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Processed data and code for manuscript "Non-negligible impact of Stokes drift and wave-driven Eulerian currents on simulated surface particle dispersal in the Mediterranean Sea"
<p>This repository contains the python code and processed data to reproduce analysis and figures from Rühs et al. (2024, Ocean Science): "Non-negligible impact of Stokes drift and wave-driven Eulerian currents on simulated surface particle dispersal in the Mediterranean Sea".</p> <p>To reproduce the whole analysis, including the calculations of the trajectories, the following needs to be downloaded/included into a local working directory:</p> <ul> <li>the content of this repository in respective sub-directories, i.e. code (created and maintained at <a href="https://github.com/sruehs/RuehsEtAl2024_ImpactWavesSurfaceDispersal">https://github.com/sruehs/RuehsEtAl2024_ImpactWavesSurfaceDispersal</a>), data-proc, figs</li> <li>the original surface velocity data, to be downloaded here: <a href="https://zenodo.org/records/10879702">https://zenodo.org/records/10879702</a>, in an additional sub-directory named data-orig</li> </ul> <p>Additionally, the OceanParcels package, available via <a href="https://github.com/OceanParcels/parcels">https://github.com/OceanParcels/parcels</a> or <a href="https://anaconda.org/conda-forge/parcels">https://anaconda.org/conda-forge/parcels</a> needs to be installed in the python working environment. Then, the scripts in the code directory can be executed to re-run the trajectory simulations and analysis. Alternatively, the output in forms of figures and processed data can be accesed directly in the respective sub-directories.</p>
Dataset and Analysis Code for an Experiment on Phosphorus Fertilizers
<p>Link to GitHub repository: <a href="https://github.com/jmalonso55/fosfatos">https://github.com/jmalonso55/fosfatos</a></p> <p>Link to analysis code and results: <a href="https://github.com/jmalonso55/fosfatos/blob/main/An%C3%A1lise_fosfatos_g.md">https://github.com/jmalonso55/fosfatos/blob/main/An%C3%A1lise_fosfatos_g.md</a></p> <p> </p> <h1><strong>About</strong></h1> <p>This repository contains the data and R code for the statistical analysis and results visualization of the paper: Ramos, J. F. K., Alves, B. J. R., Alonso, J. M., Teixeira, P. C., & Benites, V. D. M. (2025). Characterization and agronomic efficiency of natural and recovered phosphates in tropical soil with corrected acidity. <em>Rev. Bras. Ciênc. Solo</em>, <em>49</em>(spe1). Available in: <a href="https://dx.doi.org/10.36783/18069657rbcs20240099">https://dx.doi.org/10.36783/18069657rbcs20240099</a></p> <p>The study is part of the Master’s Dissertation of Ramos, J.F.K. (Ramos, J.F.K. (2023). Caracterização química, mineralógica e eficiência agronômica de diferentes fosfatos [Dissertation]. Universidade Federal Rural do Rio de Janeiro, Seropédica, Brasil). Available in: <a href="https://rima.ufrrj.br/jspui/handle/20.500.14407/18645">https://rima.ufrrj.br/jspui/handle/20.500.14407/18645</a>.</p> <h2>Methodological aspects</h2> <p>This study examined eleven phosphate fertilizer samples, encompassing Brazilian and imported products, as well as residue-recovered and soluble phosphates. The phosphate rocks of igneous origin were exclusively sourced from Brazil, specifically Catalão (Goiás) and Registro (São Paulo). Sedimentary sources included samples from Brazil (Arraias in Tocantins, Bonito in Mato Grosso do Sul, and Pratápolis in Minas Gerais) and from Morocco, Algeria, and Peru (Bayóvar). These phosphates are referred to as Catalão, Registro, Arraias, Bonito, Pratápolis, Morocco, Algeria, and Bayóvar, respectively.</p> <p>The experiment was carried out in a greenhouse, using plastic pots as experimental units, each containing 2 kg of a Ferralsol sample. The soil, initially identified as acidic (pH 4.68), was subjected to a correction process prior to the experiment. The study employed a completely randomized design with 12 treatments and four replicates, resulting in a total of 48 experimental units. The treatments included phosphate rocks (Catalão, Registro, Bonito, Pratápolis, Arraias, Morocco, Algeria, and Bayóvar), two animal-origin phosphates (Bonechar and ERCP), triple superphosphate (TSP) as a reference, and a control treatment without a phosphorus source.