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379 results for “absorber”
Colored dissolved organic matter (CDOM) absorbance from lagoon, ocean, and river sites along the Alaska Beaufort Sea coast, 2021-ongoing
Multiple water types (river, lagoon, ocean) from the North Slope of Alaska and nearshore Beaufort Sea are sampled seasonally by the Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program to investigate biogeochemical linkages between terrestrial, lagoon, and open ocean ecosystems. Water samples from multiple depths are collected during full ice cover (April), ice break-up (mid-June to early July), and open water (late July and August) periods, filtered, and analyzed for light absorption spectra within 24 hours of collection. Wavelength-specific light absorption coefficients are reported between 250 and 600 nanometers. The data is organized in "long" or "tidy" format, with columns of station, date, wavelength, and absorption. Please see included MakeColumnsAsWavelengths.R, MakeColumnsAsDates.R, and ReshapeDataInExcel.txt for some common ways to reorganize the table for further CDOM analysis. In 2022, data from 2019 were removed due to quality issues (please see revision 1 of this dataset for 2019 CDOM values). For users who may have used 2019 data from this dataset, there are additional files to inform decisions going forward. "BLE_LTER_CDOM_2019_sample_flags.csv" lists which 2019 samples are entirely unreliable, versus usable with caution. "BLE_LTER_CDOM_2021_blank_mean_sd_absorptions.csv" lists mean and standard deviations at each wavelength from all blanks taken in 2021; this is meant to give info on the instruments used and will not be updated further. Please see the methods section for more information on 2019 data.
Multispectral absorbance and fluorescence analysis of dissolved organic carbon in water samples taken from the Upper Clark Fork River (Montana, USA) during water years 2017 and 2018 (1 Oct 2016 - 30 Sep 2018)
The Upper Clark Fork River (UCFR) Long Term Research in Environmental Biology (LTREB) umbrella monitoring project generating these data is conducted separately and complementarily to the 200-million-dollar (USD) superfund project for ecological restoration of the UCFR, associated tributaries, and head water streams including Silver Bow and Warm Springs Creeks. Restoration along the UCFR in western Montana includes removal of metal-laden floodplain soils, lowering of the floodplain to its original elevation, and re-vegetation of over 70 km of the river’s floodplain closest to contaminant sources. The UCFR LTREB project includes bi-weekly water quality monitoring across the first 200 km of the river and its major tributaries along a gradient of heavy metal contamination associated with historic mining. Monitoring includes inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and dissolved and whole-water heavy metal concentrations. The monitoring program began in 2017 with funding likely to be extended through 2028. The original analytical intent for these data was to assess the response of river dissolved organic carbon to the floodplain restoration. Data are multispectral absorbance and fluorescence analyses of organic carbon dissolved in samples of well-mixed river thalweg water. Data include excitation-emission matrices, absorbance spectroscopy, as well as absorbance and fluorometric summary indices calculated at specific wavelengths of excitation and emission. Data are from the 2017 and 2018 water years (1 Oct 2016 to 30 Sep 2018). Data were collected on the Upper Clark Fork River (USGS HUC 17010201) at 13 project sites distributed along the river from the vicinity of Anaconda to Missoula, Montana, USA. These data are a correction of a previously published data product (doi:10.6073/pasta/6ba30f4ebb63175a4399c5d0aa6a8698). Inconsistencies between availability of EEMS data, absorbance data, and fluorometric summary metrics have been corrected. P
Multispectral absorbance and fluorescence analysis of dissolved organic carbon in water samples taken from the Upper Clark Fork River (Montana, USA) during water year 2019 (1 Oct 2018 - 30 Sep 2019)
The Upper Clark Fork River (UCFR) Long Term Research in Environmental Biology (LTREB) umbrella monitoring project generating these data is conducted separately and complementarily to the 200-million-dollar (USD) superfund project for ecological restoration of the UCFR, associated tributaries, and head water streams including Silver Bow and Warm Springs Creeks. Restoration along the UCFR in western Montana includes removal of metal-laden floodplain soils, lowering of the floodplain to its original elevation, and re-vegetation of over 70 km of the river’s floodplain closest to contaminant sources. The UCFR LTREB project includes bi-weekly water quality monitoring across the first 200 km of the river and its major tributaries along a gradient of heavy metal contamination associated with historic mining. Monitoring includes inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and dissolved and whole-water heavy metal concentrations. The monitoring program began in 2017 with funding likely to be extended through 2028. The original analytical intent for these data was to assess the response of river dissolved organic carbon to the floodplain restoration. Data are multispectral absorbance and fluorescence analyses of organic carbon dissolved in samples of well-mixed river thalweg water. Data include excitation-emission matrices, absorbance spectroscopy, as well as absorbance and fluorometric summary indices calculated at specific wavelengths of excitation and emission. Data are from the 2019 water year (1 Oct 2018 to 30 Sep 2019). Data were collected on the Upper Clark Fork River (USGS HUC 17010201) at 13 project sites distributed along the river from the vicinity of Anaconda to Missoula, Montana, USA.
