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100 results for “Reproduction package”
Reproduction package for the paper "The Apertif Radio Transient System (ARTS): Design, Commissioning, Data Release, and Detection of the first 5 Fast Radio Bursts"
<p>This is a basic reproduction package for the paper "The Apertif Radio Transient System (ARTS): Design, Commissioning, Data Release, and Detection of the first 5 Fast Radio Bursts" by van Leeuwen et al. (2023).</p> <p>* arXiv:<a href="https://arxiv.org/abs/2205.12362">arXiv:2205.12362</a><br> * DOI: <a href="https://doi.org/10.1051/0004-6361/202244107">10.1051/0004-6361/202244107</a></p> <p> </p>
Reproduction Package for STTT Submission `Cooperative Verification: A Literature Review'
<p>This artifact contains the aggregated data used for the article “Cooperative Verification: A Literature Review”.</p> <p>The artifact consists of the following data files:</p> <p>|– stage-1_search-space.csv<br> |– stage-2-3-4_keyword-search_process-title-abstract.csv<br> |– review_sheet.csv</p> <p><strong>Search space for literature review</strong></p> <p>The file <code>stage-1_search-space.csv</code> contains metadata for the articles comprising the search space for our literature review. These data correspond to the output of <code>Stage 1</code> in the methodology described in the paper.</p> <p><strong>Filtering process</strong></p> <p>The file <code>stage-2-3-4_keyword-search_process-title-abstract.csv</code> contains the data corresponding to the stages 2, 3, and 4 of the methodology described in the paper. It contains metadata for the articles that passed the filter of <code>keyword-search</code>, and the decisions based on reviewing titles and abstracts.</p> <p><strong>Review sheet</strong></p> <p>The file <code>review_sheet.csv</code> contains metadata for the articles we reviewed. It contains the information related to the application of our definition to the techniques presented in these articles, as well as the class assigned to the cooperative techniques.</p> <p><strong>Generating numbers</strong></p> <p>Following commands can be executed to reproduce the numbers used in our literature review.</p> <pre><code># Change directory to the directory containing the CSV files of this artifact. # Number of papers in our search space. cat stage-1_search-space.csv | tail -n +2 | wc -l # Number of papers after keyword search. cat stage-2-3-4_keyword-search_process-title-abstract.csv | tail -n +2 | wc -l # Number of papers that are excluded based on titles. cut -f11 stage-2-3-4_keyword-search_process-title-abstract.csv | tail -n +2 | sort | uniq -c # Number of papers that are excluded based on abstracts. cut -f12 stage-2-3-4_keyword-search_process-title-abstract.csv | tail -n +2 | sort | uniq -c # Number of papers in different combination classes. cut -f8 review_sheet.csv | tail -n +2 | sort | uniq -c</code></pre>
Reproduction package for the paper "Massive pre-main-sequence stars in M17: Firtst and second overtone CO bandhead emission and the thermal infrared"
<p>This is a basic reproduction package for the paper "Massive pre-main-sequence stars in M17: First and second overtone CO bandhead emission and the thermal infrared" by J. Poorta et al. 2023. It aims to provide the most important data products and software to check and reproduce the main results of the paper.</p>
Reproduction package for the paper "The Impact of Hard and Easy Negative Training Data on Vulnerability Prediction Performance"
<p>This Reproduction package contains the datasets, code and results for the paper "The Impact of Hard and Easy Negative Training Data on Vulnerability Prediction Performance" for other researchers to use for reproducing or improving our work. </p>
Reproduction package for "ClG 0217+70: A massive merging galaxy cluster with a large radio halo and relics"
<p>This is the reproduction package for "ClG 0217+70: A massive merging galaxy cluster with a large radio halo and relics", which has been accepted for publication in A&A.</p> <p>To use this package, please read the README.</p> <p>This package is tested in an environment that contains:</p> <ul> <li>SPEX v3.06</li> <li>CIAO v4.12</li> <li>python 3.6.5 <ul> <li>numpy 1.14.3</li> <li>astropy 3.0.2</li> <li>astroquery 0.4</li> <li>scipy 1.1.0</li> <li>matplotlib 2.2.2</li> </ul> </li> </ul>
