Find research datasets worth reusing

opencc-by-4.0Oct 2022View details →

Geomagnetic (NGK, EYR) and Geoelectric (NGK) Field Measurements

The Niemegk (NGK) geomagnetic and geoelectric field measurements were provided by Juergen Matzka GFZ German Research Centre for Geosciences, Potsdam, Germany. The original Eyrewell (EYR) geomagnetic field measurements were provided by Tanja Petersen (GNS Science, New Zealand), and subsequently processed to MATLAB format by Craig Rodger (University of Otago, New Zealand). File Descriptions: ng0v031029a.dat NGK geomagnetic field measurements are provided in XYZ coordinates at 0.5 s resolution t2003-10-29_302.ngk NGK geoelectric field measurements are provided in geographic coordinates (x=north, y=east) in units of mV at 1s resolution. To get the electric field in mV/km, you have to divide the numbers by 1 km for Ex (electrode spacing is 1000 m) and by 0.95 km for Ey (electrode spacing is 950 m). EYR5sec10292003.mat EYR geomagnetic field measurements (horizontal magnitude of the magnetic field) are provided in units of nT at 5s resolution.

opencc-by-4.0Oct 2022View details →

Data from: "Lithium-ion battery degradation: measuring rapid loss of active silicon in silicon-graphite composite electrodes"

