998 resultados para Armington Assumption


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Offspring size is thought to strongly affect offspring fitness and many studies have shown strong offspring size/fitness relationships in marine and terrestrial organisms. This relationship is strongly mitigated by local environmental conditions and the optimal offspring size that mothers should produce will vary among different environments. It is assumed that offspring size will consistently affect the same traits among populations but this assumption has not been tested. Here I use a common garden experiment to examine the effects of offspring size on subsequent performance for the marine bryozoan Bugula neritina using larvae from two very different populations. The local conditions at one population (Williamstown) favour early reproduction whereas the other population (Pt. Wilson) favours early growth. Despite being placed in the same habitat, the effects of parental larval size were extremely variable and crossed generations. For larvae from Williamstown, parental larval size positively affected initial colony growth and larval size in the next generation. For larvae from the other population, parental larval size positively affected colony fecundity and negatively affected larval size in the next generation. Traditionally, exogenous factors have been viewed as the sole source of variation in offspring size/fitness relationship but these results show that endogenous factors (maternal source population) can also cause variation in this crucial relationship. It appears offspring size effects can be highly variable among populations and organisms can adapt to local conditions without changing the size of their offspring.

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A central tenet of life-history theory is the presence of a trade-off between the size and number of offspring that a female can produce for a given clutch. A crucial assumption of this trade-off is that larger offspring perform better than smaller offspring. Despite the importance of this assumption empirical, field-based tests are rare, especially for marine organisms. We tested this assumption for the marine invertebrate, Diplosoma listerianum, a colonial ascidian that commonly occurs in temperate marine communities. Colonies that came from larger larvae had larger feeding structures than colonies that came from smaller larvae. Colonies that came from larger larvae also had higher survival and growth after 2 weeks in the field than colonies that came from smaller larvae. However, after 3 weeks in the field the colonies began to fragment and we could not detect an effect of larval size. We suggest that offspring size can have strong effects on the initial recruitment of D. listerianum but because of the tendency of this species to fragment, offspring size effects are less persistent in this species than in others.

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We examine a problem with n players each facing the same binary choice. One choice is superior to the other. The simple assumption of competition - that an individual's payoff falls with a rise in the number of players making the same choice, guarantees the existence of a unique symmetric equilibrium (involving mixed strategies). As n increases, there are two opposing effects. First, events in the middle of the distribution - where a player finds itself having made the same choice as many others - become more likely, but the payoffs in these events fall. In opposition, events in the tails of the distribution - where a player finds itself having made the same choice as few others - become less likely, but the payoffs in these events remain high. We provide a sufficient condition (strong competition) under which an increase in the number of players leads to a reduction in the equilibrium probability that the superior choice is made.

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High-frequency beach water table fluctuations due to wave run-up and rundown have been observed in the field [Waddell, 1976]. Such fluctuations affect the infiltration/exfiltration process across the beach face and the interstitial oxygenation process in the beach ecosystem. Accurate representation of high-frequency water table fluctuations is of importance in the modeling of (1) the interaction between seawater and groundwater, more important, the effects on swash sediment transport and (2) the biological activities in the beach ecosystem. Capillarity effects provide a mechanism for high-frequency water table fluctuations. Previous modeling approaches adopted the assumption of saturated flow only and failed to predict the propagation of high-frequency fluctuations in the aquifer. In this paper we develop a modified kinematic boundary condition (kbc) for the water table which incorporates capillarity effects. The application of this kbc in a boundary element model enables the simulation of high-frequency water table fluctuations due to wave run-up. Numerical tests were carried out for a rectangular domain with small-amplitude oscillations; the behavior of water table responses was found to be similar to that predicted by an analytical solution based on the one-dimensional Boussinesq equation. The model was also applied to simulate the water table response to wave run-up on a doping beach. The results showed similar features of water table fluctuations observed in the field. In particular, these fluctuations are standing wave-like with the amplitude becoming increasingly damped inland. We conclude that the modified kbc presented here is a reasonable approximation of capillarity effects on beach water table fluctuations. However, further model validation is necessary before the model can confidently be used to simulate high-frequency water table fluctuations due to wave run-up.

