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  • 1
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    Journal of Biomedical Materials Research 23 (1989), S. 491-506 
    ISSN: 0021-9304
    Keywords: Chemistry ; Polymer and Materials Science
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Medicine , Technology
    Notes: Our previous two articles have shown that glutaraldehyde-fixed bovine pericardium is nearly isotropic, whether fixed without constraints, with tethering, or with pressure. In this study, we have used uniaxial stress during fixation to produce bovine pericardial material with marked tensile anisotropy. Rectangular and cruciate pericardial samples have been mechanically examined after one of four treatments: (i) fixation under 88-kPa uniaxial stress, (ii) fixation under 176-kPa uniaxial stress, (iii) 3 h of 176-kPa uniaxial stress in saline followed by 24-h fixation under the same stress, (iv) fixation under 176-kPa uniaxial stress followed by a second fixation under 176-kPa stress in a direction normal to the first. Strips of material were cut at 0°, 30°, 60°, and 90° to direction of the initial stress, and tested for response to cyclic loading, stress relaxation, plastic deformation, and fracture properties. Fixation under uniaxial stress produced anistropy similar to that seen in porcine aortic valve leaflets; however, the overall extensibility of the material depended on the applied stress and the aspect ratio of the stressed sample. While loading in saline produced no change, the sequential biaxial stressing produced a reduction in anisotropy, suggesting exposure of additional crosslinking sites. Uniaxial stress during fixation may be a useful method for construction of anisotropic heart valve leaflets.
    Additional Material: 12 Ill.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2012-09-14
    Description: Journal of the American Chemical Society DOI: 10.1021/ja307431k
    Print ISSN: 0002-7863
    Electronic ISSN: 1520-5126
    Topics: Chemistry and Pharmacology
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  • 3
    Publication Date: 2019-01-09
    Description: Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM2.5). We use a forward geophysical approach to derive ground-level PM2.5 distributions from satellite AOD at 1 km2 resolution for 2011 over the northeastern US by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12×12 km2 horizontal resolution). Seasonal average satellite-derived PM2.5 reveals more spatial detail and best captures observed surface PM2.5 levels during summer. At the daily scale, however, satellite-derived PM2.5 is not only subject to measurement uncertainties from satellite instruments, but more importantly to uncertainties in the relationship between surface PM2.5 and column AOD. Using 11 ground-based AOD measurements within 10 km of surface PM2.5 monitors, we show that uncertainties in modeled PM2.5∕AOD can explain more than 70 % of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM2.5 evaluated at PM2.5 monitors. This finding implies that a successful geophysical approach to deriving daily PM2.5 from satellite AOD requires model skill at capturing day-to-day variations in PM2.5∕AOD relationships. Overall, we estimate that uncertainties in the modeled PM2.5∕AOD lead to an error of 11 µg m−3 in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8 µg m−3. Using multi-platform ground, airborne, and radiosonde measurements, we show that uncertainties of modeled PM2.5∕AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model representation of relative humidity and aerosol vertical profile shape contributes some systematic biases. The parameterization of aerosol optical properties, which determines the mass extinction efficiency, also contributes to random uncertainty, with the size distribution being the largest source of uncertainty and hygroscopicity of inorganic salt the second largest. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM2.5 from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM2.5.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 4
    Publication Date: 2018-10-04
    Description: Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM2.5). We use a forward geophysical approach to derive ground-level PM2.5 distributions from satellite AOD at 1km2 resolution for 2011 over the Northeast USA by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12×12km2 horizontal resolution). Seasonal average satellite-derived PM2.5 reveals more spatial detail and best captures observed surface PM2.5 levels during summer. At the daily scale, however, satellite-derived PM2.5 is not only subject to measurement uncertainties from satellite instruments, but more importantly, to uncertainties in the relationship between surface PM2.5 and column AOD. Using 11 ground-based AOD measurements within 10km of surface PM2.5 monitors, we show that uncertainties in modeled PM2.5/AOD can explain more than 70% of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM2.5 evaluated at PM2.5 monitors. This finding implies that a successful geophysical approach to deriving daily PM2.5 from satellite AOD requires model skill at capturing day-to-day variations in PM2.5/AOD relationships. Overall, we estimate that uncertainties in the modeled PM2.5/AOD lead to an error of 11μg/m3 in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8μg/m3. Using multi-platform ground, airborne and radiosonde measurements, we show that uncertainties of modeled PM2.5/AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model uncertainties of relative humidity and aerosol vertical profile shape contribute some systematic biases. The parameterization of aerosol optical properties, which determines the mass-extinction efficiency, also contributes to random uncertainty, with the size distribution the largest source of uncertainty, and hygroscopicity of inorganic salt the second. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM2.5 from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM2.5.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 5
  • 6
    Publication Date: 2019-07-13
    Description: Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM2.5). We use a forward geophysical approach to derive ground-level PM2.5 distributions from satellite AOD at 1 km2(exp) resolution for 2011 over the northeastern US by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 1212 km2(exp) horizontal resolution). Seasonal average satellite-derived PM2.5 reveals more spatial detail and best captures observed surface PM2.5 levels during summer. At the daily scale, however, satellite-derived PM2.5 is not only subject to measurement uncertainties from satellite instruments, but more importantly to uncertainties in the relationship between surface PM2.5 and column AOD. Using 11 ground-based AOD measurements within 10 km of surface PM2.5 monitors, we show that uncertainties in modeled PM2.5AOD can explain more than 70 % of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM2.5 evaluated at PM2.5 monitors. This finding implies that a successful geophysical approach to deriving daily PM2.5 from satellite AOD requires model skill at capturing day-to-day variations in PM2.5AOD relationships. Overall, we estimate that uncertainties in the modeled PM2.5AOD lead to an error of 11 g m3(exp) in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8 g m3(exp). Using multi-platform ground, airborne, and radiosonde measurements, we show that uncertainties of modeled PM2.5AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model representation of relative humidity and aerosol vertical profile shape contributes some systematic biases. The parameterization of aerosol optical properties, which determines the mass extinction efficiency, also contributes to random uncertainty, with the size distribution being the largest source of uncertainty and hygroscopicity of inorganic salt the second largest. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM2.5 from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM2.5.
    Keywords: Geosciences (General)
    Type: GSFC-E-DAA-TN66622 , Atmospheric Chemistry & Physics (e-ISSN 1680-7324); 19; 1; 295-313
    Format: text
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