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1,609 results for “Polarization”
Supporting Information for Disclosing Spin-Polarized Bonds on Isolable Molecules
<p>The file corresponds to the Bachelor Thesis of Ms. Elena Paulus. It contains the xyz coordinates of all optimized structures and their corresponding electronic energy in Hartree.</p>
Experimental characterization of transversal-heterogeneous clay mixtures by the spectral induced polarization method
<p>In this folder you will find multiple datasets (*.txt) from SIP measurements of transversal-heterogeneous clay mixtures using spectral induced polarization acquired between April and May 2022. Additionally, we include two python codes to read and process the data.</p> <p>SIP_Plot_ReWrite.py is a python program aimed to process a .res file from a SIP Fuchs III.<br> It gives a .txt file with the frequency, the resistivity, the phase and the associated errors.<br> In order for the program to give the resistivity, you will need to enter the geometric factor of the studied sample.</p> <p><br> The six text files in the folder (excluding README.txt) were created using SIP_Plot_ReWrite.py.</p> <p>IL_1by1.txt and IL_1by1_V2.txt are from two different homogeneous mixtures of illite and water with a concentration of initially 0.01 mol/L of NaCl.<br> MtR_1by1.txt is from a homogeneous mixture of red montmorillonite and water with a concentration of initially 0.01 mol/L of NaCl.</p> <p>IL_MtR_1by2.txt, IL_MtR_1by4.txt and IL_MtR_1by8.txt are from three transversal-heterogeneous mixtures of illite and red montmorillonite with water containing a concentration of initially 0.01 mol/L of NaCl.</p> <p><br> For IL_MtR_1by2.txt, there was one portion of each clay types, occupying a half of the cylindrical container each.</p> <p><br> For IL_MtR_1by4.txt, there was two portions of each clay types, occupying a quarter of the cylindrical container each.</p> <p><br> These two samples were made using the same mixtures as for IL_1by1.txt and MtR_1by1.txt.</p> <p><br> For IL_MtR_1by8.txt, there was four portions of each clay types, occupying an eighth of the cylindrical container each.<br> This sample was made using the same mixtures as for IL_1by1_V2.txt and MtR_1by1.txt.</p> <p><br> TestDoubleColeColeFit.py is a python program which optimizes a double Cole-Cole model by multiplication on SIP data.<br> This program needs a file with the same structure as the .txt file made by SIP_Plot_ReWrite.py.</p>
Data set for the manuscript 'Polarization-controlled chromo-encryption'
<p>In this dataset, there are 1 pdf and 2 zip files.</p> <p>The manuscript (<strong><em>Zenodo OpenData for chromo encryption<em>.</em>pdf</em></strong>) contains the figures of simulated and measured spectra.</p> <p>The corresponding raw data can refer to the 2 zip files (<strong><em>Simulated.zip </em></strong>and<strong><em> </em></strong><strong><em>Measured<em>.</em>pdf</em></strong>).</p>
Data for "Three-Dimensional Broadband Interferometric Mapping and Polarization (BIMAP-3D) Observations of Lightning Discharge Processes" by Shao et al.
