Find research datasets worth reusing

opencc-by-4.0Jan 2021View details →

Fixed-Wing Micro UAV Open Data With Digicam And Raw INS/GNSS - IGN Flight 8

The data set originate from a series of flights conducted with fixed-wing micro UAV carrying high-quality small camera and navigation sensors. This data was previously used in several peer-reviewed publications and will also be used in ISPRS workshop on dynamic networks given during the 2021 ISPRS Congress. This is part of a larger series of data that will be released gradually after incorporating user's feedback (e.g., on formats, description,etc.). The data set contains the sensor measurements from GPS, IMU and Camera.

opencc-by-4.0Feb 2024View details →

Data for: First experimental time-of-flight-based proton radiography using low gain avalanche diodes

Data for: First experimental time-of-flight-based proton radiography using low gain avalanche diodes The associated publication can be found on https://iopscience.iop.org/article/10.1088/1361-6560/ad3326. All graphs inside the publication can be recreated with this dataset. Similar to the publication, the data for the timewalk and offset correction are only given for one sensor and one channel as they only serve a representative purpose. The raw data for all other channels can be shared upon request. Furthermore, as in the publication, the data for the water-equivalent-thickness (WET) calibration and proton radiography (pRAD) creation are given by the median and the interquartile range of the measured quantities of the individual graphs. Those data are also calibrated. If required, the raw, unprocessed data of each measurement can be shared upon request. In the following, a description of the individual files and corresponding figures in the publication is given. If not specified otherwise, the physical units are given in brackets next to the name of the corresponding physical quantity (usually first line in file): <ul> <li>Figure 6: <ul> <li> RawToTspectrumrescaledLGAD3.txt: <ul> <li>Describes the re-scaled time-over-threshold (ToT) spectrum measured inside the third LGAD of the time-of-flight-based ion computed tomography (TOF-iCT) demonstrator using 800 MeV protons (Figure 6a). The first column gives the channel number on the LGAD (channelnr[#]), the second column, the ToT value measured in this channel (ToT[ps]) and the third channel, the corresponding occurrence  (counts[#]).</li> </ul> </li> <li>ToTspectrumrescaledLocMaxLGAD3.txt <ul> <li>Describes the re-scaled ToT spectrum measured inside the third LGAD of the TOF-iCT demonstrator using only the local ToT maxima inside each 4D-cluster. The spectrum was obtained using 800 MeV protons (Figure 6b). The first column gives the channel number on the LGAD (channelnr[#]), the second column, the ToT value measured in this channel (ToT[ps]) and the third channel, the corresponding occurrence  (counts[#]).</li> </ul> </li> </ul> </li> <li>Figure 7: <ul> <li>offsetpraecalib.txt: <ul> <li>Describes the raw, uncalibrated time difference spectrum in LGAD3 measured between all channels on LGAD3 and a central reference channel on LGAD4 (figure 7a). The first column represents the detector channel nr in LGAD3, the second column the raw, uncalibrated time difference between LGAD3 and LGAD4 (TDiff[ns]) and the third column the number of corresponding counts (counts[#]).</li> </ul> </li> <li>offsetpraecalib.txt: <ul> <li>Describes the time walk and offset-calibrated time difference spectrum in LGAD3 measured between all channels on LGAD3 and a central reference channel on LGAD4 (figure 7b). The first column represents the detector channel nr in LGAD3, the second column the calibrated time difference between LGAD3 and LGAD4 (TDiff[ns]) and the third column the number of corresponding counts (counts[#]).</li> </ul> </li> <li> praetwdata.txt: <ul> <li>Describes the ToT dependence of the measured time difference between LGAD1 and LGAD2 using the raw ToT of channel 31 in LGAD1 (figure 7c). The first column represents the raw, unscaled and uncalibrated ToT in LGAD 1 (ToT[ns]), the second column the measured time difference (TDiff[ns]) and the last column, the number of corresponding counts (counts[#]). A ToT cut on the reference channel on LGAD2 has been applied in advance to guarantee a correlation between only true particle hits in the second sensor.