72 resultados para Physicochemical parameters


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Herd Companion uses routine milk‐recording records to generate twelve‐month rolling averages that indicate performance trends. This article looks at Herd Somatic Cell Count (SCC) and four other SCC‐related parameters from 252 National Milk Records (NMR) recorded herds to assess how each parameter correlates with the Herd SCC. The analysis provides evidence for the importance of targeting individual cows with high SCC recordings (>200,000 cells/ml and >500,000 cells/ml) and/or individual cows with repeatedly high SCC recordings (chronic high SCC) and/or cows that begin lactation with a high SCC recording (dry period infection) in order to achieve bulk milk Herd SCC below 200,000 cells/ml.

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The paper presents an analysis of WAXS (wide-angle X-ray scattering) data which aids an understanding of the structure of non-crystalline polymers. Experimental results are compared with calculations of scattering from possible models. Evidence is presented which supports the view that the chains in molten PE do not lie parallel but have a conformation in accord with the predictions of energy calculations. However, the evidence indicates that in “molten” PTFE the chains lie parallel over distances well in excess of their diameters. WAXS-based proposals are made for the conformations of a-PMMA and a-PS.

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The organization of non-crystalline polymeric materials at a local level, namely on a spatial scale between a few and 100 a, is still unclear in many respects. The determination of the local structure in terms of the configuration and conformation of the polymer chain and of the packing characteristics of the chain in the bulk material represents a challenging problem. Data from wide-angle diffraction experiments are very difficult to interpret due to the very large amount of information that they carry, that is the large number of correlations present in the diffraction patterns.We describe new approaches that permit a detailed analysis of the complex neutron diffraction patterns characterizing polymer melts and glasses. The coupling of different computer modelling strategies with neutron scattering data over a wide Q range allows the extraction of detailed quantitative information on the structural arrangements of the materials of interest. Proceeding from modelling routes as diverse as force field calculations, single-chain modelling and reverse Monte Carlo, we show the successes and pitfalls of each approach in describing model systems, which illustrate the need to attack the data analysis problem simultaneously from several fronts.

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A direct method is presented for determining the uncertainty in reservoir pressure, flow, and net present value (NPV) using the time-dependent, one phase, two- or three-dimensional equations of flow through a porous medium. The uncertainty in the solution is modelled as a probability distribution function and is computed from given statistical data for input parameters such as permeability. The method generates an expansion for the mean of the pressure about a deterministic solution to the system equations using a perturbation to the mean of the input parameters. Hierarchical equations that define approximations to the mean solution at each point and to the field covariance of the pressure are developed and solved numerically. The procedure is then used to find the statistics of the flow and the risked value of the field, defined by the NPV, for a given development scenario. This method involves only one (albeit complicated) solution of the equations and contrasts with the more usual Monte-Carlo approach where many such solutions are required. The procedure is applied easily to other physical systems modelled by linear or nonlinear partial differential equations with uncertain data.

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Physiological and yield traits such as stomatal conductance (mmol m-2s-1), Leaf relative water content (RWC %) and grain yield per plant were studied in a separate experiment. Results revealed that five out of sixteen cultivars viz. Anmol, Moomal, Sarsabz, Bhitai and Pavan, appeared to be relatively more drought tolerant. Based on morphophysiological results, studies were continued to look at these cultivars for drought tolerance at molecular level. Initially, four well recognized primers for dehydrin genes (DHNs) responsible for drought induction in T. durum L., T. aestivum L. and O. sativa L. were used for profiling gene sequence of sixteen wheat cultivars. The primers amplified the DHN genes variably like Primer WDHN13 (T. aestivum L.) amplified the DHN gene in only seven cultivars whereas primer TdDHN15 (T. durum L.) amplified all the sixteen cultivars with even different DNA banding patterns some showing second weaker DNA bands. Third primer TdDHN16 (T. durum L.) has shown entirely different PCR amplification prototype, specially showing two strong DNA bands while fourth primer RAB16C (O. sativa L.) failed to amplify DHN gene in any of the cultivars. Examination of DNA sequences revealed several interesting features. First, it identified the two exon/one intron structure of this gene (complete sequences were not shown), a feature not previously described in the two database cDNA sequences available from T. aestivum L. (gi|21850). Secondly, the analysis identified several single nucleotide polymorphisms (SNPs), positions in gene sequence. Although complete gene sequence was not obtained for all the cultivars, yet there were a total of 38 variable positions in exonic (coding region) sequence, from a total gene length of 453 nucleotides. Matrix of SNP shows these 37 positions with individual sequence at positions given for each of the 14 cultivars (sequence of two cultivars was not obtained) included in this analysis. It demonstrated a considerable diversity for this gene with only three cultivars i.e. TJ-83, Marvi and TD-1 being similar to the consensus sequence. All other cultivars showed a unique combination of SNPs. In order to prove a functional link between these polymorphisms and drought tolerance in wheat, it would be necessary to conduct a more detailed study involving directed mutation of this gene and DHN gene expression.

