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1,034 results for “HOT”
Data of the publication Hot ion implantation to create dense NV center ensembles in diamond
<p>Data of the publication published under the reference: M.W.<em> </em>Ngambeu Ngambou, Appl. Phys. Lett. 124, 134002 (2024).</p>
The metal content of the hot atmospheres of galaxy groups - supporting data
<p>Supporting data used to generate the figures included in the review chapter "The metal content of the hot atmospheres of galaxy groups", to appear in the MDPI journal "Universe". These values were collected and compiled from existing literature; each text file lists the relevant references to the original articles where various sets of results were initially published. </p>
Supplementary Information to: "Living on the edge: Response of rudist bivalves (Hippuritida) to hot and highly seasonal climate in the low-latitude Saiwan site, Oman"
<p>This dataset contains supplementary information required to understand and reproduce the study detailed in our manuscript titled "<em>Living on the edge: Response of rudist bivalves (Hippuritida) to hot and highly seasonal climate in the low-latitude Saiwan site, Oman</em>" which was submitted for publication to Palaeogeography, Palaeoclimatology, Palaeoecology.</p>
Measuring Bulk Crystallographic Texture from Ti-6Al-4V Hot-Rolled Sample Matrices using Synchrotron X-ray Diffraction (Analysis Dataset)
<p>A dataset of synchrotron X-ray diffraction (SXRD) analysis files, recording the refinement of crystallographic texture from a number of Ti-6Al-4V (Ti-64) sample matrices, containing a total of 93 hot-rolled samples, from three different orthogonal sample directions. The aim of the work was to accurately quantify bulk macro-texture for both the α (hexagonal close packed, hcp) and β (body-centred cubic, bcc) phases across a range of different processing conditions.</p> <p><strong>Material </strong></p> <p>Prior to the experiment, the Ti-64 materials had been hot-rolled at a range of different temperatures, and to different reductions, followed by air-cooling, using a rolling mill at The University of Manchester. Rectangular specimens (6 mm x 5 mm x 2 mm) were then machined from the centre of these rolled blocks, and from the starting material. The samples were cut along different orthogonal rolling directions and are referenced according to alignment of the rolling directions (RD – rolling direction, TD – transverse direction, ND – normal direction) with the long horizontal (X) axis and short vertical (Y) axis of the rectangular specimens. Samples of the same orientation were glued together to form matrices for the synchrotron analysis. The material, rolling conditions, sample orientations and experiment reference numbers used for the synchrotron diffraction analysis are included in the data as an excel spreadsheet.</p> <p><strong>SXRD Data Collection </strong></p> <p>Data was recorded using a high energy 90 keV synchrotron X-ray beam and a 5 second exposure at the detector for each measurement point. The slits were adjusted to give a 0.5 x 0.5 mm beam area, chosen to optimally resolve both the α and β phase peaks. The SXRD data was recorded by stage-scanning the beam in sequential X-Y positions at 0.5 mm increments across the rectangular sample matrices, containing a number of samples glued together, to analyse a total of 93 samples from the different processing conditions and orientations. Post-processing of the data was then used to sort the data into a rectangular grid of measurement points from each individual sample.</p> <p><strong>Diffraction Pattern Averaging </strong></p> <p>The stage-scan diffraction pattern images from each matrix were sorted into individual samples, and the images averaged together for each specimen, using a Python notebook <a href="https://github.com/LightForm-group/sxrd-tiff-summer">sxrd-tiff-summer</a>. The averaged .tiff images each capture average diffraction peak intensities from an area of about 30 mm<sup>2</sup> (equivalent to a total volume of ~ 60 mm<sup>3</sup>), with three different sample orientations then used to calculate the bulk crystallographic texture from each rolling condition.</p> <p><strong>SXRD Data Analysis </strong></p> <p>A new Fourier-based peak fitting method from the <a href="https://pypi.org/project/continuous-peak-fit/">Continuous-Peak-Fit</a> Python package was used to fit full diffraction pattern ring intensities, using a range of different lattice plane peaks for determining crystallographic texture in both the α and β phases. Bulk texture was calculated by combining the ring intensities from three different sample orientations.