</p> <p>Each treatment received a single application of 320 mg P per pot (equivalent to 160 mg P per kg of soil), which was thoroughly incorporated into the soil before planting. The experiment spanned two successive cropping cycles, each lasting 45 days. At the end of each cycle, the aboveground parts of the plants were harvested, dried in a forced-air oven at 65°C until a constant weight was achieved, and their shoot dry mass (SDM) was recorded. The dried samples were finely ground in a Wiley mill and further processed in a ball mill for phosphorus content analysis. To evaluate the agronomic efficiency of the phosphate sources, the study calculated the Relative Agronomic Efficiency Index (RAE) and Phosphorus Efficiency (PE).</p>
Two-bubble simulation and gravitational wave spectrum codes and data
<p><span>Code and data used in the paper with title</span><a href="https://doi.org/10.1103/PhysRevD.104.075039"><span> <em>Vacuum bubble collisions: from microphysics to gravitational waves </em>by Oliver Gould, Satumaaria Sukuvaara, and David Weir</span></a><span> [</span><a href="https://arxiv.org/abs/2107.05657"><span>arXiv:2107.05657</span></a><span>]. </span></p> <p><span>The field simulation and gravitational wave spectrum calculation codes are based on Gravitational radiation from colliding vacuum bubbles by Arthur Kosowsky, Michael S. Turner and Richard Watkins [</span><a href="https://inspirehep.net/literature/324187"><span>Inspire</span></a><span>].</span></p> <p><span>Contains files:</span></p> <ul> <li> <p><span>two_bubbles_code-v1.0.1.zip is a snapshot of a</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_code/"><span> git repository</span></a><span>, corresponding to</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_code/-/tree/v1.0.1?ref_type=tags"><span> commit v1.0.1</span></a><span>. Contains the codes with which the majority of the data was produced.</span><span><br><br></span></p> </li> <li> <p><span>two_bubbles_data-v1.0.1.zip is a snapshot of a</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_data/"><span> git repository</span></a><span>, corresponding to</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_data/-/tree/v1.0.1?ref_type=tags"><span> commit v1.0.1</span></a><span>. It contains the majority of data used in the paper. Note however that the simulation pickle files are examples run on a coarser lattice due to Zenodo file size restrictions. Apart from few exceptions, the data in this file was produced by the codes in two_bubbles_code-v1.0.1.zip.</span><span><br><br></span></p> </li> </ul> <p><span>README.md files, specifying and explaining the contents and usage, are included within. The v1.0.1 of</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_code/-/blob/v1.0.1/README.md?ref_type=tags"><span> </span><span>code README.md</span></a><span> and the</span><a href="https://version.helsinki.fi/two_bubbles/two_bubbles_data/-/blob/v1.0.1/README.md?ref_type=tags"><span> </span><span>data README.md</span></a><span> can be found from the repositories as well.</span></p> <p><span>The update v1.0.1 updates the README and fixes a small error in the calculation of the gravitational wave spectrum. We thank Toby Opferkuch for pointing this out. The error in the code does not affect the results in two_bubbles_data-v1.0.0.zip or the paper as they were produced with a slightly earlier version of the code, before the appearance of this error. The version two_bubbles_data-v1.0.1 updates the README, clarifying some points.</span></p>
Code and Data for "Anticoncentration and state design of random tensor networks"