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Buffalo milk contains (40–60 %) more protein, fat and calcium than cows’ milk. These constituents were enhanced by ultrafiltration (UF) of cows’ milk to give a product with similar levels to those found in the buffalo milk. Mozzarella-type curd was made from buffalo, cows’ and UF cows’ milk to compare the overall curd yield and quality. The curd yield on both dry and wet weight basis, curd moisture content and overall curd fat retention were found to be higher in the UF cows’ milk than for either the buffalo or the cows’ milk preparations. The minimum whey fat losses occurred in the UF cows’ curd when compared to the cows’ and the buffalo curd. The whey protein losses were found to be higher in the UF cows’ curd than those for the buffalo and the cows’ curds. The total mineral content of the curd was also higher in the UF cows’ milk than that found in either the buffalo or the cows’ milk. SEM micrographs showed that casein micelles sizes were different in the two different types of milk. Casein micelles were also observed to be deformed in the UF cows’ milk samples. UF cows’ milk contained higher amounts of both the αs1- and αs2-casein moieties than either the buffalo or the cows’ milk. Buffalo milk was found to contain a higher concentration of β-casein than either the UF cows’ or untreated cows’ milk samples. Gel strength was found to be higher in the resultant buffalo curd than for curds made from either native cows’ milk or those made from UF cows’ milk. The mineral distribution was also different in the three different types of bovine milk, measured by energy-dispersive X-ray (EDX) analysis. Differences in the curd quality observed between the buffalo and the cows’ milk appear to result from the differences in casein composition and overall micelle structure, rather than casein concentration alone.

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Linear models of bidirectional reflectance distribution are useful tools for understanding the angular variability of surface reflectance as observed by medium-resolution sensors such as the Moderate Resolution Imaging Spectrometer. These models are operationally used to normalize data to common view and illumination geometries and to calculate integral quantities such as albedo. Currently, to compensate for noise in observed reflectance, these models are inverted against data collected during some temporal window for which the model parameters are assumed to be constant. Despite this, the retrieved parameters are often noisy for regions where sufficient observations are not available. This paper demonstrates the use of Lagrangian multipliers to allow arbitrarily large windows and, at the same time, produce individual parameter sets for each day even for regions where only sparse observations are available.

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The rheological, emulsification and certain physicochemical properties of purified exopolysaccharides (EPS) of Bifidobacterium longum subsp. infantis CCUG 52486 and Bifidobacterium infantis NCIMB 702205 were studied and compared with those of guar gum and xanthan gum. The two strains were grown in skim milk supplemented with 1.5% (w/v) casein hydrolysate at 37 ◦C for 24 h; they both produced heteropolysaccharides with different molecular mass and composition. The carbohydrate content of both polymers was more than 92% and no protein was detected. The EPS of B. longum subsp. infantis CCUG 52486 showed highly branched entangled porous structure under scanning electron microscopy. Higher intrinsic viscosity was observed for the EPS of B. longum subsp. infantis CCUG 52486 compared to the EPS of B. infantis NCIMB 702205 and guar gum. Both polymers showed pseudoplastic non-Newtonian fluid behaviour in an aqueous solution. The EPS of B. infantis NCIMB 702205 and B. longum subsp. infantis CCUG 52486 produced more stable emulsions with orange oil, sunflower seed oil, coconut oil and xylene compared to guar and xanthan gum. The EPS of B. longum subsp. infantis CCUG 52486 is the most promising one for applications in the food industry, as it had higher intrinsic viscosity, higher apparent viscosity in aqueous solution, porous dense entangled structure and good emulsification activity.

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The aim of this study was to investigate the effect of atmospheric frying followed by drainage under vacuum on the stability of oil, compared to similar frying with drainage at atmospheric pressure. Changes in the oil were assessed by the free fatty acid (FFA) content, p-anisidine value (AnV), colour, viscosity, fatty acid profile and concentration of tocols. The rate of FFA formation in the case of vacuum drainage was found to be about half that of atmospheric drainage. Oil deterioration by oxidation and polymerisation was also reduced by the use of vacuum drainage. The AnV of the oil after vacuum drainage was lower by about 12%, the total colour difference was improved by 14% and viscosity was slightly reduced after 5 days of frying, compared to the values for oil that had been drained at atmospheric pressure. There was a reduction in the loss of polyunsaturated fatty acids in the case of vacuum drainage after 5 days of frying but differences in retention of tocols were only evident in the first two days of frying.