</li> </ul> </li> <li>posttwdata.txt <ul> <li>Describes the time walk-calibrated ToT vs TDiff spectrum using the measured time difference between LGAD1 and LGAD2 and the  ToT of channel 31 in LGAD1 (figure 7d). The first column represents the  ToT in LGAD 1 (ToT[ns]), the second column the measured time difference (TDiff[ns]) and the last column the number of corresponding counts (counts[#]). A ToT cut on the reference channel on LGAD2 has been applied in advance to guarantee a correlation between only true particle hits in the second sensor.</li> </ul> </li> </ul> </li> <li>Figure 8: <ul> <li>tofinaridata.txt: <ul> <li>Describes the measured TOF in air through the scanner w.r.t the TOF measured at 800MeV, i.e. the median TOF value at 800MeV was subtracted from all data points (Figure 8a). The first column describes the beam energy (beamenergy[MeV]), the second column the first quartile of the measured TOF per pixel (TOFperpixelQ1[ps]), the second column the median TOF per pixel (TOFperpixelQ2[ps]) and the last column the third quartile of the measured TOF per pixel (TOFperpixelQ3[ps]).</li> </ul> </li> <li>tofinairtheodata.txt: <ul> <li>Describes the theoretical TOF in air through the scanner w.r.t the theoretical TOF at 800MeV, i.e. the theoretical TOF value at 800MeV was subtracted from all data points (Figure 8a).</li> </ul> </li> <li>intrinsictimeresolution.txt: <ul> <li>Describes the energy dependence of the intrinsic time resolution per channel measured inside LGAD1 (figure 8b). The first column represents the primary beam energy (beamenergy[MeV), the second column the corresponding energy loss in MIPs (relativeenergylossi[MIP]), the third column the first quartile of the intrinsic time resolution per LGAD channel (timeresperpixelQ1[ps]), the fourth column the median of the intrinsic time resolution per LGAD channel and the last column the third quartile of the intrinsic time resolution per LGAD channel (timeresperpixelmedian[ps],timeresperpixelQ3[ps]).</li> </ul> </li> </ul> </li> <li>Figure 9: <ul> <li>wetcalib.txt <ul> <li>Describes the measured TOF increase per pixel w.r.t to the TOF in air (i.e. without a phantom) for a given WET and primary beam energy. The first column represents the WET of the irradiated sample (WET[mm]), the second column the used beam energy (beamenergy[MeV]), the third column the first quartile of the measured TOF distribution (TOFperpixelQ1[ps]), the fourth column the median (TOFperpixelQ2[ps]) and the sixth column the third quartile (TOFperpixelQ3[ps]).</li> <li>For each energy, a fifth-order polynomial was used to fit the WET and the TOF increase (Delta TOF(E)~sum_i a_i*(WET_i )^i, with i in [0,5] ). The fit parameters are given in the following for each beam energy: <ul> <li>83 MeV: a_i=[-4.70496227e-02,4.64323118e-01, -2.71391535e-02,4.23655842e-03, -1.13034255e-04,1.23725678e-06]</li> <li>100.4 MeV: a_i=[-3.28976022e-02,-3.68818468e-02,1.96339858e-02,7.31585040e-04, -4.38697681e-05 ,7.52163384e-07]</li> </ul> </li> </ul> </li> </ul> </li> <li>Figure 10: <ul> <li>wetsperpixel83MeV.txt <ul> <li>Describes the proton radiography (pCR) for 83 MeV (Figure 10a). The first column represents the x position of the pixel (x[mm]), the second column the y position of the pixel (y[mm]) and the last column the corresponding WET (WET[mm]).</li> </ul> </li> <li>wetsperpixel83MeV.txt <ul> <li>Describes the proton radiography (pCR) for 100.4 MeV (Figure 10b). The first column represents the x position of the pixel (x[mm]), the second column the y position of the pixel (y[mm]) and the last column the corresponding WET (WET[mm]).</li> </ul> </li> </ul> </li> <li>Figure 11: <ul> <li>wetdistrdata83MeV.txt <ul> <li>Describes the measured TOF per pixel inside the ROI for 83 MeV protons (Figure 11a). The first column represents the lower boundary of each WET bin (WETlowerbinboundary[mm]), the second column the upper boundary of each WET bin (WETupperbinboundary[mm) and the last column the corresponding counts per bin (counts[#]).</li> </ul> </li> <li>wetdistrdata100MeV.txt <ul> <li>Describes the measured TOF per pixel inside the ROI for 100.4 MeV protons (Figure 11b). The first column represents the lower boundary of each WET bin (WETlowerbinboundary[mm]), the second column the upper boundary of each WET bin (WETupperbinboundary[mm) and the last column the corresponding counts per bin (counts[#]).</li> </ul> </li> </ul> </li> </ul>

