Find research datasets worth reusing

opencc-by-4.0Jun 2022View details →

Figure 3 in The web amount and quality of web spiders (Agelenidae, Pholcidae), Agelena labyrinthica (Clerck, 1757) and Holocnemus pluchei (Scopoli, 1763), depending on food and temperature

Figure 3. Webs of A. labyrinthica, A) side view; B) top view; C) top view.

opencc-by-4.0Jun 2022View details →

Figure 1 in The web amount and quality of web spiders (Agelenidae, Pholcidae), Agelena labyrinthica (Clerck, 1757) and Holocnemus pluchei (Scopoli, 1763), depending on food and temperature

Figure 1. Cultivation of Drosophila melanogaster.

Figure 15 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model

Figure 15. Species accumulation curve for tintinnid ciliates diversity in the Arctic Ocean.

Figure 7 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model

Figure 7. Species accumulation curve for tintinnid ciliates diversity in the Mediterranean Sea.

Figure 19 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model

Figure 19. Species accumulation curve for tintinnid ciliates diversity in global ocean.

Figure 22 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model

Figure 22. The Whittaker index dependence on the distance (power function).

Figure 21 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model

Figure 21. The Whittaker index values in different water areas.

Figure 17 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model

Figure 17. Species accumulation curve for tintinnid ciliates diversity in the Southern Ocean.

grain.js dependencies data

Each file represents a version of <a href="https://github.com/meezwhite/p5.grain">grain.js</a>. For each file (=version), and for each of the dependencies (direct and indirect) of this version, the following data has been gathered (if possible) : { "version": "x.x.x", "name": "xxx", "dependencies": {...}, "commit_count": "x", "last_commit_date": "xxxx-xx-xx xx:xx:xx", "contributor_count": x, "contributors": [...], } Additionally, for all versions, the following data has been gathered : "release_date": "xxxx-xx-xx xx:xx:xx", "dependencies_count": x, "js_file_count": x, "json_file_count":  The last file (version-date.json) is a dictionary combining the name of a version with it's release date, which can be useful since the lexical order of the versions doesn't match the chronological order. This data gathering project is part of a university project (for an individual student) for the University of Montreal. More information <a href="https://www-ens.iro.umontreal.ca/ete/~allixlal/3150/VDL/TreeViz.html">here</a>.

p5.js dependencies data

Each file represents a version of <a href="https://github.com/processing/p5.js" target="_blank" rel="noopener">p5.js</a>. For each file (=version), and for each of the dependencies (direct and indirect) of this version, the following data has been gathered (if possible) : { "version": "x.x.x", "name": "xxx", "dependencies": {...}, "commit_count": "x", "last_commit_date": "xxxx-xx-xx xx:xx:xx", "contributor_count": x, "contributors": [...], } Additionally, for all versions, the following data has been gathered : "release_date": "xxxx-xx-xx xx:xx:xx", "dependencies_count": x, "js_file_count": x, "json_file_count":  The last file (version-date.json) is a dictionary combining the name of a version with it's release date, which can be useful since the lexical order of the versions doesn't match the chronological order. This data gathering project is part of a university project (for an individual student) for the University of Montreal. More information <a href="https://www-ens.iro.umontreal.ca/ete/~allixlal/3150/VDL/TreeViz.html">here</a>.

Tone.js dependencies data

Each file represents a version of <a href="https://github.com/Tonejs/Tone.js">Tone.js</a>. For each file (=version), and for each of the dependencies (direct and indirect) of this version, the following data has been gathered (if possible) : { "version": "x.x.x", "name": "xxx", "dependencies": {...}, "commit_count": "x", "last_commit_date": "xxxx-xx-xx xx:xx:xx", "contributor_count": x, "contributors": [...], } Additionally, for all versions, the following data has been gathered : "release_date": "xxxx-xx-xx xx:xx:xx", "dependencies_count": x, "js_file_count": x, "json_file_count":  The last file (version-date.json) is a dictionary combining the name of a version with it's release date, which can be useful since the lexical order of the versions doesn't match the chronological order. This data gathering project is part of a university project (for an individual student) for the University of Montreal. More information <a href="https://www-ens.iro.umontreal.ca/ete/~allixlal/3150/VDL/TreeViz.html">here</a>.