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Computer modelling has shown that electrical characteristics of individual pixels may be extracted from within multiple-frequency electrical impedance tomography (MFEIT) images formed using a reference data set obtained from a purely resistive, homogeneous medium. In some applications it is desirable to extract the electrical characteristics of individual pixels from images where a purely resistive, homogeneous reference data set is not available. One such application of the technique of MFEIT is to allow the acquisition of in vivo images using reference data sets obtained from a non-homogeneous medium with a reactive component. However, the reactive component of the reference data set introduces difficulties with the extraction of the true electrical characteristics from the image pixels. This study was a preliminary investigation of a technique to extract electrical parameters from multifrequency images when the reference data set has a reactive component. Unlike the situation in which a homogenous, resistive data set is available, it is not possible to obtain the impedance and phase information directly from the image pixel values of the MFEIT images data set, as the phase of the reactive reference is not known. The method reported here to extract the electrical characteristics (the Cole-Cole plot) initially assumes that this phase angle is zero. With this assumption, an impedance spectrum can be directly extracted from the image set. To obtain the true Cole-Cole plot a correction must be applied to account for the inherent rotation of the extracted impedance spectrum about the origin, which is a result of the assumption. This work shows that the angle of rotation associated with the reactive component of the reference data set may be determined using a priori knowledge of the distribution of frequencies of the Cole-Cole plot. Using this angle of rotation, the true Cole-Cole plot can be obtained from the impedance spectrum extracted from the MFEIT image data set. The method was investigated using simulated data, both with and without noise, and also for image data obtained in vitro. The in vitro studies involved 32 logarithmically spaced frequencies from 4 kHz up to 1 MHz and demonstrated that differences between the true characteristics and those of the impedance spectrum were reduced significantly after application of the correction technique. The differences between the extracted parameters and the true values prior to correction were in the range from 16% to 70%. Following application of the correction technique the differences were reduced to less than 5%. The parameters obtained from the Cole-Cole plot may be useful as a characterization of the nature and health of the imaged tissues.

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Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

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Experimental data for E. coli debris size reduction during high-pressure homogenisation at 55 MPa are presented. A mathematical model based on grinding theory is developed to describe the data. The model is based on first-order breakage and compensation conditions. It does not require any assumption of a specified distribution for debris size and can be used given information on the initial size distribution of whole cells and the disruption efficiency during homogenisation. The number of homogeniser passes is incorporated into the model and used to describe the size reduction of non-induced stationary and induced E. coil cells during homogenisation. Regressing the results to the model equations gave an excellent fit to experimental data ( > 98.7% of variance explained for both fermentations), confirming the model's potential for predicting size reduction during high-pressure homogenisation. This study provides a means to optimise both homogenisation and disc-stack centrifugation conditions for recombinant product recovery. (C) 1997 Elsevier Science Ltd.

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The dispersion model with mixed boundary conditions uses a single parameter, the dispersion number, to describe the hepatic elimination of xenobiotics and endogenous substances. An implicit a priori assumption of the model is that the transit time density of intravascular indicators is approximated by an inverse Gaussian distribution. This approximation is limited in that the model poorly describes the tail part of the hepatic outflow curves of vascular indicators. A sum of two inverse Gaussian functions is proposed as ail alternative, more flexible empirical model for transit time densities of vascular references. This model suggests that a more accurate description of the tail portion of vascular reference curves yields an elimination rate constant (or intrinsic clearance) which is 40% less than predicted by the dispersion model with mixed boundary conditions. The results emphasize the need to accurately describe outflow curves in using them as a basis for determining pharmacokinetic parameters using hepatic elimination models. (C) 1997 Society for Mathematical Biology.

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We measured bone mineral content (BMC) and estimated calcium accretion in children to provide insight into dietary calcium requirements during growth. Anthropometric measurements were done semiannually and whole-body BMC was measured annually by dual-energy X-ray absorptiometry for 4 y in 228 children (471 scans in 113 boys and 507 scans in 115,girls). Mean values for BMC, skeletal area, and height were calculated for 1-y age groups from 9.5 to 19.5 y of age. Cross-sectional analysis of the pooled data gave peak height velocity and peak BMC velocity (PBMCV) and the ages at which these occurred (13.3 y in boys and 11.4 y in girls). PBMCV did not peak until 1.2 y after peak height velocity in boys and 1.6 y after peak height velocity in girls. Within 3 y on either side of PBMCV, boys had consistently higher BMC and BMC velocity compared with girls and the discrepancy increased steadily through puberty. Three years before PBMCV, BMC Values in girls were 69% of those in boys; 3 y after peak height velocity this proportion fell to 51%. PBMCV was 320 g/y in boys and 240 g/y in girls. Under the assumption that bone mineral is 32.2% calcium, these values corresponded to a daily calcium retention of 282 mg in boys and 212 mg in girls. Individual Values could be much greater. In one boy in a group of six subjects for whom there were enough data for individual analysis through puberty, PBMCV was 555 g Ca/y or 490 mg Ca/d. Such high skeletal demands for calcium require large dietary calcium intakes and such requirements may not be met immediately in some children.