<p>Data set for manuscript of “Three-Dimensional Broadband Interferometric Mapping and Polarization (BIMAP-3D) Observations of Lightning Discharge Processes” by Shao et al. submitted to Journal of Geophysical Research-atmosphere</p>
Earthquake rupture front tracked by polarization azimuths: Codes and extra material
<p>Set of matlab codes to calculate the rupture front position and migration speed every second starting from a set of SAC files.</p> <p>delays_turkey_event.m needs as input SAC files and returns a set of figures displaying the rupture front position and migrations speed. It needs some ad-hoc functions that are contained in this repository. </p> <p>list_of_accelerometers.txt contains the list of instruments processed in the code. </p> <p>turkey_section.py plots the seismic section of a subset of instruments located on or close the East Anatolian Fault line slipped during the Mw 7.8 2023 Kahramanmaraş earthquake.</p> <p>For all details, see Palo and Zollo, Small-scale segmented fault rupture along the East Anatolian Fault during the 2023 Kahramanmaraş earthquake, <em>Commun Earth Environ, 2024. </em>Uploaded files .fig correspond to the source figures of the graphs included in this paper. </p> <p> </p>
Supplementary files for "Pressure-enhanced ferroelectric polarisation in polar perovskite-like [C2H5NH3]Na0.5Cr0.5(HCOO)3 metal-organic framework"
<p>DFT optimised structures for the paper: Pressure-enhanced ferroelectric polarisation in polar perovskite-like [C2H5NH3]Na0.5Cr0.5(HCOO)3 metal-organic framework. See the paper for additional information on the computational setup.</p> <p>Files are named HP or LP for high-pressure and low-pressure phases, followed by the pressure as calculated by DFT. The HP structure was optimized in two different space groups and are labelled accordingly. The DFT optimized structure without volume restrictions is found in opt-vol.POSCAR</p> <p> </p>
Replication Data for: Determination of Intrinsic Effective Fields and Microwave Polarizations by High-Resolution Spectroscopy of Single NV Center Spins
<p>Data repository for: <strong>Determination of Intrinsic Effective Fields and Microwave Polarizations by High-Resolution Spectroscopy of Single NV Center Spins</strong></p> <p><em>Data description.pdf</em> describes the uploaded data.<br> <em>Data.xlsx</em> is the data represented in the paper.<br> <em>Esrfit_Npeak.m</em>, <em>Esrfit_xN.m</em>, <em>GaussianFunc.m</em>, <em>Gaussian_xN_Func.m</em>, <em>Lorentz_Func.m</em>, <em>Lorentz_xN_Func.m</em>, <em>Rabifit_xN.m</em>, <em>Rabi_xN_Func.m</em>, <em>FourierTransformRabi.m</em> are Matlab code files to transform and fit the data.</p>
Dataset for the evaluation of Supercritical Fluid Chromatography Polar Stationary Phases with OH moieties
<p>Raw data used for the evaluation of supercritical fluid chromatography stationary phases with OH moieties published in article "Advancing Fundamental Understanding of Retention Interactions in Supercritical Fluid Chromatography Using Artificial Neural Networks: Polar Stationary Phases with OH moieties" in Analytical Chemistry, 2024. Data set contains: (i) chromatograms of 107 analytes measured on silica, hybrid silica, and diol column using methanol, 10 mmol/L ammonium in methanol, and 2% water in methanol as organic modifiers in 8 points during 1 year (Empower project, Excel sheets of retention times and measured mixtures), (ii) 226 molecular descriptors calculated by CDK Descriptor Calculator (v.1.4.8) from 3D structures of the 107 analytes optimized by semi-empirical AM1 quantum mechanical calculations using the MOPAC application of Chem 3D Pro version 14.0 software (CambridgeSoft) (Excel sheet), (iii) weights assigned to each molecular descriptor at each chromatographic conditions by artificial neural network created using the neural network simulator in Matlab R2023a with the deep learning toolbox V.23.2 (The MathWorks, Inc., Massachusetts, USA) and a sigmoid activation function, a backpropagation learning algorithm with 500 learning cycles (Excel sheet). </p>
