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756 results for “Monte”
PM_034673_E_Oviedo_Monte_Naranco
<u>File Name</u>: PM_034673_E_Oviedo_Monte_Naranco.jpg <br><u>Sublocation</u>: Iglesia Santa Maria del Naranco <br><u>Location</u>: Oviedo (Monte Naranco) <br><u>Province</u>: Asturias <br><u>Country</u>: Spain <br><u>Header</u>: Exterior. Originalmente un palacio o salón de justicia. Siglo IX. <br><u>Description</u>: Church (Santa María del Naranco) Exterior Originally a palace or justice hall 9th century <br><u>Keywords</u>: Asturias, Cultural heritage, Europe, Monuments, Naranco, Oviedo, Pre-Romanesque art, Romanesque, Spain, Styles <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>
PM_034675_E_Oviedo_Monte_Naranco
<u>File Name</u>: PM_034675_E_Oviedo_Monte_Naranco.jpg <br><u>Sublocation</u>: Iglesia Santa Maria del Naranco <br><u>Location</u>: Oviedo (Monte Naranco) <br><u>Province</u>: Asturias <br><u>Country</u>: Spain <br><u>Header</u>: Exterior. Originalmente un palacio o salón de justicia. Siglo IX. <br><u>Description</u>: Church (Santa María del Naranco) Exterior Originally a palace or justice hall 9th century <br><u>Keywords</u>: Asturias, Cultural heritage, Europe, Monuments, Naranco, Oviedo, Pre-Romanesque art, Romanesque, Spain, Styles <br><br><u>Author</u>: Photo: Paul M.R. Maeyaert <br><u>Copyright</u>: Paul M.R. Maeyaert <br>
Updated NLL-SSST-coherence earthquake relocation catalog for the 2020 Mw 6.5 Monte Cristo Range, Nevada earthquake sequence.
<p>CSV catalog and plots of NLL-SSST-coherence earthquake relocations of 17583 events M≥1 2020.01.01 to 2021.08.20 for the 2020 Mw 6.5 Monte Cristo Range, Nevada earthquake sequence.</p> <p>This dataset is an update of the relocations presented in the pre-print article:<br> The 2020 Mw 6.5 Monte Cristo Range, Nevada earthquake: relocated seismicity shows rupture of a complete shear-crack system<br> https://eartharxiv.org/repository/view/1904/</p> <p> </p> <p>Plots show map, view from south and view from N73E of NLL-SSST-coherence relocations events with error-ellipsoid, semi-major axis ≤ 5 km. Caption (adapted from https://eartharxiv.org/repository/dashboard/1904/ ; Fig 2):</p> <p>Event color showing hypocenter depth and symbol size proportional to magnitude. Re-picked Mw6.5 hypocenter and its proxy (mean hypocenter of 3 well constrained foreshocks) indicated by small and large, dark red, cross symbols, respectively. SHmin and SHmax show directions of regional minimum and maximum compressive stress, respectively; the intermediate principal stress axis is vertical. Seismic stations shown as dark gray tetrahedrons. Brown lines show faults from the Quaternary fault and fold database for the United States. Background topography image from OpenTopgraphy.org. Red lines show mapped surface ruptures from http://www.nbmg.unr.edu/Geohazards/Earthquakes/MonteCristoRangeEQData.html and https://doi.org/10.1785/0220200371</p>
Datasets of fitted toy Monte Carlo samples for "Gaussian Process-based calculation of look-elsewhere trials factor"
<p>For the paper "Gaussian Process-based calculation of look-elsewhere trials factor", we generated and fitted a number of toy Monte Carlo samples which can be used to reproduce figures from the paper or do tests of hypotheses inspired by the method suggested in the article.</p> <p>Together with the hdf5 files containing the samples, we also provide a Jupyter notebook which was used to produce the figures.</p>
Reference Dataset for Benchmarking Organ Doses Derived from Monte Carlo Simulations of CT Exams
<p>This reference dataset contains CT scanner x-ray source characteristics, filtration profile, de-identified patient image data and size characteristics, voxelized patient models, exam characteristics, x-ray tube current data, and organ dose results in tabular form from Monte Carlo (MC) simulations of abdominal/pelvis CT exams of pregnant patients. This dataset can be used for benchmarking MC simulation codes for CT dosimetry.</p>
Taming the fixed-node error in diffusion Monte Carlo via range separation
<p>Suplementary information.</p> <p>Contains the org-mode computational notebook with all the input data (geometries, basis sets, pseudo-potentials) and output data (computed energies, densities, number of determinants) related to the article.</p> <p>A csv file is created by the notebook and an HTML export of the notebook is also provided.</p>
Example of reverse Monte Carlo simulation for fcc high-entropy alloy CrMnFeCoNi
<p>The data set contains the example of reverse Monte Carlo (RMC) simulation of EXAFS spectra collected for fcc high-entropy alloy CrMnFeCoNi.</p> <p>The simulation was performed by the EvAX code freely available from http://www.dragon.lv/evax/. </p> <p> </p>
Quantum Monte Carlo data for 4He inside Ar-Preplated MCM-41 Nanopores
<p>Raw quantum Monte Carlo data for argon pre-plated MCM-41 nanopores with L = 50 Å.</p> <p>Details of the simulations are published here: https://journals.aps.org/prb/abstract/10.1103/PhysRevB.102.144505</p>
Determinant Quantum Monte Carlo data for the Hubbard model on the square and honeycomb lattice.
