscale water flows"
<p>This is the data supporting the paper "Fluctuation-induced quantum friction in nanoscale water flows" by N. Kavokine, M.-L. Bocquet and L. Bocquet (arXiv 2105.03413). </p>
Figure 2 in The Zagros Mountains acting as a natural barrier to gene flow in the Middle East: more evidence from the evolutionary history of spiny-tailed lizards (Uromasticinae: Saara)
Figure 2. The phylogenetic tree of the Uromasticinae subfamily, including the genera Saara and Uromastyx, based two mtDNA (Cytb and 16S) and one nDNA (ACM4) genes. The trees showed the same topologies for both ML and BI trees, and therefore, only the BI tree is presented. The ML bootstrap values and BI posterior probabilities are next to the nodes, respectively.
Figure 5 in The Zagros Mountains acting as a natural barrier to gene flow in the Middle East: more evidence from the evolutionary history of spiny-tailed lizards (Uromasticinae: Saara)
Figure 5. The biogeographic analysis of Saara with S-DIVA (A) and BBM (B) based on Cytb. For these analyses, three regions were considered: (A: blue nodes) the Mesopotamian plain [or western part of Zagros Mountains (WZM); distribution of S. loricata], (B: green nodes) the central Iranian Plateau [or eastern part of Zagros Mountains (EZM); distribution of S. asmussi] and (C: pink nodes) India/Pakistan (IP); distribution of S. hardwickii. The dark blue and dark green circles around nodes show dispersal and vicariance events, respectively.
Figure 1 in The Zagros Mountains acting as a natural barrier to gene flow in the Middle East: more evidence from the evolutionary history of spiny-tailed lizards (Uromasticinae: Saara)
Figure 1. Geographical distribution range of the genus Saara. The grey circles represent distribution points (the points were obtained from valid references e.g. GBIF, reptile database, etc.) and black circles refer to locations of samples that were used in the genetic analyses. Distribution ranges of S. loricata, S. asmussi and S. hardwickii are illustrated with blue, green and pink cross-hatches, respectively.
Figure 3 in The Zagros Mountains acting as a natural barrier to gene flow in the Middle East: more evidence from the evolutionary history of spiny-tailed lizards (Uromasticinae: Saara)
Figure 3. Parsimony haplotype networks of Saara loricata and S. asmussi based on two mtDNA (Cytb and 16S) genes. The haplogroups (A) and (B) refer to S. loricata with Cytb and 16S, respectively. The haplogroups (C) and (D) refer to S. asmussi with Cytb and 16S, respectively.
Figure 3 in Asymmetric acoustic signal recognition led to asymmetric gene flow between two parapatric frogs
Figure 3. Acoustic response of Buergeria choui (blue) and B. otai (orange) against conspecific and heterospecific calls. Both species showed highest response against the calls from their own kind. However, the eastern and western populations of B. otai represent behavioral difference. The western population shows the strongest response to the 'chicken trills' (Type 2), which was unique for this species; whereas the eastern population response strongest to Type 1b, which is a shared 'cricket trills' similar to Type 1a produced by B. choui.
Figure 2. A, G in Asymmetric acoustic signal recognition led to asymmetric gene flow between two parapatric frogs
Figure 2. A, G-PHOCS estimates of effective population sizes, divergence times, and migration rates between two clades of Buergeria otai and B. choui. There were two significant migrations: one from the ancestors of B. otai to B. choui, and the recent one from B. choui to eastern B. otai. Gene flow estimated by MIGRATE-N (B) and δaδi (C) revealed congruent results, indicating the gene flow only occurred between B. choui and the eastern B. otai.
Figure 1 in Mitogenomics of the endangered Mediterranean monk seal (Monachus monachus) reveals dramatic loss of diversity and supports historical gene-flow between Atlantic and eastern Mediterranean populations
Figure 1. Sampling sites (number of specimens per location in brackets) with the current Mediterranean monk seal distribution range in green.
Figure 3 in Mitogenomics of the endangered Mediterranean monk seal (Monachus monachus) reveals dramatic loss of diversity and supports historical gene-flow between Atlantic and eastern Mediterranean populations
Figure 3. Mitochondrial genome clades sequenced in our study. A, female monk seal with its pup on Desertas Islands (Madeira); photo credit: Rosa Pires. B, Bayesian phylogeny using the complete mtDNA. Black dots indicate posterior probability values ≥ 0.95. (*) indicates historical specimens. The colours of the bars match the colours used on the network analyses and maps in Figure 2.
Figure 2 in Considering gene flow when using coalescent methods to delimit lineages of North American pitvipers of the genus Agkistrodon
Figure 2. Species tree showing the phylogenetic relationships within the genus Agkistrodon implemented in *BEAST (Heled & Drummond, 2010). Posterior probability support for nodes is indicated above branches. The guide trees used for subsequent species delimitation in BPP (Yang & Rannala, 2010) are shown in the insets.
Figure 3 in Considering gene flow when using coalescent methods to delimit lineages of North American pitvipers of the genus Agkistrodon
Figure 3. Posterior probability of speciation inferred by BPP, version 2.0 (Yang & Rannala, 2010) with an increasing proportion of hybrids included in the dataset for Agkistrodon contortrix (A) and Agkistrodon piscivorus (B). Results are shown for both species with hybrids assigned to the population that contributed the majority of alleles with a fully resolved starting tree (1) and a fully collapsed starting tree (0), as well as hybrids assigned to the population that contributed the minority of alleles with both starting trees.
