2026-05-20T20:05:26Z https://rodare.hzdr.de/oai2d

oai:rodare.hzdr.de:1939 2022-11-10T08:13:54Z openaire_data user-casus user-rodare

Davoodi Monfared, Mansoor Ghaffari, Mohsen 2022-11-09 The codes and data for the paper "Learning-based systems for assessing hazard places of contagious diseases and diagnosing patient possibility" https://rodare.hzdr.de/record/1939 10.14278/rodare.1939 oai:rodare.hzdr.de:1939 eng doi:10.1016/j.eswa.2022.119043 url:https://www.hzdr.de/publications/Publ-35381 url:https://www.hzdr.de/publications/Publ-35419 doi:10.14278/rodare.1938 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Machine learning Trajectory tracking Patient prediction Hidden Markov model Covid-19 Trajectory clustering Data publication: Learning-based systems for assessing hazard places of contagious diseases and diagnosing patient possibility info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:1493 2022-03-25T09:53:56Z openaire_data openaire_data user-casus user-rodare

Senapati, Abhishek Rana, Sourav Das, Tamalendu Chattopadhyay, Joydev 2022-03-23 This contains a set of MATLAB scripts and data that were used to generate the figures and results in the manuscripts. https://rodare.hzdr.de/record/1493 10.14278/rodare.1493 oai:rodare.hzdr.de:1493 url:https://www.hzdr.de/publications/Publ-33828 doi:10.14278/rodare.1492 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode COVID-19 Mathematical modelling Basic reproduction number Intervention Outbreak India Data publication: Impact of intervention on the spread of COVID-19 in India: A model based study info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:3725 2025-06-27T09:18:30Z software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software software user-casus user-hzdr user-rodare

Hernandez Acosta, Uwe Thekke Veettil, Sachin Krishnan Wicaksono, Damar Canggih Kissinger, Jannik Hecht, Michael 2025-04-30 minterpy is an open-source Python package for a multivariate generalization of the classical Newton and Lagrange interpolation schemes as well as related tasks. It is based on an optimized re-implementation of the multivariate interpolation prototype algorithm (MIP) by Hecht et al.1 and thereby provides software solutions that lift the curse of dimensionality from interpolation tasks. While interpolation occurs as the bottleneck of most computational challenges, minterpy aims to free empirical sciences from their computational limitations. https://rodare.hzdr.de/record/3725 10.14278/rodare.3725 oai:rodare.hzdr.de:3725 eng url:https://www.hzdr.de/publications/Publ-36106 doi:10.14278/rodare.2058 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT multivariate interpolation multivariate polynomials numerical modelling Minterpy - multivariate polynomial interpolation info:eu-repo/semantics/other software

oai:rodare.hzdr.de:2531 2025-05-06T09:07:12Z software user-hzdr user-rodare user-casus

Wicaksono, Damar Canggih Hecht, Michael 2023-10-30 UQTestFuns is an open-source Python3 library of test functions commonly used within the applied uncertainty quantification (UQ) community. Specifically, the package provides: an implementation with minimal dependencies (i.e., NumPy and SciPy) and a common interface of many test functions a single entry point collecting test functions and their probabilistic input specifications in a single Python package an opportunity for an open-source contribution, supporting the implementation of new test functions or posting reference results. In short, UQTestFuns is an homage to the Virtual Library of Simulation Experiments (VLSE). v0.4.1 includes one additional test function used in the context of metamodeling. The package documentation has been updated following the review process during the submission to the Journal of Open Source Software (JOSS). This release is part of the acceptance of the package to JOSS. This archive is part of the archival process to ROBIS. https://rodare.hzdr.de/record/2531 10.14278/rodare.2531 oai:rodare.hzdr.de:2531 eng doi:10.21105/joss.05671 url:https://www.hzdr.de/publications/Publ-37736 url:https://www.hzdr.de/publications/Publ-37735 doi:10.14278/rodare.2530 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT python uncertainty-quantification benchmark sensitivity-analysis metamodeling reliability-analysis UQTestFuns: A Python3 Library of Uncertainty Quantification (UQ) Test Functions info:eu-repo/semantics/other software

oai:rodare.hzdr.de:1424 2022-03-25T09:53:24Z openaire_data user-casus user-rodare