<p>Data generated with QUEST 1.4.9. For documentation see these two homepages:<br> Original homepage: http://quest.ucdavis.edu/<br> Newest version available at: https://code.google.com/archive/p/quest-qmc/</p> <p>Available data from equal time measurements:</p> <ul> <li>up-up charge correlation function</li> <li>up-dn charge correlation function</li> <li>sz-sz spin correlation function</li> <li>pair correlation function</li> <li>kinetic energy</li> <li>total energy</li> <li>chi thermal</li> <li>squared magnetization</li> <li>ZZ AF structure factor</li> </ul> <p>Data for the square lattice calculated for</p> <ul> <li>lattice sizes 8x8, 10x10, 12x12</li> <li>trotter discretizations 0.05, 0.1, 0.2</li> <li>U 0.0 to 7.1 in steps of 0.1</li> </ul> <p>Data for the honeycomb lattice calculated for</p> <ul> <li>lattice sizes 6x6, 9x9, 12x12</li> <li>trotter discretizations 0.05, 0.1, 0.2</li> <li>U 0.0 to 7.1 in steps of 0.1</li> </ul> <p>All energies are in units of the hopping parameters which is set to t=1. All simulations are done for half filling.</p> <p>The data are used in the publication "First-order metal-insulator transitions in the extended Hubbard model due to self-consistent screening of the effective interaction" available on the arXiv (arXiv:1706.09644). There it is used to do an extrapolation of finite size and finite trotter errors and finally calculate derivatives of charge correlation functions w.r.t. the interaction U.</p> <p>The data are available in hdf5 archives and can easily be accessed, e.g., with python and h5py. An example python script is included. Relevant input parameters are included in the h5 files.</p> <p>All calculated quantities are averaged over multiple consecutive simulations, which is why the data is not presented in the usual QUEST output. This was necessary due to limited walltime on the used supercomputer.</p> <p>This version (v2) includes the number of bins used in each simulation and a slighlty changed python script to read the data.</p>
Accompanying dataset for: A Monte Carlo Method for Metamorphic Testing of Machine Translation Services
<p>This dataset includes enhanced analysis of the machine translation data. The original dataset has been reported in [1], where white spaces were used to separate words in different languages. This is however not the best method of analyzing some Asian languages such as the Chinese language. In the present analysis, we used a character-based approach to separating the Chinese and Japanese results, hence obtaining a different set of BLEU and Cosine Similarity scores. These new scores are given in the present dataset.</p> <p>[1] Daniel Pesu, Zhi Quan Zhou, Jingfeng Zhen, & Dave Towey. (2018). Accompanying dataset for: A Monte Carlo Method for Metamorphic Testing of Machine Translation Services (Version 1.0) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1194560</p>
The Monte Carlo PUF
<p>Collected MUPUF results with different design parameters and temperatures.</p> <p>These datasets were used to analysis the error rate and intra-distance of MCPUF.</p> <p> </p> <p>Abstract of paper "The Monte Carlo PUF":</p> <p>Physically unclonable functions are used for IP protection, hardware authentication and supply chain security. While many PUF constructions have been put forward in the past decade, only few of them are applicable to FPGA platforms. Strict constraints on the placement and routing are the main disadvantages of the existing PUFs on FPGAs, because they place a high effort on the designer. In this paper we propose a new delay-based PUF construction called Monte Carlo PUF, that does not require low-level placement and routing control. This construction relies on the on-chip Monte Carlo method that is applied for measuring the delays of logic elements in order to extract a unique device fingerprint. The proposed construction allows a trade-off between the evaluation time and the error rate. The Monte Carlo PUF is implemented and evaluated on Xilinx Spartan-6 FPGAs.</p>
Herbarium specimen image of Stenogramme interrupta (C.Agardh) Mont. ex Harv., part of the collection of Royal Botanic Garden Edinburgh
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Herbarium specimen image of Stenogramme interrupta (C.Agardh) Mont. ex Harv., part of the collection of Royal Botanic Garden Edinburgh
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter : Weighted Monte Carlo samples for neutron star observables
<p>This data release contains weighted Monte Carlo samples associated with</p> <p>Legred, Chatziioannou, Essick, Han, and Landry, 2021</p> <p>"Impact of PSR J0740+6620 radius constraint on the properties of high-density matter"</p> <p>Phys. Rev. D 104, 063003;</p> <p>doi:10.1103/PhysRevD.104.063003</p> <p> </p> <p> </p> <p> </p> <p> </p>
