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2,649 results for “Optical”
Mueller matrix imaging combining optical parameters of mice non-melanoma skin cancer tissue
<p>The dataset consists of the Mueller matrix elements and optical parameters acquired from the backscattered light using a CCD camera and Mueller matrix imaging technique.</p><p>This dataset contains 90 samples including 20 feature vectors for SCC, 33 feature vectors for normal and 37 feature vectors for papilloma.</p>
Time series of optical measurements (absorbance, fluorescence) for Beaverdam Reservoir, Carvins Cove Reservoir, and Falling Creek Reservoir in southwestern Virginia, USA 2019-2025
Depth profiles and surface dissolved samples analyzed for optical analyses (absorbance, fluorescence) were sampled from 2019 to 2025 in three drinking water reservoirs located in southwestern Virginia, USA including Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), and Falling Creek Reservoir (Vinton, Virginia). The reservoirs are owned and operated by the Western Virginia Water Authority as either primary or secondary drinking water sources for Roanoke, Virginia. The dataset consists of depth profiles at the deepest site of each reservoir, surface water samples from reservoir tributaries, and additional samples at within-reservoir sites. In Beaverdam and Falling Creek Reservoir, we collected depth profiles, gauged weir, and wetland samples approximately fortnightly throughout the summer stratified period (June 2019 - November 2019) and surface samples approximately monthly from May 2019 to October 2019 and in March 2020. Beaverdam Reservoir depth samples were additionally collected in summer 2022. We collected depth profiles and tributary samples monthly to seasonally in Carvins Cove Reservoir from late 2021 - 2023. From May 2024 - April 2025, we sampled depth profiles at multiple transects across the reservoir and surface water samples in one tributary approximately monthly at Carvins Cove. Absorbance was measured as colored dissolved organic matter (CDOM) using a spectrophotometer. Fluorescence was measured as fluorescent dissolved organic matter (fDOM) using a spectrofluorometer as excitation emission matrices (EEMs). Absorbance and fluorescence results are reported along with PARAFAC model results applied to the collected EEMs samples. Data visualization and quality assurance/quality control (QA/QC) scripts accompany the data package.
Mineral spectral refractive index and bulk optical property dataset for aerosol studies
<p>Version 1.3, updated 11/15/2024.</p> <p>Added a file with 27 regional dust sample mineral composition information 'NewRegionalSamples.xlsx',</p> <p>along with the refractive index data.</p> <p>All refractive index files here have 127 rows (wavelengths) and 27 columns (samples)</p> <p>'kall27_coarse.dat' is the imaginary part of the coarse mode. </p> <p>'kall27_fine.dat' is the imaginary part of the fine mode.</p> <p>'nall27_coarse.dat' is the real part of the coarse mode.</p> <p>'nall27_fine.dat' is the real part of the fine mode.</p> <p>Version 1.2, updated 04/23/2024.<br>Major changes: <br>Changed all the data file names to new format: "mix"+{property name}+{number}, rearranged the number of mixing samples</p> <p>Updated all the bulk optical property data. This version use constant values of standard deviation in the lognormal size distribution settings for the coarse mode and the fine mode respectively.</p> <p>The phase matrices are separated from the other bulk properties due to their large file sizes. The readme file is updated correspondingly. The information of scattering angles (498 angles in total) is uploaded as "TAMUdust2020_Angle.dat".</p> <p>Added supplemental file data in 'Supplemental.tar.gz'.</p> <p>Additional refractive indices are zipped in 'AdditionalRefInd.tar.gz'</p> <p>Version 1.1, updated 03/14/2024.<br>Major changes: <br>Added mixed bulk properties for "0 (99%coarse+1%fine)" and "11 (2.0 µm coarse+ 0.4 µm fine)";<br>Added "reff.dat" in the 'BulkProperties.tar.gz'. The data include four columns: fine mode fraction, bulk projected area <A>, bulk volume <V>, effective radius r_eff. The information is for mixed sample number 0 to 11, each corresponds to one row.<br>Added refractive indices for chlorite, mica, smectite, pyroxene, vermiculite and pyroxenes. These groups can be applied in some other models.</p> <p>Version 1.0, uploaded 01/02/2024.