Ghosh, Subrata Senapati, Abhishek Mishra, Arindam Chattopadhyay, Joydev Dana, Syamal K. Hens, Chittaranjan Ghosh, Dibakar 2022-01-28 Python scripts and relevant data required for reproducing the figures in the article https://rodare.hzdr.de/record/1424 10.14278/rodare.1424 oai:rodare.hzdr.de:1424 url:https://www.hzdr.de/publications/Publ-34171 url:https://www.hzdr.de/publications/Publ-34172 doi:10.14278/rodare.1423 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode COVID-19 Mathematical modelling Prediction Machine Learning Data publication: Reservoir computing on epidemic spreading: A case study on COVID-19 cases info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:613 2020-12-03T10:54:28Z openaire_data user-casus user-ecfunded user-hzdr user-rodare

Calabrese, Justin M. Fleming, Christen Noonan, Michael J. Dong, Xianghui 2020-11-27 Estimating animal home ranges is a primary purpose of collecting tracking data. All conventional home range estimators in widespread usage, including minimum convex polygons and kernel density estimators, assume independently sampled data. In stark contrast, modern GPS animal tracking datasets are almost always strongly autocorrelated. This incongruence between estimator assumptions and empirical reality leads to systematically underestimated home ranges. Autocorrelated kernel density estimation (AKDE) resolves this conflict by modeling the observed autocorrelation structure of tracking data during home range estimation, and has been shown to perform accurately across a broad range of tracking datasets. However, compared to conventional estimators, AKDE requires additional modeling steps and has heretofore only been accessible via the command-line ctmm R package. Here, we introduce ctmmweb, which provides a point-and-click graphical interface to ctmm, and streamlines AKDE, its prerequisite autocorrelation modeling steps, and a number of additional movement analyses. We demonstrate ctmmweb’s capabilities, including AKDE home range estimation and subsequent home range overlap analysis, on a dataset of four jaguars from the Brazilian Pantanal. We intend ctmmweb to open AKDE and related autocorrelation-explicit analyses to a wider audience of wildlife and conservation professionals. https://rodare.hzdr.de/record/613 10.14278/rodare.613 oai:rodare.hzdr.de:613 eng info:eu-repo/grantAgreement/NSF//1458748/ doi:10.1101/2020.05.11.087932 url:https://www.hzdr.de/publications/Publ-31776 url:https://www.hzdr.de/publications/Publ-31774 doi:10.14278/rodare.612 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/ecfunded url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/closedAccess AKDE animal movement autocorrelation ctmm telemetry tracking data Research Data for: ctmmweb: A graphical user interface for autocorrelation-informed home range estimation info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:3353 2025-04-30T11:57:02Z software user-hzdr user-rodare user-casus

Hernandez Acosta, Uwe Wicaksono, Damar Canggih Thekke Veettil, Sachin Krishnan Michelfeit, Jannik Hecht, Michael 2024-12-20 minterpy is an open-source Python package for a multivariate generalization of the classical Newton and Lagrange interpolation schemes as well as related tasks. It is based on an optimized re-implementation of the multivariate interpolation prototype algorithm (MIP) by Hecht et al.1 and thereby provides software solutions that lift the curse of dimensionality from interpolation tasks. While interpolation occurs as the bottleneck of most computational challenges, minterpy aims to free empirical sciences from their computational limitations. https://rodare.hzdr.de/record/3353 10.14278/rodare.3353 oai:rodare.hzdr.de:3353 eng url:https://www.hzdr.de/publications/Publ-36106 doi:10.14278/rodare.2058 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT multivariate interpolation multivariate polynomials numerical modelling Minterpy - multivariate polynomial interpolation info:eu-repo/semantics/other software

oai:rodare.hzdr.de:1999 2023-02-28T13:31:04Z openaire_data user-matter user-casus user-rodare

Kraisler, Eli Cangi, Attila Callow, Timothy James 2022-12-14 Data for our paper "Improved calculations of mean ionization states with an average-atom model" (arXiv) For details about the data, please see the README file after unpacking the folder, and this GitHub repository. https://rodare.hzdr.de/record/1999 10.14278/rodare.1999 oai:rodare.hzdr.de:1999 url:https://www.hzdr.de/publications/Publ-35832 url:https://www.hzdr.de/publications/Publ-34364 doi:10.1103/PhysRevResearch.5.013049 doi:10.14278/rodare.1998 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/matter url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Data publication: Improved calculations of mean ionization states with an average-atom model info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:3292 2025-03-04T08:54:39Z openaire_data user-casus user-fwg user-rodare

