920 resultados para Temporal variability


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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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The size at recruitment, temporal and spatial distribution, and abiotic factors influencing abundance of three commercially important species of penaeid prawns in the sublittoral trawl grounds of Moreton Bay (Queensland, Australia) were compared. Metapenaeus bennettae and Penaeus plebejus recruit to the trawl grounds at sizes which are relatively small (14-15 mm carapace length, CL) and below that at which prawns are selected for, and retained, in the fleet's cod-ends. In contrast, Penaeus esculenlus recruit at the relatively large size of 27 mm CL from February to May, well above the size ranges selected for. Recruitment of M. bennettae extends over several months, September-October and February March, and was thus likely to be bi-annual, while the recruitment period of P. plebejus was distinct, peaking in October-November each year. Size classes of M . bennettae were the most spatially stratified of the three species. Catch rates of recruits were negatively correlated with depth for all three species, and were also negatively correlated with salinity for M. bennettae.

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The biomass and species composition of tropical phytoplankton in Albatross Bay, Gulf of Carpentaria, northern Australia, were examined monthly for 6 yr (1986 to 1992). Chlorophyll a (chl a) concentrations were highest (2 to 5.7 mu g l(-1)) in the wet season at inshore sites, usually coinciding with low salinities (30 to 33 ppt) and high temperatures (29 to 32 degrees C). At the offshore sites chi a concentrations were lower (0.2 to 2 mu g l(-1)) and did not vary seasonally. Nitrate and phosphate concentrations were generally low (0 to 3.68 mu M and 0.09 to 3 mu M for nitrate and phosphate respectively), whereas silicate was present in concentrations in the range 0.19 to 13 mu M. The phytoplankton community was dominated by diatoms, particularly at the inshore sites, as determined by a combination of microscopic and high-performance liquid chromatography (HPLC) pigment analyses. At the offshore sites the proportion of green flagellates increased. The cyanobacterium genus Trichodesmium and the diatom genera Chaetoceros, Rhizosolenia, Bacteriastrum and Thalassionema dominated the phytoplankton caught in 37 mu m mesh nets; however, in contrast to many other coastal areas studied worldwide there was no distinct species succession of the diatoms and only Trichodesmium showed seasonal changes in abundance. This reflects a stable phytoplankton community in waters without pulses of physical and chemical disturbances. These results are discussed in the context of the commercial prawn fishery in the Gulf of Carpentaria and the possible effect of phytoplankton on prawn larval growth and survival.

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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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In this paper we tackle the problem of efficient video event detection. We argue that linear detection functions should be preferred in this regard due to their scalability and efficiency during estimation and evaluation. A popular approach in this regard is to represent a sequence using a bag of words (BOW) representation due to its: (i) fixed dimensionality irrespective of the sequence length, and (ii) its ability to compactly model the statistics in the sequence. A drawback to the BOW representation, however, is the intrinsic destruction of the temporal ordering information. In this paper we propose a new representation that leverages the uncertainty in relative temporal alignments between pairs of sequences while not destroying temporal ordering. Our representation, like BOW, is of a fixed dimensionality making it easily integrated with a linear detection function. Extensive experiments on CK+, 6DMG, and UvA-NEMO databases show significant performance improvements across both isolated and continuous event detection tasks.

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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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The G-protein-coupled receptor 54 (muGPR54) cDNA was cloned from the brain of the grey mullet, and its expression level, as well as those of the gonadotropin-releasing hormones (GnRH1, GnRH2, GnRH3) and dopamine receptor D2 (drd2), in the brain, pituitary and ovary of pubertal fish (early, intermediate, advanced) were determined by real-time quantitative RT-PCR (QPCR). The muGPR54 cDNA has an open reading frame of 1140 bp with a predicted 380 amino acid peptide, containing seven putative transmembrane domains and putative N-glycosylation and protein kinase C phosphorylation sites. QPCR results showed that the early stage of puberty in grey mullet is characterized by significantly high levels of expression of GPR54, GnRH and drd2 in the brain relative to the intermediate and advanced stages, except for GnRH1 that increased at the advanced stage of puberty. In the pituitary, drd2 expression declined significantly at the advanced stage relative to levels at the intermediate stage. Ovarian expression of GPR54 significantly increased from the intermediate stage of puberty relative to the early stage while that of GnRH1 acutely increased at the advanced stage of puberty. The ovarian expression of drd2 decreased as puberty progressed, but the changes were not significant. The results suggest the possible role of GPR54 and GnRH in positively regulating pubertal development in grey mullet and the dopaminergic inhibition of reproductive function mediated by drd2.

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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.

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Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

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Space-fractional operators have been used with success in a variety of practical applications to describe transport processes in media characterised by spatial connectivity properties and high structural heterogeneity altering the classical laws of diffusion. This study provides a systematic investigation of the spatio-temporal effects of a space-fractional model in cardiac electrophysiology. We consider a simplified model of electrical pulse propagation through cardiac tissue, namely the monodomain formulation of the Beeler-Reuter cell model on insulated tissue fibres, and obtain a space-fractional modification of the model by using the spectral definition of the one-dimensional continuous fractional Laplacian. The spectral decomposition of the fractional operator allows us to develop an efficient numerical method for the space-fractional problem. Particular attention is paid to the role played by the fractional operator in determining the solution behaviour and to the identification of crucial differences between the non-fractional and the fractional cases. We find a positive linear dependence of the depolarization peak height and a power law decay of notch and dome peak amplitudes for decreasing orders of the fractional operator. Furthermore, we establish a quadratic relationship in conduction velocity, and quantify the increasingly wider action potential foot and more pronounced dispersion of action potential duration, as the fractional order is decreased. A discussion of the physiological interpretation of the presented findings is made.