</p> <p>A .poni calibration file was created using <a href="http://www.clemensprescher.com/programs/dioptas">Dioptas</a>, through a refinement matching peak intensities from a LaB6 or CeO2 standard diffraction pattern image. Two calibrations were needed as some of the data was collected in July 2022 and some of the data was collected in August 2022. Dioptas was then used to determine peak bounds in 2θ for characterising a total of 22 α and 4 β lattice plane rings from the averaged Ti-64 diffraction pattern images, which were recorded in a .py input script. Using these two inputs, Continuous-Peak-Fit automatically converts full diffraction pattern rings into profiles of intensity versus azimuthal angle, for each 2θ section, which can also include multiple overlapping α and β peaks.</p> <p>The Continuous-Peak-Fit refinement can be launched in a notebook or from the terminal, to automatically calculate a full mathematical description, in the form of Fourier expansion terms, to match the intensity variation of each individual lattice plane ring. The results for peak position, intensity and half-width for all 22 α and 4 β lattice plane peaks were recorded at an azimuthal resolution of 1º and stored in a .fit output file. Details for setting up and running this analysis can be found in the <a href="https://github.com/LightForm-group/continuous-peak-fit-analysis">continuous-peak-fit-analysis</a> package. This package also includes a Python script for extracting lattice plane ring intensity distributions from the .fit files, matching the intensity values with spherical polar coordinates to parametrise the intensity distributions from each of the three different sample orientations, in the form of pole figures. The script can also be used to combine intensity distributions from different sample orientations. The final intensity variations are recorded for each of the lattice plane peaks as text files, which can be loaded into MTEX to plot and analyse both the α and β phase crystallographic texture.</p> <p><strong>Metadata </strong></p> <p>An accompanying YAML text file contains associated SXRD beamline metadata for each measurement. The raw data is in the form of synchrotron diffraction pattern .tiff images which were too large to upload to Zenodo and are instead stored on The University of Manchester's Research Database Storage (RDS) repository. The raw data can therefore be obtained by emailing the authors.</p> <p>The material data folder documents the machining of the samples and the sample orientations.</p> <p>The associated processing metadata for the Continuous-Peak-Fit analyses records information about the different packages used to process the data, along with details about the different files contained within this analysis dataset.</p>
Measuring Bulk Crystallographic Texture from Ti-6Al-4V Hot-Rolled Sample Matrices using Synchrotron X-ray Diffraction (Results Dataset)
<p>A dataset of crystallographic texture results for both α (hexagonal close packed, hcp) and β (body-centred cubic, bcc) phases, measured from 31 different hot-rolled Ti-6Al-4V (Ti-64) materials and 3 differently orientated samples using synchrotron X-ray diffraction (SXRD). The aim of the work was to accurately quantify bulk macro-texture for both the α and β phases across a range of different processing conditions, and to compare results with electron backscatter diffraction (EBSD) measurements. The synchrotron intensities were extracted using a new Fourier-based peak fitting method from the <a href="https://pypi.org/project/continuous-peak-fit/">Continuous-Peak-Fit</a> Python package, and then directly used to calculate the pole figures, orientation distribution functions (ODFs) and numerical values for the texture indices in <a href="https://mtex-toolbox.github.io">MTEX</a></p> <p><strong>Material </strong></p> <p>The Ti-64 materials had been hot-rolled at a range of different temperatures, and to different reductions, followed by air-cooling. Three samples of different orientation were cut from the centre of these rolled blocks, and from the starting material. The material and hot-rolling conditions are recorded in this <a href="https://doi.org/10.5281/zenodo.7438090">analysis dataset</a> as an excel spreadsheet and summarised in the table below.</p> <table align="center"> <caption>A table recording the sample number and associated hot-rolling condition.