18 resultados para SCANNING CALORIMETRIC ANALYSIS

em CentAUR: Central Archive University of Reading - UK


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Commercially supplied chicken breast muscle was subjected to simultaneous heat and pressure treatments. Treatment conditions ranged from ambient temperature to 70 °C and from 0.1 to 800 MPa, respectively, in various combinations. Texture profile analysis (TPA) of the treated samples was performed to determine changes in muscle hardness. At treatment temperatures up to and including 50 °C, heat and pressure acted synergistically to increase muscle hardness. However, at 60 and 70 °C, hardness decreased following treatments in excess of 200 MPa. TPA was performed on extracted myofibrillar protein gels that after treatment under similar conditions revealed similar effects of heat and pressure. Differential scanning calorimetry analysis of whole muscle samples revealed that at ambient pressure the unfolding of myosin was completed at 60 °C, unlike actin, which completely denatured only above 70 °C. With simultaneous pressure treatment at >200 MPa, myosin and actin unfolded at 20 °C. Unfolding of myosin and actin could be induced in extracted myofibrillar protein with simultaneous treatment at 200 MPa and 40 °C. Electrophoretic analysis indicated high pressure/temperature regimens induced disulfide bonding between myosin chains.

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A series of self-assembling terminally blocked tripeptides (containing coded amino acids) form gels in various aromatic solvents including benzene, toluene, xylenes at low concentrations. However these tripeptides do not form gels in aliphatic hydrocarbons like n-hexane, cyclohexane, n-decane etc. Morphological studies of the dried gel indicate the presence of an entangled fibrous network, which is responsible for gelation. Differential scanning calorimetric (DSC) studies of the gels produced by peptide 1 clearly demonstrates thermoreversible nature of the gel and tripeptide-solvent complex may be produced during gel formation. FT-IR and H-1 NMR studies of the gels demonstrate that an intermolecular hydrogen-bonding network is formed during gelation. Single crystal X-ray diffraction studies for peptides 1, 2 and 3 have been performed to investigate the molecular arrangement that might be responsible for forming the fibrous network of these self-assembling peptide gelators. It has been found that the morph responsible for gelation of peptides 1, 2 and 3 in benzene is somewhat different from that of its xerogel.

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Ochre samples excavated from the neolithic site at Qatalhoyuk, Turkey have been compared with "native" ochres from Clearwell Caves, UK using infrared spectroscopy backed up by Raman spectroscopy, scanning electron microscopy (with energy-dispersive X-rays (EDX) analysis), powder X-ray diffraction, diffuse reflection UV-Vis and atomic absorption spectroscopies. For the Clearwell Caves ochres, which range in colour from yellow-orange to red-brown, it is shown that the colour is related to the nature of the chromophore present and not to any differences in particle size. The darker red ochres contain predominantly haematite while the yellow ochre contains only goethite. The ochres from Qatalhoyuk contain only about one-twentieth of the levels of iron found in the Clearwell Caves ochres. The iron oxide pigment (haematite in all cases studied here) has been mixed with a soft lime plaster which also contains calcite and silicate (clay) minerals. (C) 2003 Elsevier B.V. All rights reserved.

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An eddy current testing system consists of a multi-sensor probe, a computer and a special expansion card and software for data-collection and analysis. The probe incorporates an excitation coil, and sensor coils; at least one sensor coil is a lateral current-normal coil and at least one is a current perturbation coil.

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An eddy current testing system consists of a multi-sensor probe, computer and a special expansion card and software for data collection and analysis. The probe incorporates an excitation coil, and sensor coils; at least one sensor coil is a lateral current-normal coil and at least one is a current perturbation coil.

