Find research datasets worth reusing

opencc-by-4.0Oct 2022View details →

Figures 2–5. Sampling sites – 2, 3 in First data on the mites (Mesostigmata, Oribatida) from sea debris of the Caspian Sea (Dagestan coast, Russia)

Figures 2–5. Sampling sites – 2, 3. Kizlyar Bay, canal with sea water and storm emissions within reeds; 4, 5. Marine coast in the Samoor Forest and sea debris on the beach.

43 longevity-associated SNPs genotyped in a Croatian sample of oldest-old individuals

This dataset presents genotype data for 43 single nucleotide polymorphisms (SNPs) that have been genotyped in an anonymised sample of 314 oldest-old individuals (85+ years) from Croatia. The SNPs are located in or near candidate genes for longevity, and were selected from publicly available literature databases (PubMed and repositories specialized for human longevity such as https://genomics.senescence.info/longevity/, http://ageing-map.org/). They were selected based on their strong or repeatedly reported association with human longevity and involvement in various metabolic pathways. Genotyping was performed by Kompetitive Allele Specific PCR (KASP) on genomic DNA isolated from peripheral blood using the salting-out method. The dataset also contains recoding of the genotypes for each participant according to their association with longevity: a value of 2 was assigned to the homozygous genotype of longevity allele, a value of 1 to the heterozygous genotype, and a value of 0 to the homozygous genotype of an allele not associated with longevity in our sample. In cases where there were less than 10 of either homozygous genotypes, and in cases where a dominant or recessive coding gave a more significant result in further analyses, they were additionally recoded as binary variables with only the values 0 and 1, with heterozygote being added to the less common homozygote. This data was used to perform logistic regression analyses to create the best models for predicting survival to the ages of 90 and 95. Those models were then used to create genetic risk scores (here named genetic longevity scores, GLS)  for predicting that phenotype, which are shown in this dataset as well. Information about the selected SNPs is also presented: rs code, nearest gene, chromosome position, and references for literature sources where association with longevity is reported; along with data that refers to the studied Croatian population: alleles (major/minor), minor allele frequencies (MAF), genotyping success rate, and HWE p-values.

Data for: Determining Young's modulus of arbitrarily-shaped granite samples using accurate grain-based modelling with Micro-RME

HaH 346 meteorite samples with shock melt veins are tested using the nanoindentation experiment with Berkovich indenter. The data includes Young's modulus of different rock-forming minerals  measured by nanoindentation test and  Raman spectrum data for jadeite and wadsleyite in HaH346 meteorite.

Sample locations of building types in Osaka-Kobe City-region

Geopackage containing 100 sample locations for 12 different building types within the Osaka-Kobe City-region (total of 1200 samples for 2013-14). Data related to the following journal paper "Shrinkage and Morphological Change: A Study of Building Type Evolution in the Osaka-Kobe City-region in Japan"

Tools and Sample Files to Test the DSS developed in NIVA UC1a

The sample files can be imported by a user to test the DSS, the link to install the tool (<a href="https://gitlab.com/nivaeu/uc1a_docker">https://gitlab.com/nivaeu/uc1a_docker</a> ). Please follow the instructions provided in the overview and instruction file.

opencc-zeroDec 2022View details →

dryad40/100

Testing the effectiveness of genetic monitoring using genetic non-invasive sampling

1. Effective conservation requires accurate data on population genetic diversity, inbreeding, and genetic structure. Increasingly, scientists are adopting genetic non-invasive sampling as a cost-effective population-wide genetic monitoring approach. Genetic non-invasive sampling has, however, known limitations which may impact the accuracy of downstream genetic analyses. 2. Here, using high quality SNP data from blood/tissue sampling of a free-ranging koala population (n = 430), we investigated how the reduced SNP panel size and call rate typical of genetic non-invasive samples (derived from experimental and field trials) impacts the accuracy of genetic measures, and also the effect of sampling intensity on these measures. 3. We found that genetic non-invasive sampling at small sample sizes (14% of population) can provide accurate population diversity measures, but slightly underestimated population inbreeding coefficients. Accurate measures of internal relatedness required at least 33% of the population to be sampled. Accurate geographic and genetic spatial autocorrelation analysis requires between 28% and 51% of the population to be sampled. 4. We show that genetic non-invasive sampling at low sample sizes can provide a powerful tool to aid conservation decision-making and provide recommendations for researchers looking to apply these techniques to free-ranging systems.

