Find research datasets worth reusing

opencc-by-4.0Jul 2021View details →

Bridge Cracks Monitoring: Detection, Measurement, and Comparison using Augmented Reality

Crack occurrence and propagation are among critical factors that affect the performance and lifespan of civil infrastructures such as bridges. Consequently, numerous crack detection and measurement methods have been proposed and developed in the recent decades in the areas of Structural Health Monitoring and non-destructive testing. Many novel technologies have emerged with the potential to overcome the limitations of the presented techniques of crack detection and characterization. Crack detection and characterization method used in this research lies in supplementing human visual inspection capabilities in a systematic manner through an appropriate level of automation. The Augmented Reality (AR) tool developed in this project allows a user to perform tasks in a real-world environment while visually receiving supplementary 3D computer-generated information to support the tasks. More specifically, we developed a crack detection/characterization tool in this research and deployed it in Microsoft HoloLens smart glasses. This AR tool provides the user with automatic data collection capability through AR headset camera and is a means of hands-free data sharing for inspectors while conducting their normal inspection. We conducted several laboratory and field experiments by which we evaluated the effectiveness of the developed crack detection and measurement system. The result confirm that the AR tool devised in this project has the potential to help the inspection process in terms of time, comfort and accuracy.

opencc-zeroApr 2022View details →

Data recorded for leaf size, and leaf vein and areole measurements taken from nine Magnoliaceae species

Across species, the density of major veins in leaves scales inversely with leaf area. Yet, minor vein density manifests no clear relationship with respect to leaf are, despite having the potential to provide important insights into the trade-off between investments in leaf mechanical support, hydraulics, and light interception. To examine this phenomenon, between 120−380 mature leaves from each of nine Magnoliaceae species were sampled from Nanjing Forestry University campus and Nanjing Botanical Garden, Chinese Academy of Sciences, Nanjing, China in 2019 and 2020. The leaves were boiled, and the epidermal and mesophyll tissues were removed. The remaining leaf skeleton was stained to obtain a clear leaf venation network. The software LEAF GUI was used to obtain the data of leaf size, leaf vein and areole traits. The large sample size data render it possible to explore the scaling relationships between leaf size and each trait of leaf veins and areoles. This data set includes the information of leaf length, leaf width, leaf area, total vein length, total vein area, mean areole area per leaf, and the number of the areole sizes per leaf of the nine Magnoliaceae species.

opencc-by-4.0Apr 2022View details →

Toll Dilemma Game Data: Measuring the Cooperation of the People with the Government in Iran in the Form of Seven designed Scenarios

The toll dilemma game was designed in the form of a robot and distributed in the Telegram messenger. More than 1,200 people participated in this game, who acted as testee in the game. Each actor entered one of seven pre-designed scenarios, and how he or she worked with the government was evaluated in a simulated environment. The current data are entered in SPSS software.

opencc-by-4.0Apr 2022View details →

A high pressure, high temperature gas medium apparatus to measure acoustic velocities during deformation of rock: supporting information

Processed mechanical data and raw transmitted waveforms.

opencc-zeroApr 2022View details →

Fisheries bycatch mitigation measures as an efficient tool for the conservation of seabird populations

The impact of industrial fisheries on marine biodiversity is conspicuous in large pelagic vertebrate fisheries bycatch. In seabirds, this led to the decline of many populations since the 1980s following the rise of global fishing efforts. Bycatch mitigation measures were implemented in the 2000s, but their effects on the concerned seabird populations remain poorly quantified and understood. We studied the effects of bycatch mitigation measures on the demography of the white-chinned petrel, one of the most bycatch impacted seabirds whose populations suffered dramatic declines before the implementation of mitigation measures. To do so we 1) built multi-event capture-recapture models to estimate the demographic parameters of a population from Possession Island (southern Indian Ocean) over thirty years, 2) assessed the effect of climate and fishery covariates on demographic parameters, 3) built a population matrix model to estimate stochastic growth rate according to the management in fisheries bycatch, and 4) estimated changes in breeding population density using distance sampling data. The population declined from the 1980s to the mid-2000s, while trawl and longline fisheries occurred with no bycatch mitigation measures. The negative effects of fishery bycatch through additive mortality and of rat predation on breeding success were likely the main drivers of this decline. Both modeled population growth rate and observed breeding densities showed an increase since the mid-2000s. We explained this trend by the improvement in survival probability following implementation of fishery bycatch mitigation measures and in breeding success probability with the local control of the rat population and changes in sea ice conditions on foraging grounds. Synthesis and applications: We provide a holistic approach to assess the effects of management measures by analysing datasets from sampling methods commonly employed in seabirds studies. Our conclusions should encourage the eradication of invasive predatory species in seabirds breeding areas and the strengthening of bycatch mitigation measures for the vulnerable seabird species, especially in international waters, but also the development of such measures considering the other marine large pelagic species threatened by fisheries bycatch (sharks, rays, turtles and marine mammals) since it could be crucial to avoid populations' extinction.