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Although the tube theory is successful in describing entangled polymers qualitatively, a more quantitative description requires precise and consistent definitions of its parameters. Here we investigate the simplest model of entangled polymers, namely a single Rouse chain in a cubic lattice of line obstacles, and illustrate the typical problems and uncertainties of the tube theory. In particular we show that in general one needs 3 entanglement related parameters, but only 2 combinations of them are relevant for the long-time dynamics. Conversely, the plateau modulus can not be determined from these two parameters and requires a more detailed model of entanglements with explicit entanglement forces, such as the slipsprings model. It is shown that for the grid model the Rouse time within the tube is larger than the Rouse time of the free chain, in contrast to what the standard tube theory assumes.

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There is a current need to constrain the parameters of gravity wave drag (GWD) schemes in climate models using observational information instead of tuning them subjectively. In this work, an inverse technique is developed using data assimilation principles to estimate gravity wave parameters. Because mostGWDschemes assume instantaneous vertical propagation of gravity waves within a column, observations in a single column can be used to formulate a one-dimensional assimilation problem to estimate the unknown parameters. We define a cost function that measures the differences between the unresolved drag inferred from observations (referred to here as the ‘observed’ GWD) and the GWD calculated with a parametrisation scheme. The geometry of the cost function presents some difficulties, including multiple minima and ill-conditioning because of the non-independence of the gravity wave parameters. To overcome these difficulties we propose a genetic algorithm to minimize the cost function, which provides a robust parameter estimation over a broad range of prescribed ‘true’ parameters. When real experiments using an independent estimate of the ‘observed’ GWD are performed, physically unrealistic values of the parameters can result due to the non-independence of the parameters. However, by constraining one of the parameters to lie within a physically realistic range, this degeneracy is broken and the other parameters are also found to lie within physically realistic ranges. This argues for the essential physical self-consistency of the gravity wave scheme. A much better fit to the observed GWD at high latitudes is obtained when the parameters are allowed to vary with latitude. However, a close fit can be obtained either in the upper or the lower part of the profiles, but not in both at the same time. This result is a consequence of assuming an isotropic launch spectrum. The changes of sign in theGWDfound in the tropical lower stratosphere, which are associated with part of the quasi-biennial oscillation forcing, cannot be captured by the parametrisation with optimal parameters.

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The sensitivity of the biological parameters in a nutrient-phytoplankton-zooplankton-detritus (NPZD) model in the calculation of the air-sea CO2 flux, primary production and detrital export is analysed. We explore the effect on these outputs of variation in the values of the twenty parameters that control ocean ecosystem growth in a 1-D formulation of the UK Met Office HadOCC NPZD model used in GCMs. We use and compare the results from one-at-a-time and all-at-a-time perturbations performed at three sites in the EuroSITES European Ocean Observatory Network: the Central Irminger Sea (60° N 40° W), the Porcupine Abyssal Plain (49° N 16° W) and the European Station for Time series in the Ocean Canary Islands (29° N 15° W). Reasonable changes to the values of key parameters are shown to have a large effect on the calculation of the air-sea CO2 flux, primary production, and export of biological detritus to the deep ocean. Changes in the values of key parameters have a greater effect in more productive regions than in less productive areas. The most sensitive parameters are generally found to be those controlling well-established ocean ecosystem parameterisations widely used in many NPZD-type models. The air-sea CO2 flux is most influenced by variation in the parameters that control phytoplankton growth, detrital sinking and carbonate production by phytoplankton (the rain ratio). Primary production is most sensitive to the parameters that define the shape of the photosynthesis-irradiance curve. Export production is most sensitive to the parameters that control the rate of detrital sinking and the remineralisation of detritus.

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Visual motion cues play an important role in animal and humans locomotion without the need to extract actual ego-motion information. This paper demonstrates a method for estimating the visual motion parameters, namely the Time-To-Contact (TTC), Focus of Expansion (FOE), and image angular velocities, from a sparse optical flow estimation registered from a downward looking camera. The presented method is capable of estimating the visual motion parameters in a complicated 6 degrees of freedom motion and in real time with suitable accuracy for mobile robots visual navigation.