Multiplexed histology of COVID-19 post-mortem lung samples - PROLONGED CASE 1 FOV2

Image-based data set of a post-mortem lung sample from a COVID-19 donor (PROLONGED CASE 1 FOV2) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - PROLONGED CASE 1 FOV1

Image-based data set of a post-mortem lung sample from a COVID-19 donor (PROLONGED CASE 1 FOV1) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - CONTROL CASE 1 FOV2

Image-based data set of a post-mortem lung sample from a non-COVID-related pneumonia donor (CONTROL CASE 1, FOV2) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

Multiplexed histology of COVID-19 post-mortem lung samples - CHRONIC CASE 2 FOV1

Image-based data set of a post-mortem lung sample from a COVID-19 donor (CHRONIC CASE 2 FOV1) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.

opencc-zeroMay 2015View details →

IODP Expedition 350 Sample report

Report includes detailed information about samples taken for testing: location/depth, type/form factor, test, request number, and database identifier.

opencc-zeroJul 2019View details →

IODP Expedition 376 Sample report

Report includes detailed information about samples taken for testing: location/depth, type/form factor, test, request number, and database identifier.

Text-fig. 1. The Catefica exposure along the road between Catefica and Mugideira photographed in 1989 when the mesofossil flora was discovered. The exposed strata are mainly cross-bedded light colored sands, darker horizons of clay and dark lenses with mesofossils. The most productive sample, Catefica sample 49, was collected in the basal part of the exposed sequence (arrow head). One of the authors (PRC) exploring the middle part of the section. Photo K. R. Pedersen. in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms

Text-fig. 1. The Catefica exposure along the road between Catefica and Mugideira photographed in 1989 when the mesofossil flora was discovered. The exposed strata are mainly cross-bedded light colored sands, darker horizons of clay and dark lenses with mesofossils. The most productive sample, Catefica sample 49, was collected in the basal part of the exposed sequence (arrow head). One of the authors (PRC) exploring the middle part of the section. Photo K. R. Pedersen.

G-Code associated to the trajectories of the brush in ApPEARS deliverable D5.1 Database of vector based brush strokes and sample prints that demonstrate the range of printed materials

This is appendix for the ApPEARS Deliverable: D5.1 – Database of vector based brush strokes and sample prints that demonstrate the range of printed materials. It contains G-Code Paths associated to the trajectories of the brush.

Images of the data brushes generated for the ApPEARS deliverable D5.1 Database of vector based brush strokes and sample prints that demonstrate the range of printed materials

These images are appendices of ApPEARS deliverable D5.1 Database of vector based brush strokes and sample prints that demonstrate the range of printed materials. They show the generated data brushes.

opencc-zeroJan 2023View details →

dryad40/100

Data for: Inadequate sampling of the soundscape leads to overoptimistic estimates of recogniser performance: A case study of two sympatric macaw species

Passive acoustic monitoring (PAM) offers the potential to dramatically increase the scale and robustness of species monitoring in rainforest ecosystems. PAM generates large volumes of data that require automated methods of target species detection. Species-specific recognisers, which often use supervised machine learning, can achieve this goal. However, they require a large training dataset of both target and non-target signals, which is time-consuming and challenging to create. Unfortunately, very little information about creating training datasets for supervised machine learning recognisers is available, especially for tropical ecosystems. Here we show an iterative approach to creating a training dataset that improved recogniser precision from 0.12 to 0.55. By sampling background noise using an initial small recogniser, we addressed one of the significant challenges of training dataset creation in acoustically diverse environments. Our work demonstrates that recognisers will likely fail in real-world settings unless the training dataset size is large enough and sufficiently representative of the ambient soundscape. We outline a simple workflow that can provide users with an accessible way to create a species-specific PAM recogniser that addresses these issues for tropical rainforest environments. Our work provides important lessons for PAM practitioners wanting to develop species-specific recognisers for acoustically diverse ecosystems.

opencc-zeroJan 2023View details →

Data for: Real time g(2) monitoring with 100 kHz sampling rate

Data for the publication C. Lüders, J. Thewes, and M. Assmann, Real time g(2) monitoring with 100 kHz sampling rate, Opt. Express 26, 24854-24863 (2018). We introduce a technique to determine photon correlations of optical light fields in real time. The method is based on ultrafast phase-randomized homodyne detection and allows us to follow the temporal evolution of the second-order correlation function g(2)(0) of a light field. We demonstrate the capabilities of our approach by applying it to a laser diode operated in the threshold region. In particular, we are able to monitor the emission dynamics of the diode switching back and forth between lasing and spontaneous emission with a g(2)(0)-sampling rate of 100 kHz. Funded by German Science Foundation (DFG) (AS 459/1-2).

Sample intensity and contribution function data for demcmc

Sample intensity and contribution functions. The intensities are taken from a single pixel of a Hinode/EIS map. The contribution functions were calculated using Chianti 10.0.2, assuming a pre-calculated density from the intensities.