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Iron oxidation in the bacterial ferritin EcFtnA from Escherichia coli shows marked differences from its homologue human H-chain ferritin (HuHF). While the amino acid residues that constitute the dinuclear center in these proteins are highly conserved, EcFtnA has a third iron-binding site (C site) in close proximity to the dinuclear center that is seemingly responsible for these differences. Here, we describe the first thermodynamic study of Fe2+ binding to EcFtnA and its variants to determine the location of the primary ferrous ion-binding sites on the protein and to better understand the role of the third C site in iron binding. Isothermal titration calorimetric analyses of the wild-type protein reveal the presence of two main classes of binding sites in the pH range of 6.5-7.5, ascribed to Fe2+ binding, first at the A and then the B sites. Site-directed mutagenesis of ligands in the A, B, or C sites affects the apparent Fe2+-binding stoichiometries at the unaltered sites. The data imply some degree of inter- and intrasubunit negative cooperative interaction between sites. Unlike HuHF where only the A site initially binds Fe2+, both A and B sites in EcFtnA bind Fe2+, implying a role for the C site in influencing the binding of Fe2+ at the B site of the di-iron center of EcFtnA. The ITC equations describing a binding model for three classes of independent binding sites are reported here for the first time.

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Ochre samples excavated from the neolithic site at Qatalhoyuk, Turkey have been compared with "native" ochres from Clearwell Caves, UK using infrared spectroscopy backed up by Raman spectroscopy, scanning electron microscopy (with energy-dispersive X-rays (EDX) analysis), powder X-ray diffraction, diffuse reflection UV-Vis and atomic absorption spectroscopies. For the Clearwell Caves ochres, which range in colour from yellow-orange to red-brown, it is shown that the colour is related to the nature of the chromophore present and not to any differences in particle size. The darker red ochres contain predominantly haematite while the yellow ochre contains only goethite. The ochres from Qatalhoyuk contain only about one-twentieth of the levels of iron found in the Clearwell Caves ochres. The iron oxide pigment (haematite in all cases studied here) has been mixed with a soft lime plaster which also contains calcite and silicate (clay) minerals. (C) 2003 Elsevier B.V. All rights reserved.

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A fully automated procedure to extract and to image local fibre orientation in biological tissues from scanning X-ray diffraction is presented. The preferred chitin fibre orientation in the flow sensing system of crickets is determined with high spatial resolution by applying synchrotron radiation based X-ray microbeam diffraction in conjunction with advanced sample sectioning using a UV micro-laser. The data analysis is based on an automated detection of azimuthal diffraction maxima after 2D convolution filtering (smoothing) of the 2D diffraction patterns. Under the assumption of crystallographic fibre symmetry around the morphological fibre axis, the evaluation method allows mapping the three-dimensional orientation of the fibre axes in space. The resulting two-dimensional maps of the local fibre orientations - together with the complex shape of the flow sensing system - may be useful for a better understanding of the mechanical optimization of such tissues.

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Full-waveform laser scanning data acquired with a Riegl LMS-Q560 instrument were used to classify an orange orchard into orange trees, grass and ground using waveform parameters alone. Gaussian decomposition was performed on this data capture from the National Airborne Field Experiment in November 2006 using a custom peak-detection procedure and a trust-region-reflective algorithm for fitting Gauss functions. Calibration was carried out using waveforms returned from a road surface, and the backscattering coefficient c was derived for every waveform peak. The processed data were then analysed according to the number of returns detected within each waveform and classified into three classes based on pulse width and c. For single-peak waveforms the scatterplot of c versus pulse width was used to distinguish between ground, grass and orange trees. In the case of multiple returns, the relationship between first (or first plus middle) and last return c values was used to separate ground from other targets. Refinement of this classification, and further sub-classification into grass and orange trees was performed using the c versus pulse width scatterplots of last returns. In all cases the separation was carried out using a decision tree with empirical relationships between the waveform parameters. Ground points were successfully separated from orange tree points. The most difficult class to separate and verify was grass, but those points in general corresponded well with the grass areas identified in the aerial photography. The overall accuracy reached 91%, using photography and relative elevation as ground truth. The overall accuracy for two classes, orange tree and combined class of grass and ground, yielded 95%. Finally, the backscattering coefficient c of single-peak waveforms was also used to derive reflectance values of the three classes. The reflectance of the orange tree class (0.31) and ground class (0.60) are consistent with published values at the wavelength of the Riegl scanner (1550 nm). The grass class reflectance (0.46) falls in between the other two classes as might be expected, as this class has a mixture of the contributions of both vegetation and ground reflectance properties.