</caption> <tbody> <tr> <td> <p><em><strong>Sample Number</strong></em></p> </td> <td> <p><em><strong>Rolling Condition</strong></em></p> </td> </tr> <tr> <td>1</td> <td>825ºC, 87.5% Reduction</td> </tr> <tr> <td>2</td> <td>865ºC, 87.5% Reduction</td> </tr> <tr> <td>3</td> <td>895ºC, 87.5% Reduction</td> </tr> <tr> <td>4</td> <td>915ºC, 87.5% Reduction</td> </tr> <tr> <td>5</td> <td>935ºC, 87.5% Reduction</td> </tr> <tr> <td>6</td> <td>950ºC, 87.5% Reduction</td> </tr> <tr> <td>7</td> <td>960ºC, 87.5% Reduction</td> </tr> <tr> <td>8</td> <td>975ºC, 87.5% Reduction</td> </tr> <tr> <td>9</td> <td>1020ºC, 87.5% Reduction</td> </tr> <tr> <td>10</td> <td>β-annealed, 825ºC, 87.5% Reduction</td> </tr> <tr> <td>11</td> <td>β-annealed, 915ºC, 87.5% Reduction</td> </tr> <tr> <td>12</td> <td>β-annealed, 975ºC, 87.5% Reduction</td> </tr> <tr> <td>13</td> <td>Reduced heating from 915ºC, 87.5% Reduction</td> </tr> <tr> <td>14</td> <td>Reduced heating from 975ºC, 87.5% Reduction</td> </tr> <tr> <td>15</td> <td>825ºC, 75% Reduction</td> </tr> <tr> <td>16</td> <td>865ºC, 75% Reduction</td> </tr> <tr> <td>17</td> <td>895ºC, 75% Reduction</td> </tr> <tr> <td>18</td> <td>915ºC, 75% Reduction</td> </tr> <tr> <td>19</td> <td>935ºC, 75% Reduction</td> </tr> <tr> <td>20</td> <td>950ºC, 75% Reduction</td> </tr> <tr> <td>21</td> <td>960ºC, 75% Reduction</td> </tr> <tr> <td>22</td> <td>975ºC, 75% Reduction</td> </tr> <tr> <td>23</td> <td>1020ºC, 75% Reduction</td> </tr> <tr> <td>24</td> <td>β-annealed, 825ºC, 75% Reduction</td> </tr> <tr> <td>25</td> <td>β-annealed, 915ºC, 75% Reduction</td> </tr> <tr> <td>26</td> <td>β-annealed, 975ºC, 75% Reduction</td> </tr> <tr> <td>27</td> <td>Reduced heating from 915ºC, 75% Reduction</td> </tr> <tr> <td>28</td> <td>Reduced heating from 975ºC, 75% Reduction</td> </tr> <tr> <td>29</td> <td>As-received</td> </tr> <tr> <td>30</td> <td>As-received, β-annealed</td> </tr> <tr> <td>31</td> <td>975ºC, 50% Reduction</td> </tr> </tbody> </table> <p><strong>MTEX Data Analysis</strong></p> <p>The lattice plane intensities for 22 α and 4 β phase peaks were extracted from the Continuous-Peak-Fit analysis, also included in this <a href="https://doi.org/10.5281/zenodo.7438090">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, texture indices and texture component phase fractions. A kernel half-width of 10° was found to produce optimal data fitting, for highly accurate texture strength intensity values.</p> <p><strong>Metadata </strong></p> <p>An accompanying YAML text file contains associated processing metadata for the SXRD analysis, recording information about the packages used to process the data, along with details about the different files contained within this results dataset.</p>
Spray impact onto a hot solid substrate: film boiling suppression by lubricant addition. Supplementary Data
<p>This is a Supplementary Data for a paper entitled "Spray impact onto a hot solid substrate: film boiling suppression by lubricant addition" by Gajevic Joksimovic et al. <em>Frontiers in Physics </em>(2023).</p> <p><strong>Data used for plotting of figures</strong></p> <p><em>Datasets for Fig. 5: </em></p> <p>Number at the end of the file name corresponds to the volumetric lubricant concentration used.</p> <ul> <li> Dataset_Figure5 TimeTemperatatureFlux Concentration 0.97.txt</li> <li> Dataset_Figure5 TimeTemperatatureFlux Concentration 1.09.txt</li> <li> Dataset_Figure5 TimeTemperatatureFlux Concentration 1.26.txt </li> <li> Dataset_Figure5 TimeTemperatatureFlux Concentration 1.49.txt</li> <li> Dataset_Figure5 TimeTemperatatureFlux Concentration 1.82.txt</li> <li> Dataset_Figure5 TimeTemperatatureFlux Concentration 2.34.txt</li> <li> Dataset_Figure5 TimeTemperatatureFlux Concentration 3.28.txt</li> <li> Dataset_Figure5 TimeTemperatatureFlux Concentration 5.47.txt</li> <li> Dataset_Figure5 TimeTemperatatureFlux PureWater.txt</li> </ul> <p><em>Datasets for Fig. 11:</em></p> <ul> <li>Dataset_Figure11 PHI Omega Omega nu.txt</li> </ul> <p><strong>Supplementary videos</strong></p> <p><em>The supplementary videos for Fig. 8</em>:</p> <ul> <li>supplementary video Figure8a.mp4</li> <li>supplementary video Figure9b.mp4</li> <li>supplementary video Figure9c.mp4</li> </ul> <p><em>The supplementary video for Fig. 13</em></p> <ul> <li>supplementary video Figure13.mp4</li> </ul>
Lovebirds perch in building vents to cool down during hot times of year, a study of rosy-cheeked lovebirds (Agapornis roseicollis) in the Phoenix, Arizona, USA metropolitan area (2018-2019)
Extreme heat can place significant environmental and physiological pressures on animals. One means of tolerating extreme thermal conditions is to seek cool microclimates. Few empirical studies have documented use by wild animals of human-provided cool microsites as means of thermoregulating. Here we show that rosy-cheeked lovebirds in Phoenix, Arizona – the hottest city in North America – use relief air vents on the face of a building (which direct cool air outdoors when internal air-conditioning systems are on) as perching sites, and only during extremely hot times of day and year (> 45 C). Though this highlights a wasteful anthropogenic energy system (the product of an old building with outdated temperature-control technology), our results reveal how an introduced bird species (from Africa) can tolerate extreme thermal conditions in the novel environment.