</p> <p>This database include supplemental data and files for the publication of this paper:</p> <p>Sensitivities of Spectral Optical Properties of Dust Aerosols to their Mineralogical and Microphysical Properties. Yuheng Zhang, M. Saito, P. Yang, G. L. Schuster, and C. R. Trepte, J. Geophys. Res. Atmos. 2024.</p> <p> </p> <p>*****************************************</p> <p>The supplemental data include:</p> <p>1) 'GroupRefInd.tar.gz' Mineral (group) refractive index files.<br>E. g., 1All_Illite.dat contains the complex refractive index files of illite group. Format (from left to right columns): Wavelength (unit: µm), Real part (n), Imaginary part (k), standard deviation of n, standard deviation of k.</p> <p>The file 'fine_log.dat' includes the mean and standard deviation values of n and k for all the generated fine mode dust samples at 11,044 wavelengths from 0.2 to 50 micron.</p> <p>The file 'fine_log127.dat' only includes the values at 127 wavelengths from 0.2 to 50 micron (defined in 'swav.txt' and 'lwav.txt'), and is used for the bulk property computations.</p> <p>The files 'coarse_log.dat' and 'coarse_log127.dat' are for the coarse mode dust samples.</p> <p>2) 'CompositionFraction.xlsx': Mineral composition data sources/references and composition data (mean and standard deviation values of each group).<br>'Vlog_coarse.dat': Randomly generated VOLUME FRACTION of 9 mineral groups for the coarse mode dust. Left to right: Illite, Kaolinite, Montmorillonite (Other clays), Quartz, Feldspar, Carbonate, Gypsum (Sulphate), Hematite, Goethite.</p> <p>'Vlog_fine.dat': For the fine mode dust.</p> <p>3) 'RefSources.xlsx': The data source references of mineral refractive indices. We didn't include the olivine, other silicates, soot and titanium-rich minerals in the paper, but the refractive indices are available for those who are interested. Chlorite, Mica and Vermiculite group are mentioned in some studies, and we included the refractive indices for these minerals as well.</p> <p>4) 'DustSamples.tar.gz' Dust sample refractive index files.<br>The files are enclosed in four folders: fine_sw/ fine_lw/ coarse_sw/ coarse_lw/.</p> <p>fine: fine mode. coarse: coarse mode.</p> <p>'sw' means shortwave (< 4 µm, in total 76 wavelengths defined in 'swav.txt') while 'lw' means longwave (>= 4 µm, in total 51 wavelengths defined in 'lwav.txt').</p> <p>All files start with 'rdn', which means that they are computed based on randomly generated composition (data given in sheet 2 of 'CompositionFraction.xlsx').</p> <p>The four digit number after 'rdn' is the index of each dust sample. In total, there are 5,000 samples. The sample composition is the same for the same sample index in the same size mode (fine/coarse). Data file format (from left to right columns): real part, imaginary part.</p> <p>5) 'BulkProperties.tar.gz' Bulk property files (excluding phase matrices)<br>'mixqx.dat' files format (from left to right columns): Extinction efficiency (Qext), Scattering efficiency (Qsca), Backscattering efficiency (Qbck), and Asymmetry coefficient (Qasy). To obtain asymmetry factor, use Qasy/Qsca.</p> <p>'mixbkx.dat' files format (from left to right columns): P11(pi) P12(pi) P22(pi) P33(pi) P34(pi) P44(pi).</p> <p>'x' refers to the number at the end of the file name. It can be 100 ~ 112, each represents a setting of coarse and fine mode effective radius and volume fraction (see details in "reff.dat")</p> <p>'reff.dat' contains the effective radius information of the mixture. It has 7 columns: File number "x", Fine mode volume fraction, Fine mode effective radius (µm), Coarse mode effective radius (µm), Bulk projected area (µm^2), Bulk volume (µm^3), Bulk effective radius (µm).</p> <p>6) 'PhaseMatrices.tar.gz' Phase matrices data<br>'mixphswx.dat' files contain phase matrix results at 532 nm (shortwave). From left to right: P11, P12, P22, P33, P34, P44.</p> <p>'mixphlwx.dat' files contain phase matrix results at 10.5 µm (longwave).</p> <p>There are 635,000 rows in each data file. 635,000 rows = 127 wavelengths * 5,000 samples. Row 1~127 is sample 1, row 128~254 is sample 2, etc.. Suggest to use matlab function 'reshape(property, 127, 5000)' for each column when processing the data.</p> <p>7) 'Supplemental.tar.gz'</p> <p>We also include data files mentioned in the supplemental file of the paper. The adjusted source data files of the nine mineral groups are included.</p> <p>The supplemental bulk property files are named based on the figure number.</p> <p>8) 'AdditionalRefInd.tar.gz'</p> <p>We also include additional refractive indices for chlorite, smectite, vermiculite, mica, dolomite, titanium-rich minerals, pyroxenes and soot. These data can be useful in other models.</p> <p>For more detailed information and datasets, please contact: Yuheng Zhang, yuheng98@tamu.edu or yuhengz98@qq.com.</p>
