Find research datasets worth reusing

opencc-by-4.0May 2019View details →

Supplemental material to the paper: Incorporating epistemic uncertainty in the assessment of an existing masonry building through a Point Estimate Method

This repository contains the meterials used to study numerically the effect of model uncertainties in the seismic assessment of a case-study stone masonry building. The simulations were run in the research version of the software <a href="http://www.tremuri.com/">Tremuri</a>. The repository contains input files, model results and the matlab code to reproduce the figures presented in the paper: <blockquote> Vanin F., Beyer K., "Incorporating epistemic uncertainty in the assessment of an existing masonry building through a Point Estimate Method",  submitted for publication (2019) </blockquote>

opencc-by-4.0Sep 2019View details →

Supplement of manuscript FWB-P-Nov-18-0586.R2

This folder contains analysis data from the study published as Article (Manuscript ID FWB-P-Nov-18-0586.R2): TITLE: Phylogenetic placement of environmental sequences using taxonomically reliable databases helps to rigorously assess dinophyte biodiversity in Bavarian lakes (Germany) JOURNAL: Freshwater Biology MS-ID: FWB-P-Nov-18-0586.R2 FILES: FWB-P-Nov-18-0586.R2_metadata.csv  (geo-references and metadata) FWB-P-Nov-18-0586.R2_OTU-table.csv  (OTU-table)

opencc-zeroMay 2024View details →

Supplemental material to the journal article "Tracing Homopolymers in Oikopleura dioica's mitogenome"

Supplemental material to the journal article “Tracing Homopolymers in Oikopleura dioica’s mitogenome”, consisting of: <ul> <li>The I25 mitochondrial genome (GenBank ID PP146516) and its annotation (not in GenBank)</li> <li>Transcript model sequences used to annotate the genome</li> <li>Nucleotide sequences of cytochrome oxidase I used to compute the tree in Figure 3</li> </ul> Updated on August 6th 2024: <ul> <li>Add raw reads used to assemble the mitogenome.</li> <li>ATP6 gene coordinate corrected (7110 -> 7104) to reach TAA stop codon.</li> </ul>

Supplemental Data for "Localization renormalization and quantum Hall systems"

Scripts and data to supplement the paper "Localization renormalization and quantum Hall systems".

opencc-by-4.0Apr 2020View details →

Fig 3 in Effects of plants and supplemental prey on establishment of Dicyphus hesperus (Hemiptera: Miridae)

Fig 3. Average number of Dicyphus hesperus per sample on each treatment (tomato with Ephestia eggs, mullein with and without Ephestia eggs) over 15 wk. The experiment was completed in the greenhouse at the University of Florida in Gainesville, Florida, USA, and data shown are means ± SE. Different letters describe significant differences in population size of D. hesperus on 3 different treatments each wk.

opencc-by-4.0Apr 2020View details →

Fig 2 in Effects of plants and supplemental prey on establishment of Dicyphus hesperus (Hemiptera: Miridae)

Fig 2. Adult longevity of Dicyphus hesperus reared from first instar nymphs on 4 treatments. Experiment conducted in the growth room of the University of Florida/IFAS Gulf Coast Research and Education Center, Wimauma, Florida, USA. Data shown are means ± SE; capital letters indicate significant differences within treatments for adult longevity, and lowercase letters indicate significant differences for survival of D. hesperus (Tukey's, α <0.05).

Supplement to Warwel et al. : Local Earthquake Catalogue of the Copiapó region December 2022 until June 2023

Local Seismicity Catalogue of the  Copiapó region (December 2022 until June 2023). The files contain the catalog, phase picks, and waveforms in SEISAN format.  For details see Warwel et al. (submitted).  This work was supported by the Bundesministerium für Bildung und Forschung (BMBF) under grant 03G0297A (PISAGUA).

Supplemental Material to "The Small-Amplitude Dynamics of Spontaneous Tropical Cyclogenesis. Part II: Linear Stability Analysis"

This is the supplemental material to the manuscript "The Small-Amplitude Dynamics of Spontaneous Tropical Cyclogenesis. Part II: Linear Stability Analysis". It deposits: (1) A handwritten math derivation note (math_derivation_note.pdf). (2) A movie version of Figure 1 (Part_II_movie.avi). (3) The Fortran code for amplifying the longwave radiative feedback in CM1 (Radiation_amplification_RAD_parameter_in CM1.txt). (4) The MATLAB postprocessing codes for generating data figures (postprocessing_code.zip). (5) The MATLAB solver of the four-layer QG model (four_layer_QG_solver.m). (6) Supplemental figures (supplement_figures.pdf).   Please contact Dr. Hao Fu (haofu@uchicago.edu or haofu736@gmail.com) if you have any questions.

FIGURE 4 in Effect of dietary omega-3 polyunsaturated fatty acids supplementation of Astyanax lacustris males on semen quality

FIGURE 4 | Results obtained for A. Head lateral displacement amplitude (ALH, µm) and B. Crossbeat frequency (BCF, Hz), after feeding with the inclusion of PUFAs-ô3 in the diet of Astyanax lacustris for a period of 105 days. In-0 – diet without inclusion of PUFAs-ô3; In-3 – feed with inclusion of 3% PUFAs-ô3; In-6 – feed with inclusion of 6% of PUFAs-ô3; In-9 – feed with inclusion of 9% PUFAs-ô3. Different lowercase letters indicate statistical difference between treatments for ALH and BCF (Kruskal-Wallis, p<0.05).