Manual in-situ measurements of snow depth and snow water equivalent at the Polish Polar Station Hornsund - winter seasons 2021/2022and 2022/2023
<p>The dataset presents manual measurements of snow depth and snow water equivalent collected at the Polish Polar Station Hornsund in Svalbard during the winter seasons of 2021/2022 and 2022/2023.</p> <p>Snow depth measurements have been conducted at the same location by the Station's overwintering personnel since August 1982. Snow depth is calculated from a mean of three snow stakes to avoid the effects of the drifting snow. Measurements are taken manualy, on a daily basis. </p> <p>Snow water equivalent measurements have also been carried out at the same points by the Station's overwintering crew since October 1982. These measurements are performed every five days using a VS-43 snow tube. However, measurements are not taken when the snow depth is less than 5 cm.</p>
Biogeochemical observations in adjacent mesoscale eddies of opposite polarity
<p>Datasets used for the analyses reported in the manuscript titled "Biogeochemical dynamics in adjacent mesoscale eddies of opposite polarity".</p> <p>For all files, the suffix HL4 indicates the expedition HOE-LEGACY 4, while the suffix MESOSCOPE indicates the MESO-SCOPE expedition.</p> <p>Temperature profiles measured underway across adjacent eddies are saved in files UnderwayTemperature*.csv. Station coordinates are saved in UnderwayCoordinates*.csv</p> <p>Shipboard vertical profiles of dissolved oxygen, chlorophyll fluorescence, and potential density anomaly are saved in files TransectOxygen*.csv, TransectFluorescence*.csv, and TransectSigma*.csv, respectively. Station coordinates are saved in TransectCoordinates*.csv</p> <p>Inorganic nutrient concentrations measured across adjacent eddies are saved in files EddyNutrients*.csv.</p> <p>Particulate carbon, chlorophyll a, beam attenuation, and chlorophyll fluorescence in the eddy centers are saved in file ParticlePigmentComparison_15m.csv and ParticlePigmentComparison_DCM.csv for the depth of 15 m and the depth of the DCM, respectively.</p> <p>Cell counts from flow cytometry in the eddy centers are saved in files FlowCytometry_cyclone_*.csv and FlowCytometry_anticyclone_*.csv. This files also report the depth of the DCM for each eddy center.</p> <p>Imaging FlowCytobot (IFCb) measurements during MESO-SCOPE are reported in files IFCB_Class_DCM&15m_MESOSCOPE.csv for classes and IFCB_Genera_DCM_MESOSCOPE.xlsx for genera.</p>
Data set of anthropogenic contaminants in snow from polar regions (Ny-Alesund and Dome C)
<p>The produced dataset (in MS Excel format) contains concentrations of mercury, trace elements and organic contaminants in snow samples collected in the Ny-Alesund area (Svalbard - Norway) (78.917° N 11.933° E) and from the Antarctic Plateau, Dome C (75.103°S, 123.35°E). The Arctic sampling sites are reported in figure 1. The concentrations for trace elements and mercury are in ngg<sup>-1</sup> while for the organic contaminants they are reported in ngL<sup>-1</sup>.</p> <p>The inorganic contaminants dataset reports concentration of Hg, Trace elements and Black Carbon in Arctic and Antarctic site. The Arctic sites are subdivided in annual snow pack on the glacier and surface snow sampling close to the Gruvebadet Aerosol Laboratory. In Antarctica mercury concentrations in surface snow are also reported.