Detecting cosmic voids via maps of geometric optics parameters
<ul> <li>lensing-ddbb4ac.pdf - research data in pdf format</li> <li>void_matches*.dat - plain text results files corresponding to Table 3 and Figures 2, 4, 6, 8.</li> <li>lensing-ddbb4ac-journal.tar.gz - source package for producing the article pdf, together with the reproducibility package, but without the git history; appropriate for ArXiv</li> <li>lensing-ddbb4ac-git.bundle - git source package that can be unbundled with 'git clone lensing-e4f7af0-git.bundle' and used for reproducibility: to download data, do calculations, analyse them, plot them and produce the research data pdf</li> <li>software-ddbb4ac.tar.gz - this should contain all the software, apart from a minimal POSIX-compatible system and LaTeX packages, needed for compiling and installing the software used in producing this work</li> <li>lensing-ddbb4ac-snapshot.tar.gz - source files of the project; these should be enough, provided that external software packages can be downloaded, to reproduce the full project</li> </ul> <p>The authors grant a perpetual, non-exclusive licence to distribute this pdf preprint.</p> <p>All the other materials here are free-licensed, as stated in the individual files and packages.</p>
Dissolved Organic Carbon Concentration, Dissolved Organic Matter Optical Properties, and Water Quality Indicators in the Plum Island Estuary (PIE), Massachusetts, USA (2018-2023)
This is a data set of paired in situ measurements of water quality parameters, total suspended solids concentration, and concentration and optical properties (absorption coefficient spectra and fluorescence indices) of dissolved organic matter (DOM) collected between 2018 and 2023 in the Plum Island Estuary and nearshore waters. In situ water quality measurements (salinity, temperature, optical dissolved oxygen saturation, turbidity, and dissolved organic matter fluorescence) were collected with a water quality sonde from the surface (top 1 m of water column), along with corresponding samples that were processed and analyzed in the lab for dissolved organic carbon (DOC) concentration, chromophoric DOM (CDOM), absorption coefficient spectra, DOM excitation-emission matrix (EEM) fluorescence, and total suspended sediment (TSS) concentration. The data were used in multiple studies (see manuscripts listed below) focusing on the dynamics of DOC and CDOM in the Plum Island Estuary.
stationary_granular_flow_seismicity_and_optics
<p>Raw data acquired during the study of seismic sources emitted by a laboratory landslide: a stationary granular flow in an inclined flume. The data consists in images acquired by a fast camera and accelerometers. The scripts to treat the data are also shared.</p>
Raw spectra measurements of scattered sunlight collected using a MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) instrument in the austral summer of 2016/17 during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>To achieve the objectives of the project, we installed a MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) instrument on the vessel “Akademik Tryoshnikov”. This instrument is based on the DOAS technique, which is used to measure trace gas concentrations in the atmosphere. The method consists of the analysis of the spectral absorption lines that each trace gas produces in the solar spectra. The DOAS technique uses the narrowband features that every trace gas has in their spectral absorption coefficients. This differential cross section is unique and acts like a fingerprint for the trace gases, allowing to differentiate between them and to estimate their concentrations (for further details see Platt and Stutz, 2008).</p> <p>In the past decades, atmospheric chemists have come to realize that halogen species (like Cl, Br or I and their oxides ClO, BrO and IO) exert a powerful influence on the chemical composition of the troposphere and through that influence affect the evolution of pollutants, hence having a significant impact on climate. These reactive halogen species are potent oxidizers for organic and inorganic compounds throughout the troposphere. In particular, halogen cycles can act on several compounds (such as methane, ozone, particles…), all of which are climate forcing agents through direct and indirect radiative effects. Dynamic exchange of halogens between the ocean, sea ice, snowpack and atmosphere is the main driver for the frequent occurrence of Ozone Depletion Events (ODEs) and Atmospheric Mercury Depletion Events (AMDEs) (Saiz-Lopez and von Glasow, 2012).