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917 results for “Theory”
Supplementary CIF files for "Shedding Light on the Enigmatic TcO2 ⋅ xH2O Structure with Density Functional Theory and EXAFS Spectroscopy"
<p>Optimized geometries from the paper "Shedding Light on the Enigmatic TcO2 ⋅ <em>x</em>H2O Structure with Density Functional Theory and EXAFS Spectroscopy" (<a href="https://doi.org/10.1002/chem.202202235">https://doi.org/10.1002/chem.202202235</a>), provided in CIF format.</p> <p>All structures were fully optimized (lattice vectors and atomic coordinates) using AMS/BAND (<a href="https://www.scm.com/">https://www.scm.com/</a>) with the PBE density functional, scalar relativistic effects (ZORA), and numerical atomic orbitals (NAOs) augmented with a triple-zeta polarized (TZP) set of Slater-type basis functions. For the chains, D3 dispersion corrections were also included.</p> <p> </p>
High-Throughput Density Functional Theory Screening of Double Transition Metal MXene Precursors
<p>This dataset contains density functional theory results on a set of double-transition metal MXene precursors</p>
Reliability Assessment of rock slopes by evidence theory
<p>These are the data sets on orientation collected at El Pedregal Mine by:</p> <p>1. Compass in 1997, 2011 and 2016</p> <p>2. ShapeMetrix in 2017 (station #N)</p> <p>Besides, shear strength parameters are included.</p>
Dataset: Mapping intrinsic and scattering attenuation in the southern Aegean crust using S-wave envelope inversion and sensitivity kernels derived from perturbation theory
<p><strong>Data Set S1: </strong>File “ds01.csv” contains the catalogue of relocated events used in this study. The columns in the file represent origin time (in year-month-day’H’hour’M’minute’S’seconds format), event longitude, event latitude, event depth in a sequential manner.</p> <p><strong>Data Set S2: </strong>File “ds02.zip” contains four ASCII data files (ray_prmtrs12.txt, ray_prmtrs24.txt, ray_prmtrs48.txt and ray_prmtrs816.txt). The data files contain scattering coefficient (<em>g<sup>*</sup></em>) and intrinsic coefficient (<em>b</em>) values in 1-2, 2-4 Hz, 4-8 Hz and 8-16 Hz bands respectively. The columns in the text files represent event latitude, event longitude, event depth, station latitude, station longitude, station velocity, envelope duration, <em>g<sup>*</sup></em>, <em>b</em>, early-S window length, percentage error in early-S window, percentage error for full envelope, and event origin time in a sequential manner.</p> <p><strong>Data Set S3: </strong>File “ds03.zip” contains four data files (envnodes15g_3_3_1-2.txt, envnodes15g_3_3_2-4.txt, envnodes15g_3_3_4-8.txt, and envnodes15g_3_3_8-16.txt), one BASH script containing GMT and Octave commands (Qs_envg.gmt), and a lat-long coordinate file (SAegean_poly_coord_extnd.txt) to mask the area outside the seismic network. The data files contain log<sub>10</sub>(<em>Q<sub>sc</sub></em><sup>-1</sup>) values in 1-2, 2-4, 4-8 and 8-16 Hz bands respectively. The columns in the text files represent node latitude, node longitude and log<sub>10</sub>(<em>Q<sub>sc</sub></em><sup>-1</sup>) value of the node sequentially. This GMT script also uses GSHHG coastline data whose path can be added to the script by changing the value of variable GDIR at the beginning of the script. The BASH script file can be run to see the spatial distribution of log<sub>10</sub>(<em>Q<sub>sc</sub></em><sup>-1</sup>) using GMT-6 (Wessel et al., 2019) and Octave version 5.1 and above.</p> <p><strong>Data Set S4: </strong>File “ds04.zip” contains four data files (envnodes15b_3_3_1-2.txt, envnodes15b_3_3_2-4.txt, envnodes15b_3_3_4-8.txt, and envnodes15b_3_3_8-16.txt), one BASH script containing GMT and Octave commands (Qi_env.gmt), and a lat-long coordinate file (SAegean_poly_coord_extnd.txt) to mask the area outside the seismic network. The data files contain log<sub>10</sub>(<em>Q<sub>i</sub></em><sup>-1</sup>) values in 1-2, 2-4, 4-8 and 8-16 Hz bands respectively. The columns in the text files represent node latitude, node longitude and log<sub>10</sub>(<em>Q<sub>i</sub></em><sup>-1</sup>) value of the node sequentially. This GMT script also uses GSHHG coastline data whose path can be added to the script by changing the value of variable GDIR at the beginning of the script. The BASH script file can be run to see the spatial distribution of log<sub>10</sub>(<em>Q<sub>i</sub></em><sup>-1</sup>) using GMT-6 (Wessel et al., 2019) and Octave version 5.1 and above.