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1,271 results for “Data Flow”
Relevant data for numerical simulation of Xiangjiao post-fire debris flow
<p>This is a data set used for numerical simulation analysis of post-fire debris flow in Xiangjiao catchment, Sichuan Province, including the original rainfall data on the day of the debris flow event, the interpolated rainfall data, and some relevant experimental data. If you have any questions in the process of using these data, you can contact the email: 622200090027@mails.cqjtu.edu.cn.</p>
Faster‐haplodiploid evolution under divergence‐with‐gene‐flow: Simulations and empirical data from pine‐feeding hymenopterans
<p>Although haplodiploidy is widespread in nature, the evolutionary consequences of this mode of reproduction are not well characterized. Here, we examine how genome-wide hemizygosity and a lack of recombination in haploid males affects genomic differentiation in populations that diverge via natural selection while experiencing gene flow. First, we simulated diploid and haplodiploid "genomes" (500-kb loci) evolving under an isolation-with-migration model with mutation, drift, selection, migration, and recombination; and examined differentiation at neutral sites both tightly and loosely linked to a divergently selected site. So long as there is divergent selection and migration, sex-limited hemizygosity and recombination cause elevated differentiation (i.e., produce a "faster-haplodiploid effect") in haplodiploid populations relative to otherwise equivalent diploid populations, for both recessive and codominant mutations. Second, we used genome-wide SNP data to model divergence history and describe patterns of genomic differentiation between sympatric populations of <em>Neodiprion lecontei </em>and <em>N. pinetum</em>, a pair of pine sawfly species (order: Hymenoptera; family: Diprionidae) that are specialized on different pine hosts. These analyses support a history of continuous gene exchange throughout divergence and reveal a pattern of heterogeneous genomic differentiation that is consistent with divergent selection on many unlinked loci. Third, using simulations of haplodiploid and diploid populations evolving according to the estimated divergence history of <em>N. lecontei </em>and <em>N. pinetum</em>, we found that divergent selection would lead to higher differentiation in haplodiploids. Based on these results, we hypothesize that haplodiploids undergo divergence-with-gene-flow and sympatric speciation more readily than diploids.</p>
Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose
<p><span>Copy-number and point mutations form the basis for most evolutionary novelty through the process of gene duplication and divergence. While a plethora of genomic sequence data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic system that allows us to distinguish copy-number and point mutations, we study their early and transient adaptive dynamics in real-time in <em>Escherichia</em> <em>coli</em>. We find two qualitatively different routes of adaptation depending on the level of functional improvement selected for: In conditions of high gene expression demand, the two types of mutations occur as a combination. Under</span><span> low gene expression demand, negative epistasis between the two types of mutations renders them mutually exclusive. Thus, owing to their higher frequency, adaptation is dominated by copy-number mutations. Ultimately, due to high rates of reversal and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation but also <a>constrain</a></span><span> sequence divergence over evolutionary time scales.</span></p>
Ki-67 and Bcl-2 data by flow cytometry in non-malignant bone marrow aspirates and aspirates from patients with myeloid malignancies.