</p> <p>In this dataset we present the raw spectra measurements of scattered sunlight recorded by the MAX-DOAS onboard a research vessel in the Southern Ocean and Atlantic Ocean. Included are position and vessel inclination data. Data coverage is from December 2016 to April 2017.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_maxdoas_gps.zip</li> <li>GPS_JDDD.txt, data file, ASCII text</li> <li>ace_maxdoas_inclination.zip</li> <li>Inclination_JDDD.txt, data file, ASCII text</li> <li>ace_maxdoas_spectra-YYYY-MM.zip</li> <li>- MAXDOAS<br> - - WWW<br> - - - JDDD<br> - - - - LiveInfo_DDDhhmmss.WWW, data file, ASCII text<br> - - - - Atmos<br> - - - - - DDDhhmmss_90.WWW, data file, ASCII text<br> - ZENITH<br> - - WWW<br> - - - JDDD<br> - - - - LiveInfo_DDDhhmmss.WWW, data file, ASCII text<br> - - - - Atmos<br> - - - - - DDDhhmmss_90.WWW, data file, ASCII text</li> <li>README.txt, metadata, text</li> <li>data_file_header_gps.txt, metadata, text</li> <li>data_file_header_inclination.txt, metadata, text</li> <li>data_file_header_spectra_atmos.txt, metadata, text</li> <li>data_file_header_spectra_liveinfo.txt, metadata, text</li> </ul> <p>where YYYY is the year and MM is the month. JDDD is the day of the year (Julian day) YYYY in which the file was recorded. hhmmss is the time. WWW is the central wavelength of the measured spectrum in the UV or VIS region.</p> <p><strong>Dataset license</strong></p> <p>This dataset of raw spectra of scattered sunlight measurements from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Bromine monoxide (BrO) measurements made using a MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) instrument in the austral summer of 2016/17 during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>To achieve the objectives of the project, we installed a MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) instrument on the vessel “Akademik Tryoshnikov”. This instrument is based on the DOAS technique, which is used to measure trace gas concentrations in the atmosphere. The method consists of the analysis of the spectral absorption lines that each trace gas produces in the solar spectra. The DOAS technique uses the narrowband features that every trace gas has in their spectral absorption coefficients. This differential cross section is unique and acts like a fingerprint for the trace gases, allowing to differentiate between them and to estimate their concentrations (for further details see Platt and Stutz, 2008).</p> <p>In the past decades, atmospheric chemists have come to realize that halogen species (like Cl, Br or I and their oxides ClO, BrO and IO) exert a powerful influence on the chemical composition of the troposphere and through that influence affect the evolution of pollutants, hence having a significant impact on climate. These reactive halogen species are potent oxidizers for organic and inorganic compounds throughout the troposphere. In particular, halogen cycles can act on several compounds (such as methane, ozone, particles…), all of which are climate forcing agents through direct and indirect radiative effects. Dynamic exchange of halogens between ocean, sea ice, snowpack and atmosphere is the main driver for the frequent occurrence of Ozone Depletion Events (ODEs) and Atmospheric Mercury Depletion Events (AMDEs) (Saiz-Lopez and von Glasow, 2012).</p> <p>In this dataset we present the mixing ratio and vertical column density of bromine monoxide (BrO) recorded in the austral summer of 2016/2017 in the Southern Ocean and Atlantic Ocean, averaged over one-hour time periods.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_bromine_monoxide_atmospheric_measurements.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.pdf, metadata, PDF/A-1a</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This dataset of atmospheric bromine monoxide measurements from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Iodine monoxide (IO) measurements made using a MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) instrument in the austral summer of 2016/17 during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>To achieve the objectives of the project, we installed a MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) instrument on the vessel “Akademik Tryoshnikov”. This instrument is based on the DOAS technique, which is used to measure trace gas concentrations in the atmosphere. The method consists of the analysis of the spectral absorption lines that each trace gas produces in the solar spectra. The DOAS technique uses the narrowband features that every trace gas has in their spectral absorption coefficients. This differential cross section is unique and acts like a fingerprint for the trace gases, allowing to differentiate between them and to estimate their concentrations (for further details see Platt and Stutz, 2008).