931 resultados para 065
Resumo:
TEX86 (TetraEther indeX of tetraethers consisting of 86 carbon atoms) is a sea surface temperature (SST) proxy based on the distribution of archaeal isoprenoid glycerol dialkyl glycerol tetraethers (GDGTs). In this study, we appraise the applicability of TEX86 and TEX86L in subpolar and polar regions using surface sediments. We present TEX86 and TEX86L data from 160 surface sediment samples collected in the Arctic, the Southern Ocean and the North Pacific. Most of the SST estimates derived from both TEX86 and TEX86L are anomalously high in the Arctic, especially in the vicinity of Siberian river mouths and the sea ice margin, plausibly due to additional archaeal contributions linked to terrigenous input. We found unusual GDGT distributions at five sites in the North Pacific. High GDGT-0/crenarchaeol and GDGT-2/crenarchaeol ratios at these sites suggest a substantial contribution of methanogenic and/or methanotrophic archaea to the sedimentary GDGT pool here. Apart from these anomalous findings, TEX86 and TEX86L values in the surface sediments from the Southern Ocean and the North Pacific do usually vary with overlaying SSTs. In these regions, the sedimentary TEX86-SST relationship is similar to the global calibration, and the derived temperature estimates agree well with overlaying annual mean SSTs at the sites. However, there is a systematic offset between the regional TEX86L-SST relationships and the global calibration. At these sites, temperature estimates based on the global TEX86L calibration are closer to summer SSTs than annual mean SSTs. This finding suggests that in these subpolar settings a regional TEX86L calibration may be a more suitable equation for temperature reconstruction than the global calibration.
Resumo:
Low planktic and benthic d18O and d13C values in sediments from the Nordic seas of cold stadials of the last glaciation have been attributed to brines, formed similar to modern ones in the Arctic Ocean. To expand on the carbon isotopes of this hypothesis I investigated benthic d13C from the modern Arctic Ocean. I show that mean d13C values of live epibenthic foraminifera from the deep Arctic basins are higher than mean d13C values of upper slope epibenthic foraminifera. This agrees with mean high d13C values of dissolved inorganic carbon (DIC) in Arctic Bottom Water (ABW), which are higher than mean d13CDIC values from shallower water masses of mainly Atlantic origin. However, adjustments for oceanic 13C-Suess depletion raise subsurface and intermediate water d13CDIC values over ABW d13CDIC ones. Accordingly, during preindustrial Holocene times, the d13CDIC of ABW was as high or higher than today, but lower than the d13CDIC of younger subsurface and intermediate water. If brine-enriched water significantly ventilated ABW, brines should have had high d13CDIC values. Analogously, high-d13CDIC brines may have been formed in the Nordic seas during warm interstadials. During cold stadials, when most of the Arctic Ocean was perennially sea-ice covered, a cessation of high-d13CDIC brine rejection may have lowered d13CDIC values of ABW, and ultimately the d13CDIC in Nordic seas intermediate and deep water. So, in contrast to the idea of enhanced brine formation during cold stadials, the results of this investigation imply that a cessation of brine rejection would be more likely.
Resumo:
Sedimentation of pelagic biogenic coccolithic-foraminiferal sediments predominates in the section of the South Atlantic ridge between 20° and 30°S. Sedimentation rate and thickness of Late Quaternary sediments differ in the rift valley, the crestal section of the ridge, its flanks and transform faults. Holocene and layers representing the most recent and pen¬ultimate continental glaciations and the last interglacial are distinguishable in the late Quaternary profile. During their development, changes in the mean annual sea surface temperature in the tropical zone of the South Atlantic were minimal, i.e. 1-2°C.
Resumo:
Based on the quantitative analysis of diatom assemblages preserved in 274 surface sediment samples recovered in the Pacific, Atlantic and western Indian sectors of the Southern Ocean we have defined a new reference database for quantitative estimation of late-middle Pleistocene Antarctic sea ice fields using the transfer function technique. The Detrended Canonical Analysis (DCA) of the diatom data set points to a unimodal distribution of the diatom assemblages. Canonical Correspondence Analysis (CCA) indicates that winter sea ice (WSI) but also summer sea surface temperature (SSST) represent the most prominent environmental variables that control the spatial species distribution. To test the applicability of transfer functions for sea ice reconstruction in terms of concentration and occurrence probability we applied four different methods, the Imbrie and Kipp Method (IKM), the Modern Analog Technique (MAT), Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WAPLS), using logarithm-transformed diatom data and satellite-derived (1981-2010) sea ice data as a reference. The best performance for IKM results was obtained using a subset of 172 samples with 28 diatom taxa/taxa groups, quadratic regression and a three-factor model (IKM-D172/28/3q) resulting in root mean square errors of prediction (RMSEP) of 7.27% and 11.4% for WSI and summer sea ice (SSI) concentration, respectively. MAT estimates were calculated with different numbers of analogs (4, 6) using a 274-sample/28-taxa reference data set (MAT-D274/28/4an, -6an) resulting in RMSEP's ranging from 5.52% (4an) to 5.91% (6an) for WSI as well as 8.93% (4an) to 9.05% (6an) for SSI. WA and WAPLS performed less well with the D274 data set, compared to MAT, achieving WSI concentration RMSEP's of 9.91% with WA and 11.29% with WAPLS, recommending the use of IKM and MAT. The application of IKM and MAT to surface sediment data revealed strong relations to the satellite-derived winter and summer sea ice field. Sea ice reconstructions performed on an Atlantic- and a Pacific Southern Ocean sediment core, both documenting sea ice variability over the past 150,000 years (MIS 1 - MIS 6), resulted in similar glacial/interglacial trends of IKM and MAT-based sea-ice estimates. On the average, however, IKM estimates display smaller WSI and slightly higher SSI concentration and probability at lower variability in comparison with MAT. This pattern is a result of different estimation techniques with integration of WSI and SSI signals in one single factor assemblage by applying IKM and selecting specific single samples, thus keeping close to the original diatom database and included variability, by MAT. In contrast to the estimation of WSI, reconstructions of past SSI variability remains weaker. Combined with diatom-based estimates, the abundance and flux pattern of biogenic opal represents an additional indication for the WSI and SSI extent.
Resumo:
Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.
Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.
Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.
Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.
Resumo:
The chemical composition of surface associated metabolites of two Fucus species (Fucus vesiculosus and Fucus serratus) was analysed by means of gas chromatography-mass spectrometry (GC-MS) to describe temporal patterns in chemical surface composition. Method: The two perennial brown macroalgae F. vesiculosus and F. serratus were sampled monthly at Bülk, outer Kiel Fjord, Germany (54°27'21 N / 10°11'57 E) over an entire year (August 2012 - July 2013). Per month and species six non-fertile Fucus individuals were collected from mixed stands at a depth of 0.5 m under mid water level. For surface extraction approx. 50 g of the upper 5-10 cm apical thalli tips were cut off per species. The surface extraction of Fucus was performed according to the protocol of de Nys and co-workers (1998) with minor modifications (see Rickert et al. 2015). GC/EI-MS measurements were performed with a Waters GCT premier (Waters, Manchester, UK) coupled to an Agilent 6890N GC equipped with a DB-5 ms 30 m column (0.25 mm internal diameter, 0.25 mM film thickness, Agilent, USA). The inlet temperature was maintained at 250°C and samples were injected in split 10 mode. He carrier gas flow was adjusted to 1 ml min-1. Alkanes were used for referencing of retention times. For further details (GC-MS sample preparation and analysis) see the related publication (Rickert et al. submitted to PLOS ONE).