Thermal model of the Los Humeros super-hot geothermal system, Mexico
<p>The dataset contains 3D thermal model (format - .vtk and .h5) of Los Humeros geothermal system at a local scale (extent defined in Calcagno et al., 2018). The boundary conditions used for this thermal model are obtained from Scenario 3b of regional model discussed in<strong> </strong>EU Deliverable D6.3<strong> </strong>(<a href="http://doi.org/10.5281/zenodo.3723039">10.5281/zenodo.3723039</a>) and D6.6 (<a href="https://doi.org/10.5281/zenodo.3723224">10.5281/zenodo.3723224</a>).</p> <p>Before using the results of the model, the user is advised to carefully read the model parameters, assumptions and uncertainties associated with the model as reported in Deliverable D6.3 and Deliverable D6.6.</p> <ol> <li>The .h5 file contains data and attributes (quantity, unit)</li> <li>The .vtk files contains the following information <ul> <li>x, y, z UTM coordinates (m)</li> <li>temp Temperature (°C)</li> <li>head Hydraulic head (m)</li> <li>pres Pressure (MPa)</li> <li>por Porosity (-)</li> <li>q Heat flow (W m<sup>-2</sup>)</li> <li>kx, ky, kz Permeability (m<sup>2</sup>)</li> <li>vx, vy, vz Specific discharge or Darcy velocity (m s<sup>-1</sup>)</li> <li>lx, ly, lz Thermal conductivity (W m<sup>-1</sup> K<sup>-1</sup>)</li> </ul> </li> </ol> <p>Additional information regarding the model is presented in the PDF document.</p>
2D EBSD Dataset of the Alpha and Beta Phase Orientations for a Hot-Rolled Model Zircaloy-4 with 7 wt.% Nb Alloy
<p>A set of electron backscatter diffraction (EBSD) data files for a model Zircaloy-4 with 7 wt.% Nb addition alloy following hot-rolling. </p> <p>The 2D data set contains EBSD maps recording the microstructure and texture evolution, from a beta-processed (and annealed) starting condition, following rolling at a temperature of 725C to 50% and 75% reduction. Data for annealing of the rolled materials (750C for 2 hours) is also included. <em>Note, phases in the ctf files marked as 'Titanium Cubic' refer to measurement of the 'Zirconium Cubic' phase.</em></p> <p>Please see our accompanying paper for analysis of the 2D measurements - as well as analysis of a 3D reconstruction from <a href="https://doi.org/10.5281/zenodo.3785084">10.5281/zenodo.3785084</a> - and for interpretation of the coupled crystallographic texture evolution;</p> <p>C.S. Daniel, A. Garner, P.D. Honniball, L. Bradley, M. Preuss, P.B. Prangnell, J. Quinta da Fonseca, Co-deformation and dynamic annealing effects on the texture development during alpha–beta processing of a model Zr-Nb alloy, Acta Materialia 205 (2021) 116538. <a href="https://doi.org/10.1016/j.actamat.2020.116538">10.1016/j.actamat.2020.116538</a></p>
Sign-specific stimulation "hot" and "cold" spots in Parkinson's disease validated with machine learning
<p><strong>Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become a standard therapy for Parkinson’s disease (PD). Despite extensive experience, however, the precise target of optimal stimulation and the relationship between site of stimulation and alleviation of individual signs remains unclear. We examined whether machine learning could predict the benefits in specific parkinsonian signs when informed by precise locations of stimulation.</strong></p> <p> </p> <p><strong>We studied 275 PD patients who underwent STN-DBS between 2003 and 2018. We selected pre-DBS and best available post-DBS scores from motor items of the Unified Parkinson's Disease Rating Scale (UPDRS-III) to discern sign-specific changes attributable to DBS. Volumes of tissue activated (VTAs) were computed and weighted by i) tremor, ii) rigidity, iii) bradykinesia, and iv) axial signs changes. Then, sign-specific sites of optimal (“hot spots”) and suboptimal efficacy (“cold spots”) were defined. These areas were subsequently validated using machine learning prediction of sign-specific outcomes with in-sample and out-of-sample data (n=51 STN-DBS patients from another institution).