</p> <p>In the past decades, atmospheric chemists have come to realize that halogen species (like Cl, Br or I and their oxides ClO, BrO and IO) exert a powerful influence on the chemical composition of the troposphere and through that influence affect the evolution of pollutants, hence having a significant impact on climate. These reactive halogen species are potent oxidizers for organic and inorganic compounds throughout the troposphere. In particular, halogen cycles can act on several compounds (such as methane, ozone, particles…), all of which are climate forcing agents through direct and indirect radiative effects. Dynamic exchange of halogens between ocean, sea ice, snowpack and atmosphere is the main driver for the frequent occurrence of Ozone Depletion Events (ODEs) and Atmospheric Mercury Depletion Events (AMDEs) (Saiz-Lopez and von Glasow, 2012).</p> <p>In this dataset we present the mixing ratio and vertical column density of iodine monoxide (IO) recorded in the austral summer of 2016/2017 in the Southern Ocean and Atlantic Ocean, averaged over one-hour time periods.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_iodine_monoxide_atmospheric_measurements.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.pdf, metadata, PDF/A1-a</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This dataset of atmospheric iodine monoxide measurements from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Hybrid Metrology for Nanostructured Optical Metasurfaces - Dataset
<p>This is the dataset of "Hybrid Metrology for Nanostructured Optical Metasurfaces", https://doi.org/10.1021/acsami.3c13923. </p>
Data for: Thermal volume expansion as seen by Temperature-modulated optical refractometry, Oscillating dilatometry and Thermo-mechanical analysis
<p>The data is supplementary to the publication "Thermal volume expansion as seen by Temperature-modulated optical refractometry, Oscillating dilatometry and Thermo-mechanical analysis", DOI: <a href="https://doi.org/10.1016/j.polymertesting.2024.108340" target="_blank" rel="noopener">10.1016/j.polymertesting.2024.108340</a></p> <p>Key words: Thermal volume expansion, Temperature-modulated optical refractometry, Thermo-mechanical analysis, Dilatometry, Epoxy thermoset</p> <p>The data sets contain measured data on Thermo-mechanical analysis (TMA) and Temperature-modulated optical refractometry (TMOR) of a model epoxy polymer in the viscoelastic temperature range.</p> <p>Material details:</p> <ul> <li>Bisphenol A Diglycidyl ether (DGEBA, DER332) + Difunctional and trifunctional carbocylic acids (Pripol1040, Croda) +pyridine</li> <li>n-tetradecane, C14H30</li> </ul> <p>Funding received from:</p> <ul> <li>German Research Foundation (DFG), project number: 521902629.</li> <li>(Austrian) Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology and the Federal Ministry for Digital and Economic Affairs (COMET-Module project “Chemitecture”, project-no.: 21647048)</li> </ul>
Data for: The thermo-optical coefficient as an alternative probe for the structural arrest of polymeric glass formers
<p>The data is supplementary to the publication "The thermo-optical coefficient as an alternative probe for the structural arrest of polymeric glass formers", DOI: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.polymer.2024.126868" target="_blank" rel="noreferrer noopener">10.1016/j.polymer.2024.126868</a>, and contains processed raw data.</p> <p>Key words: Temperature-modulated optical refractometry, Solidification, Glass transition temperature, Thermo-optical coefficient, Structural arrest</p> <p>The data sets contain measured data on Temperature-modulated optical refractometry (TMOR) of a model epoxy polymer from the viscoelastic temperature range, through the glass transition to the glassy state. The data sets were collected via the temperature-jump method.</p> <p>Material details:</p> <ul> <li>Bisphenol A Diglycidyl ether (DGEBA, DER332, CAS 1675-54-3) + Difunctional and trifunctional carbocylic acids (Pripol1040, Croda) +1,5,7-triazabicyclo[4.4.0]dec-5-en (TBD, CAS 5807-14-7, 10 mol-% relative to carboxylic acid functions)</li> </ul> <p>Funding received from:</p> <ul> <li>German Research Foundation (DFG), project number: 521902629</li> </ul>