</p> <p>The organic contaminants dataset reports the concentrations of Polycyclic Aromatic Hydrocarbons (PAHs) in surface snow samples collected close to the Gruvebadet Aerosol Laboratory (78.91622°N 11.89536°E, Ny Alesund, Norway). Samplings were performed from 04/10/2018 to 13/05/2019, obtaining a total of 35 samples, encompassing the entire winter season with an approximatively weekly resolution. Total PAH (sum of naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benzo(<em>a</em>)anthracene, chrysene, benzo(<em>b</em>)fluoranthene, benzo(<em>k</em>) fluoranthene, benzo(<em>a</em>)pyrene, benzo(<em>ghi</em>)perylene, indeno(<em>1,2,3-c,d</em>)pyrene and dibenzo(<em>a,h</em>)anthracene) concentrations range from 0.8 to 37 ng L<sup>-1</sup>. Individual PAHs were mean blank corrected and average percentage abundances in the samples are reported in the dataset.</p>
Polarized Emission from hexagonal-Silicon Germanium Nanowires
<p>This dataset contains the polarization dependent photoluminescence intensity measurements on hexagonal-silicon germanium nanowires. This data confirms the selection rules of the fundemental direct bandgap transition of the material. </p> <p>The data is zipped and contains a README which describes the storage of the data inside the folder.</p>
Primary data: Signal enhancement of hyperpolarized 15N sites in solution — increase in solid-state polarization at 3.35 T and prolongation of relaxation in deuterated water mixtures
<p>Primary data for DOI: 10.1002/nbm.4787</p> <p>NMR in Biomedicine. 2022;e4787</p> <p>Title: Signal enhancement of hyperpolarized 15N sites in solution—increase in solid-state polarization at 3.35 T and prolongation of relaxation in deuterated water mixtures</p> <p>Authors: Ayelet Gamliel, David Shaul, J. Moshe Gomori, Rachel Katz-Brull</p> <p>Description:</p> <p>These primary datasets contain data presented in the above publication and consist of:</p> <p>1. 15N-NMR spectra in solutions</p> <p>2. 13C polarization buildup data in solid-state</p> <p>3. 13C microwave profiles in solid state</p> <p>Please consult the Archive Guide.</p>
Supplemental Data Sets for "Buried Ice Deposits in Lunar Polar Cold Traps were Disrupted by Ballistic Sedimentation"
<p>Supporting Data Sets for manuscript "Buried Ice Deposits in Lunar Polar Cold Traps were Disrupted by Ballistic Sedimentation". Contains Data Sets S1-S7 as described in the manuscript and Supplementary information S1 (see <a href="https://doi.org/10.1029/2022JE007567">https://doi.org/10.1029/2022JE007567</a>).</p>
Polar / Plasma Waves Investigation processed dataset and ephemeris used to produced the Smith et al. (2022) catalogue (doi:10.5281/zenodo.7260994 )
<p>This data set contains Polar / Plasma Waves Investigation processed using the SPACE Labelling Tool (Louis et al., 2022, doi:10.5281/zenodo.6886528). It also contains the Polar ephemeris in the geocentric solar ecliptic (GEO) coordinate system (from https://sscweb.gsfc.nasa.gov/cgi-bin/Locator.cgi)</p> <p>This processed dataset contains Auroral Kilometric Radiation (AKR) observations and was used to produced the Smith et al. (2022) catalogue of AKR (doi:10.5281/zenodo.7260994)</p> <p>This work has been funded by Science Foundation Ireland Grant 18/FRL/6199, and by a 2022 SCOSTEP/PRESTO<br> Grant.</p>
Electronic Supplement / Data Archive for "Global Variations in the Time Delays Between Polar Ionospheric Heating and the Neutral Density Response"
<p>These files provide supplemental data to accompany the paper "Global Variations in the Time Delays Between Polar Ionospheric Heating and the Neutral Density Response" submitted to AGU journal <em>Space Weather</em>, with manuscript number 2022SW003410. Details are provided in the file <strong>ReadMe_DataArchive.pdf</strong>.<br> </p>