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.
Ultraviolet-visible spectroscopy absorbances for dissolved organic matter from Lake Mendota from June – November 2017
Dissolved organic matter (DOM) is a complex mixture of organic compounds found in all natural waters. Its composition affects its reactivity towards numerous processes. Its composition is a function of both its source (e.g., allochthonous or autochthonous) as well as the extent of environmental processing it has undergone (e.g., chemical or biological degradation). Ultraviolet-visible (UV-vis) spectroscopy is an analytical technique commonly used to assess the composition of dissolved organic matter in water samples. Here, we present spectra from Lake Mendota samples collected from June - November in 2017 at the surface of Lake Mendota as well as at specific depths within the water column. All samples were collected near the NTL-LTER research buoy. Absorbance values are listed for wavelengths 200 - 800 nm for each sample.
Time series of in situ Uv-Vis absorbance spectra and high-frequency predictions of total and soluble Fe and Mn concentrations measured at multiple depths in Falling Creek Reservoir (Vinton, VA, USA) in 2020 and 2021
High-frequency measurements of light absorbance were collected at multiple depths in Falling Creek Reservoir (FCR; Vinton, VA, USA) using a s::can Spectrolyser UV-Visible spectrophotometer coupled with a multiplexor pumping system. The system pumps water samples from individual depths into a flow-through cuvette where the UV-vis absorbance spectra of the sample are measured by the spectrophotometer. The system used in our study collected measurements of light absorbance every 2.5 nm wavelengths from 200 nm to 732.5 nm (optical path length of 10 mm) approximately at an hourly time step for seven monitoring depths in the reservoir. Data was collected during two periods; the first deployment (16 October to 9 November 2020) was to observe changes in Fe and Mn concentrations before, during, and after reservoir fall turnover and the second deployment (26 May to 21 June 2021) was to observe the effects of engineered hypolimnetic oxygenation on Fe and Mn concentrations. Partial least squares regression models were developed to generate predictions of total and soluble Fe and Mn concentrations based on the correlation between absorbance spectra and sampling data.
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) at 250 m monthly for period 2014-2019 based on COPERNICUS land products
<p>Long-term monthly Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) median value at 250 m based on the time-series of <a href="https://land.copernicus.eu/global/products/fapar">COPERNICUS FAPAR</a>. Derived using the data.table package and quantile function in R. Processing steps are available <a href="https://gitlab.com/openlandmap/global-layers/tree/master/input_layers/Copernicus_vito"><strong>here</strong></a>. Antartica is not included.</p> <p>To access and visualize maps use: <a href="http://www.openlandmap.org/">OpenLandMap.org</a></p> <p>If you discover a bug, artifact or inconsistency in the LandGIS maps, or if you have a question please use some of the following channels:</p> <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/issues">https://gitlab.com/openlandmap/global-layers/issues</a> </li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul> <p>All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention:</p> <ul> <li>veg = theme: vegetation,</li> <li>fapar = Fraction of Absorbed Photosynthetically Active Radiation,</li> <li>proba.v.oct = determination method: PROBA-V products, month October,</li> <li>d = median value,</li> <li>250m = spatial resolution / block support: 250 m,</li> <li>s0..0cm = vertical reference: land surface,</li> <li>2014..2019 = time reference: from 2014 to 2019,</li> <li>v1.0 = version number: 1.0,</li> </ul>
Absorbed soil nutrients on ion exchange membranes in the reciprocal transplant gardens at Toolik Lake, Coldfoot, and Sagwon in 2016
Transplant gardens at Toolik Lake and Sagwon were established in 2014. At each location, 60 tussocks each from ecotypes of Eriophorum vaginatum from Coldfoot (CF, 67°15′32″N, 150°10′12″W), Toolik Lake (TL, 68°37′44″N, 149°35′0″W), and Sagwon (SG, 69°25′26″N, 148°42′49″W) were transplanted. At the reciprocal transplant gardens, ion exchange membranes were used to measure nutrient availability over two time periods: Early season (June) and mid season (July). Membranes were deployed in the field for either 20 or 21 days, depending on travel constraints.