<p>We investigate quantum random tensor network states where the bond dimensions scale polynomially with the system size, N. Specifically, we examine the delocalization properties of random Matrix Product States (RMPS) in the computational basis by deriving an exact analytical expression for the Inverse Participation Ratio (IPR) of any degree, applicable to both open and closed boundary conditions. For bond dimensions χ∼γN, we determine the leading order of the associated overlaps probability distribution and demonstrate its convergence to the Porter-Thomas distribution, characteristic of Haar-random states, as γ increases. Additionally, we provide numerical evidence for the frame potential, measuring the 2-distance from the Haar ensemble, which confirms the convergence of random MPS to Haar-like behavior for χ≫\sqrt{N}. We extend this analysis to two-dimensional systems using random Projected Entangled Pair States (PEPS), where we similarly observe the convergence of IPRs to their Haar values for χ≫\sqrt{N}. These findings demonstrate that random tensor networks with bond dimensions scaling polynomially in the system size are fully Haar-anticoncentrated and approximate unitary designs, regardless of the spatial dimension.</p>
Coding data to accompany "A quantitative approach to sociotopography in Austronesian languages"
<p>Dataset consists of csv files with sample languages identified by name and Glottocode. Coding for four sociolinguistic variables, as well as an overall "orientation type." Each file corresponds to a different method for coding languages employing multiple spatial orientation strategies, as described in the document coding.pdf.</p> <p><strong>Orientation type</strong></p> <ul> <li>land-sea = axis oriented orthogonal to the coast, based on opposition between landward (inland) and seaward (toward the coast), regardless of whether these terms reflect PAN *daya and *lahud </li> <li>land-sea* = land-sea systems in which the land-sea opposition is indistinguishable from geophysical elevation</li> <li>coastal = axis oriented parallel to the coast, often but not necessarily co-lexified with vertical `up' and `down'</li> <li>elevation = axis that distinguishes global or geophysical elevation with respect to deictic center </li> <li>riverine = axis oriented parallel to the river, typically with secondary axis orientated orthogonal to river</li> <li>cardinal = axis fixed according to conventions which do not vary with local geography (although they may be motivated by environmental factors such as wind and the sun)</li> </ul> <p><strong>Distribution</strong></p> <ul> <li>distributed</li> <li>island</li> <li>village</li> </ul> <p><strong>Economy</strong></p> <ul> <li>diversified</li> <li>agriculture</li> <li>subsistence</li> </ul> <p><strong>Geography</strong></p> <ul> <li>diversified</li> <li>inland</li> <li>coast</li> </ul> <p><strong>Terrain</strong></p> <ul> <li>mountainous</li> <li>non-mountainous</li> </ul>
Code Analysis Tables for Developers Interviews on Dependencies Paper
<p>Code Analysis Tables for the ACM CCS 2020 paper "A qualitative study of dependency management and its security implications"</p>
Microscope-Cockpit find nuclei code and microscope simulation configuration
<p>This file contains instructions for setting up a simulated microscope<br> environment using Microscope-Cockpit and Python-Microscope. This<br> environment includes a large tiled image of which segments are<br> returned to simulate stage movement and different colour channels<br> returned to simulate changing an emission filter. This simulated<br> microscope is then used to test the findNuclei script showing the ease<br> of extending Cockpit functionality with Python libraries,<br> Python-openCV is used in this case.<br> </p>
Modified WRF/Chem source code, output data, and post-processing scripts for the GMD manuscript "Evaluation of WRF/Chem model (v3.9.1.1) real-time air quality forecasts over the Eastern Mediterranean"
