Find research datasets worth reusing

opencc-by-4.0Jul 2022View details →

Data from: Experimental Investigation of Efficiency and Deposit Process Temperature during Multi-Layer Friction Surfacing

This dataset contains the data for the publication "Experimental Investigation of Efficiency and Deposit Process Temperature during Multi-Layer Friction Surfacing"

opencc-by-4.0Nov 2023View details →

An Empirical Evaluation of Unsupervised Event Log Abstraction Techniques in Process Mining

This upload contains the event logs, generated by L-Sim, on which the experiments of the related paper were performed.The related paper is accepted in the journal Information Systems.

opencc-zeroDec 2021View details →

Diversity patterns and speciation processes in a two-island system with continuous migration

Geographic isolation is a central mechanism of speciation, but perfect isolation of populations is rare. Although speciation can be hindered if gene flow is large, intermediate levels of migration can enhance speciation by introducing genetic novelty in the semi-isolated populations or founding small communities of migrants. Here we consider a two-island neutral model of speciation with continuous migration and study diversity patterns as a function of the migration probability, population size, and number of genes involved in reproductive isolation (dubbed as genome size). For small genomes, low levels of migration induce speciation on the islands that otherwise would not occur. Diversity, however, drops sharply to a single species inhabiting both islands as the migration probability increases. For large genomes, sympatric speciation occurs even when the islands are strictly isolated. Then species richness per island increases with the probability of migration, but the total number of species decreases as they become cosmopolitan. For each genome size, there is an optimal migration intensity for each population size that maximizes the number of species. We discuss the observed modes of speciation induced by migration and how they increase species richness in the insular system while promoting asymmetry between the islands and hindering endemism.

opencc-by-4.0Aug 2022View details →

Processed KnockTF2 experiments of human cells

Processed perturbation experiments of human cells from <a href="http://www.licpathway.net/KnockTFv2/index.php">KnockTF2</a> to easily benchmark methods and networks using <a href="http://decoupler-py.readthedocs.io/">decoupleR</a>. The file <a href="http://www.licpathway.net/KnockTFv2_download/knocktf_v2_main_human.txt">Human Differential Expression of Genes</a> was processed to extract a matrix of logFCs were experiments are rows and genes are columns. Their associated meta-data was downloaded from the <a href="http://www.licpathway.net/KnockTFv2/browse_human.php#">Browse</a> tab. Identifiers were unified to match both matrix and meta-data. I do not claim ownership of these data. If used, please cite their original source: Chenchen Feng, Chao Song, Yuejuan Liu, Fengcui Qian, Yu Gao, Ziyu Ning, Qiuyu Wang, Yong Jiang, Yanyu Li, Meng Li, Jiaxin Chen, Jian Zhang, Chunquan Li, KnockTF: a comprehensive human gene expression profile database with knockdown/knockout of transcription factors, Nucleic Acids Research, Volume 48, Issue D1, 08 January 2020, Pages D93–D100, <a href="https://doi.org/10.1093/nar/gkz881">https://doi.org/10.1093/nar/gkz881</a>

Data and scripts for 'Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry'

This repository contains three zipped elements used in the study Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry (https://doi.org/10.5194/tc-2022-81): 1. The time-lapse DEMs (original and flow-corrected), orthomosaics (not flow-corrected) and cliff outlines (original and flow-corrected) of the 24K and Langtang survey areas used in this study. The spatial resolution is the same as used in the analysis. These zipped files also contain a .csv file (time_selection.csv) indicating for each index (indicated in the file name) the serial date number in days (date origin January 0, 0000). 2. The R and Python scripts (Scripts_final.zip) used to process the DEMs and orthomosaics from the time-lapse images as well as the script to calculate the slope-perpendicular melt. These scripts come with .csv and .txt files that serve as template for the required input data format.

