Find research datasets worth reusing

opencc-by-4.0Aug 2021View details →

GraphQL: A Systematic Mapping Study - Supplemental Material

GraphQL: A Systematic Mapping Study - Supplemental Material As supplementary material, we add online appendices to the study, containing: <table> <tbody> <tr> <td>File</td> <td>Description</td> </tr> <tr> <td>01 SMS-Study-Identification.xlsx</td> <td>Study identification process dataset</td> </tr> <tr> <td>02 SMS-GraphQL-Primary-Studies.pdf</td> <td>SMS primary study dataset</td> </tr> <tr> <td>03 SMS-GraphQL-Data-Extraction.xlsx</td> <td>Dataset of the data extraction from the SMS primary studies</td> </tr> </tbody> </table>

Data of " Micromechanical characterization of the material response in a PA12-SLS fabricated lattice structure and its correlation with bulk behavior"

<pre>Data related to the publication (we would be grateful if you could cite the paper in the case in which you are using the data) title = "Micromechanical characterization of the material response in a PA12-SLS fabricated lattice structure and its correlation with bulk behavior", journal = "Polymer Testing", pages = " ", year = "2022", issn = "####", doi = "<a href="https://doi.org/10.1016/j.polymertesting.2022.107556">https://doi.org/10.1016/j.polymertesting.2022.107556</a>", author = "L. Cobian, M. Rueda-Ruiz, J.P. Fernandez-Blazquez, V. Martinez, F. Galvez, F. Karayagiz, T. Lück, J. Segurado, M.A. Monclus"</pre> This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862015

Supplementary Material of the paper entitled "Governing Digital Twin technology on smart and sustainable tourism"

In this document, we provide some supplementary material of the paper entitled “Governing Digital Twin technology on smart and sustainable tourism’’. Rahmadian, E., Feitosa, D., Zwitter, A. (2022). Governing Digital Twin technology on smart and sustainable tourism.

Even when you know it is a placebo, you experience less sadness: First evidence from an experimental open-label placebo investigation (Open Data and Open Materials)

Open Data and Open Materials of: Even when you know it is a placebo, you experience less sadness: First evidence from an experimental open-label placebo investigation. Journal of Affective Disorders. Background: Recent studies demonstrate substantial effects of deceptive placebo on experimentally induced sadness, even on autonomic activity. Whether deception is necessary, remains to be elucidated. We investigated the effect of an open-label placebo (OLP) treatment, i.e. an openly administered placebo delivered with a convincing rationale for its sadness-protecting effect. Methods: Eighty-four healthy females were randomized to an OLP group or a no-treatment control group. All participants received the same detailed information about the OLP effect, only the OLP group received an OLP nasal spray. Before and after the OLP intervention, participants underwent a sad mood induction procedure combining self-deprecating statements (Velten's method) and sad music. Sadness was assessed by the Positive and Negative Affect Schedule (PANAS-X). Autonomic activity was measured continuously. Results: Participants in the OLP group reported a significantly attenuated increase in sadness upon mood induction and less sadness after induction compared to the control group (d = 0.79). Regardless of intervention, heart rate decreased during mood inductions with a more pronounced deceleration in the second mood induction. Limitations: Generalizability is limited due to the selective sample and the reliance on an experimentally controlled mood induction. Conclusion: OLP treatment had a beneficial effect on perceived sadness, at least at the subjective level. Hence, deception may not necessarily be required for placebos to modulate experienced sad mood. Investigating the beneficial effects of OLP in (sub-)clinical samples would seem a promising and required next step towards a clinical use of placebo-associated positive treatment expectations.

opencc-by-4.0Sep 2021View details →

Supplementary Material for "Evaluating Classifiers in SE Research: The ECSER Pipeline and Two Replication Studies"