<p>This Data in Brief article displays a flow cytometric assay that was used for the acquisition and analyses of proliferation and anti-apoptosis in hematopoietic cells. This dataset includes analysis of the Ki-67 positive fraction (Ki-67 proliferation index) and Bcl-2 positive fraction (Bcl-2 anti-apoptotic index) of the different myeloid bone marrow (BM) cell population in non-malignant BM, and the BM disorders myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). The present dataset comprises 1) the percentage of the CD34 positive blast cells, erythroid cells, myeloid cells and monocytic cells, and 2) the determined Ki-67 positive fraction and Bcl-2 positive fraction of these cell populations in tabular form. This allows the comparison and reproduction of the data when these analyses are repeated in a different setting. As gating the Ki-67 positive and Bcl-2 positive cells is a critical step in this assay, different gating approaches were compared to determine the most sensitive and specific approach. BM cells from aspirates of 50 non-malignant, 25 MDS and 50 AML cases were stained with 7 different antibody panels and subjected to flow cytometry for determination of the Ki-67 positive cells and Bcl-2 positive cells of the different myeloid cell populations. The Ki-67 or Bcl-2 positive cells were then divided by the total number of cells of the respective cell population to generate the Ki-67 positive fraction (Ki-67 proliferation index) or the Bcl-2 positive fraction (Bcl-2 anti-apoptotic index). The presented data may facilitate the establishment and standardization of flow cytometric analyses of the Ki-67 proliferation index and Bcl-2 anti-apoptotic index of the different myeloid cell populations in non-malignant BM as well as MDS and AML patients in other laboratories. Directions for proper gating of the Ki-67 positive and Bcl-2 positive fraction are crucial for achieving standardization among different laboratories. In addition, the data and the presented assay allows application of Ki-67 and Bcl-2 in a research and clinical setting and this approach can serve as the basis for optimization of the gating strategy and subsequent investigation of other cell biological processes besides proliferation and anti-apoptosis. These data can also promote future research about the role of these parameters in diagnosis of myeloid malignancies, prognosis of myeloid malignancies and therapeutic resistance against anti-cancer therapies in these malignancies. As specific populations based on cell biological characteristics were identified, these data can be useful for evaluating gating algorithms in flow cytometry in general by confirming the outcome (e.g. MDS or AML diagnosis) with the respective proliferation and anti-apoptotic profile of these malignancies. The Ki-67 proliferation index and Bcl-2 anti-apoptotic index may potentially be used for classification of MDS and AML based on supervised machine learning algorithms, while unsupervised machine learning can be deployed at the level of single cells to potentially distinguish non-malignant from malignant cells to identify minimal residual disease. Therefore, the present dataset may be of interest for internist-hematologists, immunologists with affinity for hemato-oncology, clinical chemists with sub-specialization of hematology and researchers in the field of hemato-oncology.</p>
Data from: A study on the Influence of submergence ratio on the transportation of suspended sediment in a partially vegetated channel flow
<p><span>Riparian or aquatic vegetation thrives with seasons. The understanding of canopies' Submergence-Ratio SR (stems' height to water depth) influence on suspended sediments' transportation is still limited. Thus, Large Eddy Simulations (LES) coupled with the Discrete Phase Method (DPM) are used to investigate the particles' 3-dimensional distribution in a partially vegetated straight channel. The spanwise distribution of particles is quantified by the Probability Density Function (PDF), showing a non-uniformity of particles in time as quantified by the PDF variance. The findings and conclusions: (Ⅰ) With SR rising, the particles' depletion effects exerted by the vegetation-side mixing layer are improved along the interface between vegetated and vegetation-side bare channel region. However, the SR has little effect on the variance of the particles' PDF in the spanwise direction when the mixing layer is fully developed. (Ⅱ) During the developing stage of the over-canopy mixing layer, submerged vegetation with higher SR gain a stronger upwards (vertical) entrainment capability. </span><span>The case (SR=60%) has a higher sediment concentration than other cases in the fully developed vertical mixing layer region above canopy.</span><span> (III) </span><span>The vertical suspension of particles in the vegetation-side bare channel region is analysed. Particles migrating from the vegetated region are entrained into the vegetation-side bare channel region by turbulent structures. Nevertheless, the vertical concentration profile is more uniform in the vegetated region than in the vegetation-side bare channel at the same streamwise location. The cases SR=40% and 60% still have higher sediment concentrations than other cases in the vegetation-side bare channel's upper region.</span></p>