<p>Here you will find the modified WRF/Chem code used in the simulations, the scripts used for post-processing and the model output data used in the manuscript. </p> <p>Two modifications have been made in module_aerosols_soa_vbs.F:</p> <ol> <li>ch_dust is set to1.0D-9*0.36</li> <li>The model is set not to initialize during restarts</li> </ol> <p>The model data directory includes:</p> <ol> <li>Two csv files (Winter and Summer) with the hourly concentrations of atmospheric pollutants at the locations of the ground stations. These data were used to produce Figures 4-8 in the manuscript as well as all the metrics.</li> <li>Two netcdf files (Winter and Summer) with the average ground concentrations of atmospheric pollutants over Cyprus. These data were use to produce Figure 3 in the manuscript. </li> </ol>
Phase coding of spatial representations in the human entorhinal cortex
<p>Supporting Preprocessed Electrophysiology Data for the article titled "Phase coding of spatial representations in the human entorhinal cortex".</p> <p>Data were preprocessed and analyzed using Matlab.</p> <p>Data, after decompression, are organized hierarchically in folders and subfolders (two levels).</p> <p>Main folder names are composed as subjectID_date_EC_DATA_taskNo</p> <p>Sub-folders named as: CHn_single-unit ID </p> <p>[subjectID, date, task num] + [Electrode channel, and single-unit ID] </p> <p>subjectID: (subject1, subject2)</p> <p>date: mmm-dd</p> <p>task: (1,2,3,4) Virtual environments (1: backyard, 2: Louvre, 3: Luxor, 4: desert)</p> <p>electrode Channel: CH1,CH2, CH3, CH4, CH5</p> <p>single-unit ID: 0, 1, 2, 3, 4, 5, 6</p> <p>For each channel and single-unit, the following 9 datasets were computed and saved. For instance, for the first electrode and first single-unit class (CH=1, cell ID= 0):</p> <p>CH1_Clu0.mat -- Summary of firing features of this single-unit including firing rate, and grid score of the cell. (In Matlab mat format)<br> CH1_Clu0_MeanPhaseMap.csv -- Mean spike phase map relative to gamma-band LFP<br> CH1_Clu0_Phase.csv -- Spike phase CH1_Clu0_spikeData.csv<br> CH1_Clu0_spkT.csv -- Spike times in increental order<br> CH1_Clu0_VarPhaseMap.csv -- Map of the variance of spike times in increental order<br> CH1_Clu0_xval.mat -- Summary of firing features of 50% of single-unit spikes (every other spike) for cross-validation purposes. (In Matlab mat format)<br> CH1_Clu0_xyPos.csv -- X,Y coordinates of the avatar's position in 1 ms resolution. In other words, the path taken by the avatar sampled at 1 kHz.<br> CH1_Clu0_XYspkT.csv -- X,Y coordinates of the avatar at moments of spikes. In other words, the location in space where a spike was fired by the putative neuron.</p> <p> </p>
Code for "New land-use-change emissions indicate a declining CO2 airborne fraction"
<p>Data and programming scripts for reproducing the results from the Nature publication titled:</p> <p>"New land-use-change emissions indicate a declining CO2 airborne fraction".</p> <p>Authors: Margreet J. E. van Marle*, Dave van Wees*, Richard A. Houghton, Robert D. Field, Jan Verbesselt, and Guido R. van der Werf<br> * These authors contributed equally.</p> <p>DOI: https://doi.org/10.1038/s41586-021-04376-4</p> <p> </p> <p>This dataset includes the following (All files are preceded by "Marle_et_al_Nature_AirborneFraction_"):</p> <p>- "Datasheet.xlsx": Excel dataset containing all annual and monthly emissions and CO2 time series used for the analysis, and the resulting airborne fraction time series.</p> <p>- "Script.py":<br> BEFORE RUNNING THE SCRIPT: change the 'wdir' variable to the directory containing the provided script and files.<br> NOTE: This script requires the Python module: 'pymannkendall'<br> Python script used for reproducing the results and figures from the paper. The provided Datasheet.xlsx file and the .zip and .npz files are required for this program. In case all these files are found by the script, it should run within several seconds. Successful execution of the script will save Figures 1-4 from the main text and print the data from Table 1. In case script execution takes longer, please check if the .xlsx, .zip and .npz files are correctly present in the assigned 'wdir' directory. Otherwise the script will start recalculating these files, which might take a while (see notes below).