Chakraborty, Rupsa Rachdi, Imane Thiele, Samuel Thomas Booysen, René Kirsch, Moritz Lorenz, Sandra Gloaguen, Richard Sebari, Imane 2024-06-09 The new generation of satellite hyperspectral (HS) sensors provides remarkable potential for regional-scale mineralogical mapping. However, as with any satellite sensor, mapping results are dependent on a typically complex correction procedure needed to remove atmospheric, topographic and geometric distortions before accurate reflectance spectra can be retrieved. These are typically applied by the satellite operators but use different approaches that can yield different results. In this study, we conduct a comparative analysis of PRISMA, EnMAP, and EMIT hyperspectral satellite data, alongside airborne data acquired by the HyMap sensor, to investigate the consistency between these datasets and their suitability for geological mapping. Two sites in Namibia were selected for this comparison, the Marinkas-Quellen and Epembe carbonatite complexes, based on their geological significance, relatively good exposure, arid climate and data availability. We conducted qualitative and three different quantitative comparisons of the hyperspectral data from these sites. These included correlative comparisons of (1) the reflectance values across the visible-near infrared (VNIR) to shortwave infrared (SWIR) spectral ranges, (2) established spectral indices sensitive to minerals we expect in each of the scenes, and (3) spectral abundances estimated using linear unmixing. The results highlighted a notable shift in inter-sensor consistency between the VNIR and SWIR spectral ranges, with the VNIR range being more similar between the compared sensors than the SWIR. Our qualitative comparisons suggest that the SWIR spectra from the EnMAP and EMIT sensors are the most interpretable (show the most distinct absorption features) but that latent features (i.e., endmember abundances) from the HyMap and PRISMA sensors are consistent with geological variations. We conclude that our results reinforce the need for accurate radiometric and topographic corrections, especially for the SWIR range most commonly used for geological mapping. https://rodare.hzdr.de/record/3292 10.14278/rodare.3292 oai:rodare.hzdr.de:3292 doi:10.3390/rs16122089 url:https://www.hzdr.de/publications/Publ-40090 url:https://www.hzdr.de/publications/Publ-39575 doi:10.14278/rodare.3291 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/fwg url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/restrictedAccess Hyperspectral Remote Sensing EnMAP EMIT PRISMA HyMap Carbonatite Comparitive Analysis Data: A Spectral and Spatial Comparison of Satellite-Based Hyperspectral Data for Geological Mapping info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:886 2021-11-22T12:19:57Z openaire_data user-matter user-casus user-rodare

Vorberger, Jan Militzer, Burkhard Massacrier, Gerard Soubiran, Francois Böhme, Maximilian 2021-11-19 Average atom (AA) models allow one to efficiently compute electronic and optical properties of materials over a wide range of conditions and are often employed to interpret experimental data. However, at high pressure, predictions from AA models have been shown to disagree with results from ab initio computer simulations. We represent a new innovative AA model, AvIon, that computes the electronic eigenstates with novel boundary conditions within the ion sphere. Bound and free states are derived consistently. We drop the common AA assumption that the free-particle spectrum starts at the potential threshold, which we found to be incompatible with ab initio calculations. We perform ab initio simulations of crystalline and liquid carbon and aluminum over a wide range of densities and show that the computed band structure is in very good agreement with predictions from AvIon. This data-set contains all the data that has been contributed from my part to the referenced publication. https://rodare.hzdr.de/record/886 10.14278/rodare.886 oai:rodare.hzdr.de:886 eng url:https://www.hzdr.de/publications/Publ-32435 url:https://www.hzdr.de/publications/Publ-31149 doi:10.14278/rodare.885 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/matter url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode DFT/DFT-MD IPD Publication Data info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:2059 2025-04-30T11:57:02Z software user-hzdr user-rodare user-casus

Hernandez Acosta, Uwe Thekke Veettil, Sachin Krishnan Wicaksono, Damar Canggih Michelfeit, Jannik Hecht, Michael 2021-12-06 minterpy is an open-source Python package for a multivariate generalization of the classical Newton and Lagrange interpolation schemes as well as related tasks. It is based on an optimized re-implementation of the multivariate interpolation prototype algorithm (MIP) by Hecht et al.1 and thereby provides software solutions that lift the curse of dimensionality from interpolation tasks. While interpolation occurs as the bottleneck of most computational challenges, minterpy aims to free empirical sciences from their computational limitations. https://rodare.hzdr.de/record/2059 10.14278/rodare.2059 oai:rodare.hzdr.de:2059 eng url:https://www.hzdr.de/publications/Publ-36106 doi:10.14278/rodare.2058 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT multivariate interpolation multivariate polynomials numerical modelling Minterpy - multivariate polynomial interpolation info:eu-repo/semantics/other software

oai:rodare.hzdr.de:2061 2025-04-30T11:57:02Z software software user-hzdr user-rodare user-casus