This supplementary material for the article"Evaluating Classifiers in SE Research: The ECSER Pipeline and Two Replication Studies. Dell’Anna, D.; Aydemir, F. B.; and Dalpiaz, F. Empirical Software Engineering. 2022" includes <ul> <li>ECSER-ExploratoryStudy.csv: The annotated meta-data of the papers that have been published in ICSE between 2019 and 2021.</li> <li>ECSER_ROCplots+StatTest.ipynb:  A python notebook that compares classifiers adn checks the statistical significance of the comparison results.</li> <li>ECSER_SummaryOfReplicationSteps.pdf: This table presents a summary of ECSER steps for the two original studies and our applications on ECSER.</li> <li>ECSER_RE: The directory that holds the datasets and code for the replication of Hay et al. [1] and additional runs on the new data sets.</li> <li>ECSER_FF: The directory that holds the code and data for the replication of Alshammari et al. [2]</li> <li>README.md presents the structure of the supplementary materials.</li> <li>requirements.txt lists the dependencies needed to run the code</li> </ul> In the ECSER_RE directory, the code for multiple classifiers that are compared are kept in the "Classifiers" directory. The public data sets are shared in the Datasets directory. "ECSER_RE_Compare_Classifiers.ipynb" python notebook includes the code that runs each classifier. The results are presented in "ECSER_RE_results-Promise-vs-all.csv". In the ECSER_FF directory, the data sets are presented directly under the main directory. The notebook "ECSER-FF-Compare_Classifiers.ipynb" compares the classifiers of the original study and the results are kept under the "ECSER_FF_results" directory. How to cite this repository  If you use this repository, please cite the reference paper, and the repository, as below: Dell’Anna, Davide, Fatma Başak Aydemir, and Fabiano Dalpiaz. "Evaluating classifiers in SE research: the ECSER pipeline and two replication studies." Empirical Software Engineering 28.1 (2023): 3. Davide Dell'Anna, Fatma Başak Aydemir, & Fabiano Dalpiaz. (2021). Supplementary Material for "Evaluating Classifiers in SE Research: The ECSER Pipeline and Two Replication Studies" [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6266675       <ol> <li>Tobias Hey, Jan Keim, Anne Koziolek, and Walter F. Tichy. 2020. SupplementaryMaterial of "NoRBERT: Transfer Learning for Requirements Classification". https://doi.org/10.5281/zenodo.3874137</li> <li>Abdulrahman Alshammari, Christopher Morris, Michael Hilton, and JonathanBell. 2021. FlakeFlagger: Predicting Flakiness Without Rerunning Tests. In43rdIEEE/ACM International Conference on Software Engineering, ICSE 2021, Madrid,Spain, 22-30 May 2021. IEEE, 1572–1584. https://doi.org/10.1109/ICSE43902.2021.00140</li> </ol>

opencc-by-4.0Dec 2021View details →

Modelling of static liquefaction of partially saturated non-cohesive soils - Supplementary Materials

Supplementary Material - Repository S1: Experimental data Article title: Modelling of static liquefaction of partially saturated non-cohesive soils Journal name: Applied Sciences Detailed data of undrained triaxial laboratory tests conducted on partially saturated samples of non-cohesive soils.   This spreadsheet contains values of initial parameter of each sample (saturation level, density and porosity, stress state and back pressure) and values of stresses, strains and pore pressure measured during the experiments. File includes also information about physical properties of tested soils: medium Skarpa sand and copper mining post-floating tailings OZM50.

opencc-by-4.0Dec 2021View details →

Data, code, and material associated with the paper "Biodiversity-related science communication in times of global crises"

Data, code, and material associated with the paper &bdquo;Biodiversity-related science communication in times of global crises“, subm.: <ul> <li>R script to run the analysis</li> <li>Data needed to reproduce the results and figures</li> <li>IPBES region data (from https://doi.org/10.5281/zenodo.3928281)</li> </ul>

Supplementary Materials: Laser-solid interaction studies enabled by the new capabilities of the iP2 BELLA PW beamline