opencc-by-4.0Aug 2022View details →

Airborne EM data (Belgium) from flight line 306025

This dataset contains Airborne EM data from a SkyTEM instrument from the Flanders region, Belgium.  Details about the instrument set-up can be found in the data report. Details about the region, geology, saltwater intrusion context can be found in  Delsman, J., van Baaren, E., Vermaas, T., Karaoulis, M., Bootsma, H., de Louw, P. G. B., ... & Thofte, S. (2019). TOPSOIL Airborne EM kartering van zoet en zout grondwater in Vlaanderen (FRESHEM Vlaanderen: Deelopdrachten 1 tot en met 3. When using this dataset, always cite the above reference.  The actual measured data is in "dat_skytem_306025_flightline.csv". Columns refer to either Low or High moment and time of measurement. Corresponding estimated relative errors can be found in rel_err_skytem_306025_flightline. Distances between soundings/measurment locations and their hieghts above the surface is found in "distances_between_soundings" and "altitudes_per_sounding" respectively. To use this data for the appraisal method, see https://github.com/WouterDls/AEM_appraisal. For more information, write to wouter.deleersnyder@kuleuven.be

opencc-by-4.0Jun 2024View details →

Data archive for "Flight behaviour of Red Kites within their breeding area in relation to local weather variables: Conclusions with regard to wind turbine collision mitigation"

The archive contains the data files to reproduce the results presented in the article “Flight behaviour of Red Kites within their breeding area in relation to local weather variables: Conclusions with regard to wind turbine collision mitigation” published in the Journal of Applied Ecology.

opencc-by-4.0Oct 2019View details →

Raw data supporting Identifying invertebrates from pitfall, flight interception traps and hand collecting

Raw data supporting identifying invertebrates from pitfall, flight interception traps and hand collecting: comparing metabarcoding with traditional methods. Two step PCRs were performed on each sample replicate using modified primers mICOIintF and jgHCO2198 followed by the Nextera XT index kit v2 Set A (Illumina). The pool was loaded onto an illumina MiSeq using a MiSeq Reagent Kit v2 500 cycle kit (Illumina), with 10% Phi-X to generate 250-bp paired-end reads.

opencc-by-4.0Feb 2021View details →

Data for paper "Parametric schedulability analysis of a launcher flight control system under reactivity constraints"

This is the data set (models, sources and results) for the paper "Parametric schedulability analysis of a launcher flight control system under reactivity constraints" published in Informatica Fundamentae in 2021.

opencc-by-4.0Nov 2022View details →

Data for the "Does prognostic seeding along flight tracks produce the desired effects of cirrus cloud thinning?" manuscript

Tar file of the data used to prepare the plots and write the text in: "Does prognostic seeding along flight tracks produce the desired effects of cirrus cloud thinning?" manuscript for submission to ACP. A description of each netcdf file is provided in the README file. The format of each file is in netcdf4

opencc-by-4.0Jan 2021View details →

Measurement and model data comparisons for the HALO-FAAM formation flight during EMeRGe on 17 July 2017

Within the project “Effect of Megacities on the transport and transformation of pollutants on the Regional and Global scales” (EMeRGe), the measurement flight of 13 July 2017 was performed for comparison of the instrumentation onboard of the research aircraft HALO and FAAM. The aircraft flew for 1.6 h in close formation along a racetrack pattern at three flight levels in Southern Germany. The flight started in a rather dry and clean troposphere and ended in a more polluted convective boundary layer. 28 measurement pairs sampled on both aircraft were found suitable for comparison. 17 further pairs of data are available from sampling on either HALO or FAAM. In addition, observations obtained at the DWD Hohenpeissenberg and results from 6 models are included in the comparisons. Overall, about 30% of the measured data pairs show deviations within the combined error estimates. Some measurements deviate considerably from model results. This dataset contains a pdf of the report and a zip file of the comparison data as described in that report.

opencc-zeroNov 2019View details →

Data from: Neural representation of bat predation risk and evasive flight in moths: a modelling approach

