Find research datasets worth reusing

opencc-by-4.0Oct 2021View details →

UPLC-QTOF data from a river sample extracted with various solid phase extraction phases - mz5 files with scans in centroid spectrum format

This dataset has been acquired from a river sample (Marne River, France) collected as part of the Screenatm'eau project (Observatoire des Sciences de l’Univers - Enveloppes FLUides de la Ville à l’Exobiologie - OSU-EFLUVE, Université Paris-Est Créteil). The sample was processed by solid-phase extraction using multiple cartridges and phases, in triplicates (see the list of samples in the samplemetadata.csv file). Data was acquired with a SYNAPT HDMS QTOF (Waters) coupled with a Nano ACQUITY UPLC System (Waters), in ESI positive mode. Raw data was converted using Proteowizard MSConvert version 3.0.21288, using zlib compression, with the CWT peakpicking algorithm (snr=0, peakSpace=0) to transform profile to centroid data, and the zeroSamples option (removeExtra 1-). The chosen output formats were .mzML and .mz5. A list of markers was obtained after peak picking and alignment across all samples using the PatRoon R package with the OpenMS algorithm, and exported as a markertable.csv file. Each detected marker has m/z and retention time values (see the variablemetadata.csv file), and intensity values in all samples (markertable.csv). For file naming explanation and details about each SPE phase, see the readme.txt file.

opencc-by-4.0Nov 2018View details →

Sample audio data for JSEALS article "Tonal variation in Pyen"

Audio data samples corresponding to sections 1.1, 5.1 and 6 in the JSEALS article "Tonal variation in Pyen."

opencc-byMar 2022View details →

samples data of publications related to halal meat

this is the dataset of publications downloaded from Scopus and web of science used for bibliometric analysis

