940 resultados para indirect quantification


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Use of appropriate nursery environments will maximize gain from selection for yield of wheat (Triticum aestivum L.) in the target population of environments of a breeding program. The objective of this study was to investigate how well-irrigated (low-stress) nursery environments predict yield of lines in target environments that varied in degree of water limitation. Fifteen lines were sampled from the preliminary yield evaluation stage of the Queensland wheat breeding program and tested in 26 trials under on-farm conditions (Target Environments) across nine years (1985 to 1993) and also in 27 trials conducted at three research stations (Nursery Environments) in three years (1987 to 1989). The nursery environments were structured to impose different levels of water and nitrogen (N) limitation, whereas the target environments represented a random sample of on-farm conditions from the target population of environments. Indirect selection and pattern analysis methods were used to investigate selection for yield in the nursery environments and gain from selection in the target environments. Yield under low-stress nursery conditions was an effective predictor of yield under similar low-stress target environments (r = 0.89, P < 0.01). However, the value of the low-stress nursery as a predictor of yield in the water-limited target environments decreased with increasing water stress (moderate stress r = 0.53, P < 0.05, to r = 0.38, P > 0.05; severe stress r = -0.08, P > 0.05). Yield in the stress nurseries was a poor predictor of yield in the target environments. Until there is a clear understanding of the physiological-genetic basis of variation for adaptation of wheat to the water-limited environments in Queensland, yield improvement can best be achieved by selection for a combination of yield potential in an irrigated low-stress nursery and yield in on-farm trials that sample the range of water-limited environments of the target population of environments.

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In studies using macroinvertebrates as indicators for monitoring rivers and streams, species level identifications in comparison with lower resolution identifications can have greater information content and result in more reliable site classifications and better capacity to discriminate between sites, yet many such programmes identify specimens to the resolution of family rather than species. This is often because it is cheaper to obtain family level data than species level data. Choice of appropriate taxonomic resolution is a compromise between the cost of obtaining data at high taxonomic resolutions and the loss of information at lower resolutions. Optimum taxonomic resolution should be determined by the information required to address programme objectives. Costs saved in identifying macroinvertebrates to family level may not be justified if family level data can not give the answers required and expending the extra cost to obtain species level data may not be warranted if cheaper family level data retains sufficient information to meet objectives. We investigated the influence of taxonomic resolution and sample quantification (abundance vs. presence/absence) on the representation of aquatic macroinvertebrate species assemblage patterns and species richness estimates. The study was conducted in a physically harsh dryland river system (Condamine-Balonne River system, located in south-western Queensland, Australia), characterised by low macroinvertebrate diversity. Our 29 study sites covered a wide geographic range and a diversity of lotic conditions and this was reflected by differences between sites in macroinvertebrate assemblage composition and richness. The usefulness of expending the extra cost necessary to identify macroinvertebrates to species was quantified via the benefits this higher resolution data offered in its capacity to discriminate between sites and give accurate estimates of site species richness. We found that very little information (<6%) was lost by identifying taxa to family (or genus), as opposed to species, and that quantifying the abundance of taxa provided greater resolution for pattern interpretation than simply noting their presence/absence. Species richness was very well represented by genus, family and order richness, so that each of these could be used as surrogates of species richness if, for example, surveying to identify diversity hot-spots. It is suggested that sharing of common ecological responses among species within higher taxonomic units is the most plausible mechanism for the results. Based on a cost/benefit analysis, family level abundance data is recommended as the best resolution for resolving patterns in macroinvertebrate assemblages in this system. The relevance of these findings are discussed in the context of other low diversity, harsh, dryland river systems.

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This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.

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This paper reports on the use of a local order measure to quantify the spatial ordering of a quantum dot array (QDA). By means of electron ground state energy analysis in a quantum dot pair, it is demonstrated that the length scale required for such a measure to characterize the opto-electronic properties of a QDA is of the order of a few QD radii. Therefore, as local order is the primary factor that affects the opto-electronic properties of an array of quantum dots of homogeneous size, this order was quantified through using the standard deviation of the nearest neighbor distances of the quantum dot ensemble. The local order measure is successfully applied to quantify spatial order in a range of experimentally synthesized and numerically generated arrays of nanoparticles. This measure is not limited to QDAs and has wide ranging applications in characterizing order in dense arrays of nanostructures.