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A new record of sea surface temperature (SST) for climate applications is described. This record provides independent corroboration of global variations estimated from SST measurements made in situ. Infrared imagery from Along-Track Scanning Radiometers (ATSRs) is used to create a 20 year time series of SST at 0.1° latitude-longitude resolution, in the ATSR Reprocessing for Climate (ARC) project. A very high degree of independence of in situ measurements is achieved via physics-based techniques. Skin SST and SST estimated for 20 cm depth are provided, with grid cell uncertainty estimates. Comparison with in situ data sets establishes that ARC SSTs generally have bias of order 0.1 K or smaller. The precision of the ARC SSTs is 0.14 K during 2003 to 2009, from three-way error analysis. Over the period 1994 to 2010, ARC SSTs are stable, with better than 95% confidence, to within 0.005 K yr−1(demonstrated for tropical regions). The data set appears useful for cleanly quantifying interannual variability in SST and major SST anomalies. The ARC SST global anomaly time series is compared to the in situ-based Hadley Centre SST data set version 3 (HadSST3). Within known uncertainties in bias adjustments applied to in situ measurements, the independent ARC record and HadSST3 present the same variations in global marine temperature since 1996. Since the in situ observing system evolved significantly in its mix of measurement platforms and techniques over this period, ARC SSTs provide an important corroboration that HadSST3 accurately represents recent variability and change in this essential climate variable.

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We present a new coefficient-based retrieval scheme for estimation of sea surface temperature (SST) from the Along Track Scanning Radiometer (ATSR) instruments. The new coefficients are banded by total column water vapour (TCWV), obtained from numerical weather prediction analyses. TCWV banding reduces simulated regional retrieval biases to < 0.1 K compared to biases ~ 0.2 K for global coefficients. Further, detailed treatment of the instrumental viewing geometry reduces simulated view-angle related biases from ~ 0.1 K down to < 0.005 K for dual-view retrievals using channels at 11 and 12 μm. A novel analysis of trade-offs related to the assumed noise level when defining coefficients is undertaken, and we conclude that adding a small nominal level of noise (0.01 K) is optimal for our purposes. When applied to ATSR observations, some inter-algorithm biases appear as TCWV-related differences in SSTs estimated from different channel combinations. The final step in coefficient determination is to adjust the offset coefficient in each TCWV band to match results from a reference algorithm. This reference uses the dual-view observations of 3.7 and 11 μm. The adjustment is independent of in situ measurements, preserving independence of the retrievals. The choice of reference is partly motivated by uncertainty in the calibration of the 12 μm of Advanced ATSR. Lastly, we model the sensitivities of the new retrievals to changes to TCWV and changes in true SST, confirming that dual-view SSTs are most appropriate for climatological applications

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We present new radiative transfer simulations to support determination of sea surface temperature (SST) from Along Track Scanning Radiometer (ATSR) imagery. The simulations are to be used within the ATSR Reprocessing for Climate project. The simulations are based on the “Reference Forward Model” line-by-line model linked with a sea surface emissivity model that accounts for wind speed and temperature, and with a discrete ordinates scattering model (DISORT). Input to the forward model is a revised atmospheric profile dataset, based on full resolution ERA-40, with a wider range of high-latitude profiles to address known retrieval biases in those regions. Analysis of the radiative impacts of atmospheric trace gases shows that geographical and temporal variation of N2O, CH4, HNO3, and CFC-11 and CFC-12 have effects of order 0.05, 0.2, 0.1 K on the 3.7, 11, 12 μm channels respectively. In addition several trace gases, neglected in previous studies, are included using fixed profiles contributing ~ 0.04 K to top-of-atmosphere BTs. Comparison against observations for ATSR2 and AATSR indicates that forward model biases have been reduced from 0.2 to 0.5 K for previous simulations to ~ 0.1 K.