Dataset from the publication "Lithium-ion battery degradation: measuring rapid loss of active silicon in silicon-graphite composite electrodes". Full experimental details can be found in the related publication in ACS Applied Energy Materials: <a href="https://doi.org/10.1021/acsaem.2c02047">https://doi.org/10.1021/acsaem.2c02047</a> Commercial 21700 cylindrical cells (LG M50T, LG GBM50T2170) were cycle aged under 3 different temperatures [10, 25, 40] °C and 2 SoC ranges [0-30, 0-100]%, with multiple cells tested under each condition. Cells were base-cooled at set temperatures using bespoke test rigs (see pubilcation for details). All electrochemical data were recorded using a Biologic BCS-815 battery cycler.   Break-in cycles: Prior to any ageing or performance checks, all cells were subject to 5 full charge-discharge cycles as part of the break-in procedure. This consisted of a 0.2C charge to 4.2 V with CV-hold till C/100, and 0.2C discharge to 2.5 V (repeated for 5 cycles). Cells were rested under open circuit conditions for 2 hours after each charge and 4 hours after each discharge. These break-in cycles were performed at 25°C for all cells.   Ageing Conditions: <table align="center"> <caption>Ageing Conditions</caption> <thead> <tr> <th scope="col">Expt</th> <th scope="col">SoC Range</th> <th scope="col">C-rate</th> <th scope="col">Temperature</th> <th scope="col"># of cells</th> <th scope="col">Cell IDs</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>0-30%</td> <td>0.3C / 1D</td> <td>10°C</td> <td>3</td> <td>A, B, J</td> </tr> <tr> <td>1</td> <td>0-30%</td> <td>0.3C / 1D</td> <td>25°C</td> <td>3</td> <td>D, E, F</td> </tr> <tr> <td>1</td> <td>0-30%</td> <td>0.3C / 1D</td> <td>40°C</td> <td>3</td> <td>K, L, M</td> </tr> <tr> <td>5</td> <td>0-100%</td> <td>0.3C / 1D</td> <td>10°C</td> <td>3</td> <td>A, B, C</td> </tr> <tr> <td>5</td> <td>0-100%</td> <td>0.3C / 1D</td> <td>25°C</td> <td>2</td> <td>D, E</td> </tr> <tr> <td>5</td> <td>0-100%</td> <td>0.3C / 1D</td> <td>40°C</td> <td>3</td> <td>F, G, H</td> </tr> </tbody> </table> For cells aged in the 0-30% SoC range, each ageing set consisted of 256 cycles over the 0-30% SoC range (discharge to 2.5 V, charge by passing 1500 mA h (== 0.3*nominal capacity)). C-rates were 0.3C for charge, and 1C for discharge. For cells aged in the 0-100% SoC range, each ageing set consisted of 78 cycles over the full SoC range (discharge to 2.5 V, charge to 4.2 V with CV hold till C/100). C-rates were 0.3C for charge, and 1C for discharge.   Reference Performance Tests (RPTs): All cells were characterised at beginning of life (BoL) and after each ageing set using a reference performance test (RPT). The RPT was always performed at 25°C. Two different RPT procedures were used: a longer procedure which was performed after each even-numbered ageing set, and a shorter procedure which was used after each odd-numbered ageing set. Both procedures are detailed below. A CC-CV charge at 0.3C to 4.2 V, 4.2 V till C/100 was performed between each step of the procedures. Long RPT procedure: <ol> <li>C/10 discharge-charge cycle between the voltage limits (2.5 V and 4.2 V).</li> <li>C/2 discharge-charge cycle between the voltage limits (2.5 V and 4.2 V).</li> <li>GITT discharge at 0.5C; 25 pulses with each pulse passing 200 mA h of charge, with 1 hour rest between pulses; lower cut-off voltage of 2.5 V (but continued test for all pulses).</li> <li>GITT discharge at 0.5C; 5 pulses with each pulse passing 1000 mA h of charge, with 1 hour rest between pulses; lower cut-off voltage of 2.5 V (but continued test for all pulses).</li> </ol> Short RPT procedure: <ol> <li>C/10 discharge-charge cycle between the voltage limits (2.5 V and 4.2 V).</li> <li>Hybrid CC-pulse test with average current of C/2. A baseline DC current of C/2 was applied with an HPPC-type profile superimposed on top. This was done for discharge and charge (with voltage limits of 2.5 V and 4.2 V).</li> <li>Hybrid CC-pulse test with average current of 1C. A baseline DC current of 1C was applied with an HPPC-type profile superimposed on top. This was done for discharge only (with a voltage limit of 2.5 V).</li> </ol>   Extracted Data - Main One csv file exists for each cell being tested, summarising the important data extracted from the ageing cycles and the RPTs. This includes: Ageing Set: numbered 0 (BoL) to x, where x is the number of ageing sets the cell has been subject to. Ageing Cycles: number of ageing cycles the cell has been subject to. *this is not equivalent full cycles. Ageing Set Start Date/ End date: The date that each ageing set began/ ended. Days of Degradation: Number of days between the date of the first ageing set beginning and the current ageing set ending. Age Set Average Temperature: average recorded surface temperature of the cell during cycle ageing. Temperature was recorded approximately 1/2 way up the length of the cell (i.e. between positive and negative caps) using a K-type thermocouple. Units: °C. Charge Throughput: total accumulated charge recorded during all cycles during ageing (i.e. sum of charge and discharge). This is the cummulative total since BoL (not including RPTs). Units: Ah. Energy Throughput: as with "charge throughput", but for energy. Units: Wh. C/10 Capacity: the capacity recorded during the C/10 discharge test of each RPT. Units: mAh. C/2 Capacity: the capacity recorded during the C/2 discharge test of each even-numbered RPT. Units: mAh. 0.1s Resistance: The resistance calculated from the 25-pulse GITT test of each even-numbered RPT. This value is taken from the 12th pulse of the procedure (which corresponds to ~52% SoC at BoL). The resistance is calculated by dividing the voltage drop by the current at a timecale of 0.1 seconds after the current pulse is applied (the fastest timescale possible under the 10 Hz recording condition). Units: Ohms.   Extracted Data - Degradation Modes: Degradation Mode Analysis (DMA) was also performed on the C/10 discharge data at each RPT. This analysis uses an optimisation function to determine the capacities and offset of the positive and negative electrodes by calculating a full cell voltage vs capacity curve using 1/2 cell data and comparing against the experimentally measured voltage vs capacity data from the C/10 discharge. The results of this analysis are saved in the DMA folder, with 4 csv files for each cell, which contain data for all RPTs. The 4 files contain: Fitting parameters: output from the DMA optimisation function; 5 parameters which detail the upper/lower lithitation fractions of each electrode and the capacity fraction of graphite in the negative electrode. Capacity and offset data: calculated based on the fitting parameters above alongside the measured C/10 discharge capacity. DM data: Quantities of LLI, LAM-PE, LAM-NE, LAM-NE-Gr, and LAM-NE-Si calculated from the change in capacities/offset of each electrode since BoL. RMSE data: the root-mean-square error of the optimisation function calculated from the residual between the measured and calculated voltage vs capacity profiles.   Timeseries data from RPTs: Timeseries datafiles from the Biologic battery cycler which have been exported to csv and sliced for each step of each RPT procedure to help with future use of the data. Files contain [time, voltage, current, charge, temperature] data.   Jupyter Notebook: A jupyter notebook has been included to aid futher use of this data. The notebook shows how to load the data into pandas DataFrame objects and provides a couple of example plots to view the datasets.   Notes: A faulty electrical connection to cell A of Expt 5 (i.e. one of the cells being aged at 0-100% SoC at 10°C) during RPT4 led to erroneous results for that performance check (as evidenced in the 0.1s resistance value). The faulty electrical connection was fixed prior to subsequent cycling but the RPT was not repeated. We have kept the data collected during this RPT as part of the dataset, so caution should be used when using this specific portion.