opencc-zeroApr 2022View details →

Measuring plant biomass remotely using drones in arid landscapes

Measurement of variation in plant biomass is essential for answering many ecological and evolutionary questions. Quantitative estimates require plant destruction for laboratory analyses, while field studies use allometric approaches based on simple measurement of plant dimensions. We estimated the biomass of individual shrub-sized plants, using a low cost Unmanned Aerial System (drone), enabling rapid data collection and non-destructive sampling. We compared volume measurement (a surrogate for biomass) and sampling time, from the simple dimension measurements and drone, to accurate laboratory-derived biomass weights. We focused on three Australian plant species which are ecologically important to their floodplain and terrestrial ecosystems: porcupine grass Triodia scariosa, Queensland bluebush Chenopodium auricomum and lignum Duma florulenta. Estimated volume from the drone was more accurate than simple dimension measurements for porcupine grass and Queensland bluebush, compared to estimates from laboratory analyses but, not for lignum. The latter had a sparse canopy, with thin branches, few vestigial leaves and a similar colour to the ground. Data collection and analysis consistently required more time for the drone method than the simple dimension measurements, but this would improve with automation.

opencc-by-4.0Feb 2022View details →

Identification of Performance Changes at Code Level (Measurement Configuration Dataset)

Measurement Configuration Dataset This is the anonymous reviewing version; the source code repository will be added after the review. This dataset provides reproduction data for performance measurement configuration at source code level in Java. The measurement data can be obtained using the precision-experiments repository https://anonymous.4open.science/r/precision-experiments-C613/ (Examining Different Repetition Counts) yourself. These data conatained here are the data we obtained from execution on i7-4770 CPU @ 3.40GHz. The analysis was tested on Ubuntu 20.04 and gnuplot 5.2.8. It will not work with older gnuplot versions. To execute the analysis, extract the data by <pre><code class="language-bash">tar -xvf basic-parameter-comparison.tar tar -xvf parallel-sequential-comparison.tar</code></pre> and afterwards build the precision-experiments repo and execute the analysis by <pre><code class="language-bash">cd precision-experiments/precision-analysis/ ../gradlew fatJar cd scripts/configuration-analysis/ ./executeCompleteAnalysis.sh ../../../../basic-parameter-comparison ../../../../parallel-sequential-comparison</code></pre> Afterwards, the following files will be present: <ul> <li>precision-experiments/precision-analysis/scripts/configuration-analysis/repetitionHeatmaps/heatmap_all_en.pdf (Heatmaps for different repetition counts)</li> <li>precision-experiments/precision-analysis/scripts/configuration-analysis/repetitionHeatmaps/heatmap_outlierRemoval_en.pdf (Heatmap with and without outlier removal for 1000 repetitions)</li> <li>precision-experiments/precision-analysis/scripts/configuration-analysis/histogram_outliers_en.pdf (Histogram of the outliers)</li> <li>precision-experiments/precision-analysis/scripts/configuration-analysis/heatmap_parallel_en.pdf (Heatmap with sequential and parallel execution)</li> </ul>

opencc-zeroMay 2022View details →

COVID-19 lockdown measures impacted citizen science hedgehog observation numbers in Bavaria, Germany

