Estimation of Genetic Divergence and Gene Flow between Culex pipiens and Culex quinquefasciatus (Diptera: Culicidae) in Argentina

Allele frequencies at seven polymorphic loci controlling the synthesis of enzymes were analyzed in six populations of Culex pipiens L. and Cx. quinquefasciatus Say. Sampling sites were situated along a north-south line of about 2,000 km in Argentina. The predominant alleles at Mdh, Idh, Gpdh and Gpi loci presented similar frequencies in all the samples. Frequencies at the Pgm locus were similar for populations pairs sharing the same geographic area. The loci Cat and Hk-1 presented significant geographic variation. The latter showed a marked latitudinal cline, with a frequency for allele b ranging from 0.99 in the northernmost point to 0.04 in the southernmost one, a pattern that may be explained by natural selection (FST = 0.46; p < 0.0001) on heat sensitive alleles. The average value of FST (0.088) and Nm (61.12) indicated a high gene flow between adjacent populations. A high correlation was found between genetic and geographic distance (r = 0.83; p < 0.001). The highest genetic identity (IN = 0.988) corresponded to the geographically closest samples from the central area. In one of these localities Cx. quinquefasciatus was predominant and hybrid individuals were detected, while in the other, almost all the specimens were identified as Cx. pipiens. To verify the fertility between Cx. pipiens and Cx. quinquefasciatus from the northern- and southernmost populations, experimental crosses were performed. Viable egg rafts were obtained from both reciprocal crosses. Hatching ranged from 76.5 to 100%. The hybrid progenies were fertile through two subsequent generations

A finite-population revenue management model and a risk-ratio procedure for the joint estimation of population size and parameters

Many dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.

A human immune data-informed vaccine concept elicits strong and broad T-cell specificities associated with HIV-1 control in mice and macaques

Background: None of the HIV T-cell vaccine candidates that have reached advanced clinical testing have been able to induce protective T cell immunity. A major reason for these failures may have been suboptimal T cell immunogen designs. Methods: To overcome this problem, we used a novel immunogen design approach that is based on functional T cell response data from more than 1,000 HIV-1 clade B and C infected individuals and which aims to direct the T cell response to the most vulnerable sites of HIV-1. Results: Our approach identified 16 regions in Gag, Pol, Vif and Nef that were relatively conserved and predominantly targeted by individuals with reduced viral loads. These regions formed the basis of the HIVACAT T-cell Immunogen (HTI) sequence which is 529 amino acids in length, includes more than 50 optimally defined CD4+ and CD8+ T-cell epitopes restricted by a wide range of HLA class I and II molecules and covers viral sites where mutations led to a dramatic reduction in viral replicative fitness. In both, C57BL/6 mice and Indian rhesus macaques immunized with an HTI-expressing DNA plasmid (DNA.HTI) induced broad and balanced T-cell responses to several segments within Gag, Pol, and Vif. DNA.HTI induced robust CD4+ and CD8+ T cell responses that were increased by a booster vaccination using modified virus Ankara (MVA.HTI), expanding the DNA.HTI induced response to up to 3.2% IFN-γ T-cells in macaques. HTI-specific T cells showed a central and effector memory phenotype with a significant fraction of the IFN-γ+ CD8+ T cells being Granzyme B+ and able to degranulate (CD107a+). Conclusions: These data demonstrate the immunogenicity of a novel HIV-1 T cell vaccine concept that induced broadly balanced responses to vulnerable sites of HIV-1 while avoiding the induction of responses to potential decoy targets that may divert effective T-cell responses towards variable and less protective viral determinants.

Remote estimation of thermal inertia and soil heat flux for bare soil

A method is presented which allows thermal inertia (the soil heat capacity times the square root of the soil thermal diffusivity, C(h)rootD(h)), to be estimated remotely from micrometeorological observations. The method uses the drop in surface temperature, T-s, between sunset and sunrise, and the average night-time net radiation during that period, for clear, still nights. A Fourier series analysis was applied to analyse the time series of T-s . The Fourier series constants, together with the remote estimate of thermal inertia, were used in an analytical expression to calculate diurnal estimates of the soil heat flux, G. These remote estimates of C(h)rootD(h) and G compared well with values derived from in situ sensors. The remote and in situ estimates of C(h)rootD(h) both correlated well with topsoil moisture content. This method potentially allows area-average estimates of thermal inertia and soil heat flux to be derived from remote sensing, e.g. METEOSAT Second Generation, where the area is determined by the sensor's height and viewing angle. (C) 2003 Elsevier B.V. All rights reserved.

Online bayesian inference in some time-frequency representations of non-stationary processes

The use of Bayesian inference in the inference of time-frequency representations has, thus far, been limited to offline analysis of signals, using a smoothing spline based model of the time-frequency plane. In this paper we introduce a new framework that allows the routine use of Bayesian inference for online estimation of the time-varying spectral density of a locally stationary Gaussian process. The core of our approach is the use of a likelihood inspired by a local Whittle approximation. This choice, along with the use of a recursive algorithm for non-parametric estimation of the local spectral density, permits the use of a particle filter for estimating the time-varying spectral density online. We provide demonstrations of the algorithm through tracking chirps and the analysis of musical data.