Multiple years of Seaglider observations of hydrography, dissolved oxygen, chlorophyll a, and optical backscatter at Station ALOHA
<p><strong>File descriptions:</strong></p> <p>Seaglider missions are identified as GLIDER_MISSION<em> </em>(i.e. sg148_12 is glider 148, mission 12) and each have three files associated. For example:</p> <ol> <li><strong>sg148_12_qc_pass.xlsx</strong> contains only quality controlled (QC flags = 1) core data for an entire mission. Core data may include temperature, conductivity, salinity, potential density anomaly, calibrated dissolved oxygen concentrations, calibrated chlorophyll <em>a</em> concentrations, and the backscattering coefficient due to particles (bbp) at up to three wavelengths (470, either 650 or 660, and 700 nm) and spike flags. Bbp data is corrected with an <em>in situ</em> dark subtraction from near 200 m deep. Associated metadata (datetime, latitude, longitude, depth, dive number, and vertical profile direction) is also included.</li> <li><strong>sg148_12_alldata.nc </strong>contains all data (i.e. all QC flag levels) and associated quality control flags. In addition to core and metadata, factory-only calibrated observations (e.g. dissolved oxygen concentrations, chlorophyll <em>a</em> concentrations, and bbp) are listed. </li> <li><strong>sg148_12_qctests.nc</strong><em> </em>contains all quality control test values (pass: QC = 1, input flag: QC = 2, questionable data QC = 3, bad data: QC = 4). The maximum test QC flag value (e.g. out of range, density inversions, bioflouling, etc.) was passed to the variable QC flag (e.g chla_qcflag or salin_qcflag). . </li> </ol> <p> </p> <p><strong>Dataset description:</strong></p> <p>The SCOPE-ALOHA Seaglider dataset was designed to monitor the spatial and temporal variability of physical and biogeochemical properties around the long term sampling site Station ALOHA (22°45′N, 158°W). Seagliders are autonomous underwater vehicles that take high frequency (up to 0.2 Hz in our dataset), depth-resolved observations over several months and can be used to map large spatial features. The gliders depicted in this study were equipped with sensors to measure temperature, salinity, pressure, dissolved oxygen concentration (O2), chlorophyll a concentration (Chl a) from fluorescence (excitation/emission lambda = 470/695 nm), and the particulate backscattering coefficient (bbp) at three wavelengths (lambda = 470 nm, 700 nm, and either 650 or 660 nm depending upon mission). Vertical profiles down to at least 200 m were collected for all sensors over periods of several months per mission. This dataset comprises 18 missions between 2008 and 2023 centered on Station ALOHA, totaling over 20,000 depth profiles. Chlorophyll <em>a</em> and oxygen concentrations are calibrated with discrete observations. Particulate backscattering coefficients are corrected with an additional dark subtraction. This dataset is an improvement on the raw data files as they are quality controlled, calibrated, and corrected.</p> <p>Raw data files can be found at https://hahana.soest.hawaii.edu/seagliders/index.php.</p> <p>version notes:</p> <p>v1.0 original</p> <p>v1.1 Metaadata tab on xlsx files edited, no change to data</p> <p>v1.2 fixed error: variable qc flags added to alldata.nc files</p> <p>v1.3 Added error estimates and CF_standard_name to alldata.nc files</p> <p><strong>Methods:</strong></p> <p><em><strong>Code for all processing steps is on GitHub </strong></em><strong>(</strong><em><strong>https://github.com/cathygarcia/SeagliderDataprocessing</strong></em><strong>)</strong><em><strong>.</strong> The steps listed here are a brief summary. </em></p> <p><em>Temperature, Conductivity, Salinity, and Potential Density Anomaly</em></p> <ul> <li>Both temperature and conductivity profiles were lag corrected.</li> <li>Practical salinity was calculated using the Gibbs Seawater Toolbox (gsw_SP_from_C.m), and then converted to absolute salinity (gsw_SA_from_SP.m). </li> <li>Potential density anomaly was calculated with respect to a reference water pressure of 0 db using the Gibbs Seawater Toolbox (gsw_sigma0.m).</li> </ul> <p><em>Dissolved oxygen concentrations</em></p> <ul> <li>Raw optode phase values proceeded through a series of corrections to account for the effects of temperature, salinity, pressure, and time response in addition to sensor drift (Bittig et al., 2018, Barone et al., 2019).