opencc-by-4.0Oct 2022View details →

Morphological measurements of coccoliths from surface samples of South China Sea

The dataset compiles morphological measurements of coccoliths (Gephyrocapsa spp. and Emiliania huxleyi, >2µm) from surface samples of the South China Sea retrieved at different depths of the basin during the R/V Sonne cruises (SO-95); and of Gephyrocapsa spp. from one sample from the Western Equatorial Pacific (ODP 807A, -2H-2W, 57-59 cm) used in a dissolution experiment. The columns include station names, Longitude, Latitude, Depth (m), how much Calgon was added into sediment suspension (in the dissolution experiment), number of coccoliths measured per sample, mean ks shape factor, thickness, length, volume, mass, and standard deviation of mean ks/mean ks.

opencc-zeroNov 2022View details →

Different measures of niche and fitness differences tell different tales

In Modern Coexistence Theory, species coexistence can either arise via strong niche differences or weak fitness differences. Having a common currency for interpreting these mechanisms is essential for synthesizing knowledge across different studies and systems. However, several methods for quantifying niche and fitness differences exist, with little guidance on how and why these methods differ. Here, we first organize the available methods into three groups and review their differences from a conceptual point of view.Next, we apply four methods to quantify niche and fitness differences to one simulated and one empirical data set. We show that these methods do not only differ quantitatively, but affect how we interpret coexistence. Specifically, the different methods disagree on how resource supply rates (simulated data) or plant traits (empirical data) affect niche and fitness differences. We argue for a better theoretical understanding of what connects and sets apart different methods and more precise empirical measurements to foster appropriate method selection in coexistence theory.

Synchrotron X-ray Diffraction Results - Measuring Bulk Crystallographic Texture from Differently-Orientated Ti-6Al-4V Samples