opencc-by-4.0Nov 2022View details →

Ibuprofen - Sample 3 NanED Round Robin, Data: ESR4 & ESR5

Ibuprofen The following submission contains the data collection and processing of datasets for the sample ibuprofen under the NanEd round-robin project.  Many crystals were identified, and data were collected using the continuous rotation data acquisition technique, out of which two crystals (Crystal 1 & Crystal 2), which were found to complement each other and improve the completeness of the reflection data, were selected.  All the data sets were processed with PETS2 software. The table below summarizes the data collection parameters for the data sets. The following data is also included as a word file in the data folder. <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> ESR4 & ESR5 - Round Robin </td> </tr> <tr> <td> Project Label </td> <td> RR1 </td> </tr> <tr> <td> Sample Label </td> <td> RR1-S3_PRAHA </td> </tr> <tr> <td> Data set Label </td> <td> RR1-S3_PRAHA-CROT </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Instrumental: </td> <td>   </td> </tr> <tr> <td> Instrument </td> <td> Transmission electron microscope FEI Tecnai G2 20 </td> </tr> <tr> <td> Radiation source </td> <td> LaB6 </td> </tr> <tr> <td> Accelerating voltage </td> <td> 200 kV </td> </tr> <tr> <td> Wavelength </td> <td> 0.0251 Å </td> </tr> <tr> <td> Probe Type </td> <td> Microdiffraction </td> </tr> <tr> <td> Beam Convergence </td> <td> Parallel beam, convergence <0.1mrad </td> </tr> <tr> <td> Detector </td> <td> Hybrid pixel detector ASI Cheetah (side-mounted) </td> </tr> <tr> <td> Number of pixels in the image </td> <td> 512 x 512 </td> </tr> <tr> <td> Pixel size </td> <td> 55 µm x 55 µm </td> </tr> <tr> <td> Effective camera length </td> <td> 1200 mm </td> </tr> <tr> <td> Beam Diameter (crystal 1) </td> <td> 650 nm </td> </tr> <tr> <td> Beam Diameter (crystal 2) </td> <td> 800 nm </td> </tr> <tr> <td> Calibration constant </td> <td> 0.006895 Å-1/pixel </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Sample description: </td> <td>   </td> </tr> <tr> <td> Name </td> <td> Ibuprofen </td> </tr> <tr> <td> Chemical composition </td> <td> C13H18O2 </td> </tr> <tr> <td> Sample source </td> <td> Thermo Scientific (catalog. No: 333200050, lot: A0424385) </td> </tr> <tr> <td> Sample preparation </td> <td> Powder crushed on an agate mortar and deposited on an ionized Cu grid with holey C film </td> </tr> <tr> <td>   </td> <td>   </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> Continuous Rotation </td> </tr> <tr> <td> Temperature (K) used during data collection </td> <td> 95.15 K </td> </tr> <tr> <td> Number of crystals contributing to the data set </td> <td> 2 </td> </tr> <tr> <td> Number of experimental frames: Crystal 1 </td> <td> 340 </td> </tr> <tr> <td> tilt range, tilt step, tilt per frame </td> <td> -55° to +30°, 0.25°, 0.25° </td> </tr> <tr> <td> Exposure time per frame: Crystal 1 </td> <td> 283 ms </td> </tr> <tr> <td> Number of experimental frames: Crystal 2 </td> <td> 360 </td> </tr> <tr> <td> tilt range, tilt step, tilt per frame </td> <td> -50° to +40°, 0.25°, 0.25° </td> </tr> <tr> <td> Exposure time per frame: Crystal 2 </td> <td> 283 ms </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> RATS software </td> </tr> <tr> <td> Software used for processing </td> <td> PETS2 (ver 2.2.20220701.0941) </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> Hrushikesh Chintakindi (ESR4) & Ashwin Suresh (ESR5) </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> dp-crot : Folder containing images of the diffraction pattern from each frame. </td> </tr> <tr> <td> Image format </td> <td> tiff_16bit </td> </tr> <tr> <td> Additional folders/files </td> <td> crystal_image : image of the crystal </td> </tr> <tr> <td>   </td> <td> S3_21-crot-025_petsdata: Log files of PETS2 processing for crystal 1 </td> </tr> <tr> <td>   </td> <td> S3_21-crot-025.pts2:_input file for the program PETS2 used for processing  the data for crystal 1 </td> </tr> <tr> <td>   </td> <td> S3_C7_4-crot-025_petsdata: Log files of PETS2 processing for crystal 2 </td> </tr> <tr> <td>   </td> <td> S3_C7_4-crot-025.pts2:_input file for the program PETS2 used for processing  the data for crystal 2 </td> </tr> </tbody> </table> Notes: The software, RATS used for data collection is an in-house software developed in FZU, Praha. *Project Label "RR1" stands for Round Robin 1 *Data set label "RR1-S3_PRAHA-CROT" stands for Round Robin 1 sample 3 from Prague,  data collection method Continuous Rotation. *The additional files can be found in the folder: data_collection&processing

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Data for: Effects of long-term ethanol storage of blood samples on the estimation of telomere length

Telomeres, DNA structures located at the end of eukaryotic chromosomes, shorten with each cellular cycle. The shortening rate is affected by factors associated with stress, and, thus telomere length has been used as a biomarker of ageing, disease, and different life history trade-offs. Telomere research has received much attention in the last decades; however, there is still a wide variety of factors that may affect telomere measurements and to date no study has thoroughly evaluated the possible long-term effect of a storage medium on telomere measurements. In this study we evaluated the long-term effects of ethanol on relative telomere length (RTL) measured by qPCR, using blood samples of magpies collected over twelve years and stored in absolute ethanol at room temperature. We firstly tested whether storage time had an effect on RTL and secondly we modelled the effect of time of storage (from 1 to 12 years) in differences in RTL from DNA extracted twice in consecutive years from the same blood sample. We also tested whether individual amplification efficiencies were influenced by storage time, and whether this could affect our results. Our study provides evidence of an effect of storage time on telomere length measurements. Importantly, this effect shows a pattern of decreasing loss of telomere sequence with storage time that stops after approximate 4 years of storage, which suggests that telomeres may degrade in blood samples stored in ethanol. Our method to quantify the effect of storage time could be used to evaluate other storage buffers and methods. Our results highlight the need to evaluate the long-term effects of storage on telomere measurements, particularly in long-term studies.

opencc-zeroNov 2022View details →

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.

opencc-by-4.0Dec 2022View details →

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.