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A new aerosol index for the Along-Track Scanning Radiometers (ATSRs) is presented that provides a means to detect desert dust contamination in infrared SST retrievals. The ATSR Saharan dust index (ASDI) utilises only the thermal infrared channels and may therefore be applied consistently to the entire ATSR data record (1991 to present), for both day time and night time observations. The derivation of the ASDI is based on a principal component (PC) analysis (PCA) of two unique pairs of channel brightness temperature differences (BTDs). In 2-D space (i.e. BTD vs BTD), it is found that the loci of data unaffected by aerosol are confined to a single axis of variability. In contrast, the loci of aerosol-contaminated data fall off-axis, shifting in a direction that is approximately orthogonal to the clear-sky axis. The ASDI is therefore defined to be the second PC, where the first PC accounts for the clear-sky variability. The primary ASDI utilises the ATSR nadir and forward-view observations at 11 and 12 μm (ASDI2). A secondary, three-channel nadir-only ASDI (ASDI3) is also defined for situations where data from the forward view are not available. Empirical and theoretical analyses suggest that ASDI is well correlated with aerosol optical depth (AOD: correlation r is typically > 0.7) and provides an effective tool for detecting desert mineral dust. Overall, ASDI2 is found to be more effective than ASDI3, with the latter being sensitive only to very high dust loading. In addition, use of ASDI3 is confined to night time observations as it relies on data from the 3.7 μm channel, which is sensitive to reflected solar radiation. This highlights the benefits of having data from both a nadir- and a forward-view for this particular approach to aerosol detection.

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The ability of six scanning cloud radar scan strategies to reconstruct cumulus cloud fields for radiation study is assessed. Utilizing snapshots of clean and polluted cloud fields from large eddy simulations, an analysis is undertaken of error in both the liquid water path and monochromatic downwelling surface irradiance at 870 nm of the reconstructed cloud fields. Error introduced by radar sensitivity, choice of radar scan strategy, retrieval of liquid water content (LWC), and reconstruction scheme is explored. Given an in␣nitely sensitive radar and perfect LWC retrieval, domain average surface irradiance biases are typically less than 3 W m␣2 ␣m␣1, corresponding to 5–10% of the cloud radiative effect (CRE). However, when using a realistic radar sensitivity of ␣37.5 dBZ at 1 km, optically thin areas and edges of clouds are dif␣cult to detect due to their low radar re-ectivity; in clean conditions, overestimates are of order 10 W m␣2 ␣m␣1 (~20% of the CRE), but in polluted conditions, where the droplets are smaller, this increases to 10–26 W m␣2 ␣m␣1 (~40–100% of the CRE). Drizzle drops are also problematic; if treated as cloud droplets, reconstructions are poor, leading to large underestimates of 20–46 W m␣2 ␣m␣1 in domain average surface irradiance (~40–80% of the CRE). Nevertheless, a synergistic retrieval approach combining the detailed cloud structure obtained from scanning radar with the droplet-size information and location of cloud base gained from other instruments would potentially make accurate solar radiative transfer calculations in broken cloud possible for the first time.

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We describe the approach to be adopted for a major new initiative to derive a homogeneous record of sea surface temperature for 1991–2007 from the observations of the series of three along-track scanning radiometers (ATSRs). This initiative is called (A)RC: (Advanced) ATSR Re-analysis for Climate. The main objectives are to reduce regional biases in retrieved sea surface temperature (SST) to less than 0.1 K for all global oceans, while creating a very homogenous record that is stable in time to within 0.05 K decade−1, with maximum independence of the record from existing analyses of SST used in climate change research. If these stringent targets are achieved, this record will enable significantly improved estimates of surface temperature trends and variability of sufficient quality to advance questions of climate change attribution, climate sensitivity and historical reconstruction of surface temperature changes. The approach includes development of new, consistent estimators for SST for each of the ATSRs, and detailed analysis of overlap periods. Novel aspects of the approach include generation of multiple versions of the record using alternative channel sets and cloud detection techniques, to assess for the first time the effect of such choices. There will be extensive effort in quality control, validation and analysis of the impact on climate SST data sets. Evidence for the plausibility of the 0.1 K target for systematic error is reviewed, as is the need for alternative cloud screening methods in this context.