Spectral Effects of Absorbing Aerosols on Backscattered UV Radiation
<p>Satellite measurements of backscattered UV radiation are sensitive to the presence of UV-absorbing aerosols in the atmosphere. These measurements are commonly used for determining the concentration of atmospheric trace gases such as O<sub>3</sub>, SO<sub>2</sub>, and H<sub>2</sub>CO.</p> <p>The theoretical results in this dataset describe the effects of UV-absorbing mineral dust and carbonaceous smoke aerosols on these backscatter satellite measurements between 300-400 nm. The information provided is independent of any specific trace gas retrieval algorithm and does not require detailed a priori knowledge of aerosol and surface properties.</p> <p>The results are derived from the analysis of the radiative transfer model simulations performed with the optical property data used in the Ozone Monitoring Instrument (OMI) UV aerosol retrieval algorithm, OMAERUV. Results from this algorithm have been validated with Aerosol Robotic Network (AERONET) observations (Jethva & Torres, 2011; Torres et al., 2018).</p> <p>This dataset is associated with the following publication:</p> <p>Jethva, H., Haffner, D., Bhartia, P. K., & Torres, O. (2022). Estimating Spectral Effects of Absorbing Aerosols on Backscattered UV Radiation, Earth Space Sci., Accepted.</p>
Impact of nonlinear hydrodynamic modelling on geometric optimisation of a spherical heaving point absorber
<p>Due to the amount of iterative computation involved, researchers involved in geometric optimisation of wave energy devices typically employ linear hydrodynamic models. However, the exaggerated motion of wave energy devices, aided by energy maximising control action, challenges the assumptions upon which linear hydrodynamic modelling relies. Furthermore, the optimal device geometry is also sensitive to the nature of the energy-maximisation controller employed, and to the set of wave conditions over which the optimisation is carried out.<br> <br> In order to focus on the essential issues, this study takes the simplest possible device for optimisation, a heaving sphere (with just one free parameter), but one which exhibits nonlinear hydrodynamic characteristics, due to the non-uniform cross-sectional area. The study examines the sensitivity to the inclusion of nonlinear Froude-Krylov forces. In addition, the sensitivity of the optimal device size to differences in the applied control algorithm is also studied, as are effects due to different representative sea state representations and performance evaluation criteria.</p>
EU FAR Database: EU Funds absorbed by Romanian Municipalities 2016-2021
<p>EU funds reported by each locality (municipality) in their annual budgets execution reports. The data is processed by the authors, based on the information published by the Ministry of Development, Public Works and Administration, Directorate for Local Fiscal and Budgetary Policies.</p>
Raw absorbance data and R codes for analysing enzymatic activities
<p>Raw absorbance data and sample metadata for study by Prokkola et al. (submitted 2023). See README.</p><p>Statistical analysis of data available in another repository https://doi.org/10.5281/zenodo.8014314.</p><p> </p>
Data from: Non-invasive estimation of absorbed ionizing radiation dose in mice using Near-Infrared Spectroscopy (NIRS) and aquaphotomics
<p>Accurate measurement of ionizing radiation exposure, whether therapeutic or accidental, is of utmost importance in various scenarios. This paper presents a study that addresses this critical need by utilizing near-infrared (NIR) spectroscopy and aquaphotomics to estimate radiation dose exposure in mouse models subjected to X-ray irradiation. The analysis of NIR spectra acquired from the mouse abdomen enabled non-invasive estimation of radiation doses ranging from 0.5 to 6.5 Gy, immediately following the irradiation exposure. The findings were consistent with the impact of total body irradiation in mice, as evidenced by measures such as animal survival