</p> <p><strong>Data Set S5: </strong>File “ds05.zip” contains four data files (envnodes15a_3_3_1-2.txt, envnodes15a_3_3_2-4.txt, envnodes15a_3_3_4-8.txt, and envnodes15a_3_3_8-16.txt), one BASH script containing GMT and Octave commands (albd_env.gmt), and a lat-long coordinate file (SAegean_poly_coord_extnd.txt) to mask the area outside the seismic network. The data files contain Albedo (<em>B<sub>o</sub></em>) as % values in 1-2, 2-4, 4-8 and 8-16 Hz bands respectively. The columns in the text files represent node latitude, node longitude and <em>B<sub>o</sub></em> value of the node sequentially. This GMT script also uses GSHHG coastline data whose path can be added to the script by changing the value of variable GDIR at the beginning of the script. The BASH script file can be run to see the spatial distribution of <em>B<sub>o</sub></em> using GMT-6 (Wessel et al., 2019) and Octave version 5.1 and above. </p>
A unifying framework for mean-field theories of asymmetric kinetic Ising systems [Dataset]
<p>Datasets for reproducing the results in the article Aguilera, M., Moosavi, S.A. & Shimazaki, H. A unifying framework for mean-field theories of asymmetric kinetic Ising systems. <em>Nature Communications</em> <strong>12, </strong>1197 (2021). https://doi.org/10.1038/s41467-021-20890-5. Results can be reproduced using the code repository of the article https://github.com/MiguelAguilera/kinetic-Plefka-expansions</p> <p>The main dataset contains simulations of an asymmetric, kinetic Sherrington-Kirkpatrick (SK) model around the equivalent of a ferromagnetic phase transition in the equilibrium SK model. External fields <span class="math-tex">\(H_i\)</span> are sampled from independent uniform distributions <span class="math-tex">\(\mathcal{U}(-\beta H_0, \beta H_0)\)</span> with <span class="math-tex">\(H_0=0.5\)</span>, whereas coupling terms <span class="math-tex">\(J_{ij}\)</span> are sampled from independent Gaussian distributions <span class="math-tex">\(\mathcal{N}(\beta \frac{J_0}{N},\beta^2 \frac{J_\sigma^2}{N})\)</span>, with <span class="math-tex">\(J_0=1, J_\sigma = 0.1\)</span> where <span class="math-tex">\(\beta\)</span> is a scaling parameter (i.e., an inverse temperature).</p> <p>To study the non-stationary transient dynamics of the model, we start from <span class="math-tex">\(\mathbf s_0 = \mathbf 1\)</span> (all elements set to 1 at <span class="math-tex">\(t=0\)</span>) and recursively update its state for <span class="math-tex">\(T=128\)</span> steps. We repeated this stochastic simulation for <span class="math-tex">\(10^6\)</span> trials for 21 values of <span class="math-tex">\(\beta\)</span> in the range <span class="math-tex">\([0.7\beta_c, 1.3\beta_c]\)</span>, except for the reconstruction of the phase transition where we used <span class="math-tex">\(R=10^5\)</span> and 201 values of <span class="math-tex">\(\beta\)</span> in the same range.<br> <br> Each file is stored in: 'data-H0-0.5-J0-1.0-Js-0.1-N-512-R-1000000-beta-[beta_ref].npz', where [beta_ref] contains the normalized value of <span class="math-tex">\(\beta/\beta_C\)</span> between 0.7 and 1.3.<br> <br> Furthermore, data in the folders 'forward.zip', 'inverse.zip' and 'reconstruction.zip' contain files to reproduce the results of the paper above. These files show the results of solving the forward Ising problem, the inverse Ising problem, and the reconstruction of the phase transition combining forward and inverse problems.</p>
Database - A Calculus of Tracking: Theory and Practice
<p>A manually curated sample (Top 100 Alexa domains only) of a OpenWPM database obtained from Princeton Web Census (https://webtransparency.cs.princeton.edu/webcensus/). The sample is used to instantiate the model for the paper "<a href="https://petsymposium.org/2021/files/papers/issue2/popets-2021-0027.pdf">A Calculus of Tracking: Theory and Practice</a>" to appear in PETS 2021.</p> <p>Accepted manuscript: https://petsymposium.org/2021/files/papers/issue2/popets-2021-0027.pdf</p> <p>GitHub page: https://github.com/giorgioditizio/calculus_of_tracking</p> <p> </p>
Mapping the global distribution of C4 vegetation using observations and optimality theory
