Find research datasets worth reusing

opencc-by-4.0Mar 2020View details →

Test data for running snakePipes : noncoding-RNA-seq workflow

Test files for running snakePipes workflows snakePipes are pipelines built using snakemake and python for the analysis of epigenomic datasets. Please refer to <a href="https://snakepipes.readthedocs.io/en/latest/">this link</a> for further information on snakePipes. This folder contains test files that can be used to run the noncoding-RNA-seq workflow under snakePipes. To test the workflow, follow the following steps :  <ul> <li>Download or prepare genome fasta, indices and annotations for mouse (GRCm38) genome. Repeat Masker file is required for this workflow.</li> <li>Download and install snakePipes via `conda create -n snakePipes -c mpi-ie -c bioconda -c conda-forge snakePipes`</li> <li>Update <a href="https://snakepipes.readthedocs.io/en/latest/content/running_snakePipes.html#genome-configuration-file">Genome configuration file</a> with path to indices and annotations.</li> <li>Move to this repository and run the example command.sh</li> </ul>

opencc-by-4.0Mar 2020View details →

TesCaV: An Approach for Learning Model-based Testing and Coverage in Practice, Experimental Data

The data in this sheet provides the result of the exploratory experiment presented in the following paper: Beatriz Marín, Sofía Alarcón, Giovanni Giachetti, and Monique Snoeck. (2020) TesCaV: An Approach for Learning Model-based Testing and Coverage in Practice, in  Fabiano Dalpiaz, Jelena Zdravkovic, Pericles Loucopoulos (eds), Proceedings of the 14th International Conference on Research Challenges in Information Science, LNCS, Springer.

opencc-by-4.0May 2020View details →

BigFuzz: Efficient Fuzz Testing for Data Analytics using Framework Abstraction

BigFuzz supplementary material.

openmit-licenseMay 2020View details →

Initial bootstrap of pydicom testing data

An initial snapshot of the pydicom test files as found within <a href="https://github.com/SimonBiggs/pydicom/tree/b4ff70affe40fb1054b98ff049c2a6392e3e29cd/pydicom/data/test_files">https://github.com/SimonBiggs/pydicom/tree/b4ff70affe40fb1054b98ff049c2a6392e3e29cd/pydicom/data/test_files</a> Future test files will likely be their own Zenodo submission

openapache2.0May 2020View details →

Testing Data for PyMedPhys

Testing Data for PyMedPhys

CHX test data

CHX test data

STEG data of manuscript "Electrical Generation of a Ground Level Solar Thermoelectric Generator: Experimental Tests and One-year Cycle Simulation" submitted to Energies

Figure_7_data: laboratory data of TEG output power working at low temperature differences. Data used in Figure 7 of manuscript "Electrical Generation of a Ground Level Solar Thermoelectric Generator: Experimental Tests and One-year Cycle Simulation" submitted to Energies. Figure_9_data: experimental data of TEG temperature differences from July 24 to July 31, 2017. Data used in Figure 9 of manuscript "Electrical Generation of a Ground Level Solar Thermoelectric Generator: Experimental Tests and One-year Cycle Simulation" submitted to Energies. Figures_11_14_data: input and output data of the STEG model. One-year cycle data. Used to obtain figures 11 to 14 of manuscript "Electrical Generation of a Ground Level Solar Thermoelectric Generator: Experimental Tests and One-year Cycle Simulation" submitted to Energies

opencc-by-4.0Feb 2020View details →

Gemini 3D test data

DEPRECATED: data now at: <a href="https://zenodo.org/record/3962801">https://zenodo.org/record/3962801</a> --- Gemini 3D simulation reference data https://www.github.com/gemini3d/gemini v3.2.0 new api / meta

Nitrification test data with tap water and varying natural organic matter

Laboratory scale nitrification tests with tap water. The effect of two different NOM concentrations were tested. This data is linked to the manuscript "Decreased natural organic matter in water distribution decreases nitrite formation in non-disinfected conditions, via enhanced nitrite oxidation" by Pirjo-Liisa Rantanena, Minna M. Keinänen-Toivolab, Merja Ahonenb, Alejandro Gonzalez-Martinezc, Ilkka Mellind, Riku Vahalaa a Department of Built Environment, Aalto University, P.O Box 15200, FI-00076 Aalto, Finland b Faculty of Technology, Satakunta University of Applied Sciences, PO Box 1001, FI-28101 Pori, Finland c Department of Microbiology, University of Granada, Campus Universitario de Cartuja, 18071 Granada, Spain d Department of Mathematics and Systems Analysis, Aalto University, PO Box 11100, FI-00076 Aalto, Finland