FIGURE 3 in Effect of dietary omega-3 polyunsaturated fatty acids supplementation of Astyanax lacustris males on semen quality

FIGURE 3 | Results obtained for A. Linearity (LIN, %), B. Straightness coefficient (STR, %) and C. Mean oscillation of the spatial trajectory (WOB, %), after feeding with the inclusion of PUFAs-ô3 in the diet of Astyanax lacustris for a period of 105 days. In-0 – diet without inclusion of PUFAs-ô3; In-3 – feed with inclusion of 3% PUFAs-ô3; In-6 – feed with inclusion of 6% of PUFAs-ô3; In-9 – feed with inclusion of 9% PUFAs-ô3. Different lowercase letters indicate statistical difference between treatments for LIN, STR and WOB (Kruskal-Wallis, p<0.05).

FIGURE 2 in Effect of dietary omega-3 polyunsaturated fatty acids supplementation of Astyanax lacustris males on semen quality

FIGURE 2 | Results obtained for A. Percentage of fast (SptzRápido), medium (SptzMedium) and slow (SptzSlow), B. Curvilinear velocity (VCL, µm/s), C. Linear velocity (VSL, µm/ s), D. Mean velocity (VAP, µm/s%) after feeding with the inclusion of PUFAs-ô3 in the diet of Astyanax lacustris for a period of 105 days. In-0 – diet without inclusion of PUFAs-ô3; In-3 – feed with inclusion of 3% PUFAs-ô3; In-6 – feed with inclusion of 6% of PUFAs-ô3; In-9 – feed with inclusion of 9% PUFAs-ô3. Different capital letters indicate statistical difference between treatments for SptzFast. Different lowercase letters indicate statistical difference between treatments for SptzMedium, SptzSlow percentage, VCL, VSL and VAP (Kruskal-Wallis, p<0.05).

FIGURE 1 in Effect of dietary omega-3 polyunsaturated fatty acids supplementation of Astyanax lacustris males on semen quality

FIGURE 1 | Results obtained for total (MOT, %) and progressive (PRG, %) sperm motility after feeding with the inclusion of PUFAs-ô3 in the diet of Astyanax lacustris for a period of 105 days. In-0 – diet without inclusion of PUFAs-ô3; In-3 – feed with inclusion of 3% PUFAs-ô3; In-6 – feed with inclusion of 6% of PUFAs-ô3; In-9 – feed with inclusion of 9% PUFAs-ô3. Different capital letters indicate statistical difference between treatments for MOT. Different lowercase letters indicate statistical difference between treatments for PRG (Kruskal-Wallis, p<0.05).

opencc-by-4.0Jul 2024View details →

Data Supplement for "Impact of Charged Surfaces on the Structure and Dynamics of Polymer Electrolytes: Insights from Atomistic Simulations"

Data set containing the molecular dynamics simulation data used for the journal article "Impact of Charged Surfaces on the Structure and Dynamics of Polymer Electrolytes: Insights from Atomistic Simulations" (Andreas Thum, Diddo Diddens, Andreas Heuer, J. Phys. Chem. C 2021, 125, 25392−25403, <a href="https://doi.org/10.1021/acs.jpcc.1c07751">https://doi.org/10.1021/acs.jpcc.1c07751</a>).

openmit-licenseAug 2024View details →

Estimating future climate change impacts on human mortality and crop yields via air pollution: supplemental files

Atmospheric chemistry model output and other gridded data sets necessary to estimate human mortality and crop yield losses associated with future climate change, as used in Murray et al. [PNAS, 2024] doi:10.1073/pnas.2400117121.

SeisSol model setup input files and supplement videos for the 3D dynamic rupture models of Wirp et al. 2024

Data required to run the dynamic rupture models presented in Wirp, S. A., Gabriel, A.-A., Ulrich, T., Lorito, S. (2024). The README.txt file contains detailed information about the data and data format.

Supplemental data for: Evaluation of SARS-CoV-2 response at the University of North Carolina (UNC) at Charlotte using percent positivity data and viral genomic sequence data.