The COVID-19 pandemic has led to temporary changes in human-animal interactions due to changes in human activities. Here we report on a surge in hedgehog observations during the first COVID-19 lockdown in Germany in 2020, on the citizen science web portal 'Igel in Bayern' (Hedgehogs in Bavaria) in Germany. This increase in comparison to previous years could be attributed to an increase in the number of people reporting hedgehog observations, rather than an increase in the number of hedgehog observations done by each observer. Additionally, in contrast to other studies on the effects of a COVID-19 lockdown on observations recorded by Citizen Science projects, the share of observations made in more urbanized areas during the lockdown time was not higher than the change observed in less urbanized areas. This is possibly a result of the differences in COVID-19 measures between Germany and other countries where preceding studies were carried out, in particular the lack of measures limiting outdoor activities for citizens.

Time is money: Considerations for measuring the radiological reading time

reporting/ RIS-Timestamps and real-time assessment.

Polarization Mode Dispersion Measurements on 76Km of wrapped Aerial Optical Fibre

This dataset consists of Polarisation Mode Dispersion measurements taken on 76Km of aerial fibre. The fibre is wrapped on a high voltage line.  The results with the Nexus teser where taken in April 2009 and the second set of measurements were taken using a more accurate Adaptif PMD tester in August 2009.  Hopefully this data will be useful to others.

Dataset of paper "Critical assessment of optical sensor parameters for the measurement of ultraviolet LED lamps"

Dataset of paper "Critical assessment of optical sensor parameters for the measurement of ultraviolet LED lamps" <ul> <li>Sensor specifications</li> <li>Peak wavelength of light sources studied. </li> <li>Relative spectral intensity of each light source.</li> <li>Angle of Acceptance of sensors.</li> <li>Summary of angular response of detectors.</li> <li>Change of acceptance angle of detectors with wavelength.</li> <li>Raw reference counts as measured by a saturated and unsaturated sensor.</li> <li>Change in measured intensity with integration time.</li> <li>Effect of temperature on intensity measured by the sensor.  </li> <li>Comparison between sensor measurements.</li> </ul>

Data for 'Using 40 years of spot measurements to assess stream temperature response and recovery for different harvesting systems in northern hardwood forests' by Jason Leach, Danielle Hudson and R. Dan Moore. Submitted to Hydrological Processes.

This dataset contains spot stream temperature measurements taken at 5 headwater streams draining forested hillslopes (C31, C32, C33, C34, C35) in the Turkey Lakes Watershed, approximately 65 km northwest of Sault Ste. Marie, Ontario, Canada.

Project files provided as supporting information to the manuscript "Information-theoretical measures identify accurate low-resolution representations of protein configurational space"