<p>This dataset includes annual C4 vegetation distribution and its uncertainty from 2001 to 2019. We also provide the distribution of C4 natural grasses and C4 crops during the same period, as well as the code and interim dataset to generate the main figures. Please refer to manuscript for more details:</p> <p>Luo, X., Zhou, H., Satriawan, T.W., Tian, J., Zhao, R., Keenan, T.F., Griffith, D. M., Sitch, S. Smith, N.G. & Still, C.J. (2024). Mapping the global distribution of C4 vegetation using observations and optimality theory. <em>Nature Communications.</em> https://doi.org/10.1038/s41467-024-45606-3.</p> <p><strong>Update (Nov 2023): </strong>we have updated the observational constraint from a linear model to a non-linear model - logistic curve, to better depict how C4 photosynthetic advantage translates into C4 grass coverage changes (C4_distribution_NUS_v2.2.nc).</p> <p><strong>Update (August 2023): </strong>we corrected the issue caused by a bias in the remote sensing grassland base map, and released the version 2 of the C4 vmap (C4_distribution_NUS_v2.nc).</p> <p><strong>Update (June 2023): </strong>we noticed there is a critical issue in the version 1 of our C4 map, due to the quality of remote sensing grassland base map used. We are now working on providing a new version (V2) in the next few months (Jun 2023).</p>
On the spectrum of mesons in quenched Sp(2N) gauge theories---Data release
<p>This release contains all data and metadata used to prepare the publication <a href="https://arxiv.org/abs/2312.08465" target="_blank" rel="noopener">On the spectrum of mesons in quenched Sp(2N) gauge theories</a>.</p> <p>Included are:</p> <ul> <li>The file <code>README.md</code>, containing descriptions of the data formats used for other data in this submission.</li> <li>The raw log output for: <ul> <li>The gauge field generation</li> <li>The correlation function computation</li> <li>The Wilson flow computation</li> </ul> </li> </ul> <p>in the file <code>raw_data.zip</code>.<br>These include all numbers used in the publication (aside from fit parameters) in plaintext form. The archive contains a separate <code>README.md</code> documenting the layout of these data.</p> <ul> <li>All metadata used for the fitting and subsequent analysis of these data, in the file <code>metadata.zip</code>, in files described in more detail in the README.</li> <li>All data presented in plots and tables in the paper, in CSV format, in files described in more detail in the README.</li> <li>All input files given during the gauge field generation, in <code>input_files.zip</code>. These are compatible with<a href="https://github.com/sa2c/HiRep" target="_blank" rel="noopener">the Sp(2N) extension of HiRep</a>.</li> </ul>
Online Knowledge Production in Polarized Political Memes: The Case of Critical Race Theory (Dataset)
<p>This is the supplementary dataset to the article entitled "Online Knowledge Production in Polarized Political Memes: The Case of Critical Race Theory." This study, completed by Alyvia Walters, Tawfiq Ammari, Kiran Garimella, and Shagun Jhaver, was accepted for publication in <em>New Media & Society </em>in 2024.</p> <p>Description of files:</p> <p>Memes Codebook.dox - Codebook used for qualitative coding of memes.</p> <p>Memes Project.qdpx - NVivo coding project, exported.</p> <p>all_posts.jsonl, clusters.zip, images.zip, & image_data.csv - the complete collection of data and images used for this project. Please see publication in <em>New Media & Society </em>for more information on the use and collection of these items.</p>
Dataset: Environment effects on X-ray absorption spectra with quantum embedded real-time Time-dependent density functional theory approaches
<p>This dataset collects the outputs from real-time TDDFT simulation of X-ray absorption of halides in model systems, using the frozen density embedding (FDE) and block-orthogonalized Manby-Miller embedding (BOMME), as well as processing tools and scripts used to carry out the calculations.</p>
Amplifying Indigenous Radio: Bibliography of Critical Indigenous Theory
<p>This is a working list of Indigenous critical theoretical approaches drawn on in my research into Indigenous radio.This is a work in progress rather than an exhaustive Bibliography and is open to further updating.</p>
Data for article "Theory of superconductivity mediated by Rashba coupling in incipient ferroelectrics"