</p> <p>- "MC10000_MK_ts_TRENDabs.zip": .zip file containing all results from the Monte-Carlo simulation for trend estimation for Figure 3 (calculated using Python function 'calc_AF_MonteCarlo()'). This .zip file contains multiple .npz files for different emission scenarios and data treatments. This .zip file is managed by the Python script function 'calc_AF_MonteCarlo_filemanager()', there is no need to unzip the file manually. In case the .zip file is not found by the Python script (e.g. because the .zip file was unpacked manually and deleted), the program will start recalculating and save a new .zip file. This can take several minutes dependent on the computer used. Recalculated results could differ very slightly due to the random factor in the Monte-Carlo approach, even though the 10,000 iterations bring this variation to a minimum.</p> <p>- "MC1000_MK_run50x50_TRENDabs.npz": .npz file containing the Monte-Carlo results used for producing Figure 4 (calculated using Python function 'calc_AF_MonteCarlo_ARR()'). In case the .npz file is not found by the Python script (e.g. because it was deleted or not downloaded), the program will start recalculating and save a new file. This can take around 30 hours(!) dependent on the computer used. Recalculated results could differ slightly due to the random factor in the Monte-Carlo approach.</p> <p>- "tol_colors.py": Additional Python module used in script.py, required for producing the colors used in the Main text figures. Source: https://personal.sron.nl/~pault/</p> <p>- Figure files: Figures 1-4 from the Main text saved as .pdf files. Figure 3 is saved as three independent panels. The Figures are also reproduced by script.py if executed successfully.</p> <p> </p>
Data and code for the manuscript "From white to green: Snow cover loss and increased vegetation productivity in the European Alps"
<p>Data and code used for the manuscript "From white to green: Snow cover loss and increased vegetation productivity in the European Alps" by Rumpf et al., submitted December 2021 to Science</p> <p>See file ReadMe.txt for a description of the content and the original publication for further explanations.</p> <p>You are free to use these data and code for scientific purposes but are obliged to cite the above-mentioned publication.<br> For further questions, contact sabine.rumpf@unibas.ch</p>
Source code and simulation results for nanoantennas supporting an enhanced Purcell factor due to interfering resonances
<p><strong>Summary</strong></p> <p>Data and source code relate to the article "<a href="https://doi.org/10.1103/PhysRevResearch.4.023189">Enhanced Purcell factor for nanoantennas supporting interfering resonances</a>" [1], whose subject are the effects of coupled resonances and quasibound states in the continuum on the Purcell factor in dielectric resonant nanoantennas. The provided scripts reproduce the analysis of interfering resonances in a nanodisk coupled to an enclosed emitter and can be easily adapted for further investigations. </p> <p><strong>Structure</strong></p> <p>The cases refer to different aspect ratios of the nanodisk with (a and b) and without (c and d) substrate. The scans reproduce the data used to find the aspect ratios (a and c) supporting the maximal Purcell enhancement. </p> <p><a href="https://doi.org/10.1016/j.softx.2021.100763">RPExpand</a> [2] is used for Riesz projection expansions, which quantify the interactions of the resonances.</p> <p>The directories <strong>resonance</strong> and <strong>scattering </strong>contain input files for the commercial software JCMsuite, which rigorously solves Maxwell's equations with the finite-element method (FEM). In order to switch to a custom setup, you must adapt these input files. If you want to recalculate all results, make sure that you remove the directories containing resultbags. These are stored in the directory <strong>results</strong>, e.g., results/case_a/resultbags.</p> <p><strong>Requirements</strong></p> <ul> <li>JCMsuite (tested with version: 4.6.3)</li> <li>Matlab (tested with version: R2019b)</li> </ul> <p>In order to run the scripts you must replace the corresponding place holders in the files by a path to your installation of JCMsuite. Free trial licenses are available, please refer to the homepage of <a href="https://jcmwave.com/">JCMwave</a>. </p> <p>[1] Rémi Colom, Felix Binkowski, Fridtjof Betz, Yuri Kivshar, Sven Burger, Enhanced Purcell factor for nanoantennas supporting interfering resonances, Physical Review Research <strong>4</strong>, 023189 (2022), https://doi.org/10.1103/PhysRevResearch.4.023189</p> <p>[2] Fridtjof Betz, Felix Binkowski, Sven Burger, RPExpand: Software for Riesz projection expansion of resonance phenomena, SoftwareX <strong>15</strong>, 100763 (2021), https://doi.org/10.1016/j.softx.2021.100763</p>