Interception of virtual throws reveals predictive skills based on the visual processing of throwing kinematics - Dataset

Dataset consists of a list of Matlab structures, one for each of the 21 participants. For each participant all the recorded trials are reported ("trials" field). For each trial, the dataset reports information about the associated experimental condition and the kinematics of the ball and the racket trajectories.  Information about the experimental condition are specified in the "info" field, which provides the experimental phase (Training and Experimental), the visibility  (AllVisible, ThrowerOnly, BallOnly), the target (1, 2, 3, 4), and the thrower ID (1, 2, 3, 4). The kinematics data, starting from the time of ball release, are given in the field "trajectories", which provides the time vector (in seconds), and the corresponding 3D positions of the racket and the ball (in meters) in the reference frame shown in Figure 1 of the paper.

opencc-zeroSep 2022View details →

Incorporating evolutionary and threat processes into crop wild relatives conservation

Crop wild relatives (CWR) intra- and interspecific diversity is essential for crop breeding and food security. However, intraspecific genetic diversity, which is central given the idiosyncratic threats to species in landscapes, is usually not considered in planning frameworks. Here, we introduce an approach to develop proxies of genetic differentiation to identify conservation areas, applying systematic conservation planning tools that produce hierarchical prioritizations of the landscape. It accounts for: (i) evolutionary processes, including historical and environmental drivers of genetic diversity, and (ii) threat processes, considering taxa-specific tolerance to human-modified habitats, and their extinction risk status. Our results support the development of national strategies for the conservation and use of CWR in Mexico and inform public policy to mitigate threat processes to CWR. Although we focus on Mesoamerican CWR within Mexico, our methodology offers opportunities to effectively guide conservation and monitoring strategies to safeguard the evolutionary resilience of any taxa, including in regions of complex evolutionary histories and mosaic landscapes.

Experimental Datasets and Processing Codes for the Semantic PHD Filter

The water bottle detection dataset and measurement model dataset for the paper titled "The Semantic PHD Filter for Multi-class Target Tracking: From Theory to Practice" by Jun Chen, Zhanteng Xie and Philip Dames, and the paper titled "Experimental Datasets and Processing Codes for the Semantic PHD Filter" by Zhanteng Xie, Jun Chen and Philip Dames 1. Detection dataset:   Size:  Total: 4870 images Training: 4000 images Validation: 870 images Bottle Classes: Aquafina, Deer, Kirkland, Nestle Format: PASCAL VOC, Darknet Folder Structure:  - Annotations: containing the xml label files in PASCAL VOC format  - ImageSets: containing the training index files   - JPEGImages: containing the image data in jpg format  - Labels: containing the txt label files in Darknet format 2. Measurement model dataset: Format: ROSBAG Duration: 19:59s (1199s) Topics: /darknet_ros/detection_image 3543 msgs : sensor_msgs/Image /map 1 msg : nav_msgs/OccupancyGrid /sphd_measurements 3585 msgs : sphd_msgs/SPHDMeasurements /tf 142727 msgs : tf2_msgs/TFMessage /tf_static 1 msg : tf2_msgs/TFMessage Message Types: nav_msgs/OccupancyGrid sensor_msgs/Image sphd_msgs/SPHDMeasurements tf2_msgs/TFMessage   3. Processing codes: Detection processing: Zenodo: https://doi.org/10.5281/zenodo.7066045 GitHub: https://github.com/TempleRAIL/yolov3_bottle_detector Measurement model processing: Zenodo:  https://doi.org/10.5281/zenodo.7066050 GitHub: https://github.com/TempleRAIL/sphd_sensor_models

opencc-by-4.0Aug 2022View details →

Dataset for 'A deep learning-based quality control loop of the extrusion-based bioprinting process'

Zip file containing the dataset for the paper 'A deep learning-based quality control loop of the extrusion-based bioprinting process' (available at <a href="https://ijb.whioce.com/index.php/int-j-bioprinting/article/view/620">https://ijb.whioce.com/index.php/int-j-bioprinting/article/view/620</a>). The dataset is composed of: <ul> <li>A series of video folders, each having a unique ID, and containing the processed video frames.</li> <li>A master.csv file containing all the metadata for each video.</li> </ul> The authors acknowledge the supported by the European Union’s Horizon 2020 research and innovation program under the project GIOTTO: “Giotto: Active ageing and osteoporosis: The next challenge for smart nanobiomaterials and 3D technologies,” grant agreement no. 814410.