Data for: Gene flow accelerates adaptation to a parasite
<p>Gene flow into populations can increase additive genetic variation and introduce novel beneficial alleles, thus facilitating adaptation. However, gene flow may also impede adaptation by disrupting beneficial genotypes, introducing deleterious alleles, or creating novel dominant negative interactions. While theory and fieldwork have provided insight as to the effects of gene flow, direct experimental tests are rare. Here, we evaluated the effects of gene flow on adaptation in the nematode <em>Caenorhabditis</em> <em>elegans</em> during exposure to the bacterial parasite <em>Serratia</em> <em>marcescens</em>. We evolved hosts against non-evolving parasites for ten passages while controlling host gene flow and source population. We used source nematode populations with three different genetic backgrounds (one similar to the sink population and two different) and two evolutionary histories (previously adapted to <em>S. marcescens</em> or naïve). We found that populations with gene flow exhibited greater increases in parasite resistance than those without gene flow. Additionally, gene flow from adapted populations resulted in greater increases in resistance than gene flow from naïve populations, particularly with gene flow from novel genetic backgrounds. Overall, this work demonstrates that gene flow can facilitate adaptation and suggests that the genetic architecture and evolutionary history of source populations can alter the sink population's response to selection.</p>
T-cell activity - Imaging flow cytometry experiment data
<p>Raw image data from the imaging flow cytometry experiments for correlating receptor localization and cytokine production.</p>
Data from "Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows"
<p>This is data from the paper "Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows" published in PNAS, 2023</p> <p>This is the raw imaging data from Mouse 1. The .raw file is the particle tracking video, and Geometry4.mat is a Matlab file containing the 3D z-stack and accompanying segmentation (pvs_smooth). Details regarding the subject and imaging can be found in the published paper.</p> <p>Additional codes and data used in the paper will be made available upon request.</p>
Figures: The wind farm as a sensor: learning and explaining orographic and plant-induced flow heterogeneities from operational data
<p>Python figures in pickle format</p> <p>matplotlib version 3.5.1 </p>
PEPT Data - The effect of retrofit design modifications on the macro-turbulence of a three-phase flotation tank – Flow characterisation using positron emission particle tracking (PEPT).
<p>Supporting Information: for the paper "The effect of retrofit design modifications on the macro-turbulence of a three-phase flotation tank – Flow characterisation using positron emission particle tracking (PEPT)."</p> <p>The file contains the trajectory data and graph data for azimuthal slices obtained with PEPT.</p> <p> </p>
The data files for the article "Impact of the core deformation on the tidal heating and flow in Enceladus' subsurface ocean"
<p>The data are given for each figure and each file contains a header regarding information on the columns in the data files. </p>
Ki-67 and Bcl-2 data by flow cytometry in non-malignant bone marrow aspirates and patients with myeloid malignancies