Schreiber, Janina Hernandez Acosta, Uwe Thekke Veettil, Sachin Krishnan Wicaksono, Damar Canggih Michelfeit, Jannik Hecht, Michael 2021-12-06 minterpy is an open-source Python package for a multivariate generalization of the classical Newton and Lagrange interpolation schemes as well as related tasks. It is based on an optimized re-implementation of the multivariate interpolation prototype algorithm (MIP) by Hecht et al.1 and thereby provides software solutions that lift the curse of dimensionality from interpolation tasks. While interpolation occurs as the bottleneck of most computational challenges, minterpy aims to free empirical sciences from their computational limitations. https://rodare.hzdr.de/record/2061 10.14278/rodare.2061 oai:rodare.hzdr.de:2061 eng url:https://www.hzdr.de/publications/Publ-36106 doi:10.14278/rodare.2058 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT multivariate interpolation multivariate polynomials numerical modelling Minterpy - multivariate polynomial interpolation info:eu-repo/semantics/other software

oai:rodare.hzdr.de:2062 2025-04-30T11:57:02Z software user-hzdr user-rodare user-casus

Hernandez Acosta, Uwe Thekke Veettil, Sachin Krishnan Wicaksono, Damar Canggih Michelfeit, Jannik Hecht, Michael 2023-01-06 minterpy is an open-source Python package for a multivariate generalization of the classical Newton and Lagrange interpolation schemes as well as related tasks. It is based on an optimized re-implementation of the multivariate interpolation prototype algorithm (MIP) by Hecht et al.1 and thereby provides software solutions that lift the curse of dimensionality from interpolation tasks. While interpolation occurs as the bottleneck of most computational challenges, minterpy aims to free empirical sciences from their computational limitations. https://rodare.hzdr.de/record/2062 10.14278/rodare.2062 oai:rodare.hzdr.de:2062 eng url:https://www.hzdr.de/publications/Publ-36106 doi:10.14278/rodare.2058 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT multivariate interpolation multivariate polynomials numerical modelling Minterpy - multivariate polynomial interpolation info:eu-repo/semantics/other software

oai:rodare.hzdr.de:1426 2022-03-25T09:51:44Z openaire_data user-casus user-rodare

Ghosh,Subrata Senapati, Abhishek Chattopadhyay, Joydev Hens, Chittaranjan Ghosh, Dibakar 2022-01-28 This contains all the python script and related data required for reproducing the results presented in the article https://rodare.hzdr.de/record/1426 10.14278/rodare.1426 oai:rodare.hzdr.de:1426 url:https://www.hzdr.de/publications/Publ-34173 url:https://www.hzdr.de/publications/Publ-34174 doi:10.14278/rodare.1425 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Infectious disease modelling Test-kit Complex network Intervention strategy Data publication: Optimal test-kit-based intervention strategy of epidemic spreading in heterogeneous complex networks info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:2057 2023-01-23T14:42:52Z openaire_data user-rodare user-casus

Dornheim, Tobias Moldabekov, Zhandos Vorberger, Jan Böhme, Maximilian Dornheim, Tobias Moldabekov, Zhandos Vorberger, Jan 2023-01-04 This is the archived datasets used for the publication in the article: Ab initio path integral Monte Carlo simulations of hydrogen snapshots at warm dense matter conditions. The dataset also contains the data-analysis python scripts. https://rodare.hzdr.de/record/2057 10.14278/rodare.2057 oai:rodare.hzdr.de:2057 doi:10.48550/arXiv.2207.14716 url:https://www.hzdr.de/publications/Publ-36059 url:https://www.hzdr.de/publications/Publ-34418 doi:10.14278/rodare.2056 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Path-Integral Monte-Carlo Warm Dense Hydrogen Many-body physics Data Publication: Ab initio path integral Monte Carlo simulations of hydrogen snapshots at warm dense matter conditions info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:3420 2025-05-06T09:07:13Z software user-hzdr user-rodare user-casus