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Deficiencies in iodine levels have been shown to seriously affect a child’s intellectual development and learning capacity.1 In South-East Asia, iodine deficiency remains a major public health concern. Approximately 30% of the region’s population of 503.6 million have insufficient iodine intake, and only 61% of households have access to iodized salt.1 For this reason, it is necessary to initiate effective, community-based health promotion activities that are targeted toward populations of various ages. A puppet show is one imaginative and entertaining method of health education that has been advocated for use in communicating positive health behaviours to children.2e5 The authors undertook a literature review and found no studies assessing the effectiveness of a puppet show to teach an iodine education programme...

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Background: Plasma D-dimer tests are currently used to exclude deep vein thrombosis and pulmonary embolism. Human saliva has numerous advantages over blood as a diagnostic sample. The aims of our study were to develop a reliable immunoassay to detect D-dimer levels in saliva, and to determine the correlation between salivary and blood D-dimer levels. Results/methodology: Saliva and blood samples were collected from 40 healthy volunteers. We developed a AlphaLISA((R)) immunoassay with acceptable analytical performances to quantify D-dimer levels in the samples. The median salivary D-dimer levels were 138.1 ng/ml (morning) and 140.7 ng/ml (afternoon), and the plasma levels were 75.0 ng/ml. Salivary D-dimer levels did not correlate with plasma levels (p = 0.61). Conclusion: For the first time, we have quantified D-dimer levels and found twofold increase in saliva (p < 0.05) than in plasma. Further studies are required to demonstrate the clinical relevance/utility of salivary D-dimer in patients with confirmed deep vein thrombosis and/or pulmonary embolism.

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This paper demonstrates a renewed procedure for the quantification of surface-enhanced Raman scattering (SERS) enhancement factors with improved precision. The principle of this method relies on deducting the resonance Raman scattering (RRS) contribution from surface-enhanced resonance Raman scattering (SERRS) to end up with the surface enhancement (SERS) effect alone. We employed 1,8,15,22-tetraaminophthalocyanato-cobalt(II) (4α-CoIITAPc), a resonance Raman- and electrochemically redox-active chromophore, as a probe molecule for RRS and SERRS experiments. The number of 4α-CoIITAPc molecules contributing to RRS and SERRS phenomena on plasmon inactive glassy carbon (GC) and plasmon active GC/Au surfaces, respectively, has been precisely estimated by cyclic voltammetry experiments. Furthermore, the SERS substrate enhancement factor (SSEF) quantified by our approach is compared with the traditionally employed methods. We also demonstrate that the present approach of SSEF quantification can be applied for any kind of different SERS substrates by choosing an appropriate laser line and probe molecule.

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This communication presents a new pathway for the more precise quantification of surface-enhanced Raman scattering (SERS) enhancement factor via deducing resonance Raman scattering (RRS) effect from surface-enhanced resonance Raman scattering (SERRS). To achieve this, a self-assembled monolayer of 1,8,15,22-tetraaminophthalocyanatocobalt(II) (4α-CoIITAPc) is formed on plasmon inactive glassy carbon (GC) and plasmon active GC/AuNPs surface. The surfaces are subsequently used as common probes for electrochemical and Raman (RRS and SERRS) studies. The most crucial parameters required for the quantification of SERS substrate enhancement factor (SSEF) such as real surface area of GC/AuNPs substarte and the number of 4α-CoIITAPc molecules contributing to RRS (on GC) and SERRS (on GC/AuNPs) are precisely estimated by cyclic voltammetry experiments. The present approach of SSEF quantification can be applied to varieties of surfaces by choosing an appropriate laser line and probe molecule for each surface.