On the Effectiveness of Transfer Learning for Code Search - Replication Package
<p>This repository represents the replication package for the paper <em>On the Effectiveness of Transfer Learning for Code Search</em>.</p> <p>The paper is published in the journal <em>IEEE Transactions on Software Engineering (TSE)</em>.</p> <p>In this replication package, we provide all the data and scripts we used in our study.</p>
Datasets and R codes for Prokkola et al. 2022 adipose tissue samples
<p>Data and R codes for the analyses reported in Prokkola et al. (pre-print, 2022) <em>Adipose tissue mitochondrial respiration in Atlantic salmon: implications for sex-dependent life-history variation.</em></p> <p>Overview of files can be found in the README file.</p> <p>The file "Cell size data.zip" contains TIFF-images of adipose tissue cryosections, a README file, the result files for each image file and an R code for parsing the results files.</p> <p>To skip the data parsing steps and get the final data, download the AdiposeTissue_data_all.txt file (tab-separated).</p>
Dataset and codes for 'Climatic control on seasonal variations of glacier surface velocity'
<p><strong>This repository contains the codes and processed data used to retrieve 10-day changes in glacier surface velocity over the Western Pamir.</strong></p> <p>The supp_CODES.zip contains all details and codes to use COSI-CORR (<a href="http://www.tectonics.caltech.edu/slip_history/spot_coseis/">http://www.tectonics.caltech.edu/slip_history/spot_coseis/</a>) to process a large batch of satellite images. The images can be downloaded directly via <a href="https://earthexplorer.usgs.gov/">https://earthexplorer.usgs.gov/</a> or <a href="https://scihub.copernicus.eu/">https://scihub.copernicus.eu</a>. Please read the Methods and Data section of the associated manuscript for details.</p> <p> </p> <p>The Matrix_velocities.zip contains, for each of the 48 investigated glaciers, the DEM, X, Y (NANNI_2022_supp_glacier_centreline_DEM_XY_1px_30m_1.txt) as well as a matrix of n*m with m the distance along flow and n the number of time step over which the velocity is calculated (NANNI_2022_supp_glacier_centreline_vel_matrix_1px_30m_1.txt), ans the associated figure that show the multi year velocity changes together with the one year average and the along centreline profiles. An example is shown in the two figures for glacier 48 in the main repository.</p> <p> </p> <p>The NANNI_2022_supp_glacier_characteristics file contains the glacier characteristics (48*8), as shown in the associated figures.</p> <p> </p> <p>The NANNI_2022_supp_pickedpoints_migration_AUTUMN/SPRING contains the automatically picked points for the onset of the acceleration in Spring and Autmun for each glacier. The headers contains the information, and the files contains is shown in the associated figure.</p> <p>the temperature profiles used to calculate the Iso 0C are in NANNI_2022_supp_temp_perday_fedchenko_2400m</p> <p>The position of each 48 glacier is shown in the associated figure.</p> <p> </p> <p>You can also find the processed velocity fields (velocity magnitude) under the different path an row: p151r33.zip and p152r33.zip for Landsat8, T42SYJ.zip and T43SBD.zip for Sentinel 2. In these folder you will a find a .tif file names similar to:</p> <p><em>Working_cosicorr_windows_FCorr_16days_p152r33_159_175_AB_1101110_Filtered_correlations_p152r33_filtered_abs.tif</em></p> <p>The name of the files gives information about the time span used (16days), the path and raw (p152r33), the data of the slave in DOY from 2013 (159) and of the master (175).