Data set for the manuscript "Reproductive physiology corresponds to adult nutrition and task performance in a Neotropical paper wasp: a test of dominance-nutrition hypothesis predictions"

Data set for the manuscript "Reproductive physiology corresponds to adult nutrition and task performance in a Neotropical paper wasp: a test of dominance-nutrition hypothesis predictions"

PARE module test data

PARE soil sample and ARG dataset

opencc-by-4.0Oct 2019View details →

Numerical Fire Spread Simulation Based on Material Pyrolysis - An Application to the CHRISTIFIRE Phase 1 Horizontal Cable Tray Tests - Data Set

This data set is a supplementary resource for the article "<a href="http://www.mdpi.com/2571-6255/3/3/33">Numerical Fire Spread Simulation Based on Material Pyrolysis - An Application to the CHRISTIFIRE Phase 1 Horizontal Cable Tray Tests</a>", published by the peer-reviewed open access journal <a href="https://www.mdpi.com/journal/fire">Fire</a>. It is part of the "<a href="https://www.researchgate.net/project/Fire-Propagation-in-Cable-Tray-Installations">Fire Propagation in Cable Tray Installations</a>" project. The provided data is only a summary of the full data produced for the article, due to its size. This article was previously submitted to the Fire Safety Journal and got eventually rejected. The information is structured into multiple *.rar archieves, which mimic the sub-directory structure created for the work. To be able to run the analysis scripts without much tweaking, extract all archieves into the same directory, with each archieve being a sub-directory in it. The data set is comprised of: <ul> <li>The PROPTI and FDS input files used for the inverse modelling process (IMP) -- the 13* archieves.</li> <li>Full FDS simulation data of the mirco-combustion calorimeter (MCC) simulations of the best parameter sets per generation of the IMP runs, for jacket and insulator materials.</li> <li>Full FDS simulation data of the Cone Calorimeter simulations of the best parameter sets per generation of the IMP runs, for all three (25 kW/m², 50 kW/m², 75 kW/m²) incident heat flux conditions.</li> <li>FDS input files for the MT3 simulations, but full data only for the best parameter sets per IMP run (see below).</li> <li>Jupyter notebooks used for the analysis of the simulation responses including the scripts and plots generated for, and used in, the paper (RunReports).</li> <li>A general information directory, containing the FDS input file templates, experimental data used as target and Python scripts containing helper functions.</li> <li>Videos of a qualitative comparison of the SmokeView animation of the best parameter set in a cable tray simulation against a video from the experiment and an animation of the GAUGE_HEAT_FLUX development for the same simulation over the course of the simulation.</li> </ul> Due to the size of the MT3 simulation data, only the FDS input files for the best parameter sets per generation are uploaded. Complete FDS simulation data is only provieded for the best perameter set of each IMP run, these are : IMP run, best rep. -------------------------------- imp_13b, 110751 imp_13c, 121106 imp_13d, 137738 imp_13e, 97493 imp_13f, 91988 imp_13g, 86988 imp_13h, 17480 imp_13b_1, 19033 imp_13b_2, 25043 imp_13b_3b, 24149 imp_13b_4, 29666 imp_13h_1, 10685 imp_13h_2, 10024 imp_13h_3, 10109 imp_13i, 13253   Note: The individual runs of the IMP are named differently as compared to the labeling used in the paper, as described below: IMP run, label in paper -------------------------------- imp_13b, Tb imp_13c, Ta imp_13d, Tc imp_13e, Ta,b,c imp_13f, Tb,c imp_13g, Ta,c imp_13h, Ta,b,cLA,L1,HC imp_13b_1, TbL1 imp_13b_2, TbPL1 imp_13b_3b, TbPL1L1 imp_13b_4, TbPL2,HT imp_13h_1, Ta,b,cPA,L1,HCL1 imp_13h_2, Ta,b,cPA,L1,HCL2 imp_13h_3, Ta,b,cPA,L1,HCL3 imp_13i, TbPA,L1,HC   Version 2 changes: Added pre-print.   Version 3 changes: Added new files that where produced during the revision process, after the original manuscript got rejected by the Fire Safety Journal. This revision corresponds to the intitial manuscript that was submitted to the journal <a href="https://www.mdpi.com/journal/fire">Fire</a>. The respective Zip archieves are labeled with a "_Revision01".