Wicaksono, Damar Canggih Hecht, Michael 2025-01-21 UQTestFuns is an open-source Python3 library of test functions commonly used within the applied uncertainty quantification (UQ) community. Specifically, the package provides: an implementation with minimal dependencies (i.e., NumPy and SciPy) and a common interface of many test functions a single entry point collecting test functions and their probabilistic input specifications in a single Python package an opportunity for an open-source contribution, supporting the implementation of new test functions or posting reference results. In short, UQTestFuns is an homage to the Virtual Library of Simulation Experiments (VLSE). v0.6.0 is a minor release that further expands the library of available UQ test functions and introduces several bug fixes. This update introduces 19 new test functions, bringing the total to 75. See the complete CHANGELOG. v0.5.0 is a minor release that further expands the library of available UQ test functions. This update introduces 14 new test functions, bringing the total to 56. https://rodare.hzdr.de/record/3420 10.14278/rodare.3420 oai:rodare.hzdr.de:3420 eng doi:10.21105/joss.05671 url:https://www.hzdr.de/publications/Publ-37736 url:https://www.hzdr.de/publications/Publ-37735 doi:10.14278/rodare.2530 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT python uncertainty-quantification benchmark sensitivity-analysis metamodeling reliability-analysis UQTestFuns: A Python3 Library of Uncertainty Quantification (UQ) Test Functions info:eu-repo/semantics/other software

oai:rodare.hzdr.de:3717 2025-06-27T09:18:30Z openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data openaire_data user-casus user-hzdr user-rodare

Wicaksono, Damar Canggih Hernandez Acosta, Uwe Thekke Veettil, Sachin Krishnan Kissinger, Jannik Hecht, Michael 2025-04-24 This release includes the dataset used to generate the convergence plot featured in the paper "Minterpy: Multivariate Polynomial Interpolation in Python," submitted to the Journal of Open Source Software (JOSS). It also provides instructions for reproducing both the data from scratch and the plot derived from that data. This is the second release of the dataset, prepared following feedback from the JOSS review process. https://rodare.hzdr.de/record/3717 10.14278/rodare.3717 oai:rodare.hzdr.de:3717 url:https://www.hzdr.de/publications/Publ-40457 url:https://www.hzdr.de/publications/Publ-40367 url:https://github.com/minterpy-project/minterpy-joss-data/releases/tag/v2.0.0 doi:10.14278/rodare.3378 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT Data to "Minterpy: Multivariate polynomial interpolation in Python" info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:1373 2022-01-10T13:57:27Z user-casus user-rodare

Günther, Ulrik Harrington, Kyle 2021-02-07 This is the video recording of the talk. https://rodare.hzdr.de/record/1373 10.14278/rodare.1373 oai:rodare.hzdr.de:1373 eng url:https://www.hzdr.de/publications/Publ-33910 url:https://www.hzdr.de/publications/Publ-33911 doi:10.14278/rodare.1372 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode visualisation rendering kotlin java jvm Data publication: Realtime 3D graphics and VR with Kotlin and Vulkan info:eu-repo/semantics/other video

oai:rodare.hzdr.de:1950 2023-01-17T10:48:11Z software user-hzdr user-casus user-rodare

Senapati, Abhishek Mertel, Adam Schlechte-Welnicz, Weronika Calabrese, Justin 2022-11-11 Codes for reproducing the results in the research article "Estimating cross-border mobility from the difference in peak-timing: A case study in Poland-Germany border regions" https://rodare.hzdr.de/record/1950 10.14278/rodare.1950 oai:rodare.hzdr.de:1950 url:https://www.hzdr.de/publications/Publ-35427 url:https://www.hzdr.de/publications/Publ-35428 doi:10.14278/rodare.1949 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Coupling strength Disease outbreak Spatio-temporal model Stochastic simulation Maximum likelihood estimation Software publication: Estimating cross-border mobility from the difference in peak-timing: A case study in Poland-Germany border regions info:eu-repo/semantics/other software

oai:rodare.hzdr.de:3633 2025-03-21T12:26:50Z openaire_data user-casus user-rodare

García-Andrade, AB Colombo, EH Calabrese, JM 2025-02-27 The two folders contain the networks at high resolution (HQ) and at a coarser resolution (HS07). Both datasets contain networks from 10 to 1000 nodes approximatly. HQ contains smaller rivers while HS07 contains the major and most relevant rivers. https://rodare.hzdr.de/record/3633 10.14278/rodare.3633 oai:rodare.hzdr.de:3633 url:https://www.hzdr.de/publications/Publ-41044 doi:10.14278/rodare.3586 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode river networks Real-world and OCN river networks info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:2164 2023-08-31T09:09:44Z openaire_data user-rodare user-hzdr user-casus