A dataset of crystallographic texture results for both α (hexagonal close packed, hcp) and β (body-centred cubic, bcc) phases, measured from six differently orientated Ti-6Al-4V (Ti-64) samples, using two different analysis techniques of synchrotron X-ray diffraction (SXRD) data. The texture results are produced from two refinement methods for fitting intensities from SXRD pattern images; an established Rietveld refinement method using the software package <a href="http://maud.radiographema.eu">MAUD (Materials Analysis Using Diffraction)</a> and a new Fourier-based peak fitting method from the <a href="https://pypi.org/project/continuous-peak-fit/">Continuous-Peak-Fit</a> Python package. The texture results were also compared with electron backscatter diffraction (EBSD) measurements from a single sample orientation. The SXRD and EBSD textures were analysed using <a href="https://mtex-toolbox.github.io">MTEX</a> to enable a direct comparison of the pole figures, orientation distribution functions (ODFs) and numerical values for the texture indices. The SXRD texture is calculated from each of the six different sample orientations, a combination of the six sample orientations, and in a batch processing method for calculating spatially-resolved texture variation from 387 individual X-Y stage-scan SXRD measurements across one of the samples. The texture variation measured using stage-scan SXRD is directly compared with EBSD, by splitting up the EBSD map into an equivalent grid matrix using an automated script in MTEX. Material The Ti-64 material used in this study was pre-rolled to 87.5% reduction at 915ºC and then air-cooled to develop a characteristic texture. The run numbers from the experiment reference six different sample orientations, according to their alignment with the original rolling directions (RD – rolling direction, TD – transverse direction, ND – normal direction), and alignment with the horizontal (X) and vertical (Y) axes of the synchrotron detector. MAUD / MTEX Analysis The α and β phase texture for each of the six different sample orientations was calculated using MAUD, included in this <a href="https://doi.org/10.5281/zenodo.7311323">analysis dataset</a>, which produced ODFs in the form of text files. The texture files were analysed in MTEX using scripts from the <a href="https://github.com/LightForm-group/MAUD-batch-analysis">MAUD-batch-analysis</a> package, for plotting of the pole figures and ODF slices, along with calculation of pole figure maxima, ODF maxima and texture indices. The same procedure was used to analyse texture from all six orientations together; using MTEX to fit a single ODF text file. And a series of ODF text files were analysed to calculate texture variation from an X-Y stage scan of Sample 1 (103845). Two different ODF resolutions of 5º and 15º were initially used to fit the texture in MAUD, with the same ODF resolution applied to analyse the data in MTEX. However, an ODF resolution of 15° was found to reproduce the most reasonable texture strength intensity values, with the closest match to the EBSD results. Continuous-Peak-Fit / MTEX Analysis The lattice plane intensities for 21 α and 4 β phase peaks were extracted from the Continuous-Peak-Fit analysis, included in this <a href="https://doi.org/10.5281/zenodo.7311323">analysis dataset</a>, and saved as text files in the form of pole figures. The lattice intensity text files were analysed in MTEX using scripts from the <a href="https://github.com/LightForm-group/continuous-peak-fit-analysis">continuous-peak-fit-analysis</a> package, to plot pole figures and ODF slices, and to calculate pole figure maxima, ODF maxima and texture indices. The same procedure was used to analyse texture from all six orientations together, along with combinations of different sample orientations, by fitting combined lattice intensity text files in MTEX. And a series of lattice intensity text files were analysed to calculate texture variation from the X-Y stage scan of Sample 1 (103845). Lattice plane intensity distributions which had been normalised to a Ti-64 powder sample measurement were also analysed, to see if this had any effect on the texture intensities. Nevertheless, the powder-corrected texture was found to exactly match the raw intensity measurements. Three different ODF resolutions of 5º, 10º and 15º were initially used to fit the texture in MTEX. However, a kernel half-width of 10° was found to produce optimal data fitting, for highly accurate texture strength intensity values. EBSD / MTEX Analysis The indexed α-phase EBSD measurements were recorded over an area of around 100 mm2, with an equivalent sized map of β-phase orientations reconstructed from the data. Both the α and the β phase maps were analysed using the <a href="https://github.com/LightForm-group/MTEX-texture-block-analysis">MTEX-texture-block-analysis</a> package, which was used to split up the map into 387 individual square sections, with equivalent dimensions to the SXRD stage-scan measurement grid. For each of the 387 sections, MTEX was used to plot pole figures and ODF slices, and to calculate pole figure maxima, ODF maxima and texture indices. Texture Variation Comparison The texture values calculated from the SXRD stage scan measurements, with the two analysis methods, were used for a direct comparison with the texture variation recorded using EBSD. This analysis was recorded in the <a href="https://github.com/LightForm-group/texture-strength-comparison">texture-strength-comparison</a> package. The results show differences in texture variation across the piece depending on the method used to analyse the SXRD data. The Continuous-Peak-Fit analysis method shows the closest match with EBSD, producing clear texture intensity spikes for the different α and β lattice plane pole figure intensities, ODF maxima and texture indices, at the centre of the piece. The results were also used to develop SXRD maps showing the distribution of texture intensities across the sample. Metadata An accompanying YAML text file contains associated processing metadata for the SXRD and EBSD analyses, recording information about the different packages used to process the data, along with details about the different files contained within this results dataset.