opencc-by-sa-4.0Sep 2022View details →

Collection of videos documenting the silk weaving process (Silk pilot, Mingei)

Documentation videos of the Weaving process from the Silk pilot of the Mingei project.

opencc-zeroSep 2022View details →

Neutral processes related to regional bee commonness and dispersal distances are important predictors of plant-pollinator networks along gradients of climate and landscape conditions

Understanding how niche-based and neutral processes contribute to the spatial variation in plant-pollinator interactions is central to designing effective pollination conservation schemes. Such schemes are needed to reverse declines of wild bees and other pollinating insects and to promote pollination services to wild and cultivated plants. We used data on wild bee interactions with plants belonging to the four tribes Loteae, Trifolieae, Anthemideae, and either spring- or summer-flowering Cichorieae, sampled systematically along a 682km latitudinal gradient to build models that allowed us to (a) predict occurrences of pairwise bee-flower interactions across 115 sampling locations, and (b) estimate the contribution of variables hypothesized to be related to niche-based assembly structuring processes (viz. annual mean temperature, landscape diversity, bee sociality, bee phenology, and flower preferences of bees) and neutral processes (viz. regional commonness and dispersal distance to conspecifics). While neutral processes were important predictors of plant-pollinator distributions, niche-based processes were reflected in the contrasting distributions of solitary bee and bumble bees along the temperature gradient, and in the influence of bee flower preferences on the distribution of bee species across plant types. In particular, bee flower preferences separated bees into three main groups, albeit with some overlap: visitors to spring-flowering Cichorieae; visitors to Anthemideae and summer-flowering Cichorieae; and visitors to Trifolieae and Loteae. Our findings suggest that both neutral and niche-based processes are significant contributors to the spatial distribution of plant-pollinator interactions so that conservation actions in our region should be directed towards areas: near high concentrations of known occurrences of regionally rare bees; in mild climatic conditions; and that are surrounded by heterogeneous landscapes. Given the observed niche-based differences, the proportion of functionally distinct plants in flower-mixes could be chosen to target bee species, or guilds, of conservation concern.

r-process abundances in neutron star merger dynamical ejecta given different fission yields

This data release contains nucleosynthesis predictions following Vassh et al. (2020) for the r-process abundances of binary neutron star merger ejecta based on the simulation trajectories of Radice et al. (2018), which were mapped to parametrized trajectories based on their neutron-richness (Ye), entropy (s), and expansion timescale (tau). The neutron star merger scenarios considered here cover a wide range of neutron star masses. Calculations were performed with the PRISM code (Mumpower et al. 2018) which accounts for nuclear reheating. Results are reported for two fission yield sets, the Finite Range Liquid Drop Model (FRLDM, Mumpower et al. 2020) and 50/50 symmetric splits. All calculations assumed FRDM12 (Möller et al. 2016) for the nuclear mass model and apply the SFHO equation of state when obtaining the initial composition from nuclear statistical equilibrium (NSE). When using these nucleosynthesis yields, please cite this Zenodo data release (Vassh 2022). Refer to Vassh et al. (2020) for further details on the nuclear physics inputs, to Mumpower et al. (2018) for further details on FRLDM, and to Radice et al. (2018) for further details on the merger ejecta trajectories.

opencc-by-4.0Dec 2021View details →

Ancillary data for the wrf_to_tell processing chain

This data supports the sequence of processing scripts that convert the meteorology from IM3's climate simulations using the Weather Research and Forecasting (WRF) model into input files ready for use in the Total ELectricity Load (TELL) model. More details about the processing chain and the associated scripts can be found in the IM3 components library: https://github.com/IMMM-SFA/im3components/tree/main/im3components/wrf_to_tell.