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>

opencc-by-4.0Mar 2022View details →

Epidote - Sample 1 NanED, Data ESR1 & ESR2

The following submission contains the data collection frames for the sample Epidote under the NanEd round-robin project.  Precession Electron Diffraction (PED) was carried out on a single crystal. The datasets were processed with PETS2 software and refined kinematically and dynamically using Jana. The table below summarizes the data collection parameters for the data sets.   <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>ESR1 & ESR2</td> </tr> <tr> <td>Instrumental</td> <td> </td> </tr> <tr> <td>Instrument</td> <td>Zeiss Libra 120</td> </tr> <tr> <td>Radiation source</td> <td>LaB6</td> </tr> <tr> <td>Accelerating voltage</td> <td>120 kV</td> </tr> <tr> <td>Wavelength</td> <td>0.0335 Å</td> </tr> <tr> <td>Probe Type</td> <td>Nanodiffraction</td> </tr> <tr> <td>Beam Diameter</td> <td>150 nm</td> </tr> <tr> <td>Beam Convergence</td> <td>Parallel beam</td> </tr> <tr> <td>Detector</td> <td>Timepix Single Electron Detector</td> </tr> <tr> <td>Number of pixels in the image</td> <td>512 x 512</td> </tr> <tr> <td>Physical pixel size</td> <td>55 µm * 55 µm</td> </tr> <tr> <td>Effective camera length</td> <td>144 mm</td> </tr> <tr> <td>Calibration constant</td> <td>0.006027 Å-1/pixel</td> </tr> <tr> <td> </td> <td> </td> </tr> <tr> <td>Sample description</td> <td> </td> </tr> <tr> <td>Name</td> <td>Epidote</td> </tr> <tr> <td>Chemical composition</td> <td>Ca2FexAl3-xSi3O13H</td> </tr> <tr> <td>Sample source</td> <td>Natural source from Val d'Ossola, Italy</td> </tr> <tr> <td>Sample preparation</td> <td>Crushed with a mortar and diluted using isopropanol before depositing a drop on a Cu grid.</td> </tr> <tr> <td> </td> <td> </td> </tr> <tr> <td>Experimental</td> <td> </td> </tr> <tr> <td>Data type</td> <td>3D Electron Diffraction (3D-ED)</td> </tr> <tr> <td>Data collection method</td> <td>Precession</td> </tr> <tr> <td>Precession semiangle</td> <td>1º</td> </tr> <tr> <td>Temperature</td> <td>293 K</td> </tr> <tr> <td>Number of crystals contributing to the dataset</td> <td>1</td> </tr> <tr> <td>Number of experimental frames</td> <td>121</td> </tr> <tr> <td>Tilt range, tilt step</td> <td>+60º to -60º, -1º</td> </tr> <tr> <td>Exposure time per frame</td> <td>1000 ms</td> </tr> <tr> <td> </td> <td> </td> </tr> <tr> <td>Software</td> <td> </td> </tr> <tr> <td>Software used for data collection</td> <td>WinTEM (Zeiss), Digistar (NanoMEGAS) and Sophy (Software for Physics)</td> </tr> <tr> <td>Software used for processing</td> <td>PETS2</td> </tr> <tr> <td>Software used for solution</td> <td>Jana</td> </tr> <tr> <td>Software used for refinement</td> <td>Jana</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>Moussa Diame FAYE (ESR1) & Vincentia Emerson Agbemeh (ESR2)</td> </tr> <tr> <td>Related data</td> <td> </td> </tr> <tr> <td>Publication(s)</td> <td> </td> </tr> <tr> <td> </td> <td> </td> </tr> </tbody> </table>

Sample data for JRC_seeker test run

This is sample data as part of the test run for JRC_seeker, a Snakemake pipeline for the genome-wide discovery of jointly regulated CpGs (JRCs) in pooled whole genome bisulfite sequencing (WGBS) data (https://github.com/BenjaminPlanterose/JRC_seeker).