rate, alterations in body weight observed over a 30-day post-exposure period, and changes in hematocrit levels. The spectroscopic measurements were based on detecting changes in the molecular structure of body water after radiation exposure, utilizing the water spectral pattern as a multidimensional biomarker. While further validation in nonhuman primates is necessary, the findings demonstrate a simple, non-destructive, and rapid method that holds promise for the estimation of radiation exposure across a range of doses, applicable to both clinical applications and catastrophic radiation events. These advancements in radiation dose quantification have significant implications for the timely and precise assessment of radiation exposure in humans.</p>
Riverine truly dissolved, colloidal, and operationally dissolved ferric iron, dissolved organic carbon, UV-vis absorbance at 254 and 412 nm, and specific UV absorbance (SUVA) at 254 nm
<p>This dataset is attached to the following article:</p> <p>Logozzo, L.A., Martin, J.W., McArthur, J., Raymond, P.A. Contributions of Fe(III) to UV-vis absorbance in river water: A case study on the Connecticut River and argument for the systematic tandem measurement of Fe(III) and CDOM. <em>Biogeochemistry</em> <strong>160</strong>: 17–33 (2022). https://doi.org/10.1007/s10533-022-00937-5</p> <p>This dataset includes concentrations of ferric iron, Fe(III), and dissolved organic carbon (DOC) along with UV-vis absorbance at 254 nm and 412 nm on the operationally dissolved size fraction (<0.22 μm), as well as the truly dissolved (<0.02 μm) and colloidal (0.02-0.22 μm) size fractions. Samples were collected every two weeks at five sites along the Connecticut River mainstem from 2018 to 2020 and at 7 sites in the Connecticut River watershed sampled once synoptically during the summer 2019.</p>
Fig. 2 in Absorbing Hybridization Of Cobitis Taenia And Sabanejewia Aurata (Cypriniformes, Cobitidae) In Water Reservoirs Of Northern Ukraine Connected With Diploid-Polyploid Complex Formation
Fig. 2. Electrophoretic spectra of enzymes coding by allozymic loci: aspartate amynotransferase (1 — Aat- 1100/100, 2 — Aat-1100/110-110, 3 — Aat-195/110-110, 4 — Aat-1100-100/110, 5 — Aat-195-95/110, 6 — Aat-195-100/110), lactate dehydrogenase (1 — Ldh-B90/90, 2 — Ldh-B100/100, 3 — Ldh-B90/100-100, 4 — Ldh-B90/100/110), malate dehydrogenase (1 — Mdh-1A100/100, 2 — Mdh-1A100/110-110, 3 — Mdh-1A100-100/110).
Data to reproduce the results presented in Lake et al. 2024. Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2024.131930. ("High-frequency spatial sediment source fingerprinting using in situ absorbance data")
<p>This repository contains data on the used absorbance data, measured at the field site, as described in Lake et al., 2024 (<span>h</span><span>t</span><span>t</span><span>p</span><span>s</span><span>:</span><span>/</span><span>/</span><span>d</span><span>o</span><span>i</span><span>.</span><span>o</span><span>r</span><span>g</span><span>/</span><span>1</span><span>0</span><span>.</span><span>1</span><span>0</span><span>1</span><span>6</span><span>/</span><span>j</span><span>.</span><span>j</span><span>h</span><span>y</span><span>d</span><span>r</span><span>o</span><span>l</span><span>.</span><span>2</span><span>0</span><span>2</span><span>4</span><span>.</span><span>1</span><span>3</span><span>1</span><span>9</span><span>3</span><span>0).</span> Furthermore, data on the turbidity, used calibration curves and R code to prepare the input data for the MixSIAR model are included in the data repository.</p>
Dataset of the manuscript: Predictive design to determine optimal absorber placement in colloidal photonic crystals