CTAO Monte Carlo Simulations - Eventlists on DL2 data level - prod5
<p>Author: Cherenkov Telescope Array Observatory; Cherenkov Telescope Array Consortium<br>Contact: open-data@cta-observatory.org</p> <p>The <a href="https://www.cta-observatory.org/">Cherenkov Telescope Array Observatory (CTAO)</a> will be the next-generation gamma-ray observatory and is currently under construction on the island of La Palma (Spain) and near Paranal (Chile). <br>This repository provides access to reconstructed event information (DL2- and DL1-level, simulation parameters) from Monte Carlo simulations of the CTAO Northern Array (production 5).</p> <p>The Monte Carlo simulations for prod5 are described in <a href="https://arxiv.org/abs/2108.04512">arXiv:2108.04512</a>, the simulation telescopes models used in the telescope simulation program <a href="https://www.mpi-hd.mpg.de/hfm/~bernlohr/sim_telarray/">sim_telarray</a> and the configuration used in the air-shower code <a href="https://www.iap.kit.edu/corsika/index.php">CORSIKA</a> are available from the Zenodo archive for <a href="../record/6218687">CTA Prod5 Telescope Models</a>.</p> <p>MC events are calibrated and reconstructed using the <a href="https://ctapipe.readthedocs.io/">ctapipe</a> package and stored for the following data levels:</p> <ul> <li> R1-MC: simulated raw data (output from sim_telarray)</li> <li> <strong>DL1 (this repository)</strong>: telescope level data including images and image parameters</li> <li> <strong>DL2 (this repository)</strong>: reconstructed event parameters such as energy, <strong>direction</strong>, gamma/hadron discrimination parameters. Note that this repository only contains the direction information.</li> <li>DL3: selected events with associated instrument response functions (IRFs). Preliminary DL3-IRFs are available from [here](https://doi.org/10.5281/zenodo.5499839).</li> </ul> <p>For a description of the file format and data model, <a href="https://ctapipe.readthedocs.io/en/latest/user-guide/data_models/index.html">see ctapipe Data Model</a>.</p> <p>Data set description:</p> <ul> <li>using ctapipe version 0.17 (<a href="https://github.com/cta-observatory/ctapipe/releases/tag/v0.17.0">GitHub release page</a>, <a href="../record/7118605">Zenodo page</a>)</li> <li>CTAO Northern Array on La Palma for the Alpha configuration (4 large-sized telescopes, 9 mid-sized telescopes)</li> <li>Zenith angles of 20 deg, telescope pointing direction north and south</li> <li>Primary particles: photons, protons</li> <li>Contained information: DL1 image and parameter data, DL2 geometry, simulation truths</li> <li>For convenience, the same data is provided in a single, large file per particle type for the whole dataset which do not contain the low-level DL1 image information and a larger number of files including this information.</li> </ul> <p>We explicitly note that the products provided are preliminary and do not reflect the final performance of the CTA Observatory, neither are data structure or formats finalized. We also note that these data products are different to those used for the <a href="../record/5499840">CTAO Instrument Response Functions</a>.<br>In cases in which the data provided in this repository are used in a research project, we ask that the following acknowledgment is added in any resulting publication:</p> <p>"This research has made use of the CTA DL1 and DL2 Event lists provided by the CTA Observatory and Consortium (version prod5-DL2-release1-DL2)" and cite this repository in the reference section of your publication.</p> <p>We would like to thank the computing centers that provided resources for the generation of the Prod5 simulation set,<a href="../record/5499840"> click here for a list of service providers</a>.</p>
Simulation output for Improving the stability of bivariate correlations using informative Bayesian priors: A Monte Carlo simulation study
<p>This repository contains the (compressed) simulation output from <em>Improving the stability of bivariate correlations using informative Bayesian priors: A Monte Carlo simulation study</em>. On a Linux-based system, extract the contents with:</p> <pre><code class="language-bash">tar -xvzf raw_output_compressed.tar.gz </code></pre> <p>Please refer to the published article (https://doi.org/10.3389/fpsyg.2023.1253452) and the associated GitHub (<a href="https://github.com/carldelfin/stability-of-bivariate-correlations">github.com/carldelfin/stability-of-bivariate-correlations</a>) for additional information.</p>
Data from: Properties of Markov chain Monte Carlo performance across many empirical alignments -- part I