Natrolite - Sample 2 NanED Round Robin, Data: ESR12

Natrolite The following submission contains the data collection and processing of datasets for the sample epidote under the NanEd round-robin project.  A single crystal was identified, and precession data acquisition techniques were used to collect datasets on the same crystal.  All the data sets were processed with PETS2 software. The table below summarizes the data collection parameters for the data sets. The following data is also included as a text file in the data folder.     Precession: <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> ESR12 - Round Robin </td> </tr> <tr> <td> Project Label </td> <td> RR1 </td> </tr> <tr> <td> Sample Label </td> <td> RR1-S2 </td> </tr> <tr> <td> Data set Label </td> <td> RR1-sample2-PEDT </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Instrumental: </td> <td>   </td> </tr> <tr> <td> Instrument </td> <td> Transmission electron microscope Jeol F200 </td> </tr> <tr> <td> Radiation source </td> <td> Cold FEG </td> </tr> <tr> <td> Accelerating voltage </td> <td> 200 kV </td> </tr> <tr> <td> Wavelength </td> <td> 0.0251 Å </td> </tr> <tr> <td> Probe Type </td> <td> Microdiffraction </td> </tr> <tr> <td> Beam Diameter </td> <td> 75nm </td> </tr> <tr> <td> Beam Convergence </td> <td> Parallel beam, convergence <0.1mrad </td> </tr> <tr> <td> Detector </td> <td> Hybrid pixel detector ASI Cheetah M3 (bottom mounted) </td> </tr> <tr> <td> Number of pixels in the image </td> <td> 512 x 512 </td> </tr> <tr> <td> Pixel size </td> <td> 55 µm x 55 µm </td> </tr> <tr> <td> Effective camera length </td> <td> 250 mm </td> </tr> <tr> <td> Calibration constant </td> <td> 0.005835 Å-1/pixel </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Sample description: </td> <td>   </td> </tr> <tr> <td> Name </td> <td> Natrolite </td> </tr> <tr> <td> Chemical composition </td> <td> Na2Si3Al2O10.(H2O)2 </td> </tr> <tr> <td> Sample source </td> <td> </td> </tr> <tr> <td> Sample preparation </td> <td> Powder crushed in a mortar and dispersed in n-butanol, drop deposited on a Cu grid with holey C film </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> 293 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> 109 </td> </tr> <tr> <td> tilt range, tilt step, tilt per frame </td> <td> -49° to +59°, 1°, 0° </td> </tr> <tr> <td> Precession angle </td> <td> 1.35° </td> </tr> <tr> <td> Exposure time per frame </td> <td> 500ms </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> Instamatic software </td> </tr> <tr> <td> Software used for processing </td> <td> PETS2 (ver 2.1.20211012.1037) </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> Sara Passuti (ESR12) </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> tiff : Folder containing images of the diffraction pattern from each frames. </td> </tr> <tr> <td> Image format </td> <td> tiff_16bit </td> </tr> <tr> <td> Additional folders/files </td> <td> sample2_crystal_image : image of the crystal </td> </tr> <tr> <td>   </td> <td> sample2-exp3_petsdata : Log files of PETS2 processing </td> </tr> <tr> <td>   </td> <td> sample2-exp3.pts2 : input file for the program PETS2 used for processing  the data </td> </tr> </tbody> </table>   <table> <tbody> <tr> <td> Notes: *Project Label "RR1" stands for Round Robin 1 *Data set label "RR1-sample2-PEDT" stands for Round Robin 1 sample 2, data collection method Precession. *The additional files can be found in the folder: Precession\data_collection_processing </td> </tr> </tbody> </table>