opencc-by-4.0Jul 2024View details →

Energy-dependence of the response of X-ray multimeter for mammography- radiation qualities

Supplementary data to the manuscript “Energy-dependence of the response of X-ray multimeter for mammography- radiation qualities” by Elisabeth Salomon and Paula Toroi

Understanding How Feature Dependent Variables Affect Configurable System Comprehensibility

Background: #ifdefs allow developers to define source code related to features that should or should not be compiled. A feature dependency occurs in a configurable system when source code snippets of different features share code elements, such as variables. Variables that produce feature dependency are called dependent variables. The dependency between two features may include just one dependent variable or more than one. It is reasonable to suspect that a high number of dependent variables and their use make the analysis of variability scenarios more complex. In fact, previous studies show that #ifdefs may affect comprehensibility, especially when their use implies feature dependency. Aims: In this sense, our goal is to understand how feature dependent variables affect the comprehensibility of configurable system source code. We conducted two complementary empirical studies. In Study 1, we evaluate if the comprehensibility of configurable system source code varies according to the number of dependent variables. Testing this hypothesis is important so that we can recommend practitioners and researchers the extent to which writing #ifdef code with dependencies is harmful. In study 2, we carried out an experiment in which developers analyzed programs with different degrees of variability. Our results show that the degree of variability did not affect the comprehensibility of programs with feature dependent variables. Method: We executed a controlled experiment with 12 participants who analyzed programs trying to specify their output. We quantified comprehensibility using metrics based on time and attempts to answer tasks correctly, participants’ visual effort, and participants' heart rate. Results: Our results indicate that the higher the number of dependent variables the more difficult it was to understand programs with feature dependency. Conclusions: In practice, our results indicate that comprehensibility is more negatively affected in programs with higher number of dependent variables and when these variables are defined at a point far from the points where they are used.

opencc-by-4.0Sep 2024View details →

Data Analysis for Context- and sex-dependent links between sire sexual success and offspring pathogen resistance

Data Analysis for "Context- and sex-dependent links between sire sexual success and offspring pathogen resistance" By Aijuan Liao and Tadeusz J. Kawecki

opencc-by-4.0Jul 2024View details →

MetTLM 20NRM01 TU/e Dataset: Dependence of Temporal Frequency and Chromaticity on the Visibility of the Phantom Array Effect

The dataset has the following format: 20 (Participants) by 18 (= 3 Chromaticities × 6 Temporal Frequencies) Chromaticities:              Red (R); Green (G); Warm White (W) Temporal Frequencies: F1 = 80 Hz; F2 = 300 Hz; F3 = 600 Hz; F4 = 900 Hz; F5 = 1200 Hz; F6 = 1800 Hz. <table> <tbody> <tr> <td> </td> <td>  R F1 </td> <td> R F2 </td> <td> R F3 </td> <td> R F4 </td> <td> R F5 </td> <td> R F6 </td> <td> G F1 </td> <td> G F2 </td> <td> G F3 </td> <td> G F4 </td> <td> G F5 </td> <td> G F6 </td> <td> W F1 </td> <td> W F2 </td> <td> W F3 </td> <td> W F4 </td> <td> W F5 </td> <td> W F6 </td> </tr> <tr> <td>P01</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>P02</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>P03</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>P04</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>...</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>P19</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>P20</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> </tbody> </table> Due to the fractional factorial 3 (colour) × 6 (temporal frequency) mixed design, there are some empty cells. The details are described in Table 2 of the publication. The values in the table represent the visibility thresholds in Modulation Depth (MD). For example, the values of 0.05, 0.1, and 1 means a MD of 5%, 10% and 100% respectively.