</strong></p> <p><strong> </strong></p> <p><strong>Tremor and rigidity hot spots were largely located outside and dorsolateral to STN whereas hot spots for bradykinesia and axial signs had larger overlap with STN. Using VTA overlap with sign-specific hot and cold spots, support vector machine (SVM) classified patients into quartiles of efficacy with ≥92% accuracy. The accuracy remained high (68-98%) when only considering VTA overlap with hot spots but was markedly lower (41-72%) when only using cold spots. The model also performed poorly (44-48%) when using only stimulation voltage, irrespective of stimulation location. Out-of-sample validation accuracy was ≥96% when using VTA overlap with the sign-specific hot and cold spots.</strong></p> <p><br> <strong>In two independent datasets, distinct brain areas could predict sign-specific clinical changes in PD patients with STN-DBS. With future prospective validation, these findings could individualize stimulation delivery to optimize quality of life improvement. </strong></p> <p><strong>Hot and cold spots for each sign are publicly available as binary labels in NIfTI format. </strong></p>
Classifying hot water chemistry: Application of MULTIVARIATE STATISTICS - Dataset
<p>These files are the dataset for the following paper "Classifying hot water chemistry: Application of MULTIVARIATE STATISTICS". Authors: Prihadi Sumintadireja<sup>1</sup>, Dasapta Erwin Irawan<sup>1</sup>, Yuano Rezky<sup>2</sup>, Prana Ugiana Gio<sup>3, </sup>Anggita Agustin<sup>1</sup></p>
Dataset to accompany publication "Distinguishing Inner and Outer-Sphere Hot Electron Transfer in Au/p-GaN Photocathodes"
<p>This dataset accompanies the publication "Distinguishing Inner and Outer-Sphere Hot Electron Transfer in Au/p-GaN Photocathodes" published in Nano Letters. The data can be used to reproduce the original plots in figures 2-4 in the main text and all original plots in figures S1-S13 in the supporting information. All files are in .xlsx and easily readable. <br>The abstract for the associated paper is as follows:<br>Exploring nonequilibrium hot carriers from plasmonic metal nanostructures is a dynamic field in optoelectronics, with applications including photochemical reactions for solar fuel generation. The hot carrier injection mechanism and the reaction rate are highly impacted by the metal/molecule interaction. However, determining the primary type of the reaction and thus the injection mechanism of hot carriers has remained elusive. In this work, we reveal an electron injection mechanism deviating from a purely outer-sphere process for the reduction of ferricyanide redox molecule in a gold/p-type gallium nitride (Au/p-GaN) photocathode system. Combining our experimental approach with ab-initio simulations, we discover that an efficient inner-sphere transfer of low-energy electrons leads to an enhancement in the photocathode device performance in the interband regime. These findings provide important mechanistic insights, showing our methodology as a powerful tool for analyzing and engineering hot-carrier-driven processes in plasmonic photocatalytic systems and optoelectronic devices.</p>
Global dry and hot extreme events detection
<p>Workflow for the global detection of dry and hot extreme weather events. ERA5 is the ECMWF Reanalysis of the climate. PET is potential reference evapotranspiration. PEI is the daily difference between precipitation and evapotranspiration averaged over the preceding days (here 30, 90 and 180). Data cubes are stored in zarr format. Statistics are saved in a csv table.</p>
Reproduction package for "A strong H− opacity signal in the near-infrared emission spectrum of the ultra-hot Jupiter KELT-9b"
<p>This is a basic reproduction package for the paper "A strong H− opacity signal</p><p>in the near-infrared emission spectrum of the ultra-hot Jupiter KELT-9b"</p><p>by [Jacobs, B.; Désert, J. -M.; Pino, L. et al. (2022)](https://doi.org/10.1051/0004-6361/202244533).