<p>Ab initio frozen-phonon splitting of the electronic bands, normalized with the polar displacement. The data is plotted in figure 3 (b) of the article Phys. Rev. B <strong>105</strong>, 224503 (2022). </p>
Lattice studies of the Sp(4) gauge theory with two fundamental and three antisymmetric Dirac fermions—data release
<p>This dataset contains the raw data and metadata used to prepare the publication <a href="https://arxiv.org/abs/2202.05516">Lattice studies of the Sp(4) gauge theory with two fundamental and three antisymmetric Dirac fermions</a>. </p> <p>Included are:</p> <ul> <li>The raw log output from the configuration generation, correlation function calculation, and Dirac eigenvalue computation, as well as metadata describing the ensembles used for the mass spectrum calculation, in `raw_data.zip`. These include all numbers used in the publication (aside from fit parameters) in plaintext form.</li> <li>All numbers included in the above logs, restructured into HDF5 format for convenience, in `data.h5`.</li> <li>The fit parameters used to compute the spectrum, including the thermalisation length, and the plateau start and end points, in `fit_params.zip`.</li> <li>The data underlying tables 2–6 of the publication above, in CSV format.</li> </ul> <p>More details can be found in the file README.md.</p> <p>Version history:</p> <ul> <li>v1.1: Replace out_corr_48x24x24x24b6.5mas-1.01mf-0.71 due to a mistake where the wrong version of the measurement code was used.</li> <li>v1.0: Initial release</li> </ul>
Sp(2N) Yang-Mills theories on the lattice: scale setting and topology—data release
<p>This release contains all data and metadata used to prepare the publications <a href="https://arxiv.org/abs/2205.09254">Topological susceptibility in Yang-Mills theories</a> and <a href="https://arxiv.org/abs/2205.09364">Sp(2N) Yang-Mills theories on the lattice: scale setting and topology</a>.</p> <p>Included are:</p> <ul> <li>The raw log output from the Wilson flow computation, as well as metadata describing the ensembles used, in `raw_data.zip`. These include all numbers used in the publication (aside from fit parameters) in plaintext form. The archive contains a separate `README.md` describing the layout of the data.</li> <li>All numbers included in the above logs, restructured into HDF5 format for convenience, in `datapackage.h5`.</li> <li>The data presented in all tables in both papers, in CSV format, as described in more detail below.</li> </ul> <p>Further details are given in the file README.md.</p>
Disorder-free localization transition in a two dimensional lattice gauge theory
<p>Data files for Figs 2 and 3 from the paper "Disorder-free localization transition in a two dimensional lattice gauge theory".</p>
A phenomenological law for complex granular materials from Mohr-Coulomb theory
<p>The compressed directory contains the data in .csv format used for the PCA analysis for each dataset (1, 2 and 3). </p>
Dynamical mean field theory data for single band Hubbard model
<p>Dynamical mean field theory (DMFT) data for the half filled repulsive single band Hubbard model on four lattices: cubic, diamond, hypercubic in <span class="math-tex">\(d=\infty\)</span>, and hyperdiamond in <span class="math-tex">\(d=\infty\)</span>.</p> <p>It is allowed for long range antiferromagnetic ordering, i.e., the self-consistency condition as seen in Eq. 97 of Georges et al., Rev. Mod. Phys. 68, 13 is used.</p> <p>The simulations are done for different temperatures between <span class="math-tex">\(\beta t = 3\)</span> and <span class="math-tex">\(\beta t = 40\)</span>.</p> <p>The interaction <span class="math-tex">\(U\)</span> is chosen in steps of 0.1 centered around the respective Mott transitions.</p> <p>Available data are</p> <ul> <li>interacting Greens function on Matsubara frequencies</li> <li>self energy on Matsubara frequencies</li> <li>double occupation</li> <li>spin up and spin down occupation</li> </ul> <p>Data is generated using triqs 1.4 and the continous time quantum Monte Carlo application 1.4, compare homepage at https://triqs.ipht.cnrs.fr</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 calculate derivatives of the double occupancy 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> </p>
Symbol Representation of the Three Gluon Form Factor in N=4 Planar Super Yang-Mills Theory