Accompanying data for the paper "Experimental characterization of material strain-rate dependence based on full-field Data-Driven Identification"

Experimental Data accompanying the paper "Experimental characterization of material strain-rate dependence based on full-field Data-Driven Identification" <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.ijimpeng.2024.105083" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ijimpeng.2024.105083</a> One (holed and double notched) specimen is dynamically loaded via an hydraulic tensile test machine (MTS-819, 20 kN) at 5 m/s. The specimen were cut from a 0.8 mm-thick DC04 (XES French standards) sheet in the rolling direction provided by ONERA. Reference image is captured using a high definition camera (29 Mpix, Prosilica GT from Stemmer) combined with the same objective lens than the one used for experiments. Deformed sample images are captured using the rotating mirror Ultra-high speed (HR-UHS) Cordin camera Model 580 at 68 kfps with a resolution of 3296 x 2472 pixels. The field of view is 35.8mm x 47.9mm leading to a pixel size of 14.49um. Ufreckles <a href="https://doi.org/10.5281/zenodo.1433776">10.5281/zenodo.1433775</a> is used to perform FE-based DIC using T3P1 linear triangular elements and a Tikhonov regularisation (over 3 elements). Eventually, kinematic data and load measurement  are used to identify stress fields via Data-Driven stress Identification (DDI) method. Are provided: <ul> <li>raw images, camera distortion modes and parameters, load net force and timeline</li> <li>kinematic fields obtained from Digital Image Correlation</li> <li>Stress fields identified using Data-Driven stress Identification</li> </ul> Matlab Codes to produce results (working with Ufreckles) <ul> <li>MultiSensor_DIC_script.m: in /Codes/ is the main script to run DIC</li> <li>Shape functions: in /Codes/shape_functions/ containing Zernike polynomial shape functions and deconvolution algorithm to get effective displacement from total displacement knowing camera distortions</li> </ul>

Microservice Semantic Dependency

This dataset is associated with a publication on component-based semantic dependency detection methodology in microservices-based systems. It includes a prototype implementation and the generated semantic clones data derived from the TrainTicket v0.1.0 benchmark.

Characterization of bakuchiol-β-cyclodextrin inclusion complexes and their pH-dependent formation

Open the record for dataset details and reuse information.

Data related to "Lysosomal damage triggers a p38 MAPK-dependent phosphorylation cascade to promote lysophagy via the small heat shock protein HSP27."

Data used to generate figures, as well as all uncropped blots. Article abstract: "Maintenance of lysosomal integrity is essential for cell viability. Upon injury, lysosomes may be targeted for degradation via a selective form of autophagy known as lysophagy. The engulfment of a damaged lysosome by an autophagosome is mediated by the recruitment of adaptor proteins, including SQSTM1/p62. p62 promotes lysophagy via the formation of phase separated condensates in a mechanism that is regulated by the heat shock protein HSP27. Here, we demonstrate a direct interaction between HSP27 and p62. We used structural modeling to predict the binding interface between HSP27 and p62 and identify several disease-associated mutations that map to this interface. We used proteomics to identify post-translational modifications of HSP27 that regulate HSP27 recruitment to stressed lysosomes, finding robust phosphorylation at several serine residues. Next, we characterized the upstream signaling mechanism leading to HSP27 phosphorylation, and found that p38 MAPK and its effector kinase MK2 are activated upon lysosomal damage by the kinase mTOR and the production of intracellular reactive oxygen species (ROS). Increased ROS activates p38 MAPK, which in turn allows MK2-dependent phosphorylation of HSP27.  Depletion of HSP27 or the inhibition of HSP27 phosphorylation alters the dynamics of p62 condensates on stressed lysosomes, significantly inhibiting p62-dependent lysophagy. Thus, we define a novel lysosomal quality control mechanism in which lysosomal injury triggers a p38 MAPK/MK2 signaling cascade promoting p62-dependent lysophagy. Further, this signaling cascade is activated by many cellular stressors, including oxidative and heat stress, suggesting that other forms of selective autophagy may be regulated by p38 MAPK/MK2/HSP27."