Figure 1 in Considering gene flow when using coalescent methods to delimit lineages of North American pitvipers of the genus Agkistrodon
Figure 1. Map of the USA showing the sampling localities and distribution of inferred lineages of Agkistrodon contortrix (A) and Agkistrodon piscivorus (B). The distribution of both species is indicated by a bold outline. The key to the right of each map indicates the population membership of individuals and also identifies admixture in individuals.
Figure 4 in Considering gene flow when using coalescent methods to delimit lineages of North American pitvipers of the genus Agkistrodon
Figure 4. Niche predictions for each species of the Agkistrodon contortrix complex with hybrids included in training the model (A), Agkistrodon contortrix complex with hybrids excluded (B), Agkistrodon piscivorus complex with hybrids included in training the model (C), Agkistrodon piscivorus complex with hybrids excluded (D), and East and Central lineages of Agkistrodon contortrix inferred by mtDNA (E). The distribution of colubriod samples obtained from the Herpnet database used to correct for sampling bias is shown in (F). Overlap between predicted suitable habitat is indicated by the darkest intermediate shade.
Figure 5 in Considering gene flow when using coalescent methods to delimit lineages of North American pitvipers of the genus Agkistrodon
Figure 5. The distribution of species within the Agkistrodon contortrix complex (A) and Agkistrodon piscivorus complex (B) inferred by Bayesian species delimitation. Putative hybrids zones are identified with cross-hatches. Distributions are adapted from Gloyd & Conant (1990) and the results from ecological niche modelling.
Image flow cytometry data of T-cells from healthy and Sezary patients
<p>The purpose of our experiments was to investigate the morphology of T-cells using a custom build image flow cytometry device. Blood (T-cells) from healthy donors and Sezary patients was imaged.</p>
Data for "A Comparison of Linear Solvers for Resolving Flow in Three-Dimensional Discrete Fracture Networks"
<p>This data is related to the manuscript "A Comparison of Linear Solvers for Resolving Flow in Three-Dimensional Discrete Fracture Networks". It contains meshes, boundary conditions, and medium properties for discrete fracture networks used to test fluid flow solvers.</p>
51013-Instream Flow Protection: Southeast-Phase 15
<p>Streamflow data collected during AKSSF Grant 51013-Instream Flow Protection: Southeast-Phase 15.</p>
Facilitation of neural responses to targets moving against optic flow
<p>For the human observer, it can be difficult to follow the motion of small objects, especially when they move against background clutter. In contrast, insects efficiently do this, as evidenced by their ability to capture prey, pursue conspecifics, or defend territories, even in highly textured surrounds. We here recorded from target selective descending neurons (TSDNs) which likely subserve these impressive behaviors. To simulate the type of optic flow that would be generated by the pursuer's own movements through the world, we used the motion of a perspective corrected sparse dot field. We show that hoverfly TSDN responses to target motion are suppressed when such optic flow moves syn-directional to the target. Indeed, neural responses are strongly suppressed when targets move over either translational sideslip or rotational yaw. More strikingly, we show that TSDNs are facilitated by optic flow moving counter-directional to the target, if the target moves horizontally. Furthermore, we show that a small, frontal spatial window of optic flow is enough to fully facilitate or suppress TSDN responses to target motion. We argue that such TSDN response facilitation could be beneficial in modulating corrective turns during target pursuit.</p>
Data Set of Publication on Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams
<p>This data set contains the evaluation data of our publication on "<a href="https://doi.org/10.1016/j.jss.2021.111138">Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams</a>". The data set contains an overview on our implementation, description of the evaluation cases, and the evaluation results.</p> <p>The application to produce this data is available in another data set, which is linked to this data set.</p>
Use of WRF-Hydro in postfire debris-flow hazard simulation
<p>This is the dataset used in a study named "Use of WRF-Hydro to Simulate Runoff-Generated Debris Flow Hazards in Burn Scars" by C. Li<sup>1</sup>, A. L. Handwerger<sup>2,3</sup>, J. Wang<sup>4</sup>, W. Yu<sup>5,6</sup>, X. Li<sup>7</sup>, N. J. Finnegan<sup>8</sup>, Y. Xie<sup>9,10</sup>, G. Buscarnera<sup>7</sup>, and D. E. Horton<sup>1</sup></p> <p><sup>1 </sup>Department of Earth and Planetary Sciences, Northwestern University</p> <p><sup>2 </sup>Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, 90095, USA</p> <p><sup>3 </sup>Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA</p> <p><sup>4 </sup>Environmental Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA</p> <p><sup>5 </sup>Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder</p> <p><sup>6 </sup>NOAA/Global Systems Laboratory, 325 Broadway, Boulder, Colorado</p> <p><sup>7 </sup>Department of Civil and Environmental Engineering, Northwestern University</p> <p><sup>8 </sup>University of California Santa Cruz, Department of Earth and Planetary Sciences, Santa Cruz, CA, 95064, USA</p> <p><sup>9</sup> Program in Environmental Sciences, Northwestern University, 2145 Sheridan Road, Evanston, IL, 60208, USA</p> <p><sup>10 </sup>Department of Biological Sciences, Purdue University, 915 W State St, West Lafayette, IN 47907, USA</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.