944 resultados para intraindividual variability


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In this study, the nature of basin-scale hydroclimatic association for Indian subcontinent is investigated. It is found that, the large-scale circulation information from Indian Ocean is also equally important in addition to the El Nino-Southern Oscillation (ENSO), owing to the geographical location of Indian subcontinent. The hydroclimatic association of the variation of monsoon inflow into the Hirakud reservoir in India is investigated using ENSO and EQUatorial INdian Ocean Oscillation (EQUINOO, the atmospheric part of Indian Ocean Dipole mode) as the large-scale circulation information from tropical Pacific Ocean and Indian Ocean regions respectively. Individual associations of ENSO & EQUINOO indices with inflow into Hirakud reservoir are also assessed and found to be weak. However, the association of inflows into Hirakud reservoir with the composite index (CI) of ENSO and EQUINOO is quite strong. Thus, the large-scale circulation information from Indian Ocean is also important apart form the ENSO. The potential of the combined information of ENSO and EQUINOO for predicting the inflows during monsoon is also investigated with promising results. The results of this study will be helpful to water resources managers due to fact that the nature of monsoon inflow is becoming available as an early prediction.

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In this paper an attempt has been made to evaluate the spatial variability of the depth of weathered and engineering bedrock in Bangalore, south India using Multichannel Analysis of Surface Wave (MASW) survey. One-dimensional MASW survey has been carried out at 58 locations and shear-wave velocities are measured. Using velocity profiles, the depth of weathered rock and engineering rock surface levels has been determined. Based on the literature, shear-wave velocity of 330 ± 30 m/s for weathered rock or soft rock and 760 ± 60 m/s for engineering rock or hard rock has been considered. Depths corresponding to these velocity ranges are evaluated with respect to ground contour levels and top surface levels have been mapped with an interpolation technique using natural neighborhood. The depth of weathered rock varies from 1 m to about 21 m. In 58 testing locations, only 42 locations reached the depths which have a shear-wave velocity of more than 760 ± 60 m/s. The depth of engineering rock is evaluated from these data and it varies from 1 m to about 50 m. Further, these rock depths have been compared with a subsurface profile obtained from a two-dimensional (2-D) MASW survey at 20 locations and a few selected available bore logs from the deep geotechnical boreholes.

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Estimation of von Bertalanffy growth parameters has received considerable attention in fisheries research. Since Sainsbury (1980, Can. J. Fish. Aquat. Sci. 37: 241-247) much of this research effort has centered on accounting for individual variability in the growth parameters. In this paper we demonstrate that, in analysis of tagging data, Sainsbury's method and its derivatives do not, in general, satisfactorily account for individual variability in growth, leading to inconsistent parameter estimates (the bias does not tend to zero as sample size increases to infinity). The bias arises because these methods do not use appropriate conditional expectations as a basis for estimation. This bias is found to be similar to that of the Fabens method. Such methods would be appropriate only under the assumption that the individual growth parameters that generate the growth increment were independent of the growth parameters that generated the initial length. However, such an assumption would be unrealistic. The results are derived analytically, and illustrated with a simulation study. Until techniques that take full account of the appropriate conditioning have been developed, the effect of individual variability on growth has yet to be fully understood.

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We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock and derive the underlying length distribution of the population and the catch when there is individual variability in the von Bertalanffy growth parameter L-infinity. The model is flexible enough to accommodate 1) any recruitment pattern as a function of both time and length, 2) length-specific selectivity, and 3) varying fishing effort over time. The maximum likelihood method gives consistent estimates, provided the underlying distribution for individual variation in growth is correctly specified. Simulation results indicate that our method is reasonably robust to violations in the assumptions. The method is applied to tiger prawn data (Penaeus semisulcatus) to obtain estimates of natural and fishing mortality.

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Recently, reports have appeared which show structural variations in B-DNA and indicate deviations from a uniform helical structure. We report for the first time that these indications are also present in the B-form fibre diffraction patterns for the lithium salt of natural DNA. We have used an improved method of controlling the salt concentration in the fibres. Our results are based on the appearance and disappearance of meridional reflections on different layer lines depending upon the salt.