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Absorption kinetics of solutes given with the subcutaneous administration of fluids is ill-defined. The gamma emitter, technitium pertechnetate, enabled estimates of absorption rate to be estimated independently using two approaches. In the first approach, the counts remaining at the site were estimated by imaging above the subcutaneous administration site, whereas in the second approach, the plasma technetium concentration-time profiles were monitored up to 8 hr after technetium administration. Boluses of technetium pertechnetate were given both intravenously and subcutaneously on separate occasions with a multiple dosing regimen using three doses on each occasion. The disposition of technetium after iv administration was best described by biexponential kinetics with a V-ss of 0.30 +/- 0.11 L/kg and a clearance of 30.0 +/- 13.1 ml/min. The subcutaneous absorption kinetics was best described as a single exponential process with a half-life of 18.16 +/- 3.97 min by image analysis and a half-life of 11.58 +/- 2.48 min using plasma technetium time data. The bioavailability of technetium by the subcutaneous route was estimated to be 0.96 +/- 0.12. The absorption half-life showed no consistent change with the duration of the subcutaneous infusion. The amount remaining at the absorption site with time was similar when analyzed using image analysis, and plasma concentrations assuming multiexponential disposition kinetics and a first-order absorption process. Profiles of fraction remaining at the absorption sire generated by deconvolution analysis, image analysis, and assumption of a constant first-order absorption process were similar. Slowing of absorption from the subcutaneous administration site is apparent after the last bolus dose in three of the subjects and can De associated with the stopping of the infusion. In a fourth subject, the retention of technetium at the subcutaneous site is more consistent with accumulation of technetium near the absorption site as a result of systemic recirculation.

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The metallic voice is usually confused with ring or nasality by singers and nontrained listeners. who are not used to perceptual vocal analysis. They believe a metallic voice results from a rise in fundamental frequency. A diagnostic error in this aspect may lead to lowering pitch, an incorrect procedure that Could Cause vocal overload and fatigue. The purpose of this article is to Study the quality of metallic voice considering the correlation between information of the physiological and acoustic plans, based on a perceptive consensual assumption. Fiberscopic video pharyngolaryngoscopy was performed on 21 professional singers while speaking vowel [e]-in normal and metallic modes to observe muscular movements and structural changes of the velopharynx, pharynx, and larynx. Vocal samples captured simultaneously to the fiberscopic examination were acoustically analyzed. Frequency and amplitude of the first four formants (F(1), F(2), F(3), and F(4)) were extracted by means of linear predictor coefficients (LPC) Spectrum and were statistically analyzed. Vocal tract adjustments such as velar lowering, pharyngeal wall narrowing, laryngeal rise, aryepiglottic, and lateral laryngeal constrictions were frequently found: there were no significant changes in frequency and amplitude of F(1) in the metallic voiced there were significant increases in amplitudes of F(2), F(3), and F(4) and in frequency for F, metallic Voice perceived as louder was correlated to an increase ill amplitude of F(3) and F(4). Physiological adjustments of velopharynx, pharynx, and larynx are combined in characterizing the metallic voice and can be acoustically related to changes in formant pattern.

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In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.

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Hantaviruses are rodent-borne Bunyaviruses that infect the Arvicolinae, Murinae, and Sigmodontinae subfamilies of Muridae. The rate of molecular evolution in the hantaviruses has been previously estimated at approximately 10(-7) nucleotide substitutions per site, per year (substitutions/site/year), based on the assumption of codivergence and hence shared divergence times with their rodent hosts. If substantiated, this would make the hantaviruses among the slowest evolving of all RNA viruses. However, as hantaviruses replicate with an RNA-dependent RNA polymerase, with error rates in the region of one mutation per genome replication, this low rate of nucleotide substitution is anomalous. Here, we use a Bayesian coalescent approach to estimate the rate of nucleotide substitution from serially sampled gene sequence data for hantaviruses known to infect each of the 3 rodent subfamilies: Araraquara virus ( Sigmodontinae), Dobrava virus ( Murinae), Puumala virus ( Arvicolinae), and Tula virus ( Arvicolinae). Our results reveal that hantaviruses exhibit shortterm substitution rates of 10(-2) to 10(-4) substitutions/site/year and so are within the range exhibited by other RNA viruses. The disparity between this substitution rate and that estimated assuming rodent-hantavirus codivergence suggests that the codivergence hypothesis may need to be reevaluated.

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Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

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Background and Purpose-Functional MRI is a powerful tool to investigate recovery of brain function in patients with stroke. An inherent assumption in functional MRI data analysis is that the blood oxygenation level-dependent (BOLD) signal is stable over the course of the examination. In this study, we evaluated the validity of such assumption in patients with chronic stroke. Methods-Fifteen patients performed a simple motor task with repeated epochs using the paretic and the unaffected hand in separate runs. The corresponding BOLD signal time courses were extracted from the primary and supplementary motor areas of both hemispheres. Statistical maps were obtained by the conventional General Linear Model and by a parametric General Linear Model. Results-Stable BOLD amplitude was observed when the task was executed with the unaffected hand. Conversely, the BOLD signal amplitude in both primary and supplementary motor areas was progressively attenuated in every patient when the task was executed with the paretic hand. The conventional General Linear Model analysis failed to detect brain activation during movement of the paretic hand. However, the proposed parametric General Linear Model corrected the misdetection problem and showed robust activation in both primary and supplementary motor areas. Conclusions-The use of data analysis tools that are built on the premise of a stable BOLD signal may lead to misdetection of functional regions and underestimation of brain activity in patients with stroke. The present data urge the use of caution when relying on the BOLD response as a marker of brain reorganization in patients with stroke. (Stroke. 2010; 41:1921-1926.)