Uncovering the Benefits and Challenges of Continuous Integration Practices - Reproduction Package
<p>This is a reproduction package for our paper on continuous practices in software organizations.</p>
Reproduction package for the paper: "Detection of ultra-fast radio bursts from FRB 20121102A"
<p><br># Reproduction package for the paper "Detection of ultra-fast radio bursts from FRB 20121102A"<br>Authors: Mark P. Snelders, K. Nimmo, J.W.T. Hessels, Z. Bensellam, L.P. Zwaan, P. Chawla, O.S. Ould-Boukattine, F. Kirsten, J.T. Faber and V. Gajjar.<br>arXiv link: https://arxiv.org/abs/2307.02303<br>DOI published article: Nature Astronomy, 19 October 2023, https://doi.org/10.1038/s41550-023-02101-x<br><br>This work has been made possible by an NWO Vici grant (Principal investigator, J.W.T.H.). <br><br>## Raw Data<br><br><strong>- The data are 100% publicly available and are explained in great detail in the following post: http://seti.berkeley.edu:8000/frb-data/</strong><br><strong>- The data are available from the Breakthrough Initiatives Open Data Portal with target name FRB121102: https://breakthroughinitiatives.org/opendatasearch</strong><br><br>In this paper we have re-processed and re-analysed data from the Green Bank Telescope that made use of the Breakthrough Listen digital backend. I will call this the GBT BL data. Below you can find links to multiple papers, GitHub repositories and blogposts that explain the GBT BL data.</p><p>- My paper describing the search and analysis of the ultra-fast radio bursts:<br> * https://ui.adsabs.harvard.edu/abs/2023arXiv230702303S/abstract<br> * https://www.nature.com/articles/s41550-023-02101-x<br>- First detection of the bursts at 8 GHz: https://ui.adsabs.harvard.edu/abs/2018ApJ...863....2G/abstract<br>- More bursts from the same dataset with machine learning detections: https://ui.adsabs.harvard.edu/abs/2018ApJ...866..149Z/abstract<br>- Explaining the Breakthrough Listen project: https://ui.adsabs.harvard.edu/abs/2017AcAau.139...98W/abstract<br>- Explaining the GBT breakthrough listen recorder: https://ui.adsabs.harvard.edu/abs/2018PASP..130d4502M/abstract<br>- Explaining the data formats: https://ui.adsabs.harvard.edu/abs/2019PASP..131l4505L/abstract<br>- Python 2 code to work with the baseband data: https://github.com/greghell/extractor (NOTE THAT IT IS PYTHON 2!!) (I recommend using Python 2.7 if you make use of that repo)<br>- Structure of the baseband data: https://github.com/UCBerkeleySETI/breakthrough/blob/master/doc/RAW-File-Format.md<br>- More information: https://github.com/UCBerkeleySETI/breakthrough/blob/master/GBT/waterfall.md<br>- A version of dspsr, called bl-dspsr, that can work with the GBT BL baseband data: https://github.com/UCBerkeleySETI/bl-dspsr<br><br>## Software<br><br>- The data was processed on multiple machines with various operating systems, which include, but are not limited to, macOS, Ubuntu and centOS.<br>- All the used software is open source, see the section above for more information, and also see the 'software' section in the paper.<br><br>## Figures and Tables</p><p>The files in this Zenodo package should be self-explanatory. E.g. `table_1.tar` contains all the scripts/notebooks/files needed to make table_1, and also contains table 1 itself. <br>The file: 'general_info.tar' is basically a txt file with the same info as provided here and it contains an offline version of the Breakthrough Listen blogpost that that explains the raw data. <br>The file: `helper_functions.tar` is a tarball that contains a Python file with a collection of helper functions that are used in the Jupyter notebooks (and the figures are made in the Jupyter notebooks). It also contains some files that are needed to e.g. remove the instrumental delay from the data.<br> <br>## End-to-End analysis scripts<br>The Python code/Jupyter notebooks in the tarfiles are end-to-end. </p><p>## Intermediate data products </p><p>The file `data_and_data_info.tar` contains two intermediate data products (both several gigabytes in size) and a txt file explaining the files and how they were made. Due to the Zenodo file size limitations I cannot upload everything. Please contact me at snelders@astron.nl or m.p.snelders@uva.nl or via ORCID to request any other files. <br><br><br><br> </p>
Reproduction Package for the paper "The early evolution of young massive clusters. II. The kinematic history of NGC 6618 / M 17"