opencc-zeroOct 2022View details →

Estimation of reinforced urn processes under left-truncation and right-censoring

We propose a nonparametric estimator for bivariate left-truncated and right-censored (LTRC) observations that combines the Expectation-Maximization (EM) algorithm and the Reinforced Urn Process (RUP). The resulting Expectation-Reinforcement (ER) algorithm allows for the inclusion of experts' knowledge in the form of a prior distribution, thus belonging to the class of Bayesian models. This can be relevant in applications where the data is incomplete, due to biases in the sampling process, as in the case of left-truncation and right-censoring. With this new approach, the distribution of the truncation variables is also recovered, granting further insight into those biases, and playing an important role in applications like prevalent cohort studies. The estimators are tested numerically using artificial and empirical datasets and compared with other methodologies such as copula models and the Kaplan-Meier estimator.

opencc-by-4.0Jul 2022View details →

AVANGARD | In Situ Monitoring of Welding Quality of GMAW Process

In the framework of the AVANAGRD project, a series of collaborative sensors were used in a feasibility study to develop inline quality monitoring of welding processes, such as microphones, acoustic emission sensors, and thermal cameras, besides of course the arc parameters. In this video, some examples of thermal filming are shown, performed during extreme conditions of GMAW applied on T-joints. Besides the art that each frame already is, it’s possible to provide key information about process stability that will be translated into welding defects. Using a combination of those techniques with Artificial Intelligence, there is no limit on what we can reach related to productivity, quality, and zero-defect manufacturing. The AVANGARD project (Advanced Manufacturing Solution Tightly Aligned with Business Need) is funded by the European Union within the frame of the Horizon 2020 research and development program under Grant Agreement No. 869986. <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbnNoM1F3ZnBManZKUlVKT0h1WnhyMUVDY3BpUXxBQ3Jtc0ttR2FwOWVRbXY0am1NNGxWNk5JUndJdS05cnF2U2s2S1lJMEo5YzcycWdWdWRxMEdIM1hNVy1yelpYWW84M0V3anFsVGg0SDZTbFNZVHJIY2RiNnNZQ2pZY2huNE1Da2ZVY2NxZ3lkSVBvUVE0TkdkSQ&q=http%3A%2F%2Fwww.avangard-project.eu%2F&v=7HgNP1rdeHI">http://www.avangard-project.eu/</a>

Surgical case mixes and distributions of perioperative surgical process durations for German hospitals

The data set consists of parameters of distributions of perioperative surgical process durations in German hospitals subdivided by the level of care, the surgical specialty, patient type (in- or outpatient), and the procedure’s main OPS code. We consider the following processes: anesthesia induction time, anesthesia emergence time, surgical lead-in, incision-to-closure time, surgical lead-out, and closure-to-incision time (as described in the German Perioperative Procedural Time Glossary). In addition, we provide the number of cases (classified by the procedure’s main OPS code) treated in one year per level of care, surgical specialty, and patient type (in- or outpatient). The supplied data set is the result of processing the 2019 surgical process data set from the Operating Room benchmarking program of German-speaking countries provided by the company digmed GmbH. In total, we considered 2,035,126 recorded surgeries from 212 different hospitals. The data set was created and published to facilitate and promote research on Operating Room planning in the field of Operations Research. It can be used for generating specific problem instances or benchmark sets for Operating Room planning problems.

opencc-by-4.0Dec 2021View details →

Text-fig. 4. Lepidocarpon cone in the process of disaggregating as part of the dispersal strategy of the plants. When preserved isolated, the sporophylls are assigned to the fossil-genus Lepidostrobophyllum. Refigured from Thomas (1981). Grovesend Formation (upper Asrturian – lower Moscovian), Kilmersdon Tip, Radstock Coalfield, UK; Natural History Museum (London) specimen V.60431. in Naming Of Parts: The Use Of Fossil-Taxa In Palaeobotany

Text-fig. 4. Lepidocarpon cone in the process of disaggregating as part of the dispersal strategy of the plants. When preserved isolated, the sporophylls are assigned to the fossil-genus Lepidostrobophyllum. Refigured from Thomas (1981). Grovesend Formation (upper Asrturian – lower Moscovian), Kilmersdon Tip, Radstock Coalfield, UK; Natural History Museum (London) specimen V.60431.