Supplemental data for: Evaluation of SARS-CoV-2 response at the University of North Carolina (UNC) at Charlotte using percent positivity data and viral genomic sequence data. Submitted to Biocarla 2024 https://carla2024.org/portfolios/biocarla/ Authors: Daniel Janies 1,2,3 [0000−0002−7890−9906], Shirish Yasa 1,2,3 [0000−0003−3217−4921], Colby T. Ford 1,3,4 [0000−0002−7859−3622] Jannatul Ferdous 2,3 [0000−0003−3053−9616], William Taylor 2,3 [0009−0000−6204−1172], April Harris 2,3 [0009−0009−2557−7926], Sam Kunkleman 2,3 [0000−0002−2309−6418], Juan Bolanos 2,3, Kevin Lambirth 2,3 [0000-0002-6568-543X], Denis Jacob Machado 1,2,3 [0000−0001−9858−4515], Cynthia Gibas 1,2,3 [0000−0002−1288−9543], and Jessica Schlueter 1,2,3 [0000−0002−6490−0580] Affiliations: 1) Center for Computational Intelligence to Predict Health and Environmental Risks (CIPHER), University of North Carolina at Charlotte 28223, USA Correspondence to: djanies@charlotte.edu https://cipher.charlotte.edu 2) Department of Bioinformatics and Genomics, University of North Carolina at Charlotte 28223, USA https://cci.charlotte.edu/departments/ department-of-bioinformatics-and-genomics/ 3) College of Computing and Informatics, University of North Carolina at Charlotte 28223, USA https://cci.charlotte.edu 4) School of Data Science, University of North Carolina at Charlotte 28223, USA https://sds.charlotte.edu 5) Division of Research, University of North Carolina at Charlotte 28223, USA https://research.charlotte.edu/

Supplemental data for "Widespread and rapid dynamics of subglacial water in the Canadian Arctic"

<h2>What's inside</h2> This data set contains: <ol> <li>Inventory: The inventory of the active subglacial water bodies in the Canadian Arctic.</li> <li>Workflows: Data analysis code that produces the study results. </li> <li>Results: The derived ArcticDEM strip data and visualizations generated by this study.</li> </ol> See "README.md" for more information.

opencc-by-4.0Mar 2024View details →

Supplement: Genomic and phenotypic imprints of microbial domestication on cheese starter cultures

This data repository contains the latest version of the supplemental data, code and figures for the following manuscript: Vincent Somerville, Nadine Thierer, Remo S. Schmidt, Alexandra Roetschi, Laurianne Braillard, Monika Haueter, Hélène Berthoud, Noam Shani , Ueli von Ah, Florent Mazel & Philipp Engel 2024. “Genomic and phenotypic imprints of Neolithic domestication on Cheese Starter cultures”  All additional genomic data is stored under the following Bioprojects on NCBI: PRJNA717134 PRJNA1048529 PRJNA1083966 PRJNA1157897

Supplemental material for: Software System Testing assisted by Large Language Models: An Exploratory Study

This is the supplemental material of the paper titled as “Software System Testing Assisted by Large Language Models: An Exploratory Study” presented at the 36th International Conference on Testing Software and Systems. It contains the raw execution data generated by both models, GPT-4o and GPT-4omini, during the exploratory study. The supplementary material includes the following files: <ul> <li>GPT-4ominiRQ1-2ExecutionData.zip: contains the JSON outputs from the OpenAI API for the GPT-4o mini model. Each output is labeled according to the research question number and the corresponding timestamp (for RQ1) or the requested test case (for RQ2), all provided in plain text format.</li> <li>GPT-4oRQ1-2ExecutionData.zip: contains the JSON outputs from the OpenAI API for the GPT-4o model. Like the previous file, each output is named in plain text format based on the research question number and timestamp (for RQ1) or the requested test case (for RQ2).</li> </ul> To cite this work:  C. Augusto, J. Morán, A. Bertolino, C. de la Riva and J. Tuya, “Software System Testing assisted by Large Language Models: An Exploratory Study”, in Testing Software and Systems (pp. 239–255). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-80889-0_17

Supplementary data and code for "Predicting anthropogenic food supplementation from individual tracking data"

This repository contains data and R-Scripts to reproduce the results presented in the paper “Predicting anthropogenic food supplementation from individual tracking data” published in Ibis. Please note that some data (basemap of Switzerland, forests, buildings) are publicly available from <a href="https://map.geo.admin.ch/">https://map.geo.admin.ch/</a> and are therefore not provided here. The abstract of the article is as follows: Many wildlife species consume food or refuse provided by humans. To understand the effect of anthropogenic food subsidies on wildlife populations, we first need to quantify where and when individuals can access such food sources. The red kite Milvus milvus is an opportunistic raptor species and uses both inadvertent and deliberate food subsidies provided by citizens. Here we present a new approach using GPS-tracking data to predict where anthropogenic food subsidies likely occur. We tracked 497 individuals with solar-powered GPS transmitters over an average of 3.2 (range 1 – 9) breeding seasons in Switzerland, and combined these data with locations of 125 known feeding sites obtained through interviews. We used two sequential random forest models, at both individual movement and population levels, to predict where anthropogenic food subsidies were attended by red kites. The first model classified locations that were frequently and regularly revisited, and successfully predicted 85% of locations that were within 50 m of an externally validated feeding site. These predicted locations were aggregated in 500 m grid cells to calculate the proportion of individuals and locations associated with predicted food subsidy. A second model related the presence of known food subsidies to the aggregated predictions. In our study area, 80% of known anthropogenic food provision locations could be correctly identified using red kite tracking data, but data sparsity beyond the core range of tracked individuals limits predictions of anthropogenic food subsidies at larger geographic scales. Nonetheless, biologging data can identify ephemeral food sources, and facilitate an assessment of the importance of anthropogenic food subsidies on the fitness of individuals in tracked populations.