Training and Testing Data, Associated Code, and SCAM Validations Code and Data for ResNet in moist physics (ResCu)

Data and codes for a deep convolutional residual neural network moist physics parameterization (ResCu). In this new version, the randomly selected training data samples and part of testing data samples (June, July and August) are provided. They are processed into a new data structure, which can be directly utilized in training and testing. For the entire second year training samples and the entire third year testing samples, we provide them in a repository at Dryad (<a href="https://doi.org/10.6075/J0CZ35PP">https://doi.org/10.6075/J0CZ35PP</a> and https://doi.org/10.6075/J03J3BGF). Please download and decompress ResCu_Han_et_al_JAMES.tar.gz. Follow the instructions in README.txt and download the training and testing data (The Dryad depositary is provided in the description).  Here we provide 3 parts of data and codes: 1, Training and testing data from SPCAM; 2, Training and testing codes for ResCu and many other NN architectures; 3, SCAM validations.

opencc-byJun 2020View details →

Politecnico di Milano - Wind tunnel test data on high-rise building

High-resolution pressure data recorded in wind tunnel tests performed at the Politecnico di Milano wind tunnel on a generic prismatic high-rise building. If you use these data, please cite: Lamberti, G., Amerio, L., Pomaranzi, G., Zasso, A., & Gorlé, C. (2020). Comparison of high resolution pressure measurements on a high-rise building in a closed and open-section wind tunnel. Journal of wind engineering and industrial aerodynamics, 204, 104247. DOI: 10.1016/j.jweia.2020.104247

opencc-zeroJul 2020View details →

Data from: Brain size does not predict learning strategies in a serial reversal learning test

Reversal learning assays are commonly used across a wide range of taxa to investigate associative learning and behavioural flexibility. In serial reversal learning, the reward contingency in a binary discrimination is reversed multiple times. Performance during serial reversal learning varies greatly at the interspecific level, as some animals adapt a rule-based strategy that enables them to switch quickly between reward contingencies. Enhanced learning ability and increased behavioural flexibility generated by a larger relative brain size has been proposed to be an important factor underlying this variation. Here we experimentally test this hypothesis at the intraspecific level. We use guppies (Poecilia reticulata) artificially selected for small and large relative brain size, with matching differences in neuron number, in a serial reversal learning assay. We tested 96 individuals over ten serial reversals and found that learning performance and memory were predicted by brain size, whereas differences in efficient learning strategies were not. We conclude that variation in brain size and neuron number is important for variation in learning performance and memory, but these differences are not great enough to cause the larger differences in efficient learning strategies observed at higher taxonomic levels.

opencc-zeroJul 2020View details →

Data from: Contingent tradeoff decisions with feedbacks in cyclical environments: testing alternative theories

This archive contains the model code and input for the simulation experiments published in: Railsback, Harvey, and Ayllón, in press. Contingent tradeoff decisions with feedbacks in cyclical environments: testing alternative theories. Behavioral Ecology. BEHECO-2019-0460.R3. That paper formulates and tests four alternative theories for how animals make tradeoff decisions throughout the circadian light cycle in a population context, with the behavior of each individual affecting the resources available to others. The example application is to stream trout selecting when and where to feed vs. hide, during dawn, day, dusk, and night. These theories are tested against observed patterns reported in the literature. The archive provides separate NetLogo program files for each theory and each simulation experiment. These files allow complete reproduction of the simulation experiments.

opencc-zeroAug 2020View details →

Data from: Characteristics of university students supported by counseling services: analysis of psychological tests and pulse rate variability