Determination of fiber length and juvenile and mature wood zones from Hevea brasiliensis trees grown in Brazil

The aim of this study was to verify the average fiber length and the juvenile and mature wood zones from Hevea brasiliensis proveniences from a reforestation area in São Paulo, Brazil. For this purpose, five Hevea brasiliensis trees were randomly collected from a 50-year-old plantation, located in Balsamo, São Paulo, Brazil. The trees were cut and five flat sawn boards were obtained. The juvenile and mature wood zones were determined by fiber length measurement from the pith to the bark. The results showed that: (a) the juvenile wood of this species occurred approx. between 40 and 55 mm, from the pith, and from this point forward, the mature wood zone was found; (b) there was a significant difference between the average fiber length of juvenile wood (1.26 mm) and mature wood (1.51 mm).

X charts with supplementary samples to control the mean and variance

A standard X chart for controlling a process takes regular individual observations, for instance every half hour. This article proposes a modification of the X chart that allows one to take supplementary samples. The supplementary sample is taken (and the (X) over bar and R values computed) when the current value of X falls outside the control limits. With the supplementary sample, the signal of out-of-control is given by an (X) over bar value outside the (X) over bar chart's control limits or an R value outside the R chart's control limit. The proposed chart is designed to hold the supplementary sample frequency, during the in-control period, as low as 5% or less. In this context, the practitioner might prefer to verify an out-of-control condition by simply comparing the (X) over bar and R values with the control limits. In other words, without plotting the (X) over bar and R points. The X chart with supplementary samples has two major advantages when compared with the standard (X) over bar and A charts: (a) the user will be plotting X values instead of (X) over bar and R values; (b) the shifts in the process mean and/or changes in the process variance are detected faster.

Efeito alelopático de extrato aquoso de folhas de Azadirachta indica A. Juss. em alface, soja, milho, feijão e picão-preto

The family Meliaceae has been identified as one of the most promising for biological control, as most species have biologically active compounds. Among the species, the Neem (Azadirachta indica A. Juss) is that stands out most for its efficiency and low toxicity, and it is utilized to control insects, fungi and nematodes. The aim of this work was to verify the allelopathic potential of aqueous extract of fresh leaves of Neem on germination of lettuce, soybeans, maize, beans and Bidens pilosa, as a way to control this weed. The extract was obtained by grinding 200g/L of fresh leaves of the Neem (considered extract 100%) and diluting in distilled water at concentrations of 80, 60, 40, and 20%, and a control with only water. The seeds were kept in the germination chamber at a temperature of 25 degrees C, with photoperiod of 12 hours of light. The aqueous extract affected the germination percentage and average length root of lettuce, with values of 1% and 0.1, cm respectively. For the soybeans, the extract influenced negatively the average time of germination and average speed of germination. There was a drastic reduction of the average root length at higher concentration for soybean, corn and beans. For Bidens pilosa all the parameters analyzed were negatively affected, which means sensitivity to the extract. The bioassay performed in the laboratory showed that the aqueous extract of fresh leaves of Azadirachta indica has allelopathic effect on all species.

Estimation of variance components and prediction of breeding values in rubber tree breeding using the REML/BLUP procedure

The present paper deals with estimation of variance components, prediction of breeding values and selection in a population of rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Müell.-Arg.] from Rio Branco, State of Acre, Brazil. The REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure was applied. For this purpose, 37 rubber tree families were obtained and assessed in a randomized complete block design, with three unbalanced replications. The field trial was carried out at the Experimental Station of UNESP, located in Selvíria, State of Mato Grosso do Sul, Brazil. The quantitative traits evaluated were: girth (G), bark thickness (BT), number of latex vessel rings (NR), and plant height (PH). Given the unbalanced condition of the progeny test, the REML/BLUP procedure was used for estimation. The narrow-sense individual heritability estimates were 0.43 for G, 0.18 for BT, 0.01 for NR, and 0.51 for PH. Two selection strategies were adopted: one short-term (ST - selection intensity of 8.85%) and the other long-term (LT - selection intensity of 26.56%). For G, the estimated genetic gains in relation to the population average were 26.80% and 17.94%, respectively, according to the ST and LT strategies. The effective population sizes were 22.35 and 46.03, respectively. The LT and ST strategies maintained 45.80% and 28.24%, respectively, of the original genetic diversity represented in the progeny test. So, it can be inferred that this population has potential for both breeding and ex situ genetic conservation as a supplier of genetic material for advanced rubber tree breeding programs. Copyright by the Brazilian Society of Genetics.