Raw measurements data of piezo actuator displacements, in a form of a groove pattern, obtained with a laser interferometer and a roundness instrument

A brief description of the repository content The data presented here were obtained during an experimental calibration of the Taylor Hobson 130 (Leicester, UK) roundness instrument with the Thorlabs LPS710M (Thorlabs, Newton, NJ, USA) piezo actuator driven by Thorlabs PPC001 Piezo Controller and controlled with Kinesis® (Thorlabs) software. Before the calibration, the piezo actuator itself was calibrated with the Renishaw XL-80 interferometer system (Renishaw, Wotton-under-Edge, UK) along with the Renishaw small optics kit (A-8003-3244). These data are included in the repository as well. Description of the dataset Inside the .zip file, the data obtained with the Renishaw XL-80 laser interferometer and the Taylor Hobson 130 roundness instrument are stored in the “Renishaw_XL-80” and “Taylor_Hobson_130” folders, respectively. Each of these folders contains six subfolders: “0.24um”, “0.75um”, “2.4um”, “7.5um”, “24um”, and “75um”, which include the measurements data obtained with these devices (not simultaneously) while Thorlabs LPS710M piezo actuator was performing displacements simulating a groove pattern. The names of subfolders correspond to the groove’s depth. The data from the measurements performed with the Renishaw XL-80 interferometer were exported with the Laser XL system’s software and are saved with the extension “.RTX”. Two data files are available for each depth being considered that correspond to two measurement series. Inside each file, 40 s recording is stored. Eight grooves should be visible (nominal values: 1.5 s groove width, 3 s distance between subsequent grooves). The data were acquired with a 50 kS/s sampling rate. The data from the measurements performed with the Taylor Hobson 130 roundness instrument were exported with the Ultra® (Taylor Hobson) software and are saved with the extension “.SBF”. 30 data files are available for each depth being considered - 15 files for each of two measurement series. Inside each file, 10 s recording is stored. Two grooves should be visible (nominal values: 1 s groove width, 4 s distance between subsequent grooves). The data were acquired with a 360 S/s sampling rate. Caution: <ul> <li>No synchronisation between the piezo actuator and XL-80 interferometer or Taylor Hobson 130 roundness instrument was used. Thus, the first or the last groove within the response to the simulated pattern might be too short to be considered valid.</li> <li>The square excitation of the piezo actuator was used. Thus, ringing oscillations near the grooves’ edges are present.</li> <li>The motion of the piezo actuator might happen to be initiated while the acquisition already had started. Thus, the first response inside each file should be analysed carefully.</li> <li>The piezo actuator did not hold time dependencies properly. The widths of simulated grooves usually differ from their nominal values to some extent.</li> </ul> Acknowledgement This dataset was obtained within the 18RP01 ProbeTrace project. This project (18RP01 – ProbeTrace) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme. Project title: Traceability for contact probe and stylus instrument measurements Funder name: European Metrology Programme for Innovation and Research (EMPIR) Funder ID: 10.13039/100014132 Grant number: 18RP01 ProbeTrace Link to project homepage: http://probetrace.org/

Footwall Relief Measurements for faults in the Zomba Graben, Malawi

Footwall releif measurements for faults in the Zomba Graben Malawi. Footwall relief was measured every 1 km along strike using stacked profiles of TanDEM-X topographic data that had been sampled every 100 m along strike. We measured the difference in elevation between the highest point on the footwall within 3 km of the fault surface trace, and the elevation of the fault itself.   #1 - Longitude #2 - Latitude #3 - Footwall Relief (m) #4 - Uncertainty (m)