<p>Datasets describing the symbol of the three-gluon form factor in N=4 planar super Yang-Mills theory, generated using the amplitude bootstrap approach. The file "EZ_symb_new_norm" contains the symbol form of this quantity at 1 through 5 loops of precision, while the file "EZ6_symb_new_norm" contains the symbol at 6 loops. The file "EZ_symb_quad_new_norm" contains the symbol at 1 through 6 loops in compressed "quad" form, where the final-entry conditions described in (https://arxiv.org/pdf/2204.11901) are used to dramatically reduce the total number of terms in the symbol. The file "EZ7_symb_quad_new_norm" contains the symbol at 7 loops in the "quad" form. </p> <p>The tag “new_norm” refers to the fact that in the symbols given here, the letters a,b,c are defined by a = sqrt(u/(v*w)), b = sqrt(v/(w*u)), c = sqrt(w/(u*v)), as in arXiv:2405.06107, in order to make all coefficients integers. In contrast, in arXiv:2204.11901, the letters a,b,c were defined by a = u/(v*w), b = v/(w*u), c = w/(u*v).</p> <p>In addition to the funding sources listed, MW was supported by research grant 00025445 from Villum Fonden.</p>
German Student Responses to Probability Theory and Statistics Bachelor Course (WuS24): Evaluated with Rubrics
<p><strong>Description:</strong></p> <p>This dataset contains questions and answers from an introductory computer science bachelor course on statistics and probability theory at Hochschule Bonn-Rhein-Sieg. The dataset includes three questions and a total of 90 answers, each evaluated using binary rubrics (yes/no) associated with specific scores.</p> <p> </p> <p><strong>Dataset Components:</strong></p> <ol> <li><em>questions.csv</em>: Contains the details of the three questions. <ul> <li>Columns: <ul> <li><em>question_id</em>: Unique identifier for each question</li> <li><em>question</em>: The text of the question</li> <li><em>solution</em>: The reference answer for the question</li> <li><em>max_score</em>: The maximum score for this question</li> </ul> </li> </ul> </li> <li><em>rubrics.csv</em>: Contains the grading rubrics for each question. <ul> <li>Columns: <ul> <li><em>question_id</em>: Unique identifier for each question</li> <li><em>rubric_id</em>: Unique identifier for each rubric within a question</li> <li><em>rubric</em>: The rubric phrased as a question</li> <li><em>score</em>: The score associated with fulfilling the rubric</li> </ul> </li> </ul> </li> <li><em>answers.csv</em>: Contains 90 student answers to the questions. <ul> <li>Columns: <ul> <li><em>answer_id</em>: Unique identifier for each answer</li> <li><em>question_id</em>: Unique identifier of the question that is answered</li> <li><em>answer</em>: The text of the student's answer</li> <li><em>score</em>: The score associated with fulfilling the rubric</li> </ul> </li> </ul> </li> <li><em>answer_rubrics.csv</em>: Contains the evaluations of rubrics for each answer.<br> <ul> <li>Columns: <ul> <li><em>answer_id</em>: The identifier of the answer.</li> <li><em>question_id</em>: The identifier of the question.</li> <li><em>rubric_id</em>: The identifier of the rubric for that question.</li> <li><em>label</em>: Indicates if the rubric crierion is fulfilled for the specific answer (true / false).</li> </ul> </li> </ul> </li> </ol> <pre><strong><br>Working with the Dataset:</strong> The easiest way to work with this dataset is using the class `RubricsDataset` defined in the file `dataloader.py`. Example:<br><br></pre> <pre><code>from dataloader import RubricsDataset<br><br>dataset = RubricsDataset.from_directory("data")<br> dataset.get_question(1) # Get a dictionary containing info about the first question, including rubrics dataset.get_answers(1) # Get all the answers for the first question as a list. Each answer is a dictionary with answer, score, rubrics.</code></pre>
From social categorization to implicit citizenship theories: Advancing the socio-cognitive foundations of state–citizen interactions
<p>Data for the following article: Vogel, R., Vogel, D., Liegat, M. C., & Hensel, D. (2024). From social categorization to implicit citizenship theories: Advancing the socio‐cognitive foundations of state–citizen interactions. Public Administration Review, Article puar.13844. Advance online publication. https://doi.org/10.1111/puar.13844</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.