S-Ibuprofen - Sample 3 NanED Round Robin, Data: ESR8 & ESR9

S-Ibuprofen The following submission contains the data collection and processing for the sample s-ibuprofen under the NanEd round-robin project.  Precession Electron Diffraction (PED) was used to collect the dataset on the target crystal.  The dataset was processed with PETS2 and eADT software. The table below summarizes the data collection parameters for the dataset.   <table> <tbody> <tr> <td> General information: </td> <td>   </td> </tr> <tr> <td> Project </td> <td> NanED (www.naned.eu) </td> </tr> <tr> <td> ESR Project </td> <td> ESR8 & ESR9 - Round Robin </td> </tr> <tr> <td> Project Label </td> <td> RR3 </td> </tr> <tr> <td> Sample Label </td> <td> RR3-S3_PRAHA </td> </tr> <tr> <td> Data set Label </td> <td> RR_Cry8 </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Instrumental: </td> <td>   </td> </tr> <tr> <td> Instrument </td> <td> FEI TECNAI F30 STWIN </td> </tr> <tr> <td> Radiation source </td> <td> FEG </td> </tr> <tr> <td> Accelerating voltage </td> <td> 300 kV </td> </tr> <tr> <td> Wavelength </td> <td> 0.0197 Å </td> </tr> <tr> <td> Probe Type </td> <td> Nanodiffraction </td> </tr> <tr> <td> Beam Diameter </td> <td> 200nm </td> </tr> <tr> <td> Beam Convergence </td> <td> Semi-parallel beam </td> </tr> <tr> <td> Detector </td> <td> US4000 - CCD camera GATAN (16-bit) (bottom mounted) </td> </tr> <tr> <td> Number of pixels in the image </td> <td> 1024 x 1024 </td> </tr> <tr> <td> Pixel size </td> <td> 15 µm x 15 µm </td> </tr> <tr> <td> Camera length / Effective Camera length </td> <td> 1000 mm / 1153 mm </td> </tr> <tr> <td> Calibration constant (not corrected for Effective Camera length) </td> <td> 0.00252 Å-1/pixel </td> </tr> <tr> <td> Hardware Binning </td> <td> 4 </td> </tr> <tr> <td> Sample description: </td> <td>   </td> </tr> <tr> <td> Name </td> <td> S-Ibuprofen </td> </tr> <tr> <td> Chemical composition </td> <td> C13H18O2 </td> </tr> <tr> <td> Sample source </td> <td> </td> </tr> <tr> <td> Sample preparation </td> <td> Crystals were grinded in an Agatha mortar, and part of the resulting powder was loaded directly on the carbon side of a carbon-coated copper grid (300 mesh). Sample cooled to liquid nitrogen temperature in the pre-specimen chamber. </td> </tr> <tr> <td> Experimental: </td> <td>   </td> </tr> <tr> <td> Data Type </td> <td> Electron diffraction data - 3D ED </td> </tr> <tr> <td> Data collection method </td> <td> Precession </td> </tr> <tr> <td> Temperature (K) used during data collection </td> <td> 77 K </td> </tr> <tr> <td> Number of crystals contributing to the data set </td> <td> 1 </td> </tr> <tr> <td> Number of experimental frames </td> <td> 116 </td> </tr> <tr> <td> tilt range, tilt step, tilt per frame </td> <td> -50° to +65°, 1°, 0° </td> </tr> <tr> <td> Precession angle </td> <td> 1° </td> </tr> <tr> <td> Exposure time per frame </td> <td> 1 s </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Software: </td> <td>   </td> </tr> <tr> <td> Software used for the data collection </td> <td> Gatan Digital Micrograph software </td> </tr> <tr> <td> Software used for processing </td> <td> PETS2 and eADT </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Authorship and bibliography </td> <td>   </td> </tr> <tr> <td> Author(s) of the data </td> <td> Laura Gemmrich Hernández (ESR8) & Marco Santucci (ESR9) </td> </tr> <tr> <td> Related data </td> <td>   </td> </tr> <tr> <td> Publication(s) </td> <td>   </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Files and data formats </td> <td>   </td> </tr> <tr> <td> Image folder </td> <td> img: Folder containing images of the diffraction pattern from each frame. </td> </tr> <tr> <td> Image format </td> <td> tiff_16bit_unsigned </td> </tr> <tr> <td>   </td> <td>   </td> </tr> </tbody> </table>

Multiplexed histology of COVID-19 post-mortem lung samples - ACUTE CASE 2 FOV1

Image-based data set of a post-mortem lung sample from a COVID-19 donor (ACUTE CASE 2 FOV1) Each image shows the same field of view (FOV), sequentially stained with the depicted fluorescence-labelled antibodies, including surface proteins, intracellular proteins and transcription factors. Images contain 2024 x 2024 pixels and are generated using an inverted wide-field fluorescence microscope with a 20x objective, a lateral resolution of 325 nm and an axial resolution above 5 µm. Images have been normalized and intensities adjusted.