Most animals are at risk from multiple predators and can vary anti-predator behaviour based on the level of threat posed by each predator. Animals use sensory systems to detect predator cues, but the relationship between the tuning of sensory systems and the sensory cues related to predator threat are not well-studied at the community level. Noctuid moths have ultrasound-sensitive ears to detect the echolocation calls of predatory bats. Here, combining empirical data and mathematical modelling, we show that moth hearing is adapted to provide information about the threat posed by different sympatric bat species. First, we found that multiple characteristics related to the threat posed by bats to moths correlate with bat echolocation call frequency. Second, the frequency tuning of the most sensitive auditory receptor in noctuid moth ears provides information allowing moths to escape detection by all sympatric bats with similar safety margin distances. Third, the least sensitive auditory receptor usually responds to bat echolocation calls at a similar distance across all moth species for a given bat species. If this neuron triggers last-ditch evasive flight, it suggests that there is an ideal reaction distance for each bat species, regardless of moth size. This study shows that even a very simple sensory system can adapt to deliver information suitable for triggering appropriate defensive reactions to each predator in a multiple predator community.

opencc-by-4.0Mar 2022View details →

Data: Physical constraints on thermoregulation and flight drive morphological evolution in bats

Body size and shape fundamentally determine organismal energy requirements by modulating heat and mass exchange with the environment and the costs of locomotion, thermoregulation, and maintenance. Ecologists have long used the physical linkage between morphology and energy balance to explain why the body size and shape of many organisms vary across climatic gradients, e.g., why larger endotherms are more common in colder regions. However, few modeling exercises have aimed at investigating this link from first principles. Body size evolution in bats contrasts with the patterns observed in other endotherms, probably because physical constraints on flight limit morphological adaptations. Here, we develop a biophysical model based on heat transfer and aerodynamic principles to investigate energy constraints on morphological evolution in bats. Our biophysical model predicts that the energy costs of thermoregulation and flight, respectively, impose upper and lower limits on the relationship of wing surface area to body mass (S-MR), giving rise to an optimal S-MR at which both energy costs are minimized. A comparative analysis of 278 species of bats supports the model’s prediction that S-MR evolves toward an optimal shape and that the strength of selection is higher among species experiencing greater energy demands for thermoregulation in cold climates. Our study suggests that energy costs modulate the mode of morphological evolution in bats—hence shedding light on a long-standing debate over bats’ conformity to ecogeographical patterns observed in other mammals—and offers a procedure for investigating complex macroecological patterns from first principles.

opencc-by-4.0Apr 2022View details →

Data from: Operando Proton Transfer Reaction-Time of Flight-Mass Spectrometry of Carbon Dioxide Reduction Electrocatalysis

Seven top-level folders GC-PTR-TOF-MS - Raw data and Jupyter Notebook used for analysis of GC-PTR-TOF-MS data LSV-PTR-TOF-MS - Raw data and Jupyter Notebook used for analysis of PTR-TOF-MS data under linear sweep voltammetry MSCP-PTR-TOF-MS - Raw data and Jupyter Notebook used for analysis of PTR-TOF-MS data under multi-step chronopotentiometry PTR-TOF-MS-Calibration - Raw data and Jupyter Notebook used for analysis of PTR-TOF-MS calibration data SEM - Raw images from scanning electron microscope Stability - Raw data of electrochemical stability TEM - Raw images from transmission electron microscopy

opencc-by-4.0Oct 2022View details →

ALIMA and BAHAMAS data for SOUTHTRAC flight ST08

Temperature vertical profiles from the ALIMA lidar during SOUTHTRAC flight ST08. The three components of velocity, pressure and temperature recorded from BAHAMAS instrument along the airplane trajectory.