Objective Mental health is an essential issue during adolescence. The number of students who use counseling services is increasing in universities. We attempted to confirm the characteristics of the students who access counseling services using both psychological tests and pulse rate variability (PRV) for better support for students' academic success. Methods We recruited the participants for this study from the students who had counseling sessions at Kanazawa University (Group S). As a control group, we also recruited students who had no experience in counseling services (Group H). We obtained health information from the database of annual health checkups. Participants received the Wechsler Adult Intelligence Scale (WAIS) III, Autism-Spectrum Quotient (AQ), Sukemune-Hiew (S-H) Resilience Test, and State-Trait Anxiety Inventory-JYZ (STAI). We also studied the SF-12v2 Health Survey. As a physiological test, we examined the spectral analyses of pulse rate variability (PRV) by accelerating plethysmography. We performed a linear analysis of PRV for LF, HF, and LF/HF as indexes of autonomic nervous function. We also conducted a non-linear analysis of PRV for the largest Lyapunov exponent (LLE). Additionally, we examined participants' blood for autoantibodies against glutamate decarboxylase (GAD) 65. Results A total of 105 students participated in this study. Group S had 37 participants (Male: 26, Female: 11), and Group H had 68 participants (Male: 27, Female 41). <a name="_Hlk24561145">There were five males and one female who had diagnoses of autism spectrum disorder (ASD), and three males and no female with attention deficit hyperactivity disorder (ADHD) by medical institutes in Group S. Additionally, four males and two females had diagnoses of ASD with ADHD by medical institutes in Group S.</a> A male with ASD in Group S had epilepsy. The students of Group S had characteristics as follows: 1) lower power of WMI despite high Full-Scale IQ, 2) higher ASD traits especially in Male, 3) lower resilience powers, 4) higher anxiety trait, 5) lower QOL in Role/social component in both Male and Female, 6) lower QOL in Mental component in Male 7) shifting of autonomic nervous balance toward higher sympathetic activity. Conclusion We could confirm the characteristics of students who visited counseling rooms for mental support. We also found gender differences in specificities of Group S. The educational system is changing rapidly to adjust social requests. These changes make conflict with the features of students of Group S. We should think about appropriate supports for the students who would pioneer the future of humanity.

opencc-zeroAug 2020View details →

Data from: Testing models of reciprocal relations between social influence and integration in STEM across the college years

The present study tests predictions from the Tripartite Integration Model of Social Influences (TIMSI) concerning processes linking social interactions to social integration into science, technology, engineering, and mathematics (STEM) communities and careers. Students from historically overrepresented groups in STEM were followed from their senior year of high school through their senior year in college. Based on TIMSI, we hypothesized that interactions with social influence agents (operationalized as mentor network diversity, faculty mentor support, and research experiences) would promote both short- and long-term integration into STEM via social influence processes (operationalized as science self-efficacy, identity, and internalized community values). Moreover, we examined the previously untested hypothesis of reciprocal influences from early levels of social integration in STEM to future engagement with social influence agents. Results of a series of longitudinal structural equation model-based mediation analyses indicate that, in the short term, higher levels of faculty mentorship support and research engagement, and to a lesser degree more diverse mentor networks in college promote deeper integration into the STEM community through the development of science identity and science community values. Moreover, results indicate that, in the long term, earlier high levels of integration in STEM indirectly influences research engagement through the development of higher science identity. These results extend our understanding of the TIMSI framework and advance our understanding of the reciprocal nature of social influences that draw students into STEM careers.

opencc-zeroOct 2019View details →

Data from: Using text-mined trait data to test for cooperate-and-radiate co-evolution between ants and plants

Mutualisms may be "key innovations" that spur lineage diversification by augmenting niche breadth, geographic range, or population size, thereby increasing speciation rates or decreasing extinction rates. Whether mutualism accelerates diversification in both interacting lineages is an open question. Research suggests that plants that attract ant mutualists have higher diversification rates than non-ant associated lineages. We ask whether the reciprocal is true: does the interaction between ants and plants also accelerate diversification in ants, i.e. do ants and plants cooperate-and-radiate? We used a novel text-mining approach to determine which ant species associate with plants in defensive or seed dispersal mutualisms. We investigated patterns of lineage diversification across a recent ant phylogeny using BiSSE, BAMM, and HiSSE models. Ants that associate mutualistically with plants had elevated diversification rates compared to non-mutualistic ants in the BiSSE model, with a similar trend in BAMM, suggesting ants and plants cooperate-and-radiate. However, the best-fitting model was a HiSSE model with a hidden state, meaning that diversification models that do no account for unmeasured traits are inappropriate to assess the relationship between mutualism and ant diversification. Against a backdrop of diversification rate heterogeneity, the best-fitting HiSSE model found that mutualism actually decreases diversification: mutualism evolved much more frequently in rapidly diversifying ant lineages, but then subsequently slowed diversification. Thus, it appears that ant lineages first radiated, then cooperated with plants.