Moldabekov, Zhandos Lokamani, Mani Vorberger, Jan Cangi, Attila Dornheim, Tobias 2023-02-20 This repository contains the DFT simulation results presented in the article "Assessing the accuracy of hybrid exchange-correlation functionals for the density response of warm dense electrons". The minimal dataset that would be necessary to interpret, replicate and build upon the findings reported in the article. https://rodare.hzdr.de/record/2164 10.14278/rodare.2164 oai:rodare.hzdr.de:2164 doi:10.1063/5.0135729 url:https://www.hzdr.de/publications/Publ-36547 url:https://www.hzdr.de/publications/Publ-35898 doi:10.14278/rodare.2163 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode warm dense matter hybrid functionals Hartree-Fock Data publication: Assessing the accuracy of hybrid exchange-correlation functionals for the density response of warm dense electrons info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:1316 2021-12-15T07:28:30Z openaire_data user-casus user-hzdr user-rodare

Brosse, Sébastien Charpin, Nicolas Su, Guohuan Toussaint, Aurèle Herrera-R, Guido A. Tedesco, Pablo A. Villéger, Sébastien 2021-09-17 This dataset is publiched in the paper "FISHMORPH: A global database on morphological traits of freshwater fishes" in Global Ecology and Biogeography (doi.org/10.1111/geb.13395). The FISHMORPH database includes 10 morphological traits measured on 8,342 freshwater fish species, covering 48.69% of the world freshwater fish fauna. It provides the most comprehensive database on fish morphological traits to date. It represents an essential source of information for ecologists and environmental managers seeking to consider morphological patterns of fish faunas throughout the globe, and for those interested in current and future impacts of human activities on the morphological structure of fish assemblages. This study was supported by "Investissement d'Avenir" grants (Centre d'Etude de la Biodiversité Amazonienne, ANR-10-LABX-0025; Towards a unified theory of biotic interactions (TULIP), ANR-10-LABX-41). https://rodare.hzdr.de/record/1316 10.14278/rodare.1316 oai:rodare.hzdr.de:1316 url:https://www.hzdr.de/publications/Publ-33638 doi:10.14278/rodare.1315 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Dataset in paper 'FISHMORPH: A global database on morphological traits of freshwater fishes' info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:2720 2024-08-14T12:27:05Z openaire_data user-casus user-matter user-rodare user-zrt

Martinetto, Vincent Shah, Karan Cangi, Attila Pribram-Jones, Aurora 2024-02-01 This data repository contains the datasets used in the paper "Inverting the Kohn-Sham equations with physics-informed machine learning". It contains the data generation scripts, datasets for the systems used in the paper (Single Well - 1D atom, Double Well - 1D diatomic molecule) and output potentials generated by the physics-informed machine learning models (physics-informed neural networks and Fourier neural operators). https://rodare.hzdr.de/record/2720 10.14278/rodare.2720 oai:rodare.hzdr.de:2720 doi:10.48550/arXiv.2312.15301 url:https://www.hzdr.de/publications/Publ-38725 doi:10.14278/rodare.2719 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/matter url:https://rodare.hzdr.de/communities/rodare url:https://rodare.hzdr.de/communities/zrt info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode density functional theory machine learning Inverting the Kohn-Sham equations with physics-informed machine learning info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:318 2022-11-03T07:54:50Z openaire_data user-casus user-hzdr user-rodare

Moldabekov, Zhandos Vorberger, Jan Dornheim, Tobias Groth, Simon 2020-05-08 PIMC data for the static density response obtained by Dornheim et al. (Plasma Phys. Control. Fusion, https://doi.org/10.1088/1361-6587/ab8bb4). These data can be freely used by other researchers and contain a README file with additional information. https://rodare.hzdr.de/record/318 10.14278/rodare.318 oai:rodare.hzdr.de:318 eng doi:10.1088/1361-6587/ab8bb4 doi:10.1088/1361-6587/ab8bb4 url:https://www.hzdr.de/publications/Publ-30990 url:https://www.hzdr.de/publications/Publ-30992 doi:10.14278/rodare.317 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Path integral Monte Carlo uniform electron gas PIMC data for the uniform electron gas in the high energy density regime info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:3355 2025-05-06T09:07:12Z software user-hzdr user-rodare user-casus