<h2>Reproduction package for the paper "The early evolution of young massive clusters. II. The kinematic history of NGC 6618 / M 17".</h2><ul><li>This reproduction package aims for open science, with the internal API designation of 'Gold'</li><li>Authors: M. Stoop, A. Derkink, L. Kaper, A. de Koter, C. Rogers, M.C. Ramírez-Tannus, D. Guo, N. Azatyan</li><li>Paper DOI: https://doi.org/10.1051/0004-6361/202347383</li><li>Arxiv DOI: https://doi.org/10.48550/arXiv.2311.04174</li><li>Zenodo DOI: http://doi.org/10.5281/zenodo.8120575</li><li>Accepted for publication in Astronomy and Astrophysics (date of acceptance: 2023/10/27)</li></ul><h2>Raw Data</h2><ul><li>./gaia_files/ gives the ADQL queries on how to obtain the raw data from the Gaia database along with the raw Gaia data itself.</li><li>./other_files/ gives the other raw data obtained from other sources. For example the literature, Aladin, parsec isochrones.</li><li>We have cited the relevant references in the paper for raw data taken from the literature.</li><li>Optical VLT, SALT, WHT spectra (raw data, software and end-products) described in Appendix A can be requested from Annelotte Derkink.</li></ul><h2>Software</h2><ul><li>MacOS Big Sur 11.6</li><li>Jupyter Notebook (6.3.0)</li><li>Programming languages used: Python (3.9.7)</li><li>Python packages used: numpy (1.22.3), math (comes with Python), pandas (1.2.1), matplotlib (3.3.3), scipy (1.6.0), os (comes with Python), zero_point (0.0.1) (https://gitlab.com/icc-ub/public/gaiadr3_zeropoint), pyUPMASK (requires os, time, multiprocessing, astropy, pathlib) (https://github.com/msolpera/pyUPMASK)</li><li>Aladin Desktop (Version 11.0) (https://aladin.u-strasbg.fr/AladinDesktop/), will need java installed</li><li>Aladin Lite (https://aladin.cds.unistra.fr/AladinLite/)</li></ul><h2>Figures and Tables</h2><ul><li>Figures can be reproduced from the ./figures/ folder.</li><li>All material and data used are available either in the Raw Data or in the Intermediate Data</li><li>Jupyter notebooks (.ipynb files) provide the option to execute all code as ready-made to produce the figures: 'Cell' -> 'Run All'.</li><li>The figures shown in the paper will be saved in ./figures/figures_paper/ folder.</li><li>Tables can be reproduced from the ./tables/ folder similar to the figures.</li><li>Tables are saved in .csv files so they can easily be used. Tables are also saved in _latex.csv form for easy implementation in latex.</li></ul><h2>Intermediate data products</h2><ul><li>Intermediate data, such as the determined members of NGC6618 or found runaway stars, can be found in the /output_files/ folder.</li><li>The 'raw' data is also given here, because small corrections have been applied, which are recommended by the Gaia Consortium. This 'raw' data file is not the same as the one given in the ./gaia_files/ folder! This is to ensure that both the raw and intermediate data products are available.</li><li>./modules/ is part of the Python pyUPMASK module.</li></ul><h2>End-to-End analysis scripts</h2><ul><li>The end-to-end analysis to determine the members is given in the Jupyter Notebook 'membership_pyupmask.ipynb'.</li><li>The end-to-end analysis to search for runaways is given in the Jupyter Notebook 'runaways.ipynb'.</li><li>Minor 'end-to-end' analysis is done in the relevant figure or table Jupyter Notebook.</li></ul>
Reproduction package for 'Low-frequency radio observations of recurrent nova RS Ophiuchi with MeerKAT and LOFAR'
<p>This is a basic reproduction package for the paper "Low-frequency radio observations of recurrent nova RS Ophiuchi with MeerKAT and LOFAR".</p><p> </p><p> </p>
Reproduction package for the paper "A LOFAR sample of luminous compact sources coincident with nearby dwarf galaxies"
<p>Scripts to reproduce analyses from Vohl et al. 2023, A&A.</p>
Reproduction package for "What happened before?. Disks around the precursors of young Herbig Ae/Be stars"
<p>This is a basic reproduction package for the paper "What happened before?. Disks around the precursors of young Herbig Ae/Be stars" by Valegard et al. (2021)(https://doi.org/10.1051/0004-6361/202039802). It aims to provide the most important data products to check and reproduce the main results of the paper.</p>
Digging for Decision Trees: A Case Study in Strategy Sampling and Learning (experimental reproduction package)
