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295 results for “Approximation”
Data from: Inferring the origin of populations introduced from a genetically structured native range by approximate Bayesian computation: case study of the invasive ladybird Harmonia axyridis
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Data from: Wheat alleles introgress into selfing wild relatives: empirical estimates from Approximate Bayesian Computation in Aegilops triuncialis.
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Data from: Cophylogeny Reconstruction via an Approximate Bayesian Computation
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Data from: An approximate solution for a penny-shaped hydraulic fracture that accounts for fracture toughness, fluid viscosity and leak-off
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Data from: Dynamics of pre-choice and post-choice behaviour: rats approximate optimal strategy in a discrete-trial decision task
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Data from: Natural hybridization between genera that diverged from each other approximately 60 million years ago
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Microplastics and Microfibers extracted from box core of sediment sampled from Santa Barbara Basin, on Cal-ECHOES cruise, 2010, at 34°17.228’ N, 120°02.135’ W, in approximately 580 m water depth.
A box core was taken in the Santa Barbara Basin on the Cal-ECHOES cruise, in October 2010, at 34°17.228’ N, 120°02.135’ W, in approximately 580 m water depth. X-radiographs were taken of the core to date it to a 1-2 year timescale. The core was cut every 0.5 cm with a thin wire, oven-dried, washed, and wet-sieved over a 104 μm sieve. The >104 μm was first sorted for fish otoliths by William Jones, and then sorted again for this study for microplastics and microfibers with a dissecting microscope. Every particle was measured, photographed, and categorized. A subset of particles were also spectrally identified as plastic or not plastic via FTIR spectroscopy. These are the lengths of the particles measured.
Microplastics and Microfibers extracted from box core of sediment sampled from Santa Barbara Basin, on Cal-ECHOES cruise, 2010, at 34°17.228’ N, 120°02.135’ W, in approximately 580 m water depth.
A box core was taken in the Santa Barbara Basin on the Cal-ECHOES cruise, in October 2010, at 34°17.228’ N, 120°02.135’ W, in approximately 580 m water depth. X-radiographs were taken of the core to date it to a 1-2 year timescale. The core was cut every 0.5 cm with a thin wire, oven-dried, washed, and wet-sieved over a 104 μm sieve. The >104 μm was first sorted for fish otoliths by William Jones, and then sorted again for this study for microplastics and microfibers with a dissecting microscope. Every particle was measured, photographed, and categorized. A subset of particles were also spectrally identified as plastic or not plastic via FTIR spectroscopy.
RNA seq analysis of murine whole colon using Takara SMART-Seq Stranded kit. Libraries were sequenced on an Illumina NovaSeq 6000 to an approximate sequencing depth of 60 million total reads
GEO Series GSE181502. Mus musculus. 28 samples. Type: Expression profiling by high throughput sequencing.
RNAseq of approximately 500 sorted congenic wild type or CAR deficient CD4+ T cells isolated from small intestine lamina propria, colonic lamina propria, or spleen from Rag deficient hosts at 3 weeks
GEO Series GSE149218. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
The expression levels of genes on trisomic chromosomes (chromosome 13, 18 or 21) are increased approximately 1.5-fold on average compared with diploid cells
GEO Series GSE120291. Homo sapiens. 16 samples. Type: Expression profiling by array.
Data for "Abrupt transitions in an atmospheric single-column model with weak temperature gradient approximation"
<p>These are the main output files for the experiment studied in the paper "Abrupt transitions in a single-column model with weak temperature gradient approximation". File names and descriptions are as follows:</p> <ol> <li>hysteresis.mat: A MATLAB file that contains WRF output from the hysteresis test used to create Figure 5 of the paper. The variable names should be straightforward to someone familiar with WRF. (Full WRF output was not saved for these runs.)</li> <li>input_soil: surface initial conditions for WRF SCM, same for all experiments</li> <li>input_sounding: initial sounding, same for all experiments</li> <li>main_fls1: a WTG SST-ramping experiment showing <span class="math-tex">\(f_{\rm LS}\to 1\)</span> as described in the paper.</li> <li>main_rce_ramp: a SST-ramping experiment without the weak temperature gradient approximation</li> <li>namelist.input.rce: the namelist input file for the "rce_run" experiment</li> <li>namelist.input.wtg: the namelist input files for the "wtg_ramp_run1" experiment</li> <li>rce_run: the main RCE experiment used to create the background WTG profile for the wtg_ramp_run1 experiment and the wtg_noramp experiment</li> <li>wtg_noramp: a 180-day experiment with WTG but no ramping, for comparison</li> <li>wtg_ramp_run1: the main WTG ramping experiment showing the abrupt transitions</li> </ol> <p> </p>
Data for ""Approximate multifractal correlation and products of universal multifractal fields, with application to rainfall data" by Auguste Gires, Ioulia Tchiguirinskaia, and Daniel Schertzer, NPG 2020
<p>This data set corresponds to the python scripts and data that were used for the paper :<br> “Approximate multifractal correlation and products of universal multifractal fields, with application to rainfall data” by Auguste Gires, Ioulia Tchiguirinskaia, and Daniel Schertzer which has been published in 2020 in Nonlin. Processes Geophys. (https://www.nonlinear-processes-in-geophysics.net/).</p> <p>Should this data be used, the above mentioned paper should be cited.</p>
Data for "Abrupt transitions in an atmospheric single-column model with weak temperature gradient approximation"