<pre>Supplementary Materials ======================= Corresponding manuscript: "Laser-solid interaction studies enabled by the new capabilities of the iP2 BELLA PW beamline" by Sahel Hakimi, Lieselotte Obst-Huebl, Axel Huebl, Kei Nakamura, Stepan S. Bulanov, Sven Steinke, Wim P. Leemans, Zachary Kober, Tobias M. Ostermayr, Thomas Schenkel, Anthony J. Gonsalves, Jean-Luc Vay, Jeroen van Tilborg, Csaba Toth, Carl B. Schroeder, Eric Esarey, and Cameron G.R. Geddes (2022) Structure of this Archive ------------------------- This archive is structured as follows in sub-directories: - `WarpXsource/`: the simulation source code, build instructions/documentation and references - `WarpXDataAndInputs/`: the simulation inputs, submission scripts, and representative output - `FigureDataAndScripts/`: the analysis scripts and, where applicable, processed data for individual figures Note that raw data output of simulations is approximately 180 TByte per simulation and can thus not easily be shared in this data archive. Instead, we make all source code, documenation and build instructions, selected processed/reduced data, and relevant analysis scripts available to ensure reproducibility of the raw data basis. Please see the individual subdirectories for further `README.txt` files. Contacts -------- For general questions about the publication and data archive, please contact the corresponding authors. Please see the archive metadata and the publication manuscript for contacts.</pre>

Second-strain gradient elasticity parameters for centrosymmetric materials

This is a collection of material parameters sets describing 999, thermodynamically admissible, isotropic, centrosymmetric, elastic materials featuring second-strain gradient elasticity. The notations are according to Mindlin R.D. (1965) Second-gradient theory of strain and surface tension in linear elasticity. Int. J. Solids Structures 1:417-438.

Supplementary materials of Brain Extract of Subacute Traumatic Brain Injury Promotes Neuronal Differentiation of Human Neural Stem Cells Via Autophagy

Figure S1: Characterization of hNSCs. In proliferate medium, the embryo derived hNSCs could form the neurospheres (A). Markers of NSCs (NES, SOX2, SOX1) were detected (B). The SOX2+ cells accounted for >95% of all cells (C). Bar scale: 60μm; Figure S2: The proliferation of hNSCs in TBI brain extracts with different phases. Differentiated hNSCs could be labeled with EdU in TBI brain extracts with different phases (A). Ratio of EdU+ cells was decreased with the progression of days post-injury (B). Bar scale: 75μm; ****: P<0.0001; Figure S3: The GO annotations and KEGG pathway analysis of different expressed pro-teins in acute brain extract and subacute brain extract; Table S1: The protein profiles of brain extract in acute phase and subacute phase after TBI.

Chemical analysis of Food Contact Materials

Chemical analysis of food contact materials fromUK, EU and China

opencc-by-4.0Dec 2021View details →

NIAS data Food Contact Materials

NIAS data for food contact materials

Dataset: "Generalized scaling of spin qubit coherence in over 12,000 host materials"

Accompanying data for the main text and supplemental materials of Generalized scaling of spin qubit coherence in over 12,000 host materials

opencc-by-4.0Sep 2021View details →

Seismic acquisition parameters to improve imaging beneath mafic igneous units: Case study from Australia's Northwest Shelf; supplementary material

This dataset comprises two supplementary materials. Supplementary Materials A includes seismic processing workflows conducted by industry on the seismic lines used in this study. The seismic processing workflows are not the property of the author but are publicly available on the NOPIMS and WAPIMS databases. Collating these workflows into supplementary materials provides a simple method for readers to access material important for this research paper. Supplementary Materials B is a collection of 2D seismic lines the author conducted stratigraphic horizon mapping on for this study as viewed in 3D. More details on this dataset can be found throughout the research paper "Seismic acquisition parameters to improve imaging beneath mafic igneous units: Case study from Australia’s Northwest Shelf".