</li> <li> Optode phase values were converted to dissolved oxygen concentrations, and re-calibrated using discrete Winkler measurements. </li> </ul> <p><em>Chlorophyll</em> <em>a</em></p> <ul> <li>Factory-calibrated chlorophyll <em>a</em> observations were re-calibrated using discrete measurements of either HPLC chlorophyll <em>a </em>(16 missions) or fluorometric chlorophyll <em>a</em> (2 missions).</li> <li>Daytime chlorophyll <em>a</em> values are not quench corrected, and may be lower than actual values. It is recommended to use nighttime profiles near the surface. </li> <li>Additionally, a spike flag is included based on published protocol (Briggs et al., 2011).</li> </ul> <p><em>Backscattering coefficient due to particles (bbp)</em></p> <ul> <li>Factory-calibrated bbp values could have a large offset, that was not expected based on natural variability.</li> <li>A mission-specific deep dark correction (1st percentile of bbp at 190-200 m) was subtracted for each bbp dataset. Both the uncorrected and corrected data are available.</li> <li>Additionally, a spike flag is included based on published protocol (Briggs et al., 2011).</li> </ul> <p> </p>
EUV optical constants data set
<p>Dataset of optical constants in the extreme ultraviolet (EUV) spectral range, including 13.5nm, obtained from reflectivity measurements.</p>
Data of publication Ultra-narrow Optical Linewidths in Rare-Earth Molecular Crystals
<p>Data corresponding to main text Figures, Extended Data figures, and Supplementary Figures in publication 'Ultra-narrow Optical Linewidths in Rare-Earth Molecular Crystals, by D. Serrano, S. Kumar Kuppusamy, B. Heinrich, O. Fuhr, M. Ruben and P. Goldner.</p>
Confocal Microscopy Visualizes Particle-Crack Interactions in Epoxy Composites with Optical Force Probe-Crosslinked Rubber Particles
<p>Data (*.csv and *.lif) corresponding to Figures 2-7 of the manuscript and Figures S1-S2 of the Supporting Information.</p>
MeV TOF SIMS determination of deposition order between optically distinguishable and indistinguishable inks
<p>In the forensic investigation of questioned documents, it is often very important to know the deposition order of ink traces from two different writing tools at their intersection on a paper. In the present work, intersections of inks from several writing tools were studied using optical techniques that are standardly applied for questioned documents examination in a forensic laboratory, and an accelerator-based Ion Beam Analysis (IBA) technique called Secondary Ion Mass Spectrometry using MeV ions (MeV SIMS) that is applied in an accelerator facility. MeV SIMS provides molecular information about the studied inks from writing tools, which is an added value and can be also applied for the determination of deposition order but was so far relatively rarely used in forensic studies. Aim of this paper is to compare performance of optical techniques and MeV SIMS for several combinations of intersecting lines. Cases were divided into those in which optical techniques can distinguish used inks and those which are optically completely indistinguishable. In the latter cases, we show that although mass spectra of used inks (from blue ballpoint pens) had extremely small differences, these in combination with advanced and most importantly objective multivariate algorithms could be very beneficial in resolving the deposition order at the intersection of optically indistinguishable inks. In general, MeV SIMS proved to be more efficient for oil-based inks while difficulties were encountered with water-based ones, similar to optical methods.</p>
Dataset for "Fast and efficient demultiplexing of single photons from a GaAs quantum dot with resonantly enhanced electro-optic modulators"
<p><strong>Dataset for "Fast and efficient demultiplexing of single photons from a quantum dot with resonantly enhanced electro-optic modulators"</strong></p> <p>A description of the dataset is found in the <strong>readme.md</strong> file (markdown markup language).</p>
Leaf moisture content (live-fuel moisture content) at global scale from passive microwave satellite observations of vegetation optical depth (VOD2LFMC)