</p><p> </p><p>Abstract:</p><p>We present the analysis of a spectroscopic secondary eclipse of the hottest transiting exoplanet detected to date, KELT-9b, obtained with the Wide Field Camera 3 aboard the <i>Hubble</i> Space Telescope. We complement these data with literature information on stellar pulsations and <i>Spitzer</i>/Infrared Array Camera and Transiting Exoplanet Survey Satellite eclipse depths of this target to obtain a broadband thermal emission spectrum. Our extracted spectrum exhibits a clear turnoff at 1.4 μm. This points to H− bound-free opacities shaping the spectrum. To interpret the spectrum, we perform grid retrievals of self-consistent 1D equilibrium chemistry forward models, varying the composition and energy budget. The model with solar metallicity and C/O ratio provides a poor fit because the H− signal is stronger than expected, requiring an excess of electrons. This pushes our retrievals toward high atmospheric metallicities ([M/H] = 1.98−0.21+0.19) and a C/O ratio that is subsolar by 2.4<i>σ</i>. We question the viability of forming such a high-metallicity planet, and therefore provide other scenarios to increase the electron density in this atmosphere. We also look at an alternative model in which we quench TiO and VO. This fit results in an atmosphere with a slightly subsolar metallicity and subsolar C/O ratio ([M/H] = −0.22−0.13+0.17, log (C/O) = −0.34−0.34+0.19). However, the required TiO abundances are disputed by recent high-resolution measurements of the same planet.</p>
HPF data for "A Large and Variable Leading Tail of Helium in a Hot Saturn Undergoing Runaway Inflation"
<p>Data from the Habitable Zone Planet Finder (HPF) Spectrograph at McDonald Observatory, in the form of high resolution infrared echelle spectra. The target is HAT-P-67, a planet host star. The spectra were acquired by Queue observations with the Hobby Eberly Telescope in the period 2020-2022. The data were reduced with the "Goldilocks" pipeline. The full dataset is described in detail in the paper "A Large and Variable Leading Tail of Helium in a Hot Saturn Undergoing Runaway Inflation". </p> <p>The abstract for that paper is reproduced below:</p> <div> <div>Atmospheric escape shapes the fate of exoplanets, with statistical evidence for transformative mass loss imprinted across the mass-radius-insolation distribution. Here we present transit spectroscopy of the highly irradiated, low-gravity, inflated hot Saturn HAT-P-67 b. The Habitable Zone Planet Finder (HPF) spectra show a detection of up to 10% absorption depth of the 10833 Angstrom Helium triplet. The 13.8 hours of on-sky integration time over 39 nights sample the entire planet orbit, uncovering excess Helium absorption preceding the transit by up to 130 planetary radii in a large leading tail. This configuration can be understood as the escaping material overflowing its small Roche lobe and advecting most of the gas into the stellar---and not planetary---rest frame, consistent with the Doppler velocity structure seen in the Helium line profiles. The prominent leading tail serves as direct evidence for dayside mass loss with a strong day-/night- side asymmetry. We see some transit-to-transit variability in the line profile, consistent with the interplay of stellar and planetary winds. We employ 1D Parker wind models to estimate the mass loss rate, finding values on the order of 2x10^13 g/s, with large uncertainties owing to the unknown XUV flux of the F host star. The large mass loss in HAT-P-67 b represents a valuable example of an inflated hot Saturn, a class of planets recently identified to be rare as their atmospheres are predicted to evaporate quickly. We contrast two physical mechanisms for runaway evaporation: Ohmic dissipation and XUV irradiation, slightly favoring the latter.</div> </div>
Processing, Spectroscopic and Laboratory Testing Data from a Medical Grade Hot-Melt Extrusion Process
<p>This dataset contains a collection of raw processing data, spectroscopic data, and laboratory test results of medical-grade polymer extrusion experiments. The data was collected in several experiments conducted in a hot-melt extrusion process. The process involved extruding PLA through a slit die and drawing the extruded strands onto spools to obtain the desired dimensional and mechanical properties. The strands were later knitted to form the final medical implant. Throughout the experiments, the extrusion process and equipment were upgraded and refined. Various operational scenarios were simulated under different nozzle configurations. The experiments start using a single-screw extruder and later progress to a double-screw extruder. Medical Grade PURASORB PLA (PLDLA 96/4) material was used when the hardware upgrades were complete. This dataset contains many variations in experimental conditions. However, enough overlap exists to derive working datasets from this compiled raw data.