Epidote - Sample 1 NanED Round Robin, Data: ESR12

Epidote The following submission contains the data collection and processing of datasets for the sample epidote under the NanEd round-robin project.  A single crystal was identified, and precession data acquisition techniques were used to collect datasets on the same crystal. The data sets were processed with PETS2 software. The table below summarizes the data collection parameters for the data sets. The following data is also included as a text file in the data folder. Precession: <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> ESR12 - Round Robin </td> </tr> <tr> <td> Project Label </td> <td> RR1 </td> </tr> <tr> <td> Sample Label </td> <td> RR1-S1 </td> </tr> <tr> <td> Data set Label </td> <td> RR1-sample1-PEDT </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Instrumental: </td> <td>   </td> </tr> <tr> <td> Instrument </td> <td> Transmission electron microscope Jeol F200 </td> </tr> <tr> <td> Radiation source </td> <td> Cold FEG </td> </tr> <tr> <td> Accelerating voltage </td> <td> 200 kV </td> </tr> <tr> <td> Wavelength </td> <td> 0.0251 Å </td> </tr> <tr> <td> Probe Type </td> <td> Microdiffraction </td> </tr> <tr> <td> Beam Diameter </td> <td> 75nm </td> </tr> <tr> <td> Beam Convergence </td> <td> Parallel beam, convergence <0.1mrad </td> </tr> <tr> <td> Detector </td> <td> Hybrid pixel detector ASI Cheetah M3 (bottom mounted) </td> </tr> <tr> <td> Number of pixels in the image </td> <td> 512 x 512 </td> </tr> <tr> <td> Pixel size </td> <td> 55 µm x 55 µm </td> </tr> <tr> <td> Effective camera length </td> <td> 200 mm </td> </tr> <tr> <td> Calibration constant </td> <td> 0.00720 Å-1/pixel </td> </tr> <tr> <td>   </td> <td>   </td> </tr> <tr> <td> Sample description: </td> <td>   </td> </tr> <tr> <td> Name </td> <td> Epidote </td> </tr> <tr> <td> Chemical composition </td> <td> Ca2FexAl3-xSi3O13H </td> </tr> <tr> <td> Sample source </td> <td> Natural source from Val d'Ossola, Italy </td> </tr> <tr> <td> Sample preparation </td> <td> Powder crushed on a mortar and dispersed in n-butanol, drop deposited on a Cu grid with holey C film </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> PEDT </td> </tr> <tr> <td> Temperature (K) used during data collection </td> <td> 293 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> 95 </td> </tr> <tr> <td> tilt range, tilt step, tilt per frame </td> <td> -49.4° to +61.6°, 1°, 0° </td> </tr> <tr> <td> Precession angle </td> <td> 1.25° </td> </tr> <tr> <td> Exposure time per frame </td> <td> 500ms </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> Instamatic software </td> </tr> <tr> <td> Software used for processing </td> <td> PETS2 (ver 2.1.20211012.1037) </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> Sara Passuti (ESR12) </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> tiff : Folder containing images of the diffraction pattern from each frames. </td> </tr> <tr> <td> Image format </td> <td> tiff_16bit </td> </tr> <tr> <td> Additional folders/files </td> <td> sample1_crystal_image : image of the crystal </td> </tr> <tr> <td>   </td> <td> sample1-exp4_petsdata : Log files of PETS2 processing </td> </tr> <tr> <td>   </td> <td> sample1-exp4.pts2 :_input file for the program PETS2 used for processing  the data </td> </tr> </tbody> </table>   <table> <tbody> <tr> <td> Notes: *Project Label "RR1" stands for Round Robin 1 *Data set label "RR1-sample-PEDT" stands for Round Robin 1 sample 1, data collection method Precession. *The additional files can be found in the folder: Precession\Data_collection_processing </td> </tr> </tbody> </table>

Sample data for JRC_sorter test run

This is sample data as part of the test run for JRC_sorter, a classifier for Jointly Regulated CpGs (JRCs) (https://github.com/BenjaminPlanterose/JRC_sorter).

opencc-zeroFeb 2023View details →

dryad40/100

Data from: Flying high: Sampling savanna vegetation with UAV-lidar

The flexibility of UAV-lidar remote sensing offers a myriad of new opportunities for savanna ecology, enabling researchers to measure vegetation structure at a variety of temporal and spatial scales. However, this flexibility also increases the number of customizable variables, such as flight altitude, pattern, and sensor parameters, that, when adjusted, can impact data quality as well as the applicability of a dataset to a specific research interest. To better understand the impacts that UAV flight patterns and sensor parameters have on vegetation metrics, we compared 7 lidar point clouds collected with a Riegl VUX-1LR over a 300 x 300 m area in the Kruger National Park, South Africa. We varied the altitude (60 m above ground, 100 m, 180 m, and 300 m) and sampling pattern (slowing the flight speed, increasing the overlap between flightlines, and flying a crosshatch pattern), and compared a variety of vertical vegetation metrics related to height and fractional cover. Comparing vegetation metrics from acquisitions with different flight patterns and sensor parameters, we found that both flight altitude and pattern had significant impacts on derived structure metrics, with variation in altitude causing the largest impacts. Flying higher resulted in lower point cloud heights, leading to a consistent downward trend in percentile height metrics and fractional cover. The magnitude and direction of these trends also varied depending on the vegetation type sampled (trees, shrubs, or grasses), showing that the structure and composition of savanna vegetation can interact with the lidar signal and alter derived metrics. While there were statistically significant differences in metrics among acquisitions, the average differences were often on the order of a few centimeters or less, which shows great promise for future comparison studies. We discuss how these results apply in practice, explaining the potential trade-offs of flying at higher altitudes and alternating flight pattern. We highlight how flight and sensor parameters can be geared toward specific ecological applications and vegetation types, and we explore future opportunities for optimizing UAV-lidar sampling designs in savannas.