The dataset contains the following compressed folder: -Notebooks.zip: This folder contains:   -python_script:         -RESREL.py: script performing the clusterization and computing the relevance resolution curves         -random_curves.py: script generating the random value and computing the corresponding RES-REV curves_s         -Cluster_distance_matrix.py: script returning the distance among clusters for a given partition.   -python_notebook:         -Exploratory_analysis.ipynb:  Analysis performed on the 12-protein_dataset         -DMAPS_ANTI.ipynb: Diffusion Map for the Antibody         -DMAPS_COV_1ake.ipynb: Diffusion Map + Inter-Intra state decomposition of covariance for 1ake Packages required for the usage of these python scripts/notebooks:   -numpy   -pandas   -matplotlib   -seaborn   -multiprocessing   -scipy   ======== RAW DATA ======== The raw data produced and employed in this study are available on a Google Drive folder at the following address: https://drive.google.com/drive/folders/1PasAUCgpR5-gdzUVEdyusgZIayQN0Le9 In this folder, together with the compressed Notebooks.zip folder, one can fin the compressed folder Data.zip, within which the following data are present: -12-protein_dataset:     -md.mdp: the .mdp file used in the MD simulations     -PROTEIN_PDB_CODE:         -Hk_{sel}.npy & Hs_{sel}.npy: the Rel & Res curves, sel=[all, CA, CB]         -RMSD_{sel}.npy: the RMSD matrix, sel=[all, CA, CB]         -npt.gro:protein+water+ions structure @TEO the equilibration (NVT+NPT)         -MSR_df.csv: a dataset containing the following columns                   'area' : area behind the Relevance-Resolution curve;                   'selection': the atomic selection (['all', 'CA', 'CB']) used to compute the RMSD matrix used for the clusterization (and consequently the Relevance-Resolution curves)                   'method': the linkage measure used in the clustering procedure, an integer in [0,6];                   'method_name': the linkage measure used in the clustering procedure, a string in ['average','ward','complete','single','centroid','median','weighted'];                   'rmsd_mean': the mean value of the rmsd vector along the trajectory computed wrt the first frame;                   'rmsd_var': the variance of the rmsd vector along the trajectory computed wrt the first frame;                   'rgy_mean': the mean value of the radius of gyration  along the trajectory;                   'rgy_var': the variance of the radius of gyration  along the trajectory;                   'rmsf_mean': the mean value of the rmsf;                   'rmsf_var': the variance of the rmsf;                   'RMSD_M_mean': the mean value of the RMSD matrix.                   'RMSD_M_var': the variance of the RMSD matrix.   -Random:     -curves.npy= 100K Relevance-Resolution Random curves for M=40001     -curves_s.npy= 100K Relevance-Resolution Random curves for M=15000   -validation_dataset:     -antibody:         -Hk_CB.npy & Hs_CB.npy: the Rel & Res curves         -RMSD_CB.npy: the RMSD matrix         -DIFF_{M}.npy: the eigenvalue/vector of the 10-D diffusion space         -Label_{method}.npy: the label vector for n_clusters     -1ake:         -Hk_{sel}.npy & Hs_{sel}.npy: the Rel & Res curves         -RMSD_{sel}.npy: the RMSD matrix         -DIFF_{M}.npy: the eigenvalue/vector of the 10-D diffusion space         -Label_{method}.npy: the label vector for n_clusters         -intra_{m}.npy: the intra-cluster covariance matrix         -inter_cov_{m}.npy: the inter-cluster correlation matrix   NOTE ===== The matrices of the cluster distances for adenylate kinase and antibody have been computed through the script Cluster_distance_matrix.py. These matrices have not been included in the dataset because of their large size; the raw data are however available upon request.

PKR-CAL detector, PbWO4 crystals characterization measurements

This dataset contains the data from the different characterization measurements of the PbWO4 crystals for the POKER PKR-CAL detector. Specifically, ten PbWO4 crystals from CRYTUR company were characterized, to assess their properties and determine the technical requirements for the samples to be used in the final detector. The size of the crystals is 20x20x250 mm3. <ul> <li>The file "LongitudinalTransmission.tar" reports the longitudinal transparency measurements performed at the CERN Crystals Laboratory, with a custom spectrophotometer. The spectrophotometer light beam is not polarized, and the crystal  optical axis is aligned perpendicularly to the small crystal face where the beam is impinging on. The file format is "%f %f", where the fist column reports the wavelength (in nm) and the second the optical transparency (in %). The name of each file reports the unique identifier of the crystal it refers to.</li> <li>The file "TransverseTransmission.tar" contains the transverse transparency measurements performed at the Giessen University, using a Hitachi spectrophotometer. The spectrophotometer light beam is not polarized. The light beam has a transverse size (diameter) of about 0.5 cm. For each crystal, the transparency was measured at different positions along the crystal axis. The crystal was aligned so that the Z direction was perpendicular to the growing axis. Each file name is in the format "ID_POS_beforeIrradiation.dat", where "ID" is the unique crystal identifier provided by the manufacture, "POS" is the position along the axis where the measurement was taken (in units of 100 um). The file format is "%f %f", where the fist column reports the wavelenght (in nm) and the second the optical transparency (in %).</li> <li>The file "LightYield.tar" contains the light yield measurements performed at the CERN crystals laboratory, using the "B3" facility. This is based on a setup where an XP2020 PMT is optically coupled to a crystal, and a 60Co source is used to excite the crystal and measure the corresponding light emission. Signals from the XP2020 PMT where acquired and processed with a digital oscilloscope (Lecroy WaveRunner). In the folder, the files "outID.txt", with "ID" being the measured crystal, contain the integrated spectrum from the measurement. The ROOT macro "ana_crs.cpp" can be used to processe these files. The two data-files "single1.txt" and "single2.txt" contains the measurements performed without the radioactive source, in order to normalize the spectra to single-phe units.</li> </ul> This dataset was scrutinized as part of the PKR-CAL crystals R&D, and the obtained results are reported in the PKR-CAL TDR document.