Wicaksono, Damar Canggih Hecht, Michael 2024-11-18 UQTestFuns is an open-source Python3 library of test functions commonly used within the applied uncertainty quantification (UQ) community. Specifically, the package provides: an implementation with minimal dependencies (i.e., NumPy and SciPy) and a common interface of many test functions a single entry point collecting test functions and their probabilistic input specifications in a single Python package an opportunity for an open-source contribution, supporting the implementation of new test functions or posting reference results. In short, UQTestFuns is an homage to the Virtual Library of Simulation Experiments (VLSE). v0.5.0 is a minor release that further expands the library of available UQ test functions. This update introduces 14 new test functions, bringing the total to 56. https://rodare.hzdr.de/record/3355 10.14278/rodare.3355 oai:rodare.hzdr.de:3355 eng doi:10.21105/joss.05671 url:https://www.hzdr.de/publications/Publ-37736 url:https://www.hzdr.de/publications/Publ-37735 doi:10.14278/rodare.2530 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT python uncertainty-quantification benchmark sensitivity-analysis metamodeling reliability-analysis UQTestFuns: A Python3 Library of Uncertainty Quantification (UQ) Test Functions info:eu-repo/semantics/other software

oai:rodare.hzdr.de:3631 2025-03-18T07:08:28Z openaire_data user-rodare user-casus

Dornheim, Tobias Bellenbaum, Hannah Bethkenhagen, Mandy Hansen, Stephanie Böhme, Maximilian Döppner, Tilo Fletcher, Luke Gawne, Thomas Daniel Gericke, Dirk Hamel, Sebastien Kraus, Dominik MacDonald, Michael Moldabekov, Zhandos Preston, Thomas Redmer, Ronald Schörner, Maximilian Schwalbe, Sebastian Tolias, Panagiotis Vorberger, Jan 2025-03-17 This repository contains the raw data shown in the main text of the publication "Model-free Rayleigh weight from x-ray Thomson scattering measurements" https://rodare.hzdr.de/record/3631 10.14278/rodare.3631 oai:rodare.hzdr.de:3631 url:https://www.hzdr.de/publications/Publ-41114 url:https://www.hzdr.de/publications/Publ-39587 doi:10.14278/rodare.3630 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Data publication: Model-free Rayleigh weight from x-ray Thomson scattering measurements info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:3379 2025-04-24T15:12:29Z openaire_data user-rodare user-hzdr user-casus

Wicaksono, Damar Canggih Hernandez Acosta, Uwe Thekke Veettil, Sachin Krishnan Kissinger, Jannik Hecht, Michael 2025-01-06 Data for the draft manuscript "Minterpy: Multivariate polynomial interpolation in Python". The archive also includes the scripts to generate the data and create the plot that appears in the paper. https://rodare.hzdr.de/record/3379 10.14278/rodare.3379 oai:rodare.hzdr.de:3379 url:https://www.hzdr.de/publications/Publ-40457 url:https://www.hzdr.de/publications/Publ-40367 doi:10.14278/rodare.3378 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Data to "Minterpy: Multivariate polynomial interpolation in Python" info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:1404 2023-01-27T12:55:20Z openaire_data user-matter user-casus user-rodare

Gidopoulos, Nikitas Callow, Timothy James Pearce, Benjamin 2022-03-08 Data for the figures of the main paper (https://aip.scitation.org/doi/10.1063/5.0071991) and supplementary information, arranged by figure number. Notes: - A few energies are given as identically zero. These are not actually zero but did not converge. - All data is given in the units in which it appears in the paper, and columns are labelled using the same notation as in the paper. https://rodare.hzdr.de/record/1404 10.14278/rodare.1404 oai:rodare.hzdr.de:1404 doi:10.1063/5.0071991 url:https://aip.scitation.org/doi/10.1063/5.0071991 url:https://www.hzdr.de/publications/Publ-33603 url:https://www.hzdr.de/publications/Publ-34357 url:https://www.hzdr.de/publications/Publ-33603 doi:10.14278/rodare.1403 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/matter url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Data publication: Density functionals with spin-density accuracy for open shells info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:3587 2025-03-21T12:26:50Z openaire_data user-rodare user-casus