Dataset for "Reproducibility and FAIR Principles: The Case of a Segment Polarity Network Model"
<p>Results of random sampling the segment polarity network with the simulator COPASI. These results correspond to Fig. 2 and Table 2 of von Dassow et. al (2000) (doi:10.1038/35018085). The random sampling was carried out with file vonDassow2000_1x4_alt.cps with COPASI version 4.39 selecting the appropriate parameter set named (1-7) and setting the number of repeats in the parameter scan task to the desired number. Full results of sampling are in files prefixed with the row number of Table 2 of von Dassow et. al (2000) and extension .tsv. Results with scores below 0.2 are in corresponding files with the word "-hits" in the filename. Includes also results from a time course simulation of this model using four different simulators (COPASI, Tellurium, Amici, and VCell). Finally also contains a study on multistability carried out by random sampling of parameters and initial conditions (run with COPASI). Markdown file README.md contains more detailed explanation. See also https://github.com/pmendes/models/tree/main/vonDassow2000</p>
Total O3 columns at polar regions: TOMCAT/SLIMCAT passive and active tracers and merged SAOZ-MSR2 dataset
<p>Passive and active total ozone columns simulated by the chemical transport model TOMCAT/SLIMCAT (Chipperfield, 1999) and the merged dataset of total ozone from Système d'Analyse par Observation Zénithale (SAOZ, Pommereau and Goutail, 1988) ground-based instruments and Multi-Sensor Reanalysis (MSR2, van der A et al., 2010, 2015) for the polar stations described in the Table here below.</p> <p><strong>Table. Arctic and Antarctic stations included in the study: station name and ID, latitude, longitude and measurement periods of SAOZ and MSR2 datasets.</strong></p> <table> <tbody> <tr> <td> <p><strong>Station (ID)</strong></p> </td> <td> <p><strong>Lat, Lon</strong></p> </td> <td> <p><strong>SAOZ dataset</strong></p> </td> <td> <p><strong>MSR2 dataset </strong></p> </td> </tr> <tr> <td> <p>Eureka, Nunavut (EU)</p> </td> <td> <p>80.1°N, 86.4°W</p> </td> <td> <p>2005-2020</p> </td> <td> <p>1990-2022</p> </td> </tr> <tr> <td> <p>Ny-Alesund, Svalbard (NY)</p> </td> <td> <p>78.9°N, 11.9° E</p> </td> <td> <p>1991-2022</p> </td> <td> <p>1990-2022</p> </td> </tr> <tr> <td> <p>Thule, Greenland (TH)</p> </td> <td> <p>76.5°N, 68.8°W</p> </td> <td> <p>1999-2003, 2005-2016</p> </td> <td> <p>1990-2022</p> </td> </tr> <tr> <td> <p>Scoresbysund, Greenland (SC)</p> </td> <td> <p>70.5°N, 22.0°W</p> </td> <td> <p>1991-2017, 2019-2022</p> </td> <td> <p>1990-2022</p> </td> </tr> <tr> <td> <p>Sodankyla, Finland (SK)</p> </td> <td> <p>67.4°N, 26.6° E</p> </td> <td> <p>1991-2022</p> </td> <td> <p>1990-2022</p> </td> </tr> <tr> <td> <p>Sondre Stromfjord, Greenland (SS)</p> </td> <td> <p>67.0°N, 50.6°W</p> </td> <td> <p>2018-2022</p> </td> <td> <p>1990-2022</p> </td> </tr> <tr> <td> <p>Zhigansk, Russia (ZH)</p> </td> <td> <p>66.8°N, 123.4° E</p> </td> <td> <p>1992-2013</p> </td> <td> <p>1990-2022</p> </td> </tr> <tr> <td> <p>Salekhard, Russia (SA)</p> </td> <td> <p>66.5°N, 66.7°E</p> </td> <td> <p>2002-2016</p> </td> <td> <p>1990-2022</p> </td> </tr> <tr> <td> <p>Marambio, Antarctica (MB)</p> </td> <td> <p>64.2°S, 56.7°W</p> </td> <td> <p>-</p> </td> <td> <p>1989-2021</p> </td> </tr> <tr> <td> <p>Dumont d’Urville, Antarctica (DD)</p> </td> <td> <p>66.7°S, 140.0°E</p> </td> <td> <p>1989-2021</p> </td> <td> <p>1989-2021</p> </td> </tr> <tr> <td> <p>Rothera, Antarctica (RO)</p> </td> <td> <p>67.6°S, 68.1°W</p> </td> <td> <p>2007-2021</p> </td> <td> <p>1989-2021</p> </td> </tr> <tr> <td> <p>Syowa, Antarctica (SW)</p> </td> <td> <p>69.0°S, 39.6°E</p> </td> <td> <p>-</p> </td> <td> <p>1989-2021</p> </td> </tr> <tr> <td> <p>Neumayer, Antarctica (NM)</p> </td> <td> <p>70.7°S, 8.3°W</p> </td> <td> <p>-</p> </td> <td> <p>1989-2021</p> </td> </tr> <tr> <td> <p>Terra Nova, Antarctica (TN)</p> </td> <td> <p>74.8°S, 164.5°E</p> </td> <td> <p>-</p> </td> <td> <p>1989-2021</p> </td> </tr> <tr> <td> <p>Concordia, Antarctica (DO)</p> </td> <td> <p>75.1°S, 123.4°E</p> </td> <td> <p>2007-2021</p> </td> <td> <p>1989-2021</p> </td> </tr> <tr> <td> <p>Halley, Antarctica (HB)</p> </td> <td> <p>75.6°S, 26.8°W</p> </td> <td> <p>-</p> </td> <td> <p>1989-2021</p> </td> </tr> </tbody> </table> <p> </p> <p>Each file corresponds to the whole winter time data set of the station identified by its ID: O3_PassActSLIMCAT_CompositeMSR2SAOZ_ID.txt</p> <p>1<sup>st</sup> column: Year</p> <p>2<sup>nd</sup> column: Day of Year (DoY)</p> <p>3<sup>rd</sup> column: Passive ozone column (without chemistry) modelled by TOMCAT/SLIMCAT (O3pasS).</p> <p>4<sup>th</sup> column: Active ozone column (with full chemistry) modelled by TOMCAT/SLIMCAT (O3actS).</p> <p>5<sup>th</sup> column: merged data from SAOZ observations and MSR2 (O3comp)</p> <p>Passive and active tracers of SLIMCAT were normalized to O3comp data in the beginning of the winter.</p> <p>NaN is used when there is no observation either from SAOZ instrument or MSR2 dataset or from the model.</p> <p> </p> <p><strong>References</strong></p> <p>Chipperfield, M. P.: New version of the TOMCAT/SLIMCAT offline chemical transport model: Intercomparison of stratospheric tracer experiments, Q. J. Roy. Meteor. Soc., 132, 1179–1203, <a href="https://doi.org/10.1256/QJ.05.51">https://doi.org/10.1256/QJ.05.51</a>, 2006.</p> <p>Pommereau, J.-P., and Goutail, F.: O<sub>3</sub> and NO<sub>2</sub> ground-based measurements by visible spectrometry during arctic winter and spring 1988, Geophys. Res. Lett., 15, 891–894, <a href="https://doi.org/10.1029/GL015i008p00891">https://doi.org/10.1029/GL015i008p00891</a>,1988.</p> <p>van der A, R. J., Allaart, M. A. F., and Eskes, H. J.: Multi sensor reanalysis of total ozone, Atmos. Chem. Phys., 10, 11277–11294, <a href="https://doi.org/10.5194/acp-10-11277-2010">https://doi.org/10.5194/acp-10-11277-2010</a>, 2010.</p> <p>van der A, R. J., Allaart, M. A. F., and Eskes, H. J.: Extended and refined multi sensor reanalysis of total ozone for the period 1970–2012, Atmos. Meas. Tech., 8, 3021–3035, <a href="https://doi.org/10.5194/amt-8-3021-2015">https://doi.org/10.5194/amt-8-3021-2015</a>, 2015.</p>
Naphthalimide-Annulated [n]Helicenes: Red Circularly Polarized Light Emitters
<p>Original data to report (Abstract):<br> Two [<em>n</em>]heliceno-bis(naphthalimides) <strong>1</strong> and <strong>2</strong> (<em>n</em> = 5 and 6, respectively) where two electron-accepting naphthalimide moieties are attached at both ends of helicene core were synthesized by effective two-step strategy, and their enantiomers could be resolved by chiral stationary-phase high-performance liquid chromatography (HPLC). The single-crystal X-ray diffraction analysis of enantiopure fractions of <strong>1</strong> and <strong>2</strong> confirmed their helical structure, and together with experimental and calculated circular dichroism (CD) spectra, the absolute configuration was unambiguously assigned. Both <strong>1</strong> and <strong>2</strong> exhibit high molar extinction coefficients for the S<sub>0</sub>–S<sub>1</sub> transition and high fluorescence quantum yields (73% for <strong>1</strong> and 69% for <strong>2</strong>), both being outstanding for helicene derivatives. The red circularly polarized luminescence (CPL) emission up to 615 nm for <strong>2</strong> with CPL brightness (<em>B</em><sub>CPL</sub>) up to 66.5 M<sup>–1</sup> cm<sup>–1</sup> demonstrates its potential for applications in chiral optoelectronics. Time-dependent density functional theory (TD-DFT) calculations unambiguously showed that the large transition magnetic dipole moment |<em>m</em>| of <strong>2</strong> is responsible for its high absorbance dissymmetry (<em>g</em><sub>abs</sub>) and luminescence dissymmetry (<em>g</em><sub>lum</sub>) factor.</p>