<p>This Data in Brief article displays a flow cytometric assay that was used for the acquisition and analyses of proliferative and anti-apoptotic activity in hematopoietic cells. This dataset includes analyses of the Ki-67 positive fraction (Ki-67 proliferation index) and Bcl-2 positive fraction (Bcl-2 anti-apoptotic index) of the different myeloid bone marrow (BM) cell populations in non-malignant BM, and in BM disorders, i.e. myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). The present dataset comprises 1) the percentage of the CD34 positive blast cells, erythroid cells, myeloid cells and monocytic cells, and 2) the determined Ki-67 positive fraction and Bcl-2 positive fraction of these cell populations in tabular form. This allows the comparison and reproduction of the data when these analyses are repeated in a different setting. Because gating the Ki-67 positive and Bcl-2 positive cells is a critical step in this assay, different gating approaches were compared to determine the most sensitive and specific approach. BM cells from aspirates of 50 non-malignant, 25 MDS and 27 AML cases were stained with 7 different antibody panels and subjected to flow cytometry for determination of the Ki-67 positive cells and Bcl-2 positive cells of the different myeloid cell populations. The Ki-67 or Bcl-2 positive cells were then divided by the total number of cells of the respective cell population to generate the Ki-67 positive fraction (Ki-67 proliferation index) or the Bcl-2 positive fraction (Bcl-2 anti-apoptotic index). The presented data may facilitate the establishment and standardization of flow cytometric analyses of the Ki-67 proliferation index and Bcl-2 anti-apoptotic index of the different myeloid cell populations in non-malignant BM as well as MDS and AML patients in other laboratories. Directions for proper gating of the Ki-67 positive and Bcl-2 positive fraction are crucial for achieving standardization among different laboratories. In addition, the data and the presented assay allows application of Ki-67 and Bcl-2 in a research and clinical setting and this approach can serve as the basis for optimization of the gating strategy and subsequent investigation of other cell biological processes besides proliferation and anti-apoptosis. These data can also promote future research into the role of these parameters in diagnosis of myeloid malignancies, prognosis of myeloid malignancies and therapeutic resistance against anti-cancer therapies in these malignancies. As specific populations were identified based on cell biological characteristics, these data can be useful for evaluating gating algorithms in flow cytometry in general by confirming the outcome (e.g. MDS or AML diagnosis) with the respective proliferation and anti-apoptotic profile of these malignancies. The Ki-67 proliferation index and Bcl-2 anti-apoptotic index may potentially be used for classification of MDS and AML based on supervised machine learning algorithms, while unsupervised machine learning can be deployed at the level of single cells to potentially distinguish non-malignant from malignant cells in the identification of minimal residual disease. Therefore, the present dataset may be of interest for internist-hematologists, immunologists with affinity for hemato-oncology, clinical chemists with sub-specialization of hematology and researchers in the field of hemato-oncology.</p>
Transcriptome data from silica-preserved leaf tissue reveals gene flow patterns in a Caribbean bromeliad
<p>Transcriptome sequencing is a cost-effective approach that allows researchers to study a broad range of questions. However, to preserve RNA for transcriptome sequencing, tissue is often kept under special conditions, such as immediate ultracold freezing. Here, we demonstrate that RNA can be obtained from six-month-old, field-collected samples stored in silica gel at room temperature. Using these transcriptomes, we explore the evolutionary relationships of the genus Pitcairnia (Bromeliaceae) in the Dominican Republic and infer barriers to gene flow.</p>
Data for: A Modular Double Electrode Flow Cell with Exchangeable Generator and Detector Electrodes
<p>Raw data and processed data shown in figures of the publication titled:</p> <p>"A Modular Double Electrode Flow Cell with Exchangeable Generator and Detector Electrodes"</p> <p>DOI: <a href="https://doi.org/10.1002/celc.202300126">10.1002/celc.202300126</a></p> <p>by</p> <p>Frederik J. Stender<sup>[a]</sup>, Keisuke Obata<sup>[b]</sup>, Max Baumung<sup>[a,c]</sup>, Fatwa F. Abdi<sup>[b]</sup>, Marcel Risch<sup>[a,c]</sup></p> <p>[a] Frederik Johannes Stender, Max Baumung, Dr. Marcel Risch<br> Institut für Material Physik<br> Georg-August-Universität Göttingen<br> Friedrich-Hund-Platz 1, 37085 Göttingen<br> E-mail: mrisch@material.physik.uni-goettingen.de</p> <p>[b] Dr. Keisuke Obata, Dr. Fatwa Firdaus Abdi<br> Institut für Solare Brennstoffe<br> Helmholtz-Zentrum Berlin für Materialien und Energie GmbH<br> Hahn-Meitner-Platz 1, 14109 Berlin</p> <p>[c] Dr. Marcel Risch<br> Nachwuchsgruppe Gestaltung des Sauerstoffentwicklungsmechanismus<br> Helmholtz-Zentrum Berlin für Materialien und Energie GmbH<br> Hahn-Meitner-Platz 1, 14109 Berlin<br> E-mail: marcel.risch@helmholtz-berlin.de</p>
Effect of stochastic deformation on the vibration characteristics of a tube bundle in axial flow: code and data