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We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock when there is individual variability in the von Bertalanffy growth parameter L-infinity and investigate the possible bias in the estimates when the individual variability is ignored. Three methods are examined: (i) the regression method based on the Beverton and Holt's (1956, Rapp. P.V. Reun. Cons. Int. Explor. Mer, 140: 67-83) equation; (ii) the moment method of Powell (1979, Rapp. PV. Reun. Int. Explor. Mer, 175: 167-169); and (iii) a generalization of Powell's method that estimates the individual variability to be incorporated into the estimation. It is found that the biases in the estimates from the existing methods are, in general, substantial, even when individual variability in growth is small and recruitment is uniform, and the generalized method performs better in terms of bias but is subject to a larger variation. There is a need to develop robust and flexible methods to deal with individual variability in the analysis of length-frequency data.

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We report the design and characterization of a circuit technique to measure the on-chip delay of an individual logic gate (both inverting and noninverting) in its unmodified form. The test circuit comprises of digitally reconfigurable ring oscillator (RO). The gate under test is embedded in each stage of the ring oscillator. A system of linear equations is then formed with different configuration settings of the RO, relating the individual gate delay to the measured period of the RO, whose solution gives the delay of the individual gates. Experimental results from a test chip in 65-nm process node show the feasibility of measuring the delay of an individual inverter to within 1 ps accuracy. Delay measurements of different nominally identicall inverters in close physical proximity show variations of up to 28% indicating the large impact of local variations. As a demonstration of this technique, we have studied delay variation with poly-pitch, length of diffusion (LOD) and different orientations of layout in silicon. The proposed technique is quite suitable for early process characterization, monitoring mature process in manufacturing and correlating model-to-hardware.

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Supplements are often fed to ruminants in extensive grazing situations to provide minerals and nitrogen likely to be deficient in pasture. However a large proportion of animals offered such supplements may not consume any supplement, while among consumer animals the variability in supplement intake may be high (Wheeler et al., 1980; Dixon et al., 1998). An experiment examined the distribution of intake of a molasses-based supplement containing phosphorus and urea in a breeder herd. A herd of mixed-age breeder cows, calves, heifers and bulls were offered ad libitum a molasses-based supplement containing 13% urea and 17% phosphoric acid. After 2 weeks lithium-labelled supplement (2 mg Li/kg LW) was offered on one day to measure individual intakes of supplement. The molasses was offered in three 560 mm diameter feeders placed together near the water point.

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Loose mineral mix (LMM) supplements are often fed to ruminants in extensive grazing situations to provide minerals and nitrogen likely to be deficient in pasture. However a large proportion of animals offered such supplements may not consume any supplement, while among consumer animals the variability in supplement intake may be high (Wheeler et al., 1980; Dixon et al., 1996). Two experiments examined the distribution of intake of LMM supplements offered to heifers grazing in mob and paddock sizes representative of commercial cattle properties.

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The complete nucleocapsid (N) genes of eight Australian isolates of Lettuce necrotic yellows virus (LNYV) were amplified by reverse transcription PCR, cloned and sequenced. Phylogenetic analyses of these sequences revealed two distinct subgroups of LNYV isolates. Nucleotide sequences within each subgroup were more than 96% identical but heterogeneity between groups was about 20% at the nucleotide sequence level. However, less than 4% heterogeneity was noted at the amino acid level, indicating mostly third nucleotide position changes and a strong conservation for N protein function. There was no obvious geographical or temporal separation of the subgroups in Australia.

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The potential for large-scale use of a sensitive real time reverse transcription polymerase chain reaction (RT-PCR) assay was evaluated for the detection of Tomato spotted wilt virus (TSWV) in single and bulked leaf samples by comparing its sensitivity with that of DAS-ELISA. Using total RNA extracted with RNeasy® or leaf soak methods, real time RT-PCR detected TSWV in all infected samples collected from 16 horticultural crop species (including flowers, herbs and vegetables), two arable crop species, and four weed species by both assays. In samples in which DAS-ELISA had previously detected TSWV, real time RT-PCR was effective at detecting it in leaf tissues of all 22 plant species tested at a wide range of concentrations. Bulk samples required more robust and extensive extraction methods with real time RT-PCR, but it generally detected one infected sample in 1000 uninfected ones. By contrast, ELISA was less sensitive when used to test bulked samples, once detecting up to 1 infected in 800 samples with pepper but never detecting more than 1 infected in 200 samples in tomato and lettuce. It was also less reliable than real time RT-PCR when used to test samples from parts of the leaf where the virus concentration was low. The genetic variability among Australian isolates of TSWV was small. Direct sequencing of a 587 bp region of the nucleoprotein gene (S RNA) of 29 isolates from diverse crops and geographical locations yielded a maximum of only 4.3% nucleotide sequence difference. Phylogenetic analysis revealed no obvious groupings of isolates according to geographic origin or host species. TSWV isolates, that break TSWV resistance genes in tomato or pepper did not differ significantly in the N gene region studied, indicating that a different region of the virus genome is responsible for this trait.