García-Andrade, AB Colombo, EH Calabrese, JM 2025-02-27 This dataset contains two folder with i) Real-world river networks ii) OCN river networks ii) the metrics for i) and ii) Please see structure of the dataset below: |-- scalingrivers-data |-- Metric results |-- metrics_undirected_ocn.csv |-- metrics_undirected_real.csv |-- OCN networks |-- ocn_networks.zip |-- River networks |-- river_networks.zip |-- river_list.csv https://rodare.hzdr.de/record/3587 10.14278/rodare.3587 oai:rodare.hzdr.de:3587 url:https://www.hzdr.de/publications/Publ-41044 doi:10.14278/rodare.3586 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode river networks Real-world and OCN river networks info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:3638 2025-03-21T13:58:11Z openaire_data user-casus user-rodare

García-Andrade, AB Colombo, EH Calabrese, JM 2025-02-27 The two folders contain the networks at high resolution (HR) and at a coarser resolution (HS07). Both datasets contain networks from 10 to 1000 nodes approximatly. HQ contains smaller rivers while HS07 contains the major and most relevant rivers. https://rodare.hzdr.de/record/3638 10.14278/rodare.3638 oai:rodare.hzdr.de:3638 url:https://www.hzdr.de/publications/Publ-41044 doi:10.14278/rodare.3586 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode river networks Real-world and OCN river networks info:eu-repo/semantics/other dataset

oai:rodare.hzdr.de:3354 2025-04-30T11:57:02Z software user-hzdr user-rodare user-casus

Hernandez Acosta, Uwe Thekke Veettil, Sachin Krishnan Wicaksono, Damar Canggih Michelfeit, Jannik Hecht, Michael 2024-12-20 minterpy is an open-source Python package for a multivariate generalization of the classical Newton and Lagrange interpolation schemes as well as related tasks. It is based on an optimized re-implementation of the multivariate interpolation prototype algorithm (MIP) by Hecht et al.1 and thereby provides software solutions that lift the curse of dimensionality from interpolation tasks. While interpolation occurs as the bottleneck of most computational challenges, minterpy aims to free empirical sciences from their computational limitations. https://rodare.hzdr.de/record/3354 10.14278/rodare.3354 oai:rodare.hzdr.de:3354 eng url:https://www.hzdr.de/publications/Publ-36106 doi:10.14278/rodare.2058 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://opensource.org/licenses/MIT multivariate interpolation multivariate polynomials numerical modelling Minterpy - multivariate polynomial interpolation info:eu-repo/semantics/other software

oai:rodare.hzdr.de:1505 2023-01-17T10:25:00Z software user-casus user-rodare

Davoodi Monfared, Mansoor Batista German, Ana Celeste Senapati, Abhishek Schlechte-Welnicz, Weronika Wagner, Birgit Calabrese, Justin 2022-03-30 Algorithm for computing the optimal testing strategy and reproducing the figures. https://rodare.hzdr.de/record/1505 10.14278/rodare.1505 oai:rodare.hzdr.de:1505 doi:10.48550/arXiv.2204.02062 url:https://www.hzdr.de/publications/Publ-34453 url:https://www.hzdr.de/publications/Publ-34417 doi:10.14278/rodare.1504 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Testing strategy Retirement home COVID-19 Long-term care Nursing home Symmetry proper Pandemic Software publication: Modeling COVID-19 optimal testing strategies in long-term care facilities: An optimization-based approach info:eu-repo/semantics/other software

oai:rodare.hzdr.de:1941 2023-01-17T10:37:18Z software user-casus user-hzdr user-rodare

Davoodi Monfared, Mansoor Senapati, Abhishek Mertel, Adam Schlechte-Welnicz, Weronika Calabrese, Justin 2022-11-09 Codes for "Optimal workplace occupancy strategies during the COVID-19 pandemic" https://rodare.hzdr.de/record/1941 10.14278/rodare.1941 oai:rodare.hzdr.de:1941 url:https://www.hzdr.de/publications/Publ-34450 url:https://www.hzdr.de/publications/Publ-35422 doi:10.14278/rodare.1940 url:https://rodare.hzdr.de/communities/casus url:https://rodare.hzdr.de/communities/hzdr url:https://rodare.hzdr.de/communities/rodare info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode COVID-19 Pandemic Optimal Presence Strategy Productivity\sep Infection Software publication: Optimal workplace occupancy strategies during the COVID-19 pandemic info:eu-repo/semantics/other software