<p><span>This data publication is based on the metadata and datasets underlying the manuscript "Predictive design to determine optimal absorber placement in colloidal photonic crystals". The Data is roughly organized by the figure of appearance.</span></p> <p><span>Figure 1 contained no result data</span></p> <p><span>Figure "Figure 2" contains:</span></p> <ul> <li><span>Simulated and experimental reflectance spectra of bare PS colloidal crystal and CIELab color coordinates of simulated bare PS colloidal crystal.</span></li> </ul> <p><span>Figure "Figure 3+4" contains:</span></p> <ul> <li><span>Data for particle based and layer based designs for chroma optimization according to Eq. 2 </span></li> <ul> <li><span>convergence history J(steps)</span></li> <li><span>Optimized design absorber distributions (average of layers)</span></li> <li><span>CIELab color coordinates</span></li> <li><span>Spectra</span></li> </ul> <li><span>CIELab color coordinates and Chroma of all predictive designs sorted by threshold L value according to Eq. 3 + comparative designs: bottom absorber, top absorber, homogeneous.</span></li> </ul> <p><span>Figure "Figure 5" contains:</span></p> <ul> <li><span>Chemdraw File containing chemical structures</span></li> <li><span>Pendant drop surface tension measurements </span></li> <li><span>Surface pressure increase on Langmuir-Blodgett trough</span></li> </ul> <p><span>Figure "Figure 6" contains:</span></p> <ul> <li><span>SEM images of mono- and multilayers labeled in accordance to design and composition</span></li> </ul> <p><span>Figure "Figure 7+8" contains:</span></p> <ul> <li><span>Photographs of fabricated multilayers</span></li> <ul> <li><span>Homogeneous designs labeled in accordance to composition</span></li> <li><span>Layered designs labeled in accordance to design type (XBA: bottom absorber with X absorbing numbers; XTA: bottom absorber with X absorbing numbers; Ld_XX: predictive design with L threshold of XX)</span></li> </ul> <li><span>Spectra of all samples including their error determined from 2 measurements</span></li> <li><span>Average spectra of all designs (averaged from all samples of that design) including their error estimated using gaussian error propagation</span></li> <li><span>Color data of all samples calculated from spectra </span></li> <ul> <li><span>CIELab coordinates and Chroma</span></li> <li><span>xyz values</span></li> <li><span>RGB values</span></li> </ul> </ul> <p><span>Figure "Figure 9" contains:</span></p> <ul> <li><span>Optimized design absorber distributions, spectra and CIELab color coordinates and chroma for colloidal crystals of varying primary particle size</span></li> </ul>
Matrices for a plate with tuned vibration absorbers
<p>Matrices for a numerical model of an aluminum plate equipped with tuned vibration absorbers (TVA).</p> <p>For usage see RUNME.m and the <a href="http://modelreduction.org/index.php/Plate_with_tuned_vibration_absorbers">MOR Wiki</a>.</p> <p>Version history:</p> <ul> <li>1.0: Initial release</li> <li>1.1: Added RUNME.py</li> </ul>
5D-NP-FABTECH_FSG - Open Dataset for "Highly Conformable Terahertz Metasurface Absorbers via Two-photon Polymerization on Polymeric Ultra-thin Films"
<p>This is the open dataset for the paper: "Ottomaniello Andrea, Paolo Vezio, Omar Tricinci, Frank Marco den Hoed, Paul Dean, Alessandro Tredicucci and Virgilio Mattoli, Highly Conformable Terahertz Metasurface Absorbers via Two-photon Polymerization on Polymeric Ultra-thin Films, On line (2023) [DOI:10.5281/zenodo.7838033]".</p> <p>This include the Supplementary Information file ("suppl_j_nanoph-2022-0667_suppl.pdf"), all the source material used for the paper preparation and more. </p> <p>For each folder (sub-dataset) there is a corresponding readme file describing the content and including metadata</p>
Frozen sound: An ultra-low frequency, ultra-broadband, non-reciprocal acoustic absorber
<p>The files contains the main results found in the paper 'Frozen sound: An ultra-low frequency, ultra-broadband, non-reciprocal acoustic absorber'. </p> <p>Each file contain an absorption coefficient in the form of a vector with its corresponding frequency.</p> <p>TA: Refers to the thermoacoustic absorber, i.e in the presence of cooling.</p> <p>NoTA: Refers to the porous material without cooling.</p>
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