<p>These files accompany the following publication:</p> <p>Dolfen, H., Vandewalle, S., & Degroote, J. (2023). Effect of stochastic deformation on the vibration characteristics of a tube bundle in axial flow. Nuclear Engineering and Design, 411, 112412. <a href="https://doi.org/10.1016/j.nucengdes.2023.112412">doi:10.1016/j.nucengdes.2023.112412</a>.</p> <p>In this publication the effect of a stochastic bow deformation on the vibration characteristics of a tube bundle was investigated. The Monte Carlo and generalized Polynomial Chaos (gPC) method were used. For the latter method, the <a href="https://chaospy.readthedocs.io/en/master/">chaospy Python-package</a> was used. Further dependencies include the numpy, scipy and matplotlib Python packages. The gPC was benchmarked with the Monte Carlo method on a steady CFD case. The the gPC was used on an FSI case used to extract the output quantity of interest, the vibration characteristics. This FSI case was run in the open-source code <a href="https://github.com/pyfsi/coconut">CoCoNuT</a>. This code developed at Ghent University is Python-based and has the capability to couple existing solvers, both open-source and commercial solvers.</p> <p>The archive includes scripts to set-up the steady CFD case as well as the FSI case, the used version of CoCoNuT and some post-processing scripts. ReadMe files are provided to explain the files, and what adjustments are likely needed to make it work on a different system. For CoCoNuT to work, the 'coconut' folder should be added to the PYTHONPATH environment variable. For requirements to run CoCoNuT, refer to the <a href="http://pyfsi.github.io/coconut/">documentation</a>.</p>
Ice-Flow Perturbation Analysis: A method to estimate ice-sheet bed topography and conditions from surface datasets (data)
<p>This dataset accompanies the paper 'Ice-Flow Perturbation Analysis: A method to estimate ice-sheet bed topography and conditions from surface datasets' in Journal of Glaciology, and can be used alongside the provided code to reproduce the figures,</p>
Flow cytometry data (Multiclonal Experiments 1-3)
<p>Flow cytometry data from publication:</p> <blockquote> <p>Claus-Peter Stelzer, Maria Pichler, Peter Stadler, Genome streamlining and clonal erosion in nutrient-limited environments: a test using genome-size variable populations, <em>Evolution</em>, Volume 77, Issue 11, November 2023, Pages 2378–2391, <a href="https://doi.org/10.1093/evolut/qpad144">https://doi.org/10.1093/evolut/qpad144</a></p> </blockquote> <p>Please cite this study when using this data.</p> <p><strong>Multiclonal experiments</strong></p> <p>Experiment 1: 11.10.2017 - 22.11.2017</p> <p>Experiment 2: 15.02.2018 - 19.04.2018</p> <p>Experiment 3: 18.04.2018 - 05.07.2018</p>
Flow cytometry data (Clone triplets experiment)
<p>Flow cytometry data of publication:</p> <blockquote> <p>Stelzer, C.P., M. Pichler, P. Stadler, Genome streamlining and clonal erosion in nutrient-limited environments: a test using genome-size variable populations, <em>Evolution</em>, Volume 77, Issue 11, November 2023, Pages 2378–2391, <a href="https://doi.org/10.1093/evolut/qpad144">https://doi.org/10.1093/evolut/qpad144</a></p> </blockquote> <p>Please cite this study if you use the data.</p> <p> </p> <p>Experiments with three clones differing in genome size</p> <p>First Run (05.07.2017-09.08.2017)</p> <p>Second Run (17.08.2017-27.09.2017)</p>
Data for reconstruction of planar flow field
<p>The zip file consists of four subfolders. Refer to "Synopsis.pdf" for detailed explanations on contents in each subfolder.</p>
Tara Nutrient and Flow Cytometry Data
<p>"Tara Oceans systematically collected ~35,000 samples for morphological, genetic, and environmental analyses using standardized protocols across multiple depths at global scale, aiming to facilitate a holistic study on how environmental factors and biogeochemical cycles affect oceanic life. ... Tara Oceans collected seawater samples within the epipelagic layer, both from the surface water and the deep chlorophyll maximum (DCM) layers, as well as the mesopelagic zone." (1)<br> Data provided for time, lat, and lon are mean values based on CTD casts that matched closest in location and depth of the actual sampling locations. This dataset includes environmental, nutrient, diversity, and flow cytometry data associated with samples found in the Tara Eukaryote Annotated 18s OTU Counts and Tara Prokaryote Annotated 16s OTU Counts datasets.</p> <p>(1) https://www-science-org.offcampus.lib.washington.edu/doi/full/10.1126/science.1261359</p>
ScienceDex guides
Understand access before you commit
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.