Spectral dataset of natural light fields measured in the Netherlands

This is a spectral dataset of natural light collected in the Netherlands. The data supplement contains the rural and city cubic irradiance spectra with associated wavelength spacing. We measured natural light fields for sunny weather in the shade and light for 24 rural and urban scenes across multiple days (in total 48 cubic measurements). We also measured natural light fields from dawn till dusk on a sunny day (in total 165 cubic measurements) and a cloudy day (in total 124 cubic measurements). This spectral light-field dataset provides comprehensive illumination statistics useful for understanding biological vision. The data reveal how perceptually meaningful aspects of the light, such as the direction, colour and diffuseness of the main light components, vary over space and time in ecologically valid conditions.

opencc-zeroNov 2022View details →

Surface measurement data of polished LTCC: Characterization of pores in polished low temperature co-fired glass-ceramic composites for optimization of their micromachining

Pores are intrinsic defects of ceramic composites and influence their functional properties significantly. Their characterization is therefore a pivotal task in material and process optimization. It is demonstrated that polished section analysis allows for obtaining precise information on pore size, shape, area fraction, and homogeneous distribution. It is proven that laser scanning microscopy provides accurate height maps and is thus an appropriate technique for assessing surface features. Such data is used to compare areas with good and poor polishing results, and various surface parameters are evaluated in terms of their informative value and data processing effort. The material under investigation is a low-temperature co-fired ceramic composite. Through statistical analysis of the data, the inclination angle was identified as an appropriate parameter to describe the polishing result. By using masked data, direct conclusions can be drawn about the leveling of load-bearing surface areas, which are crucial in photolithographic processing steps and bonding technology. A broad discussion of different defects based on the results contributes to a critical analysis of the potentials and obstacles of micromachining of low-temperature cofired ceramic substrates.

opencc-zeroNov 2022View details →

Data from: Measurement of stress-induced sympathetic nervous activity using multi-wavelength photoplethysmography

The onset of stress triggers sympathetic arousal (SA), which causes detectable changes to physiological parameters such as heart rate, blood pressure, dilation of the pupils and sweat release. The objective quantification of SA has tremendous potential to prevent and manage psychological disorders. Photoplethysmography (PPG), a non-invasive method to measure skin blood flow changes, has been used to estimate SA indirectly. However, the impact of various wavelengths of the PPG signal has not been investigated for estimating SA. In this study, we explore the feasibility of using various statistical and nonlinear features derived from peak-to-peak (AC) values of PPG signals of different wavelengths (green, blue, infrared and red) to estimate stress-induced changes in SA and compare their performances. The impact of two physical stressors, Cold Pressor and Hand Grip, is studied on 32 healthy individuals. The results show that the nonlinear features are the most promising in detecting stress-induced sympathetic activity. TotalSampEn feature was capable of detecting stress-induced changes in SA for all wavelengths, whereas other features (Petrosian, AvgSampEn) are significant (AUC≥0.8$) only for IR and Red wavelengths. The outcomes of this study can be used to make device design decisions as well as develop stress detection algorithms.

Ice draft measurements from NABOS ULS, 2013-2015 at 82N 97E

This data was obtained from the mooring of Nansen and Amundsen Basins Observational System (NABOS) at 82°N 97°E (the north coast of Severnaya Zemlya Archipelago). This mooring was deployed in September 2013 and recovered in September 2015.

Identifying mountain permafrost degradation by repeating historical ERT-measurements - supplement

Ongoing global warming affects the degradation of mountainous permafrost. Permafrost thawing impacts landform evolution, reduces fresh water resources, enhances the potential of natural hazards, and thus has significant socio-economic impact. Electrical resistivity tomography (ERT) has been widely used to map the ice-containing permafrost by its resistivity contrast compared to the surrounding non-frozen medium. We analyse the temporal changes in the resistivity distribution by comparing historical with recently measured ERT profiles. Three periglacial landforms (two rock glaciers and one talus slope) are surveyed in the Swiss and Austrian Alps by repeating historical field campaigns after periods of 10, 12, and 16 years, respectively. The resistivity values have been significantly reduced concerning ice-poor permafrost at all study sites. Interestingly, resistivity values related to ice-rich permafrost in the studied active rock glacier partly increased during the studied time period. To explain this apparent contradictory (in view of observed increase) observation, geomorphological circumstances, such as the relief and creeping behaviour of the active rock glacier, are discussed. Additional remote sensing data indicates an increased velocity in and around the active part with increased resistivity. The present study highlights alpine permafrost degradation resulting from ever-accelerating global warming.