A bayesian analysis for the parameters of the exponential-logarithmic distribution

The exponential-logarithmic is a new lifetime distribution with decreasing failure rate and interesting applications in the biological and engineering sciences. Thus, a Bayesian analysis of the parameters would be desirable. Bayesian estimation requires the selection of prior distributions for all parameters of the model. In this case, researchers usually seek to choose a prior that has little information on the parameters, allowing the data to be very informative relative to the prior information. Assuming some noninformative prior distributions, we present a Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods. Jeffreys prior is derived for the parameters of exponential-logarithmic distribution and compared with other common priors such as beta, gamma, and uniform distributions. In this article, we show through a simulation study that the maximum likelihood estimate may not exist except under restrictive conditions. In addition, the posterior density is sometimes bimodal when an improper prior density is used. © 2013 Copyright Taylor and Francis Group, LLC.

Concentrado proteico de vísceras de surubim híbrido em dietas para cachara

The current study evaluated the growth performance and the haematological profile of barred sorubim fed with levels of hybrid sorubim viscera protein concentrate (0.0; 5.0; 10.0 e 15.0%) in isoprotein and isoenergetic diets. Eighty fish with an average initial weight of 39.8 ± 0.28 g and an average initial length of 19.92 ± 0.25 cm were distributed in 16 aquaria of 60 L, with recirculation system and temperature control, during 35 days. The experimental design was completely randomized with four treatments and four replications. For the growth performance assay were analyzed the follows variables: weight gain (WG), feed consumption (FC), apparent feed conversion ratio (AFCR) and protein efficiency ratio (PER). Furthermore, the hemogram were assessed on the treated fish with levels of protein concentrate. It was observed no significant difference (P>0.05) for all the parameters evaluated. It was concluded that the protein concentrate from hybrid sorubim viscera can be included up to 15% in diets for barred sorubim juveniles without negative response on the performance and health.

Hybrid sorubim viscera protein concentrate in the diets for barred sorubim

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Biometry and fetal weight estimation by two-dimensional and three-dimensional ultrasonography: an intraobserver and interobserver reliability and agreement study

Objective To evaluate and compare the intraobserver and interobserver reliability and agreement for the biparietal diameter (BPD), abdominal circumference (AC), femur length (FL) and estimated fetal weight (EFW) obtained by two-dimensional ultrasound (2D-US) and three-dimensional ultrasound (3D-US). Methods Singleton pregnant women between 24 and 40 weeks were invited to participate in this study. They were examined using 2D-US in a blinded manner, twice by one observer, intercalated by a scan by a second observer, to determine BPD, AC and FL. In each of the three examinations, three 3D-US datasets (head, abdomen and thigh) were acquired for measurements of the same parameters. We determined EFW using Hadlock's formula. Systematic errors between 3D-US and 2D-US were examined using the paired t-test. Reliability and agreement were assessed by intraclass correlation coefficients (ICCs), limits of agreement (LoA), SD of differences and proportion of differences below arbitrary points. Results We evaluated 102 singleton pregnancies. No significant systematic error between 2D-US and 3D-US was observed. The ICC values were higher for 3D-US in both intra- and interobserver evaluations; however, only for FL was there no overlap in the 95% CI. The LoA values were wider for 2D-US, suggesting that random errors were smaller when using 3D-US. Additionally, we observed that the SD values determined from 3D-US differences were smaller than those obtained for 2D-US. Higher proportions of differences were below the arbitrarily defined cut-off points when using 3D-US. Conclusion 3D-US improved the reliability and agreement of fetal measurements and EFW compared with 2D-US.

Soil carbon balance in a tropical grassland: Estimation of soil respiration and its partitioning using a semi-empirical model

In savannah and tropical grasslands, which account for 60% of grasslands worldwide, a large share of ecosystem carbon is located below ground due to high root:shoot ratios. Temporal variations in soil CO2 efflux (R-S) were investigated in a grassland of coastal Congo over two years. The objectives were (1) to identify the main factors controlling seasonal variations in R-S and (2) to develop a semi-empirical model describing R-S and including a heterotrophic component (R-H) and an autotrophic component (R-A). Plant above-ground activity was found to exert strong control over soil respiration since 71% of seasonal R-S variability was explained by the quantity of photosynthetically active radiation absorbed (APAR) by the grass canopy. We tested an additive model including a parameter enabling R-S partitioning into R-A and R-H. Assumptions underlying this model were that R-A mainly depended on the amount of photosynthates allocated below ground and that microbial and root activity was mostly controlled by soil temperature and soil moisture. The model provided a reasonably good prediction of seasonal variations in R-S (R-2 = 0.85) which varied between 5.4 mu mol m(-2) s(-1) in the wet season and 0.9 mu mol m(-2) s(-1) at the end of the dry season. The model was subsequently used to obtain annual estimates of R-S, R-A and R-H. In accordance with results reported for other tropical grasslands, we estimated that R-H accounted for 44% of R-S, which represented a flux similar to the amount of carbon brought annually to the soil from below-ground litter production. Overall, this study opens up prospects for simulating the carbon budget of tropical grasslands on a large scale using remotely sensed data. (C) 2012 Elsevier B.V. All rights reserved.