opencc-by-4.0Oct 2022View details →

Enantiopure Ibuprofen - Sample 3 NanED, Data ESR1 & ESR2

General Information   Project NanED (www.naned.eu) ESR Project ESR1 & ESR2 Instrumental   Instrument Zeiss Libra 120 Radiation source LaB6 Accelerating voltage 120 kV Wavelength 0.0335 Å Probe Type Nanodiffraction Beam Diameter 600 nm Beam Convergence Parallel beam Detector Timepix Single Electron Detector Number of pixels in the image 512 x 512 Physical pixel size 55 µm * 55 µm Effective camera length 180 mm Calibration constant 0.004815 Å-1/pixel     Sample description   Name Ibuprofen Chemical composition C13H18O2 Sample source Thermo Scientific (catalog. No: 333200050, lot: A0424385) Sample preparation Crushed between two glass slides     Experimental   Data type 3D Electron Diffraction (3D-ED) Data collection method Continuous Rotation Electron Diffraction (CRED) Rotation Speed 1.125 º/s Temperature 95.15 K Number of crystals contributing to the dataset 1 Number of experimental frames 226 Tilt range, tilt step -60º to +55, 0.5º Exposure time per frame 450 ms     Software   Software used for data collection WinTEM (Zeiss), Digistar (NanoMEGAS) and Sophy (Software for Physics) Software used for processing Pets2 Software used for solution Shelxt Software used for refinement Jana, Olex2     Authorship and bibliography   Author(s) of the data Moussa Diame FAYE (ESR1) & Vincentia Emerson Agbemeh (ESR2) Related data   Publication(s)         Precession: General Information   Project NanED (www.naned.eu) ESR Project ESR1 & ESR2 Instrumental   Instrument Zeiss Libra 120 Radiation source LaB6 Accelerating voltage 120 kV Wavelength 0.0335 Å Probe Type Nanodiffraction Beam Diameter 150 nm Beam Convergence Parallel beam Detector Timepix Single Electron Detector Number of pixels in the image 512 x 512 Physical pixel size 55 µm * 55 µm Effective camera length 180 mm Calibration constant 0.004815 Å-1/pixel     Sample description   Name Ibuprofen Chemical composition C13H18O2 Sample source Thermo Scientific (catalog. No: 333200050, lot: A0424385) Sample preparation Crushed between two glass slides     Experimental   Data type 3D Electron Diffraction (3D-ED) Data collection method Precession Precession Semiangle 1º   Temperature 95.15 K Number of crystals contributing to the dataset 1 Number of experimental frames 104 Tilt range, tilt step -60 to +55, 1º Exposure time per frame 1000 ms     Software   Software used for data collection WinTEM (Zeiss), Digistar (NanoMEGAS) and Sophy (Software for Physics) Software used for processing PETS2 Software used for solution Shelxt Software used for refinement Jana     Authorship and bibliography   Author(s) of the data Moussa Diame FAYE (ESR1) & Vincentia Emerson Agbemeh (ESR2) Related data   Publication(s)

Supporting publication for 'Prevalence sample-based guidance for reporting 2022 data'

The record is aimed at helping the reporting countries to submit their sample-based level data to the EFSA Data Collection Framework. We include here two excel files and one XML file, and we give below specific information on their use. The two Excel documents help in mapping terms from the matrix catalogue ZOO_CAT_MATRIX used in the aggregated prevalence data model to FoodEx2 codes, and offer examples on how prevalence data can be reported using SSD2 and how data are aggregated afterwards. The XML file is the same example as in the Excel file with similar title but in the XML format that allows for it be uploaded in the Data Collection Framework.