opencc-by-4.0Dec 2021View details →

Spin wave stiffness and damping in a frustrated chiral helimagnet Co8Zn8Mn4 as measured by small-angle neutron scattering

The repository contains the data presented in the figures in the manuscript entitled  "Spin wave stiffness and damping in a frustrated chiral helimagnet Co8Zn8Mn4 as measured by small-angle neutron scattering". Requests for further information can be directed to the corresponding authors Victor Ukleev (victor.ukleev 'at' psi.ch).

Zonal and meridional wind measured by meteor radar at Darwin

Meteor wind radar is operating at Darwin, Australia (12.3° S, 130.8° E) since January 2005. This data set represents hourly zonal and  meridional wind from 2005 to 2008.

Zonal and meridional wind measured by meteor radar at Cariri

Meteor wind radar is operating at São João do Cariri, Brazil (7.4∘ S, 36.5∘ W) since January 2005. This data set represents hourly zonal and  meridional wind from 2005 to 2008.

opencc-zeroMay 2022View details →

Measurement of male and female morphologies in Mercurialis annua

We provide a dataset documenting the changes in male and female morphological traits after evolution at low- and high-density during three generations in the dioecious plant species Mercurialis annua. Our dataset corresponds to results from an experimental evolution protocol in which we have measured male and female traits after the evolution of ten experimental independent populations at the two contrasting densities. Seeds were initially collected in various populations of the species range and grown for three generations in a common garden, which aim was to build a seed bank with large genetic variance for experimental evolution. The seeds resulting from this initial generation (G0) have than been grown to build ten experimental populations (POP in the dataset) that were affected either to low or high density (TREAT in the dataset). Each population was grown separately from the other populations and its assigned density was applied during the last four weeks of growth. After three generations of evolution at their assigned density, seeds resulting from the third generation of evolution were grown in a common garden with two spatial blocks (BLOCK in the dataset) in which we recorded the spatial position of each plants (x and y in the dataset) measured vegetative and reproductive traits in male and female plants.

opencc-zeroMay 2022View details →

Application of inverse theory for high spatial resolution reconstructions of thermospheric vector wind fields from Doppler shifts measured by a ground-based network of all-sky Fabry-Perot interferometers

Several types of all-sky viewing Fabry-Perot Interferometers (FPI) have been developed since the 1990s for ground-based remote sensing of thermospheric winds. The Scanning Doppler Imager (SDI) is one such instrument, which provides temporally simultaneous line-of-sight observations from hundreds of independent look directions per instrument exposure. A geographically distributed network of such instruments increases spatial coverage and, at many locations, also provides overlapping observations along multiple independent lines-of-sight. Together, these characteristics significantly increase the density and fidelity that is possible for reconstructed thermospheric vector wind fields, compared to a traditional narrow-field FPI, but at the cost of complexity and difficulty. Presently, we describe an application of inverse theory to reconstruct three-component vector thermospheric neutral wind fields using data from multiple SDI instruments. The salient features of the method used here are the ability to reconstruct three-component winds on a dense grid that is sampled regularly in latitude, longitude, and time, without assuming any a-priori underlying structure of the winds. This requires solving an inverse problem that does not in general yield a unique solution unless additional constraints are enforced. We describe this step, also known also as regularization, along with the strategy used to maximize the spatial resolution of the derived wind fields by automatically determining the minimum level of regularization that can produce stable inversions. We present example results obtained from applying this technique to one night of data from a network of SDIs in Alaska, and discuss the implications of these results for current understanding of thermospheric dynamics.

Synthesis of soft skills results in before-after measures

Synthesis of soft skills results in before-after measures