Raw and processed cell lines (melanomaC818/melanomaMUM-2B/SK-MEL-28) data for detecting DMKN's mutations in melanoma cancer

Raw and processed cell lines (melanomaC818/melanomaMUM-2B/SK-MEL-28) data for detecting DMKN's mutations in melanoma cancer. This research was concluded that DMKN is a trigger of epithelial-mesenchymal transition-driven melanoma.

Pre-processed ex vivo MRI data for manuscript titled "Neuroanatomical and cognitive biomarkers of alpha-synuclein propagation in a mouse model of synucleinopathy prior to onset of motor symptoms""

Repository for ex vivo magnetic resonance imaging data from the project titled "Presymptomatic neuroanatomical and cognitive biomarkers of alpha-synuclein propagation in a mouse model of synucleinopathy" Contains the pre-processed ex vivo T1-weighted images (Bruker 7T; 70 micron isotropic voxel resolution) for M83 alpha-synuclein A53T hemizygous mice that received either a phosphate buffered saline (PBS) or alpha-synuclein pre-formed fibrils (PFF) injection in the right dorsal striatum. Full subject list can be viewed with the "subject_list.csv" file. More details are available in the manuscript.

Processed data for FOXA2 analysis in TCGA KIRP and KIRC patients

<pre># Data and code to test whether FOXA2 is changed in KIRP patients with low FH ## Code https://github.com/ArianeMora/foxa2_kirp_kirc ## Datasets RNA count data were downloaded from TCGA (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga) using scidat (https://github.com/ArianeMora/scidat) for patients with kidney cancers (rna_df.csv). ## Processing The kidney cancer patient count data were split into KIRC and KIRP, and only the tumour data was used for this analysis, see notebook FOXA2.ipynb in the code folder. Samples were split by their expression of FH in their tumour samples, with several annotations used to separate patients for completeness: 1. Low-High: Comparing the bottom 25% (< Q1) of patients by FH vs “high” FH (i.e. top 25%, > Q3): p.adj 0.00004 2. Low-Normal: Comparing the bottom 25% of patients by FH to the patients with “normal” range FH (between Q1 and Q3): p.adj 0.053 3. Outlier-High: Comparing outlier FH to “high” (i.e. top 25%): p.adj 0.067 4. Outlier-Normal: Comparing the outlier FH (Q1 – 1.5*IQR) to all “normal” FH patients: p.adj 0.169 We did the same for KIRC patients – we don’t see FOXA2 as expected 1. Comparing the bottom 25% of patients by FH vs the top 25% of patients with FH: 0.14 2. Comparing the bottom 25% of patients by FH to the patients with “normal” range FH: 0.25 3. Comparing the outlier FH to all “normal” FH patients: 0.31 4. Comparing outlier FH to “high” (i.e. top 25%): 0.32 Each of these groups were used to also perform DE analysis between the two groups, see respective RMD files in code for details. ### References If you use this work please cite TCGA: ``` Creighton, C. J., Morgan, M., Gunaratne, P. H., Wheeler, D. A., Gibbs, R. A., Gordon Robertson, A., Chu, A., Beroukhim, R., Cibulskis, K., Signoretti, S., Vandin Hsin-Ta Wu, F., Raphael, B. J., Verhaak, R. G. W., Tamboli, P., Torres-Garcia, W., Akbani, R., Weinstein, J. N., Reuter, V., Hsieh, J. J., … University of North Carolina at Chapel Hill. (2013). Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature, 499(7456), Article 7456. https://doi.org/10.1038/nature12222 ``` </pre>