</p> <p> </p> <p>Two working datasets have been derived from this compiled raw data. Using a double-screw extruder, both working Datasets investigate polymer degradation in the hot-melt extrusion process. Both derived datasets are included in this collection.</p> <p> </p> <p>Two Jupyter notebooks are included in this data collection. The first notebook gives an example of how an initial dataset can be derived from the raw data using data science techniques. The second notebook gives an example of how a final dataset can be created from the initial dataset.</p>
Products and Models for "Nightside clouds and disequilibrium chemistry on the hot Jupiter WASP-43b"
<p>Hot Jupiters are among the best-studied exoplanets, but it is still poorly understood how their chemical composition and cloud properties vary with longitude. Theoretical models predict that clouds may condense on the nightside and that molecular abundances can be driven out of equilibrium by zonal winds. Here we report a phase-resolved emission spectrum of the hot Jupiter WASP-43b measured from 5-12 μm with JWST's Mid-Infrared Instrument (MIRI). The spectra reveal a large day-night temperature contrast (with average brightness temperatures of 1524±35 and 863±23 Kelvin, respectively) and evidence for water absorption at all orbital phases. Comparisons with three-dimensional atmospheric models show that both the phase curve shape and emission spectra strongly suggest the presence of nightside clouds which become optically thick to thermal emission at pressures greater than ~100 mbar. The dayside is consistent with a cloudless atmosphere above the mid-infrared photosphere. Contrary to expectations from equilibrium chemistry but consistent with disequilibrium kinetics models, methane is not detected on the nightside (2σ upper limit of 1-6 parts per million, depending on model assumptions).</p>
Upcycling food ingredients from orange by-products by hot air-microwave drying. Impact on energy consumption.
<p>Currently industrial citrus by-products represent a relevant environmental issue. The main aim of this work was the chemical characterization of the different bioactive compounds obtained after hot air-microwave drying (HAD+MW) of orange by-products, and their further conversion into three <strong>upcycled </strong>ingredients with health-related benefits: aqueous extract, ethanolic extract and <strong>dietary fibre</strong>. Total phenolics, antioxidant capacity, individual phenolic acids, flavonoids, limonin and carotenoids were monitored during blanching and colour extraction steps by analysing fresh by-products and process co-products: an aqueous extract rich in polyphenols and an ethanolic extract rich in carotenoids. After drying, the resulting fibre was characterized in terms of chemical composition, soluble and insoluble dietary fibre content and particle size. Technological properties and colour were compared to those of commercial citrus fibre. Energy and time consumption were compared with conventional hot air drying (HAD). Most polyphenols (50-65 %) and limonin (70 %) were extracted during the blanching step. 86 % of carotenoids were removed by soaking in ethanol. The orange fibre obtained had 71.9 g DF/ 100 g and antioxidant properties (205 mg TE/ Kg<sub>dm</sub>). Whiteness, water retention capacity and oil retention capacity were similar to commercial citrus fibre. HAD+MW reduced drying time and energy consumption by up to 50 % compared to HAD.</p>
Figs 6–9. 6 in Deepor Beel - A Ramsar Site Of India: An Interesting Hot-Spot With Its Rich Rotifera Biodiversity
Figs 6–9. 6 = Brachionus dichotomus reductus KOSTE et SHIEL, dorsal view, 7 = Notommata spinata KOSTE et SHIEL, dorsal view, 8 = Keratella edmondsoni AHLSTROM, dorsal view, 9 = Lecane blachei BERZINS, dorsal view
Fig. 1. A in Deepor Beel - A Ramsar Site Of India: An Interesting Hot-Spot With Its Rich Rotifera Biodiversity
Fig. 1. A = map of indicating location Deepor Beel, B = map showing sampling sites (2002–2003 and 2008–2010)
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.