Polar Iridium Surface Velocity Profilers (p-iSVP), and standard Iridium Surface Velocity Profilers (iSVP) during SCALE 2019 Winter and Spring Cruises
<p><strong>Brief data description</strong></p> <p>In 2019, winter and spring scientific research expeditions aboard the SA Agulhas II were conducted along the Good-Hope line (0<sup>o</sup> E) to the Antarctic marginal ice zone (MIZ) in the north-eastern Weddell Sea region as part of the <em>Southern oCean seAsonal Experiment</em> (SCALE; Ryan-Keogh and Vichi, 2022).</p> <p>During the winter expedition, three polar Iridium Surface Velocity Profilers (p-iSVPs; MetOcean model) were deployed by the South African Weather Service (SAWS) between 27 July and 28 July 2019. These buoys were analysed in de Vos et al. (2022). The region of deployment consisted of pancake-ice conditions with an average ice thickness of 40-60 cm. The instruments were deployed by hand by three people, lowered by crane from the ship to the ice on a basket cradle. The first buoy (p-iSVP 1) was deployed in water, in between pancake ice floes, while the other two buoys (p-iSVP 2 and p-iSVP 3) were deployed on roughly circular ice floes > 3 m in diameter.</p> <p>These buoys were expendable devices that recorded GPS position, air and ice temperature, and barometric pressure. The temporal resolution is 30 minutes for p-iSVP 1 and hourly for p-iSVP 2 and p-iSVP 3. The survival of these sensors depended on their battery life, since p-iSVPs can continue to drift in the ocean after ice melting and can be further refrozen in between floes. p-iSVP 1 and p-iSVP 3 continued to transmit data until 15 October 2019. p-iSVP 2 stopped transmitting data on 25 August 2019.</p> <p>During the spring expedition, three standard Iridium Surface Velocity Profilers (iSVPs 4-6; Pacific Gyre model) were deployed by SAWS between 24 October and 28 October 2019 (de Vos et al., 2022). Specifically-designed frames were built around these three iSVPs to allow them to stand securely on the ice, without damaging the non-polar battery, and also to make sure they operated as Lagrangian ice trackers. These buoys were deployed during first-year ice conditions, with an average ice thickness of 80-90 cm. The instruments were deployed with the same protocol as the winter buoys.</p> <p>These buoys recorded GPS position, air temperature and barometric pressure, every hour. Their survival, like the winter p-iSVPs, also depended on their battery life, and therefore it was possible for them to continue to drift after ice melting. The iSVPs transmitted data until 19 December 2019.</p> <p><strong>Buoy names and raw data:</strong></p> <p>p-iSVP 1: 300234067003010-300234067003010-20191015T064320UTC.csv</p> <p>p-iSVP 2: 300234067002060-300234067002060-20191015T064316UTC.csv</p> <p>p-iSVP 3: 300234066992870-300234066992870-20191015T064314UTC.csv</p> <p>iSVP 4: 300234066433050.xlsx</p> <p>iSVP 5: 300234066433051.xlsx</p> <p>iSVP 6: 300234066433052.xlsx</p> <p><strong>Related code: </strong>The buoy data has been processed using https://github.com/mvichi/antarctic-buoys/. </p>
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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.