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DNA double-strand breaks (DSBs), which are induced by either endogenous metabolic processes or by exogenous sources, are one of the most critical DNA lesions with respect to survival and preservation of genomic integrity. An early response to the induction of DSBs is phosphorylation of the H2A histone variant, H2AX, at the serine-139 residue, in the highly conserved C-terminal SQEY motif, forming gammaH2AX(1). Following induction of DSBs, H2AX is rapidly phosphorylated by the phosphatidyl-inosito 3-kinase (PIKK) family of proteins, ataxia telangiectasia mutated (ATM), DNA-protein kinase catalytic subunit and ATM and RAD3-related (ATR)(2). Typically, only a few base-pairs (bp) are implicated in a DSB, however, there is significant signal amplification, given the importance of chromatin modifications in DNA damage signalling and repair. Phosphorylation of H2AX mediated predominantly by ATM spreads to adjacent areas of chromatin, affecting approximately 0.03% of total cellular H2AX per DSB(2,3). This corresponds to phosphorylation of approximately 2000 H2AX molecules spanning approximately 2 Mbp regions of chromatin surrounding the site of the DSB and results in the formation of discrete gammaH2AX foci which can be easily visualized and quantitated by immunofluorescence microscopy(2). The loss of gammaH2AX at DSB reflects repair, however, there is some controversy as to what defines complete repair of DSBs; it has been proposed that rejoining of both strands of DNA is adequate however, it has also been suggested that re-instatement of the original chromatin state of compaction is necessary(4-8). The disappearence of gammaH2AX involves at least in part, dephosphorylation by phosphatases, phosphatase 2A and phosphatase 4C(5,6). Further, removal of gammaH2AX by redistribution involving histone exchange with H2A.Z has been implicated(7,8). Importantly, the quantitative analysis of gammaH2AX foci has led to a wide range of applications in medical and nuclear research. Here, we demonstrate the most commonly used immunofluorescence method for evaluation of initial DNA damage by detection and quantitation of gammaH2AX foci in gamma-irradiated adherent human keratinocytes(9)

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Phytochemical lures such as methyl eugenol (ME) and cue-lure are used in the management of Bactrocera fruit flies for monitoring and control. These lures are not just attractants, but also trigger physiological changes in males that lead to enhanced mating success. Additionally, in the cue-lure-responsive Bactrocera tryoni, females mated with lure-fed males exhibit changes in fecundity, remating receptivity and longevity. While the lures show current generation effects, no research has been carried out on possible multigenerational effects, although such effects have been hypothesized within a ‘sexy-son’ sexual selection model. In this study, we test for indirect, cross-generational effects of lure exposure in F1offspring of B. tryoni females mated with cue-lure-fed, zingerone-fed and lure-unfed (=control) males. The F1 attributes we recorded were immature development time, immature survival, adult survival and adult male lure foraging. No significant differences were found between treatments for any of the three life-history measurements, except that the offspring sired by zingerone-fed males had a longer egg development time than cue-lure and control offspring. However, indirect exposure to lures significantly enhanced the lure-foraging ability of F1 adult males. More offspring of cue-lure-fed males arrived at a lure source in both large flight cages and small laboratory cages over a 2-h period than did control males. The offspring of zingerone-fed males were generally intermediate between cue-lure and control offspring. This study provides the first evidence of a next generation effect of fruit fly male lures. While the results of this study support a ‘sexy-son’ sexual selection mechanism for the evolution of lure response in Bactrocera fruit flies, our discussion urges caution in interpreting our results in this way.

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This paper offers an uncertainty quantification (UQ) study applied to the performance analysis of the ERCOFTAC conical diffuser. A deterministic CFD solver is coupled with a non-statistical generalised Polynomial Chaos(gPC)representation based on a pseudo-spectral projection method. Such approach has the advantage to not require any modification of the CFD code for the propagation of random disturbances in the aerodynamic field. The stochactic results highlihgt the importance of the inlet velocity uncertainties on the pressure recovery both alone and when coupled with a second uncertain variable. From a theoretical point of view, we investigate the possibility to build our gPC representation on arbitray grid, thus increasing the flexibility of the stochastic framework.

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Intramedullary nailing is the standard fixation method for displaced diaphyseal fractures of the tibia. An optimal nail design should both facilitate insertion and anatomically fit the bone geometry at its final position in order to reduce the risk of stress fractures and malalignments. Due to the nonexistence of suitable commercial software, we developed a software tool for the automated fit assessment of nail designs. Furthermore, we demonstrated that an optimised nail, which fits better at the final position, is also easier to insert. Three-dimensional models of two nail designs and 20 tibiae were used. The fitting was quantified in terms of surface area, maximum distance, sum of surface areas and sum of maximum distances by which the nail was protruding into the cortex. The software was programmed to insert the nail into the bone model and to quantify the fit at defined increment levels. On average, the misfit during the insertion in terms of the four fitting parameters was smaller for the Expert Tibial Nail Proximal bend (476.3 mm2, 1.5 mm, 2029.8 mm2, 6.5 mm) than the Expert Tibial Nail (736.7 mm2, 2.2 mm, 2491.4 mm2, 8.0 mm). The differences were statistically significant (p ≤ 0.05). The software could be used by nail implant manufacturers for the purpose of implant design validation.