Supplemental Materials for "Schwarzschild and Ledoux are equivalent on evolutionary timescales"

This Zenodo repository contains a .tar file which contains datasets which can be used along with the code in the associated Github repository (https://github.com/evanhanders/schwarzschild_or_ledoux, an copy of which is also included here as a .tar file) to create all of the static figures in the paper. The figures can be recreated with this data by using the Python scripts in the schwarzschild_or_ledoux/publication_figures/ folder of the Git repository. The data are as follows: Figure 1: <ul> <li>early_slices.h5, late_slices.h5 - 2D slices through various planes in the simulation which show the dynamics at a few early and late times in the simulation.</li> <li>early_profiles.h5, late_profiles.h5 - 1D horizontally-average profiles at the times associated with the dynamics in the 'slices' files.</li> <li>early_scalars.h5, late_scalars.h5 - files that contain some various scalar info (e.g., where the boundary is determined by the Schwarzschild and Ledoux criteria) for the early and late dynamics.</li> </ul>   Figure 2 - <ul> <li>1D horizontally-averaged profiles for the full simulation in the paper are output into the "merged_profiles.h5" file. The output cadence is once every freefall time, so there are roughly 20,000 time points for each profile. figure 2 uses the initial state and the state at t = 17,000.</li> </ul> Figure 3 - <ul> <li>scalar_data.h5 contains scalar values inferred from merged_profiles.h5 at each point in time. This file can be re-created by the user by using the 'profile_to_scalar.py' file inside of the publication_figures/ folder in the repository.</li> </ul>

Human-robot co-manipulation of soft materials: enable a robot manual guidance using a depth map feedback [Video]

Video of the paper submitted at RO-MAN 2022  Human-robot co-manipulation of soft materials: enable a robot manual guidance using a depth map feedback Giorgio Nicola, Enrico Villagrossi, Nicola Pedrocchi Code for trainings and test available at: https://github.com/giorgionicola/SMAHRCO

Experimental materials for "The Effect of Information Content and Length on Name Recollection"

Experimental materials for the paper "The Effect of Information Content and Length on Name Recollection" published in the 30th IEEE/ACM International Conference on Program Comprehension (ICPC), 16-17 May 2022. Includes the experimental materials, responses of participants in the experiments, and analysis scripts and results for the two experiments described in the paper.

Supplementary material for: AIRBORNE LASER SCANNING CHANGE DETECTION FOR QUANTIFYING GEOMORPHOLOGICAL PROCESSES IN HIGH MOUNTAIN REGIONS

Supplementary material for: TCII/10-AIRBORNE LASER SCANNING CHANGE DETECTION FOR QUANTIFYING GEOMORPHOLOGICAL PROCESSES IN HIGH MOUNTAIN REGIONS For submission of the full paper to: International Society for Photogrammetry and Remote Sensing (ISPRS) / XXIV ISPRS Congress 2022 Nice, France, 6 - 11 June 2022. ADDITIONAL FIGURES AND MAPS Supplementary materials: Figure S1: Classification preparation and decision tree. Figure S2: 3D distance change and change offset overall map. Figure S3: Geomorphological map inventoried by manual mapping. Figure S4: Classified real changes of the valley area between 2006 and 2017. Figure S5: Classified real changes between 2006 and 2017.

opencc-by-4.0Apr 2022View details →

Results of RHD simulation of ns-prepulse with 3DLINE code for different target materials

calc_NNNN_XX.vtk files are results of RHD simulations of fs-prepulse carried with code 3DLINE in rz-geometry. Units: cm, g/ccm, keV. Parameters of prepulse:  940 ps of 1e10 W/cm2 at axis;  60 ps exponentially rising up to 1e16 W/cm2 at axis;  wavelength 815 nm; spatial profile - see intensity.txt. For further details contact IliaTsygvintsev@gmail.com.