<p><strong>Related paper:</strong> <a href="https://hess.copernicus.org/preprints/hess-2022-121/">Forkel et al. (2022)</a></p> <p>The VOD2LFMC dataset contains estimates of leaf moisture content as defined as live-fuel moisture content (LFMC) derived from passive microwave satellite observation of vegetation optical depth (VOD). LFMC is defined as the fresh mass of a leaf over the dry mass and is expressed in %:</p> <p><span class="math-tex">\(LFMC = {m_{fresh}-m_{dry}\over m_{dry}}*100\%\)</span></p> <p>LFMC was estimated from the <a href="https://doi.org/10.5281/zenodo.2575599">VODCA version 1</a> dataset of Ku-band VOD using the model approach “B” as described in Forkel et al. (2022).</p> <p>The file VOD2LFMC-B_v01_2000-2017.zip contains (unzipped ~ 57 GB):</p> <ul> <li>daily global data per month netCDF files</li> <li>a README file</li> <li>Ancillary file VOD2LFMC-B_v01_support-by-obs.nc</li> </ul> <p>Grid, time and variable definitions:</p> <ul> <li> <p>Grid-name: Geographic Lat/Lon</p> </li> <li> <p>Pixel-size: 1/4 degrees</p> </li> <li> <p>Size-x: 1440</p> </li> <li> <p>Size-y: 557</p> </li> <li> <p>Time period: February 2000 – July 2017</p> </li> <li> <p>Temporal resolution: daily</p> </li> <li> <p>Variable: Live-fuel moisture content (LFMC) in %</p> </li> <li> <p>Valid-range: 0-400%</p> </li> </ul> <p> </p>
Selected data(s) from : Five-dimensional optical data storage based on ellipse orientation and fluorescence intensity in a silver-sensitized commercial glass
<p>The data selected is based on the figures below, published in the linked article (see the doi).</p> <p>- <strong>Figure 1.</strong> (<strong>a</strong>) Femtosecond laser tight focusing in the silver-containing glass, leading to the production of fluorescent silver clusters at its periphery. (<strong>b</strong>) SLM holographic phase masks with an additional cylindrical profile leading to an elliptical pattern by DLW. (<strong>c</strong>) Oriented elliptical patterns obtained by SLM phase mask manipulation, corresponding to 2<sup>4</sup> = 16 orientation-encoded levels. <strong>(Only picture)</strong></p> <p>- <strong>Figure 2.</strong> Fabricated fluorescence calibration matrix. (<strong>a</strong>) Confocal image of all basic storage units composed by 16 intensity levels and 16 orientation levels. (<strong>b</strong>) Measured fluorescence intensity versus incident DLW intensity for the 5D decoding process. <strong>(Pictures, opj file, csv datas)</strong></p> <p><strong>- </strong> <strong>Figure 3.</strong> (<strong>a</strong>,<strong>b</strong>) are the encoded images of two Nobel laureates in 16 orientation levels and 16 intensity levels, respectively. (<strong>c</strong>) 100 × 100 entangled patterns among 16 × 16 intensity and orientation levels. (<strong>d</strong>) The fluorescence calibration matrix was fabricated for decoding (fluorescence excitation at 405 nm). <strong>(Pictures, cvs datas)</strong></p> <ol> <li>ANR_ ARCHIFLUO_ICMCB_Article_Micromachines_Figure3_2020-10-21_V01 : Figure 3</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Micromachines_Figure3a_2020-10-21_V01 : Original image oritentation</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Micromachines_Figure3b_2020-10-21_V01 : Original image intensity</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Micromachines_Figure3c_Figure3d_2020-10-21_V01 : DLW image</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Micromachines_Figure3_datas_IICT4BF_2020-10-21_V01 : Intensity image converted to 4 bit format</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Micromachines_Figure3_datas_OICT4BF_T2020-10-21_V01 : Orientation image converted to 4 bit format</li> <li>ANR_ ARCHIFLUO_ICMCB_Article_Micromachines_Figure3_datas_OICT4BFL_2020-10-21_V01 : Orientation image converted to 4 bit format level</li> </ol> <p><strong>- Figure 4.</strong> (<strong>a</strong>,<strong>b</strong>) Retrieved images from the initial images of Figure 3a,b, respectively. (<strong>c</strong>,<strong>d</strong>) Histograms of the level difference between original and decoded levels for the orientation direction and the fluorescence intensity, respectively. (<strong>Picture and csv datas</strong>)</p> <p>- <strong>Figure 5.</strong> (<strong>a</strong>) Confocal top-view image of one single elliptically-shaped storage unit fabricated by using type A DLW. (<strong>b</strong>) Fluorescence intensity profile along the horizontal and vertical cross section at focal plane. (<strong>c</strong>) Fluorescence intensity profile and Gaussian fitting along the z-axis (depth). (<strong>Picture, opj file, csv datas</strong>)</p> <p> </p> <p> </p>
ScienceDex guides
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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.