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A panel of 19 monoclonal antibodies (mAbs) was used to study the immunological variability of Lettuce mosaic virus (LMV), a member of the genus Potyvirus, and to perform a first epitope characterization of this virus. Based on their specificity of recognition against a panel of 15 LMV isolates, the mAbs could be clustered in seven reactivity groups. Surface plasmon resonance analysis indicated the presence, on the LMV particles, of at least five independent recognition/binding regions, correlating with the seven mAbs reactivity groups. The results demonstrate that LMV shows significant serological variability and shed light on the LMV epitope structure. The various mAbs should prove a new and efficient tool for LMV diagnostic and field epidemiology studies.

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Australian researchers have been developing robust yield estimation models, based mainly on the crop growth response to water availability during the crop season. However, knowledge of spatial distribution of yields within and across the production regions can be improved by the use of remote sensing techniques. Images of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, available since 1999, have the potential to contribute to crop yield estimation. The objective of this study was to analyse the relationship between winter crop yields and the spectral information available in MODIS vegetation index images at the shire level. The study was carried out in the Jondaryan and Pittsworth shires, Queensland , Australia . Five years (2000 to 2004) of 250m resolution, 16-day composite of MODIS Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images were used during the winter crop season (April to November). Seasonal variability of the profiles of the vegetation index images for each crop season using different regions of interest (cropping mask) were displayed and analysed. Correlation analysis between wheat and barley yield data and MODIS image values were also conducted. The results showed high seasonal variability in the NDVI and EVI profiles, and the EVI values were consistently lower than those of the NDVI. The highest image values were observed in 2003 (in contrast to 2004), and were associated with rainfall amount and distribution. The seasonal variability of the profiles was similar in both shires, with minimum values in June and maximum values at the end of August. NDVI and EVI images showed sensitivity to seasonal variability of the vegetation and exhibited good association (e.g. r = 0.84, r = 0.77) with winter crop yields.

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Mixtures of single odours were used to explore the receptor response profile across individual antennae of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae). Seven odours were tested including floral and green-leaf volatiles: phenyl acetaldehyde, benzaldehyde, b-caryophyllene, limonene, a-pinene, 1-hexanol, 3Z-hexenyl acetate. Electroantennograms of responses to paired mixtures of odours showed that there was considerable variation in receptor tuning across the receptor field between individuals. Data from some moth antennae showed no additivity, which indicated a restricted receptor profile. Results from other moth antennae to the same odour mixtures showed a range of partial additivity. This indicated that a wider array of receptor types was present in these moths, with a greater percentage of the receptors tuned exclusively to each odour. Peripheral receptor fields show variation in the spectrum of response within a population (of moths) when exposed to high doses of plant volatiles. This may be related to recorded variation in host choice within moth populations as reported by other authors.

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Between-subject and within-subject variability is ubiquitous in biology and physiology and understanding and dealing with this is one of the biggest challenges in medicine. At the same time it is difficult to investigate this variability by experiments alone. A recent modelling and simulation approach, known as population of models (POM), allows this exploration to take place by building a mathematical model consisting of multiple parameter sets calibrated against experimental data. However, finding such sets within a high-dimensional parameter space of complex electrophysiological models is computationally challenging. By placing the POM approach within a statistical framework, we develop a novel and efficient algorithm based on sequential Monte Carlo (SMC). We compare the SMC approach with Latin hypercube sampling (LHS), a method commonly adopted in the literature for obtaining the POM, in terms of efficiency and output variability in the presence of a drug block through an in-depth investigation via the Beeler-Reuter cardiac electrophysiological model. We show improved efficiency via SMC and that it produces similar responses to LHS when making out-of-sample predictions in the presence of a simulated drug block.