<p>This artifact permits to reproduce the experimental results obtained with the techniques and algorithms presented in the article "Digging for Decision Trees: A Case Study in Strategy Sampling and Learning" by Carlos E. Budde, Pedro R. D'Argenio, and Arnd Hartmanns (2024).</p> <p>The contents include all data and software (formal models, software tools, Python & bash scripts) used in the experimental evaluation presented in §7 of the article. Detailed instructions on how to reproduce the results are bundled in the artifact. Execution has been tested in the Virtual Machine available at https://zenodo.org/records/7113223.</p> <p> </p>
Reproduction package for the paper "Completing the X-ray view of the recently discovered supernova remnant G54.41+0.03"
<p>This is a basic reproduction package for the paper "Completing the X-ray view of the recently discovered supernova remnant G54.41+0.03" by V. Domček et al. (2021). It provides raw, intermediate and final data sets, including figures and scripts to allow the reproduction of the work performed in this paper. It also lists software used and data archives containing the public observational data. </p> <p>An open access version of the paper can be found at https://arxiv.org/abs/</p>
Reproduction package for the paper 'TUVO-21acq: A new cataclysmic variable discovered through a UV outburst'
<p>This is a basic reproduction package for the paper 'TUVO-21acq: A new cataclysmic variable discovered through a UV outburst' by Modiano et al. (2022). It aims to provide the most important data products to check and reproduce the main results of the paper, listing all software used and data archives containing the public data used.</p> <p>The paper is available on arxiv: https://arxiv.org/abs/2206.10395</p> <p>The paper has been accepted for publication in Astronomy & Astrophysics (acceptance date: 19/06/2022). DOI: <a href="https://doi.org/10.1051/0004-6361/202243870">10.1051/0004-6361/202243870</a></p>
Reproduction package for the paper "Constraining planetary mass-loss rates by simulating Parker wind profiles with Cloudy"
<p>This is a basic reproduction package for the paper "Constraining planetary mass-loss rates by simulating Parker wind profiles with Cloudy" by Linssen et al. (2022). It provides the data products necessary to reproduce the figures of the paper.</p>
Reproduction Package for SAS 2022 Article 'Case Study on Verification-Witness Validators: Where We Are and Where We Go'
<p>This artifact is a reproduction package for the SAS 2022 article 'Case Study on Verification-Witness Validators: Where We Are and Where We Go'.</p> <p>It contains instructions, data, and scripts for reproducing our results, and the data and tables that we generated in our experiment.</p>
Reproduction Package for "Preventing Refactoring Attacks on Software Plagiarism Detection through Graph-Based Structural Normalization"
<p>This repository stores all data used in the evaluation of the master's thesis "Preventing Refactoring Attacks on Software Plagiarism Detection through Graph-Based Structural Normalization". It ensures the continuous reproducibility of the results of the thesis.</p> <p>Content:</p> <ul> <li>JPlag v5.1.0 including the Java CPG frontend <ul> <li>Code base</li> <li>Runnable JAR</li> </ul> </li> <li>Data sets used for evaluation</li> <li>Evaluation results</li> <li>R script used to process the results</li> <li>Graphics and tables generated from the results</li> </ul> <p>The data sets were generated by Nils Niehues and Moritz Brödel and were originally published here:</p> <ul> <li><a href="../records/10430322">Supplementary Material for "Detecting Automatic Software Plagiarism via Token Sequence Normalization" (zenodo.org)</a></li> <li><a href="../records/10149536">Reproduction package for: Intelligent Match Merging to Prevent Obfuscation Attacks on Software Plagiarism Detectors (zenodo.org)</a></li> </ul> <p>The data sets are based partly on PROGPedia, available here:</p> <ul> <li><a href="../records/7449056">PROGpedia (zenodo.org)</a></li> </ul> <p>Visit <a title="State-of-the-Art Software Plagiarism & Collusion Detection" href="jplag.github.io/JPlag/" target="_blank" rel="noopener">JPlag</a> on GitHub for the current version.<br>See the thesis document for more information.</p> <p>Read about similar publications about Plagiarism Detection <a title="JPlag" href="https://jplag.github.io/MinimalLandingPage/" target="_blank" rel="noopener">here</a>.</p>