<p>Nearly all current Bayesian phylogenetic applications rely on Markov chain Monte Carlo (MCMC) methods to approximate the posterior distribution for trees and other parameters of the model. These approximations are only reliable if Markov chains adequately converge and sample from the joint posterior distribution. While several studies of phylogenetic MCMC convergence exist, these have focused on simulated datasets or select empirical examples. Therefore, much that is considered common knowledge about MCMC in empirical systems derives from a relatively small family of analyses under ideal conditions. To address this, we present an overview of commonly applied phylogenetic MCMC diagnostics and an assessment of patterns of these diagnostics across more than 18,000 empirical analyses. Many analyses appeared to perform well and failures in convergence were most likely to be detected using the average standard deviation of split frequencies, a diagnostic that compares topologies among independent chains. Different diagnostics yielded different information about failed convergence, demonstrating that multiple diagnostics must be employed to reliably detect problems. The number of taxa and average branch lengths in analyses have clear impacts on MCMC performance, with more taxa and shorter branches leading to more difficult convergence. We show that the usage of models that include both Γ-distributed among-site rate variation and a proportion of invariable sites are not broadly problematic for MCMC convergence but are also unnecessary. Changes to heating and the usage of model-averaged substitution models can both offer improved convergence in some cases, but neither are a panacea.</p>
Data from: Properties of Markov chain Monte Carlo performance across many empirical alignments --part II
<p>Nearly all current Bayesian phylogenetic applications rely on Markov chain Monte Carlo (MCMC) methods to approximate the posterior distribution for trees and other parameters of the model. These approximations are only reliable if Markov chains adequately converge and sample from the joint posterior distribution. While several studies of phylogenetic MCMC convergence exist, these have focused on simulated datasets or select empirical examples. Therefore, much that is considered common knowledge about MCMC in empirical systems derives from a relatively small family of analyses under ideal conditions. To address this, we present an overview of commonly applied phylogenetic MCMC diagnostics and an assessment of patterns of these diagnostics across more than 18,000 empirical analyses. Many analyses appeared to perform well and failures in convergence were most likely to be detected using the average standard deviation of split frequencies, a diagnostic that compares topologies among independent chains. Different diagnostics yielded different information about failed convergence, demonstrating that multiple diagnostics must be employed to reliably detect problems. The number of taxa and average branch lengths in analyses have clear impacts on MCMC performance, with more taxa and shorter branches leading to more difficult convergence. We show that the usage of models that include both Γ-distributed among-site rate variation and a proportion of invariable sites are not broadly problematic for MCMC convergence but are also unnecessary. Changes to heating and the usage of model-averaged substitution models can both offer improved convergence in some cases, but neither are a panacea.</p>
Photogrammetry dataset for two Bronze Age human teeth from Monte do Vale do Ouro 2 (Ferreira do Alentejo, Portugal)
<p>This photogrammetry dataset that accompanies the publication: "The embodiment of craft production in Bronze Age Portugal: Exceptional dental wear grooves in an individual from Monte do Vale do Ouro 2 (Ferreira do Alentejo, Portugal)" by John Charles Willman, António Carlos Valera, and Ana Maria Silva in the International Journal of Osteoarchaeology, 31(2):252-262. <a href="https://doi.org/10.1002/oa.2944" target="_blank" rel="noopener">https://doi.org/10.1002/oa.2944</a>. Includes photographs of a left and right mandibular lateral incisor (I<sub>2</sub>) with profound dental wear grooves on their lingual root surfaces. 3D models and texture files also included.</p> <p>Part of the “VAPP” Project (<em>Virtual Anthropology of Prehistoric Portugal, </em>Marie Skłodowska-Curie Actions Individual Fellowship, H2020-MSCA-IF-2018, No. 839822).</p>
Combining Analytical Modeling, Realistic Simulation and Real Experimentation for the Optimization of Monte-Carlo Applications on the European Grid Infrastructure
<p>Data and scripts used to generate figures presented in the paper "Combining Analytical Modeling, Realistic Simulation and Real Experimentation for the Optimization of Monte-Carlo Applications on the European Grid Infrastructure" submitted to the Future Generation Computer Systems Journal.</p>
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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.