opencc-zeroJun 2024View details →

Data from: Biomechanical properties of non-flight vibrations produced by bees

Bees use thoracic vibrations produced by their indirect flight muscles for powering wingbeats in flight, but also during mating, pollination, defence, and nest building. Previous work on non-flight vibrations has mostly focused on acoustic (airborne vibrations) and spectral properties (frequency domain). However, mechanical properties such as the vibration's acceleration amplitude are important in some behaviours, e.g., during buzz pollination, where higher amplitude vibrations remove more pollen from flowers. Bee vibrations have been studied in only a handful of species and we know very little about how they vary among species. Here, we conduct the largest survey to date of the biomechanical properties of non-flight bee buzzes. We focus on defence buzzes as they can be induced experimentally and provide a common currency to compare among taxa. We analysed 15,000 buzzes produced by 306 individuals in 65 species and six families from Mexico, Scotland, and Australia. We found a strong association between body size and the acceleration amplitude of bee buzzes. Comparison of genera that buzz-pollinate and those that do not suggests that buzz-pollinating bees produce vibrations with higher acceleration amplitude. We found no relationship between bee size and the fundamental frequency of defence buzzes. Although our results suggest that body size is a major determinant of the amplitude of non-flight vibrations, we also observed considerable variation in vibration properties among bees of equivalent size and even within individuals. Both morphology and behaviour thus affect the biomechanical properties of non-flight buzzes.

opencc-by-4.0Apr 2023View details →

Data from: Timing of departure from natal areas by Golden Eagles is not constrained by acquisition of flight skills

The post-fledging dependence period (PFDP), which extends from a fledgling’s first flight out of the nest to its departure from the parents’ territory, is crucial in the lifecycle of birds. During this period, juveniles develop their flight and foraging skills to become fully independent. Despite the importance of this life stage in basic bird ecology and conservation, it remains largely overlooked – notably its link with the acquisition of flight skills. In this study, we modeled the variation in seven proxies describing flight skills of 84 GPS-tracked Golden Eagle juveniles in France between 2016 and 2020. Juveniles had a long but highly variable PFDP, averaging 177.9 (±62.2) days after departure from the nest. This period is divided into two phases: a first phase of rapid increase in flight skills over the first 60 days after departure from the nest, followed by a plateau in which flight skills no longer develop until independence. These results suggest that the full development of flight skills is not a constraining factor during the PFDP and that it is advantageous for juveniles to choose to remain in their natal territory. We posit that parents’ tolerance of fledged juveniles is a type of parental care that may maximize their own fitness by improving the survival of their descendants. In future studies, it may be of interest to investigate the factors that may explain the high variability in the duration of this stage between individuals within the same population.

opencc-zeroSep 2023View details →

Data for: The buzzOmeter system: In situ audio recordings of pollinators in flight

<ol> <li>The role of sounds produced by free-flying insects is challenging to research due to technical difficulties in obtaining audio recordings suitable for playback experiments. Experimental studies using flight sounds are needed to understand if buzzes carry information and by whom it is perceived.</li> <li>We developed the 'buzzOmeter system' for recording untethered, flying insects in their habitat, followed by file processing that allows precise measurements of acoustic parameters, including those dependent on the distance of the sound source from the microphone, i.e. signal magnitude measurements. The system consists of commercially available elements and open-source software.</li> <li>We provide a practical guide for the assembly and use of two alternative setups of the buzzOmeter system, followed by a video tutorial on file processing and an R script for the assignment of audio recordings to the corresponding species based on mixture discriminant analysis. Recordings of nine insect species (bees, wasps and lepidopterans) obtained with the use of our system in various habitats demonstrate its feasibility for field studies. </li> <li>Diverse species interactions are based on sound, and our new tool can aid researchers studying acoustical signalling in predator-prey, pollinator-plant and mimic-model complexes, among others.</li> </ol>

opencc-zeroOct 2023View details →

Supplemental data for: Parallel shifts in flight-height associated with altitude across incipient Heliconius species

Vertical gradients in microclimate, resource availability and interspecific interactions are thought to underly stratification patterns in tropical insect communities. However, only a few studies have explored the adaptive significance of vertical space use during the early stages of reproductive isolation. We analysed flight-height variation across speciation events in Heliconius butterflies representing parallel colonisations of high-altitude forest. We measured flight-height in wild H. erato venus and H. chestertonii, parapatric lowland and mountain specialists respectively, and found that H. chestertonii consistently flies at a lower height. By comparing our data to previously published results for the ecologically equivalent H. e. cyrbia (lowland) and H. himera (high-altitude), we found that the species flying closest to the ground are those that recently colonised high-altitude forests. We show that these repeated trends largely result from shared patterns of ecological selection producing parallel trait-shifts in H. himera and H. chestertonii. Although our results imply a signature of local adaptation, we did not find an association between resource distribution and flight-height in H. e. venus and H. chestertonii. We discuss how this pattern may be explained by variation in forest structure and microclimate. Overall, our findings underscore the importance of behavioural adjustments during early divergence mediated by altitude-shifts.