<p>These are the main output files for the experiment studied in the paper "Abrupt transitions in a single-column model with weak temperature gradient approximation". File names and descriptions are as follows:</p> <ol> <li>hysteresis.mat: A MATLAB file that contains WRF output from the hysteresis test used to create Figure 5 of the paper. The variable names should be straightforward to someone familiar with WRF. (Full WRF output was not saved for these runs.)</li> <li>input_soil: surface initial conditions for WRF SCM, same for all experiments</li> <li>input_sounding: initial sounding, same for all experiments</li> <li>main_fls1: a WTG SST-ramping experiment showing fLS→1 as described in the paper.</li> <li>main_rce_ramp: a SST-ramping experiment without the weak temperature gradient approximation</li> <li>namelist.input.rce: the namelist input file for the "rce_run" experiment</li> <li>namelist.input.wtg: the namelist input files for the "wtg_ramp_run1" experiment</li> <li>rce_run: the main RCE experiment used to create the background WTG profile for the wtg_ramp_run1 experiment and the wtg_noramp experiment</li> <li>wtg_noramp: a 180-day experiment with WTG but no ramping, for comparison</li> <li>wtg_ramp_run1: the main WTG ramping experiment showing the abrupt transitions</li> </ol>
Approximating Bipartite Minimum Vertex Cover in the CONGEST model
Full video presentation of the paper: Approximating Bipartite Minimum Vertex Cover in the CONGEST model.<br><br>Appears in Session 4 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020<br><a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>
Approximate Majority With Catalytic Inputs (video)
Full video presentation of the paper: Approximate Majority With Catalytic Inputs.<br><br>Appears in Session 3 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020<br><a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>
Data from: Demographic inferences using short-read genomic data in an Approximate Bayesian Computation framework: in silico evaluation of power, biases, and proof of concept in Atlantic walrus
Approximate Bayesian Computation (ABC) is a powerful tool for model-based inference of demographic population histories from large genetic data sets. For most organisms its implementation has been hampered by the lack of sufficient genetic data. Genotyping-by-sequencing (GBS) provides cheap genome-scale data to fill this gap, but its potential has not fully been exploited. Here, we explored power, precision and biases of a coalescent-based ABC approach where GBS data were modeled with either a population mutation parameter (θ) or with a fixed sites (FS) approach, allowing single or several segregating sites per locus. With simulated data ranging from 500 to 50,000 loci a variety of demographic models could be reliably inferred across a range of timescales and migration scenarios. Posterior estimates were informative with 1,000 loci for migration and split time in simple population divergence models. In more complex models posterior distributions were wide and almost reverted to the uninformative prior even with 50,000 loci. ABC parameter estimates, however, were generally more accurate than an alternative composite-likelihood method. Bottleneck scenarios proved particularly difficult and only recent bottlenecks without recovery could be reliably detected and dated. Notably, minor allele frequency filters – usual practice for GBS data – negatively affected nearly all estimates. With this in mind, we used a combination of FS and θ approaches on empirical GBS data generated from the Atlantic walrus (Odobenus rosmarus rosmarus), collectively providing support for a population split before the last glacial maximum followed by asymmetrical migration and a range-wide bottleneck. Overall, this study evaluates the potential and limitations of GBS data in an ABC-coalescence framework and proposes a best-practice approach.
Additional Data from ``Developments in Stochastic Coupled Cluster Theory: The initiator approximation and application to the Uniform Electron Gas''
<p>We describe further details of the Stochastic Coupled Cluster method and a diagnostic of such calculations, the shoulder height, akin to the plateau found in Full Configuration Interaction Quantum Monte Carlo. We describe an initiator modification to Stochastic Coupled Cluster Theory and show that initiator calculations can be extrapolated to the unbiased limit. We apply this method to the 3D 14-electron uniform electron gas and present complete basis set limit values of the CCSD and previously unattainable CCSDT correlation energies for up to $r_s=2$, showing a requirement to include triple excitations to accurately calculate energies at high densities.</p>
Approximation quality for matrix lnsp3937
<p>Approximation quality for matrix lnsp3937. The left y-axis refers to the approximation errors <span class="math-tex">\(e^*\)</span> divided by <span class="math-tex">\(‖A‖_F\)</span> , where <span class="math-tex">\(e^*\)</span> denotes either <span class="math-tex">\(e_{rand}\)</span> (3), <span class="math-tex">\(e_{det}\)</span> (5), or the smallest error possible by the TSVD. The right y-axis refers to the error indicators <span class="math-tex">\(E^*\)</span> divided by <span class="math-tex">\(‖A‖_F\)</span> , where <span class="math-tex">\(E^*\)</span> denotes either <span class="math-tex">\(E_{rand}\)</span> (4) or <span class="math-tex">\(E_{det}\)</span> (10). As mentioned in Section II-A2, the error<br> indicator for RandQB_EI fails in double precision floating point arithmetic for approximation qualities smaller than <span class="math-tex">\(2.1\cdot 10^{-7}\)</span>.</p>
Data repository of the paper "Expectation Values from the Single-Layer Quantum Approximate Optimization Algorithm on Ising Problems"
<p>This data repository contains the I-set instances of the paper "Expectation Values from the Single-Layer Quantum Approximate Optimization Algorithm on Ising Problems". </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.