opencc-by-4.0Sep 2022View details →

Aerodynamic characterisation of porous fairings : pressure drop and Laser Doppler Velocimetry measurements

Aviation has become a mass transportation industry, and all prospective studies foresee growth in this sector. Among the challenges, noise in the vicinity of airports has gone from a marginal annoyance to a real public health concern. To address this problem, as well as others such as fuel consumption, aircraft manufacturers are considering radically new aircraft architectures that could enter service quickly. In the meantime, however, the noise of traditional aircraft must be reduced significantly. Aircraft noise, during takeoff and landing, results primarily from a combination of (i) engine noise, which is generated by the fan and jet, and (ii) airframe noise, primarily due to the landing gear (LG) and high lift devices (HLD), the latter including slats and trailing edge flaps, which are deployed at low speeds to increase lift. During takeoff, engine noise remains dominant, while on approach and landing, engines operate at low speeds (typically 50% of N1), and airframe noise becomes a significant contributor, especially for newer aircraft equipped with latest generation turbofans. Its mitigation is therefore of primary interest. However, due to the strong integration constraints imposed by other disciplines than acoustics on components such as LGs and HLDs, the development of noise reduction technologies (NRT) on these airframe components has been limited. This lack of breakthroughs is also due to the complexity of flow physics, and thus our still limited knowledge of airframe noise generation mechanisms. The noise of the landing gear, slats and flaps has been studied on a real and reduced scale, mainly on the basis of experimental means. The maturity of numerical simulations now allows to study the mechanisms of the noise sources on various complex configurations. Moreover, numerical simulation methods can be sufficiently accurate to predict the noise generated by such configurations. In order to take the next step in the maturity of numerical prediction, these NIRs must be accurately evaluated and modeled. Experimental data based on academic configurations are therefore needed to validate the new tools and numerical models. One promising NRT is the use of a fairing in front of the landing gear to reduce the noise of this system. The present study aims at collecting an experimental database (pressure drop and turbulence characteristics) of several fairing solutions in order to have validation test cases for CFD simulation and thus develop new models for such complex geometries. The fairing samples are thus tested on the "Acoustic and Aerothermal Bench" (B2A), by measuring the pressure drop of each sample and the flow field by Laser Doppler Velocimetry (LDV). The experimental methodology will be presented first. The database will then be described. Some technical validations will also be proposed on the basis of a comparison with the literature.

High-resolution large weighing lysimeter measurements with meteorological and soil-hydrological variables from a Mediterranean Savanna

Raw and processed lysimeter weighing and flux data at the instrumental site ES-LMa of six large high-precision weighing lysimeters in a Mediterranean Savanna ecosystem for the period from 2019-06-01 to 2020-05-31. Additionally, meteorological and radiometric data are provided. Additionally, code for the lysimeter processing is provided. Reproducible workflow of the article Paulus et al. 2022: Resolving seasonal and diel dynamics of non-rainfall water inputs in a Mediterranean ecosystem using lysimeters. HESS, https://doi.org/10.5194/hess-2021-519 Variables, units and detailed description are found in the README.html file.

Comparison of Large Eddy Simulations against measurements from the Lillgrund offshore wind farm - Manuscript data

Time averaged power and farm inflow velocity for the manuscript "Comparison of Large Eddy Simulations against measurements from the Lillgrund offshore wind farm" for publication in the wind energy science journal. Data is uploaded for the 5 simulation cases covered. 'Power' files contain average power production for 48 turbines. First row corresponds to LES data, second row corresponds to SCADA data from the Lillgrund wind farm. 'Velocity' files contain inflow mean velocity measurements at the 72 range gate locations. First row corresponds to LES inflow data, second row corresponds to LIDAR inflow data from the Lillgrund wind farm.