Reproduction package for Spectroscopically resolved partial phase curve of the rapid heating and cooling of the highly-eccentric Hot Jupiter HAT-P-2b with WFC3
<p>This is a basic reproduction package for the paper "<span>Spectroscopically resolved partial phase curve of the rapid heating and cooling of the highly-eccentric Hot Jupiter </span><span>HAT-P-2b with WFC3</span>"</p> <p>by [Jacobs, B.; Désert, J. -M.; Lewis, N. et al. (2024)]</p> <p>Abstract:</p> <p><span>The extreme environments of transiting close-in exoplanets in highly-eccentric orbits serve as ideal labo</span><span>ratories for testing exo-atmospheric physics. Spectroscopically resolved phase curves not only allow for the </span><span>characterization of their thermal response to irradiation changes but also unveil phase-dependent atmospheric </span><span>chemistry and dynamics.</span></p> <p><span>We observed a partial phase curve of the highly-eccentric close-in giant planet HAT-P-2b (</span><span>e</span> <span>=</span> <span>0</span><span>.</span><span>51023)</span><br><span>with the Wide Field Camera 3 (WFC3) aboard the</span> <span>Hubble Space Telescope</span><span>.</span> <span>Using these data, we update </span><span>the planet’s orbital parameters and radius, and we retrieve high-frequency pulsations consistent with those re</span><span>ported in Spitzer data. We find that the peak in planetary flux occurs at 6</span><span>.</span><span>7</span> <span>±</span> <span>0</span><span>.</span><span>6 hr after periastron, with a </span><span>heating timescale of 9</span><span>.</span><span>0</span><span>+</span><span>3</span><span>.</span><span>5</span><br><span>−</span><span>2</span><span>.</span><span>1</span> <span>hr, and a cooling timescale of 3</span><span>.</span><span>6</span><span>+</span><span>0</span><span>.</span><span>7</span><span>−</span><span>0</span><span>.</span><span>6</span> <span>hr. We compare the light-curve to a suite of</span><br><span>1-dimensional and 3-dimensional forward models, varying the planet’s chemical composition. The strong con</span><span>trast in flux increase and decrease timescales before and after periapse indicates an opacity term that emerges </span><span>during the planet’s heating phase. We suggest that more emerging H</span><span>−</span> <span>than expected from chemical equilibrium </span><span>models could be the reason for the mismatch between models and the data.</span></p> <p><span>We used a common-mode based method that does not assume a functional form to extract phase-resolved </span><span>spectra. The analysis of these spectra is challenging because of the unknown accuracy of the spectral slope and </span><span>absolute flux levels. The phase-resolved spectra are largely featureless, possibly indicating an inhomogeneous </span><span>dayside.</span> <span>However, we identified an anomalously high flux in the spectroscopic bin that coincides with the </span><span>hydrogen Paschen</span> <span>β</span> <span>line and that is potentially connected to the planet’s orbit.</span> <span>We exclude an instrumental </span><span>origin and we discuss several alternative, astrophysical origins.</span></p>
Reproduction package for "CHEERS: The chemical evolution RGS sample"
<p>This is a basic reproduction package for the paper "Cheers: The chemical evolution sample" by <a href="https://doi.org/10.1051/0004-6361/201629926">de Plaa et al. (2017)</a>. It aims to provide the most important data products to check and reproduce the main results of the paper. </p>
Replication package for 'Medically assisted reproduction and non-normative family forms: legislation and public opinion in Europe'
<p>Replication package for the paper "Medically assisted reproduction and non-normative family forms: legislation and public opinion in Europe", accepted for publication in <em>European Societies</em> (2024). </p> <p>This repository provides the R code to replicate the results. It utilizes data from the European Values Study (available at: https://europeanvaluesstudy.eu/) and an original database on the timing of MAR access legislation for single women and same-sex female couples in Europe. </p> <p> </p> <p> </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.