</p> <p>The Statistics.zip file contains for each path and row the associated DEM, glacier mask (RGI), median magnitude (ABS), median NS displacement (NS), median EW displacemnt (EW), with the associated median absolute deviation (MAD). The files containing 'bflt' corresponds to the values computed before the filtering procedure, and the one without, after the filtering procedure. </p> <p>The .tif files are not georeferenced, but are all projected on the same grid with a 30m square pixel size on a UTM 33 42N projection.</p> <p> </p> <p> </p> <p>Please contact me for any question.</p> <p> </p> <div class="notranslate"> </div>
Data for the paper 'Reducing networks of ethnographic codes co-occurrence in anthropology'
<p>Pseudonymized data supporting the paper "Reducing networks of ethnographic codes co-occurrence in anthropology", published in "Advances in Quantitative Ethnography. Fourth International Conference on Quantitative Ethnography (ICQE 2022), Copenhagen, Denmark, October 15–19, 2022, Proceedings", and edited by Amanda Barany and Crina Damsa. The paper is part of the POPREBEL project. The data were gathered in the spring and summer of 2021, as a part of a larger research project on populism in Central and Eastern Europe, to be completed by the end of 2022. They consist of 17 semi-structured interviews with Polish-speaking Internet users, who used social media to seek and share information about health against the backdrop of the COVID-19 pandemic. Research participants were asked about their opinion on the current state of affairs in their respective countries, and their political choices over the years and at present.</p> <p><a href="https://edgeryders.eu/t/long-term-ssna-data-storage-documentation-manual/12786">Data export and documentation process</a> (contains links to the code used to export the data).</p>
Data and code used in manuscript: Basal freeze-on generates complex ice-sheet stratigraphy
<p>Mapped plumes location obtained from ice-sheet radio echo sounding data of North Greenland (https://data.cresis.ku.edu/data/rds/ for 2010-2014_Greenland files) and map of calculated freeze-on index are found in 'FreezeOnIndex_MappedPlume_Data.nc'. Model code of the three models used to obtain the findings shown in the manuscript 'Basal freeze-on generates complex ice-sheet stratigraphy'. As well as code to calculate the freeze-on index.</p>
Data and code for figures: Intrinsic Kerr amplification for microwave electromechanics
<p>This directory contains the datasets and code for generating the figures in the research article "Intrinsic Kerr amplification for microwave electromechanics", <em>Appl. Phys. Lett.</em> 124, 243503 (2024).</p>
Pyenson, Huisken, Gupta, and Rehan (2024): Code & Data
<p>Code & data to accompany publication of Pyenson, Huisken, Gupta, and Rehan (2024).</p>
Source Code Accompanying the Paper "More on network approaches in Historical Chinese Phonology (音韻學)"
<p>First version of the source code and data accompanying the paper "More on Network Approaches in Historical Chinese Phonology".</p> <p>This paper is available here:</p> <ul> <li>List, Johann-Mattis (2018): <strong>More on network approaches in Historical Chinese Phonology (音韻學)</strong>. Paper prepared for the <em>LFK Society Young Scholars Symposium</em>. Taibei: Li Fang-Kuei Society ofr Chinese Linguistics. URL: <a href="https://hal.archives-ouvertes.fr/hal-01706927">https://hal.archives-ouvertes.fr/hal-01706927</a>.</li> </ul> <pre><code>@InProceedings{List2018a, author = {List, Johann-Mattis}, title = {{More on Network Approaches in Historical Chinese Phonology (音韻學)}}, booktitle = {{LFK Society Young Scholars Symposium}}, year = {2018}, publisher = {Li Fang-Kuei Society for Chinese Linguistics}, pdf = {https://hal.archives-ouvertes.fr/hal-01706927/file/main.pdf}, url = {https://hal.archives-ouvertes.fr/hal-01706927}, address = {Taipei}, hal_id = {hal-01706927}, } </code></pre> <p>See the README.md for mor information.</p> <ul> <li> </li> </ul>
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.