SNAPPING PSI surface motion measurements over selected sites presented in MDPI Remote Sensing paper "SNAPPING Services on the Geohazards Exploitation Platform for Copernicus Sentinel-1 Surface Motion Mapping"

SNAPPING PSI surface motion measurements over selected sites as presented in the paper with the title "SNAPPING Services on the Geohazards Exploitation Platform for Copernicus Sentinel-1 Surface Motion Mapping"  by Michael Foumelis, Jose Manuel Delgado Blasco, Fabrice Brito, Fabrizio Pacini, Elena Papageorgiou, Panteha Pishehvar and Philippe Bally on Remote Sensing Open Access Journal. Whenever using this dataset, please cite its original paper (<a href="https://doi.org/10.3390/rs14236075">https://doi.org/10.3390/rs14236075</a>) and include the reference to this dataset (<a href="https://doi.org/10.5281/zenodo.7369653">https://doi.org/10.5281/zenodo.7369653</a>). This dataset includes average Line-of-Sight velocities for the following sites and dates: <table> <tbody> <tr> <td>Site name</td> <td>Country</td> <td>Period</td> <td>Relative orbit</td> <td>Orbit direction</td> </tr> <tr> <td>Cap-Haïtien</td> <td>Haiti</td> <td>Jan-2017 / Dec-2019</td> <td>106</td> <td>ascending</td> </tr> <tr> <td>Gran Renaissance Ethiopian Dam</td> <td>Ethiopia</td> <td>Jan-2019 / Jun-2021</td> <td>50</td> <td>descending</td> </tr> <tr> <td>La Palma Volcano</td> <td>Spain</td> <td>Jun-2019 / Dec-2021</td> <td>169</td> <td>descending</td> </tr> <tr> <td>Santorini Volcano</td> <td>Greece</td> <td>Apr-2015 / May-2021</td> <td>29</td> <td>ascending</td> </tr> <tr> <td>San Francisco</td> <td>USA</td> <td>Jan-2016 / Dec-2020</td> <td>115</td> <td>descending</td> </tr> <tr> <td>Thessaloniki International Airport (SKG)</td> <td>Greece</td> <td>Apr-2015 / Dec-2020</td> <td>102</td> <td>ascending</td> </tr> </tbody> </table>

opencc-zeroDec 2022View details →

Data for: Triose phosphate utilization stress during photosynthesis addressed with dynamic assimilation measurements

Oscillations in CO2 assimilation rate and associated fluorescence parameters have been observed alongside the triose phosphate utilization (TPU) limitation of photosynthesis for nearly 50 years. However, the mechanics of these oscillations are poorly understood. Here we utilize the recently developed Dynamic Assimilation Techniques (DAT) for measuring the rate of CO2 assimilation to increase our understanding of what physiological condition is required to cause oscillations. We found that TPU limiting conditions alone were insufficient, and that plants must enter TPU limitation quickly to cause oscillations. We found that ramps of CO2 caused oscillations proportional in strength to the speed of the ramp, and that ramps induce oscillations with worse outcomes than oscillations induced by step change of CO2 concentration. An initial overshoot is caused due to a temporary excess of available phosphate. During the overshoot, the plant out-performs steady state TPU and ribulose 1,5-bisphosphate regeneration limitations of photosynthesis but cannot exceed the rubisco limitation. We performed additional optical measurements which support the role of photosystem I reduction and oscillations in availability of NADP+ and ATP in supporting oscillations.

opencc-by-4.0Dec 2022View details →

Sound pressure measurements and calculation of the cavitation volume for a full-scale 3500 TEU container vessel

Supplementary material comprising measurement data and MATLAB code corresponding to the published research article.

Simultaneous dynamic glucose-enhanced (DGE) MRI and fiber photometry measurements of glucose in the healthy mouse brain

This dataset was acquired for the DGE and fiber photometry study published in NeuroImage ( <a href="https://doi.org/10.1016/j.neuroimage.2022.119762">https://doi.org/10.1016/j.neuroimage.2022.119762</a>). Comprises of three datasets: DGE MRI, fiber photometry and two-photon microscopy.